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MANUAL for Measuring ICT Access and Use by Households and Individuals 2014 EDITION Printed in Switzerland Geneva, 2014 E-Couv_Measuring_Access_2014.indd 1 22.11.2013 11:10:45 Manual for Measuring ICT Access and Use by Households and Individuals 2014 Edition © ITU 2014 International Telecommunication Union Place des Nations CH-1211 Geneva Switzerland Original language of publication: English.
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Preface It is a pleasure to present to you the second edition of the ITU Manual for Measuring ICT Access and Use by Households and Individuals.
This Manual has been prepared to support countries in their efforts to collect and disseminate information and communication technology (ICT) statistics, based on internationally agreed definitions and standards.

The impressive growth in ICT infrastructure and uptake during the past decade has led to an increasing demand for accurate and comparable data and statistics on ICT.
Household surveys are an important source of ICT statistics as they provide invaluable insights into how and where people access and use ICTs, and help in assessing how ICTs impact people’s lives.

Household survey-based data are required to monitor national and international ICT- related development goals and targets, including those of the World Summit on the Information Society (WSIS), the Broadband Commission for Digital Development, and the Millennium Development Goals.
Since the publication of the first edition of this Manual, in 2009, major changes have occurred in the field of ICT.

In particular, Internet is now accessed through a multitude of devices, including tablets and similar handheld computers.

The impressive spread of mobile broadband networks has brought Internet to people who live in areas where fixed infrastructure is limited, for example outside major urban areas, in particular in developing countries.
More and more young people all over the world grow up using digital technologies.

The growth and development of the information society require a continuous review of existing ICT indicators and their definitions.

Therefore, a key component of ITU’s statistical work is the development and revision of international standards used to monitor the progress towards becoming information societies.

The revision of this Manual was carried out through ITU’s Expert Group on ICT Household Indicators (EGH).
The EGH was created in 2012, following a recommendation by the 10th World Telecommunication/ICT Indicators Meeting, held in Mauritius in December 2011.

The main mandate of EGH is to review the core indicators on ICT household access and individual use and to revise and update the ITU Manual.

This edition of the Manual reflects the work of the EGH, as well as the experiences from national statistical offices around the world that have collected ICT indicators through household surveys.
It also takes into account the lessons learnt from the delivery of the ITU training course on ICT household statistics.

The ICT household indicators covered by this Manual are collected by ITU through an annual questionnaire sent to Member States.

They are part of an extensive core list of ICT indicators, developed under the framework of the Partnership on Measuring ICT for Development and widely used around the world to produce ICT statistics.
Since its inception in 2004, the Partnership has achieved international recognition as the key initiative to promote and improve the availability of ICT statistics globally.

Its work has been repeatedly endorsed by the United Nations Statistical Commission and is referred to in the outcome documents of the WSIS and in a number of resolutions adopted by the UN Economic and Social Council.
As an active member of the Partnership, ITU has contributed significantly to developing and revising the core list of indicators, in particular those on ICT infrastructure and access, and on ICT access and use by households and individuals.

This Manual, which is based on the Partnership’s core list of indicators, is meant to be a practical tool to guide countries in their ICT data production.

It can be used as basic reference material when preparing, designing and implementing ICT household surveys.
I am confident that this Manual will become indispensable to all those involved in the production of ICT household statistics.

Brahima Sanou Director Telecommunication Development Bureau (BDT) International Telecommunication Union Foreword ICT statistics have been on the agenda of the international statistical community for many years and are receiving increasing attention due to the impact these technologies have on the economy and society in general.
The Partnership on Measuring ICT for Development has been leading a process, in cooperation with national and international stakeholders, to develop statistical standards and relevant methodologies pertinent to ICT measurement.

At its 38th session, held in 2007, the United Nations Statistical Commission endorsed a core list of ICT indicators.
The core list, which was developed by the Partnership, included indicators on ICT infrastructure and access; ICT access and use by households and individuals; ICT use by businesses and the ICT (producing) sector.

At its 43rd session in 2012, the Commission endorsed a revised and extended core list of ICT indicators, which also included new indicators on ICT in education and e-government, and asked that countries use the list as a reference for the production of ICT-related statistics.
The revision and expansion of the list also underline the fast pace of ICT development and the need for statistics to keep up and provide relevant data.

The Commission consequently urged the Partnership on Measuring ICT for Development to update the list of indicators regularly and assist countries in their capacity building efforts for ICT data collection.
This Manual is an update of the 2009 publication with the same title, dedicated to the collection of ICT statistics at the household level, reflecting the need for statistical methods and concepts to keep up with changes in the area of information and communication technologies.
This Manual complements the UNCTAD Manual on the Production of Statistics on the Information Economy, which covers ICT statistics collected through business surveys and is based on the Partnership core list of indicators on ICT use by businesses.

The two manuals provide an important set of tools at the disposal of national statistical offices for use in their ICT data collection programmes.

The publication is intended to assist national statistical offices in collecting and compiling ICT statistics.
It provides updated guidance on the collection, processing, evaluation and dissemination of ICT household statistics and will be a useful reference for ICT data producers worldwide.

I wish to congratulate the ITU on continuing to take a leading role in the development of internationally comparable indicators on ICT infrastructure and ICT access and use by households and individuals.
Stefan Schweinfest Acting Director United Nations Statistics Division Acknowledgements This edition of the Manual for Measuring ICT Access and Use by Households and Individuals is based on the 2009 edition, which was prepared by Sheridan Roberts, with substantive comments provided by Jose Luis Cervera, both consultants International Telecommunication Union (ITU).

The 2014 edition was substantively revised by José Luis Cervera, Juan Muñoz and Sheridan Roberts, consultants to the ITU.
the to The work was coordinated and supervised by the ICT Data and Statistics Division within the Telecommunication Development Bureau of ITU, and substantive contributions were provided by Susan Teltscher (Head of the Division), Doris Olaya and Esperanza Magpantay.

Useful inputs were made by Vanessa Gray, Ivan Vallejo and Lisa Kreuzenbeck.

The revision of this Manual was subject to an extensive consultation process through the ITU Expert Group on ICT Household Indicators (EGH).
EGH was created in May 2012, following a recommendation by the 9th World Telecommunication/ICT Indicators Meeting, held in Mauritius in December 2011.

The mandate of the EGH was to revise the core indicators on ICT household access and ICT individual use, of the Partnership on Measuring ICT for Development, and to revise the ITU Manual.

EGH, which has more than 170 members from 75 countries, worked through an online discussion forum between May 2012 and June 2013 to revise the indicators and the Manual.
The revisions were finalized at a meeting of the EGH the 11th World held Telecommunication/CT Indicators Symposium, held in Mexico City in December 2013. in June 2013.
The Manual was launched at in Brazil Various references were consulted for this Manual, especially publications from the Partnership on Measuring ICT for Development, International Telecommunication Union, United Nations Statistics Division, OECD, Eurostat, International Labour Organization and United Nations Educational, Scientific and Cultural Organization.

Special acknowledgement is made to national bodies and international organizations for the many examples used in the Manual.
Editing and desktop publishing were carried out by Sheridan Roberts and Nathalie Delmas.

The cover was designed by Céline Desthomas and Sarah Roxas.

Contents Chapter 1.
Page Preface ................................................................................................................................................... iii Foreword ................................................................................................................................................ v Acknowledgements .............................................................................................................................. vi Contents ............................................................................................................................................... vii Index of boxes, tables and figures ...................................................................................................... x Boxes ...................................................................................................................................................x Tables ...................................................................................................................................................x Figures ................................................................................................................................................ xi Introduction ...................................................................................................................... 1 Conceptual framework for the Information society .............................................................................. 2 International work on measuring ICT .................................................................................................. 4 International Telecommunication Union ......................................................................................... 6 United Nations Conference on Trade and Development ................................................................ 7 UNESCO Institute for Statistics ...................................................................................................... 7 Organisation for Economic Co-operation and Development .......................................................... 8 Eurostat ........................................................................................................................................... 8 United Nations Department of Economic and Social Affairs .......................................................... 8 United Nations Environment Programme Secretariat of the Basel Convention ............................. 8 United Nations University ............................................................................................................... 9 World Bank ..................................................................................................................................... 9 United Nations Regional Commissions .......................................................................................... 9 More general work by international organizations in standard setting .............................................. 10 Scope and structure of the Manual ................................................................................................... 10 Chapter 2.
Coordination among national stakeholders in ICT measurement ............................ 15 Stakeholders in the national statistics system and coordination of the production of statistics ........ 15 Issues in coordination among producers .......................................................................................... 18 Models and mechanisms for coordination ........................................................................................ 19 Multiyear planning as a mechanism for coordination ........................................................................ 20 Mechanisms for user consultation ..................................................................................................... 22 Relationships with data providers ..................................................................................................... 25 Chapter 3.
Planning and preparation for ICT household surveys ............................................... 27 ICT household survey planning ......................................................................................................... 28 Budget and management issues ....................................................................................................... 30 Other general preparatory work ........................................................................................................ 31 Staff training and selection ........................................................................................................... 32 Chapter 4.
Statistical standards and measurement topics for ICT household statistics ......... 35 Core ICT household indicators .......................................................................................................... 35 Household ICT access core indicators ......................................................................................... 36 Household ICT expenditure core indicator ................................................................................... 37 Individual ICT use core indicators................................................................................................. 37 Classifications for ICT household statistics ....................................................................................... 38 Individual characteristics ............................................................................................................... 39 Household characteristics ............................................................................................................. 42 Cross-classification of data ........................................................................................................... 43 Other classificatory variables ........................................................................................................ 43 Detailed information on core ICT household indicators .................................................................... 44 Indicator HH1: Proportion of households with a radio
 .................................................................. 45 Indicator HH2: Proportion of households with a television ........................................................... 46 Indicator HH3: Proportion of households with telephone ............................................................. 47 Indicator HH4: Proportion of households with a computer ........................................................... 49 Indicator HH5: Proportion of individuals using a computer .......................................................... 51 Indicator HH6: Proportion of households with Internet ................................................................. 53 Indicator HH7: Proportion of individuals using the Internet .......................................................... 54 Indicator HH8: Proportion of individuals using the Internet, by location ....................................... 55 Indicator HH9: Proportion of individuals using the Internet, by type of activity ............................ 57 Indicator HH10: Proportion of individuals using a mobile cellular telephone ............................... 60 Indicator HH11: Proportion of households with Internet, by type of service ................................. 62 Indicator HH12: Proportion of individuals using the Internet, by frequency ................................. 64 Indicator HH13: Proportion of households with multichannel television, by type ......................... 66 Indicator HH14: Barriers
 to household Internet access ................................................................ 68 Indicator HH15: Individuals with ICT skills, by type of skills ......................................................... 69 Indicator HH16: Household expenditure on ICT ........................................................................... 71 Other measurement topics related to ICT household statistics ........................................................ 71 E-commerce .................................................................................................................................. 72 E-security: trust in the online environment and child online protection ........................................ 73 The social and economic impacts of ICT access and use by households and individuals .......... 74 Barriers to ICT use ........................................................................................................................ 74 Gender-sensitive indicators .......................................................................................................... 75 Time-related issues ........................................................................................................................... 75 Chapter 5.
Data sources and collection techniques for ICT household statistics .................... 79 Data sources ..................................................................................................................................... 79 Types of surveys ........................................................................................................................... 79 Advantages and disadvantages of using stand-alone ICT surveys .............................................. 81 Data collection techniques ................................................................................................................ 85 Personal face-to-face interviews................................................................................................... 86 Personal telephone interviews ...................................................................................................... 87 Self-enumeration .......................................................................................................................... 90 Internet based surveys ................................................................................................................. 90 Chapter 6.
Question and questionnaire design for ICT household surveys .............................. 93 General principles of questionnaire design for household surveys .................................................. 93 ICT model questions ......................................................................................................................... 98 Reference period .......................................................................................................................... 99 ICT concepts that may be difficult to understand ......................................................................... 99 Questionnaire logic.......................................................................................................................... 103 Chapter 7.
Sampling for ICT household surveys ........................................................................ 105 Scope and coverage for households and individuals...................................................................... 105 Target populations and sample frames ........................................................................................... 106 Statistical units ................................................................................................................................ 107 Sample design and selection .......................................................................................................... 109 Chapter 8.
Data processing for ICT household statistics .......................................................... 113 Data entry ........................................................................................................................................ 113 Data editing ..................................................................................................................................... 114 Chapter 10.
Microedits .................................................................................................................................... 114 Macroedits .................................................................................................................................. 115 Imputation for missing data (non-response) ................................................................................... 125 Weighting of data ............................................................................................................................ 126 Calculating and reporting ICT household indicators ....................................................................... 127 Chapter 9.
Data quality and evaluation for ICT household statistics ....................................... 131 Sampling error ................................................................................................................................. 131 Non-sampling error.......................................................................................................................... 133 Assessment of data quality ............................................................................................................. 134 Evaluation ........................................................................................................................................ 135 Dissemination of ICT household data and metadata ........................................... 137 Data dissemination .......................................................................................................................... 137 Tabulation plans for ICT indicators ................................................................................................. 138 Metadata reporting and dissemination ............................................................................................ 144 Data collection and dissemination of ICT statistics by ITU ............................................................. 146 Annex 1.
Core list of ICT Indicators (revised 2013) ....................................................................... 147 Core indicators on ICT infrastructure and access ........................................................................... 147 Core indicators on access to, and use of, ICT by households and individuals ............................... 147 Core indicators on use of ICT by businesses ................................................................................. 150 Core indicators on the ICT (producing) sector ................................................................................ 150 Core indicators on international trade in ICT goods ........................................................................ 150 Core indicators on ICT in education ................................................................................................ 151 Core indicators on e-government .................................................................................................... 151 Annex 2.
Model questionnaire for measuring ICT access and use by households and individuals .......................................................................................................................................... 153 Notes and instructions to questionnaire designers ......................................................................... 153 Model questionnaire for measuring ICT access and use by households and individuals .............. 154 Annex 3.
Examples of imputation and weighting .......................................................................... 163 Imputation for missing data ............................................................................................................. 163 Weighting records ........................................................................................................................... 164 Annex 4.
ITU Questionnaire on Information and Communication Technology (ICT) Access and Use by Households and Individuals ................................................................................................ 167 ICT Access by urban/rural and household composition.............................................................. 168 ICT Usage by sex and urban/rural .................................................................................................. 170 ICT Usage by age and sex .............................................................................................................. 172 ICT Usage by highest education level attained* and sex ............................................................... 174 ICT Usage by labour force status and sex ...................................................................................... 176 ICT Usage by occupation ................................................................................................................ 179 Annex 5.
Glossary of terms and abbreviations .............................................................................. 183 Bibliography ....................................................................................................................................... 189 Index of boxes, tables and figures Boxes Box 1.

The Partnership on Measuring ICT for Development ................................................................... 5 Box 2.
Cooperation between the Information Technology Authority and the National Centre for Statistics and Information in the Sultanate of Oman ..............................................................18 Box 3.

Inter-institutional collaboration in Lebanon for ICT statistics ......................................................20 Box 4.

Information society statistics in the Philippines ...........................................................................21 Box 5.
National Observatory of the Telecommunications and the Information Society in Spain ...........24 Box 6.

Moroccan Observatory of Information Technology and Communication (OMTIC) .....................24 Box 7.

The Brazilian Center of Studies on Information and Communication Technologies (CETIC.br) ..............................................................................................................................25 Box 8.
An example of supervision and monitoring in ICT household surveys .......................................33 Box 9.

India: definition of rural and urban areas ....................................................................................43 Box 10.

Brazil: measuring e-commerce .................................................................................................73 Box 11.

Oman: measuring barriers to household access to a computer ...............................................75 Box 12.
Eurostat 2007 model question on barriers to use of the Internet by individuals .......................75 Box 13.

Inclusion of ICT questions in the Palestinian Housing Conditions Survey 2010 and the Multipurpose Household Survey of Costa Rica .....................................................................80 Box 14.

Lao People’s Democratic Republic: use of budget surveys to collect ICT access data ...........81 Box 15.
Nepal: surveys used to collect household ICT access data .....................................................83 Box 16.

Use of a combination of techniques to collect ICT household data ..........................................86 Box 17.

Lebanon: use of PDAs in a multipurpose household survey ....................................................87 Box 18.

Cognitive interviewing as a tool to evaluate questions: a practical case from Brazil ................95 Box 19.
How to ask the question on Internet access by type of access ..............................................101 Box 20.

Hong Kong, China: question on use of e-Government services, 2008 ...................................102 Box 21.

Interviewer instructions for ICT household surveys of Canada and Hong Kong, China .........104 Box 22.

Honduras: change in statistical units in household surveys ...................................................108 Box 23.
Definition of household used in Australia and Hong Kong, China ..........................................109 Box 24.

Greece: stratification of the sample of the ICT household survey ..........................................110 Box 25.

Example of a consistency check .............................................................................................115 Box 26.

Australia: example of post-stratification ..................................................................................127 Box 27.
Sampling error of the value of an ICT household indicator .....................................................132 Tables Table 1.

Reference material for household surveys and standards .......................................................11 Table 2.

List of core indicators on access to, and use of, ICT by households and individuals ..............36 Table 3.

Classification of ICT equipment and services, based on COICOP ..........................................38 Table 4.
ISCO major groups: 1988 and 2008.........................................................................................42 Table 5.

Detailed information on core indicators on access to, and use of, ICT by households and individuals: HH1 to HH16 .......................................................................................................45 Table 6.

Types of surveys where ICT questions have been included between 2009 and 2011 ............82 Table 7.
Inclusion of ICT related question in the last Population and Housing Census (number of countries) ...............................................................................................................................82 Table 8.

Surveys used by countries of the Latin American and Caribbean region to measure household access to, and individual use of, ICT ...................................................................84 Table 9.
Mode of data collection, survey vehicle and response rate for countries conducting the Eurostat community survey, 2011 ..........................................................................................89 Table 10.

Summary of data collection methods .....................................................................................91 Table 11.

Micro and macroedits for ICT household statistics ..............................................................116 Table 12.
Example of data reporting: partial table ...............................................................................128 Table 13.

Example tabulation for household ICT access core indicators ............................................139 Table 14.

Example tabulation for barriers to household Internet access .............................................140 Table 15.

Example tabulation for ‘whole population’ individual ICT use indicators..............................141 Table 16.
Example tabulation for the location of Internet use ..............................................................142 Table 17.

Example tabulation for ICT skills of individuals ....................................................................143 Table 18.

Metadata associated with ICT household surveys ...............................................................145 Figures Figure 1.
Information society conceptual framework ................................................................................ 2 Figure 2.

Stakeholders in the ICT statistics system ...............................................................................16 Figure 3.

Scheme of the Generic Statistical Business Process Model (GSBPM) ..................................27 Figure 4.

Structure and logic of a model questionnaire/module for collecting ICT household data .......96 Chapter 1.
Introduction 1 Chapter 1.

Introduction The availability of information and communication technology (ICT) infrastructure – 1. and the uptake in its use – continue to grow.

The Internet, in particular, is transforming society, with a growing amount of information and a large number of tools available.
These advances, together with the recognition that ICTs are a driver of social and economic development, have driven a need for reliable, comprehensive and comparable statistics to support government and industry policy decisions.

While demand for data on access to, and use of, ICT has grown, statistics are still limited – both in their quality and availability.

Measuring ICT for development has been emphasized in the World Summits on the 2.

Information Society (WSIS).


The Summits have highlighted the importance of measuring progress towards the information society through internationally comparable statistical indicators and have called upon countries and international organizations to allocate appropriate resources for the provision of ICT statistics required for the analysis of the changing information society.

3.
3.

Measuring ICT access and use by households and individuals is key to monitoring the progress of countries towards becoming information societies.

This manual will assist countries to achieve that by enabling the production of high quality and internationally comparable data.

While the Manual is primarily intended as a practical tool for official statisticians of developing economies, its content will also be relevant to developed economies.

4.
4.

The Manual focuses on household surveys as instruments to investigate access to and use of ICT by households and individuals.1 In covering many of the statistical difficulties in this field, the Manual aims to assist developing economies in their ICT household data collection endeavours, while ensuring comparability between statistics collected by all countries through adherence to globally agreed core ICT indicators and associated statistical standards.

5.
5.

This manual and the associated training course are a major part of ITU’s technical assistance work in this area of statistics.2 In this regard, ITU responds to the mandate of its member countries through the World Telecommunication Development Conference (WTDC).
At the 2010 conference, Resolution 8 covered the collection and dissemination of information and statistics, and included clause 11 (“to provide technical assistance to the relevant national authorities for the collection of ICT statistics, in particular by means of national surveys…”) and clause 12 (“to develop training material and conduct specialized training courses on information society statistics for developing economies.”) (ITU, 2010a).3 6.

This edition of the Manual is based on the 2009 edition.
It has been updated substantially taking into account comments received from users and from members of the ITU Expert Group on ICT Household Indicators (EGH).
In particular, the following revisions and additions were made: • • Complete revision of the core list of indicators and change in the presentation of the indicators; Updated definitions, classifications and examples; 1 2 The Manual generally uses the term “ICT household statistics” to refer to statistics on both household access to, and individual use of, ICT.
ITU Training Course on Measuring ICT Access and Use by Households and Individuals: http://www.itu.int/en/ITU- D/Statistics/Pages/capacitydev/default.aspx.

3 For more details of WTDC’s resolution 8, see http://www.itu.int/ITU-D/conferences/wtdc/2010/pdf/WTDC10_DraftPreliminaryReport.pdf.

Manual for Measuring ICT Access and Use by Households and Individuals 2 • • • • • • Chapter 1.
Introduction Creation of tables for each core indicator and adding complementary information, such as definitions of technical terms; clarifications and methodological issues; model questions; disaggregation and classifications; core indicator calculation; and policy relevance; Expansion of conceptual framework and international work carried out on ICT measurement; More emphasis on national coordination of ICT statistics; More emphasis on collection of ICT statistics through existing household surveys; Revision and updates to better reflect data collection practices; Revisions in the areas of survey methodology, sampling design, data collection standards specific to the core indicators.
Conceptual framework for the Information society 7.

Conceptually, the information society is a complex set of topics, entities, actions and relationships.

OECD (2009 and 2011), through its Working Party on Indicators for the Information Society (WPIIS), has developed a broad conceptual framework covering the information society measurement areas of ICT demand and supply, ICT infrastructure, ICT products, and electronic content and media.
Figure 1 provides an adapted and simplified view of the conceptual framework and shows how ICT household statistics fit into the ‘demand side’ of the framework.

Figure 1.
Figure 1.

Information society conceptual framework ICT supply ICT sector - services - manufacturing - wholesale trade Infrastructure products Skills and knowledge Public policy -Regulation -Legislation -National ICT strategies ICT demand Access and use by: - households - individuals - businesses - public organizations (government, hospitals, schools, universities, etc) - private organizations Economic and social impact of ICT Manual for Measuring ICT Access and Use by Households and Individuals Chapter 1.
Introduction 3 tools for social and economic development.

For example, The supply side provides ICT infrastructure and products.

Once these are in place, it is 8. necessary to develop the skills and knowledge to use them and to transform them into powerful they enable modernization of the government, the health system and business processes.

Citizens can then take advantage of ICT applications and services subsequently made available.
Sound public policy is necessary to ensure that maximum benefit is obtained from ICT and to facilitate the transition towards an information society.

Relevant policies can include national strategies, legislation, regulation and appropriate incentives.

The ultimate goal is that the efficient and effective use of ICT is reflected in social and economic benefits (impact) for society.

9.
9.

The recognition that ICT can be a development enabler, if applied and used appropriately, is critical to countries that are moving towards information or knowledge-based societies (ITU, 2009a).

In this process, a careful look at the social dimension of ICT impact is of key importance.
This includes aspects related to the digital divide (inequality in access to, and use of, ICTs), social interaction through ICT and, more generally, characteristics of access to technologies and their use by different demographic and social groups.

Policy- makers can maximize the benefits of ICT for their citizens by promoting equality and security of access and use, the skills required for use, the availability of ICT infrastructure, and the affordability of ICT services.
ICT (and other) skills determine the effective use that is made of ICTs, and are critical to leveraging the full potential of ICTs for socio-economic development.

Economic growth and development will remain below potential if economies are not capable of exploiting new technologies (ITU, 2009a).

10.
10.

Therefore, it is essential to take stock of the infrastructure and products available, their coverage, their benefits and shortcomings, the level of equality or inequality of their availability, their level of penetration, access and use in societies and economies, and level of required and available skills.
That is, collection of data on ICT in society is necessary to monitor the progress towards achieving an information society and to provide the information needed by policy-makers to guide that progress.

11.

The component of main interest for this manual relates to ICT demand by households and individuals, although all elements of the framework are relevant to some degree.

For instance, households use ICT infrastructure and interact with businesses and government.
The measurement of ICT demand by businesses and ICT supply, is covered in the UNCTAD Manual for the Production of Statistics on the Information Economy (UNCTAD, 2009).

Measurement of ICT demand by schools, is covered in the UNESCO Institute for Statistics (UIS) Guide to Measuring Information and Communication Technologies (ICT) in Education (UIS, 2009).
Similarly, the Framework for a set of e-government core indicators covers the measurement of ICT demand and use in government (Partnership and UNECA, 2012).

12.

It is important, at the outset, to distinguish what we mean by ICT access and ICT use.

ICT access refers to availability of ICTs within the home.

Use of ICT refers to use by one or more individuals of the household, whether at home or elsewhere.

13.
13.

Household statistics on ICT access and use are mainly produced by national statistical offices (NSOs) using traditional household surveys.

These can be broadly categorized as household surveys that are either dedicated to measuring ICT access and use or surveys that include some questions or modules on ICT access and use.

NSOs 4 have particular expertise in conducting household surveys.
Their role in ICT household statistics is 4 The term NSO as used in this manual is taken to include all government agencies that collect official statistics.

Where a national statistical system is decentralized, there may be several official statistical agencies in a country.

NSOs are usually government-funded and are responsible for providing high quality, standardized statistical data to government, industry and the public.

They may also be responsible for coordinating the national statistical system.
Manual for Measuring ICT Access and Use by Households and Individuals 4 Chapter 1.

Introduction considered in Chapter 2, which discusses the importance of relationships between data producers, data users and data providers.

International work on measuring ICT 14.

During the past decade, several international organizations have been involved in the development of statistical standards for measurement of ICT infrastructure, access and use by different sectors of the economy and society.

15.
15.

The coordination of the work of international organizations with respect to ICT statistics is done through the Partnership on Measuring ICT for Development.

The United Nations Statistical Commission validates the statistical development work of the Partnership, thus guaranteeing that standards are coherent with those of other areas of official statistics.

16.

The Partnership on Measuring ICT for Development (Box 1) is a multistakeholder initiative consisting of 13 ICT measurement.
It was established following the Geneva phase of the World Summit on the Information Society in 2003 5 and officially launched in 2004, with the overall objective of improving the availability and quality of internationally comparable ICT statistics.

international and regional organizations involved in 17.
One of the main achievements of the Partnership was the development of a core list of ICT indicators, with their corresponding definitions and other metadata, in close consultation with other stakeholders, mainly NSOs.

At its meetings of 2007 and 2012, the United Nations Statistical Commission (UNSC) endorsed the Partnership core list of ICT indicators and encouraged countries to use it in their data collection programmes.
The Commission asked for its wide circulation so that countries and other agencies could use the list as a reference, and also asked the Partnership to continue reviewing the indicators in light of rapid technological advances and widespread use of ICT (UNSC, 2007 and UNSC, 2012).
The core list, with the revisions and additions presented in this manual, is composed of 57 ICT indicators, covering ICT infrastructure, ICT access and use by households and businesses, the ICT (producing) sector, trade in ICT goods, ICT in education and e-government.

The main purpose of the core list is to help countries produce high quality and internationally comparable ICT statistics.
The indicators have associated statistical standards, including concepts, definitions, model questions, classificatory variables, and guidance on scope and statistical units.

This edition of the Manual updates standards for ICT household statistics.

18.

The work of the Partnership has been recognized by the Economic and Social Council (ECOSOC) through several resolutions.
Resolution 2008/3 recommends that the Partnership considers the creation of benchmarks and indicators, including impact indicators, for further consideration and decision by the UN Statistical Commission, in order to track progress towards the attainment of the specific goals and targets set out in the outcome documents of the World Summit on the Information Society, particularly section B of the Plan of Action adopted in Geneva.
Resolution 2009/7 recognizes its institutional strengthening and the creation of the working group to measure the economic and social impact of information and communication technologies.

Resolutions 2011/16 and 2012/5 call upon the Partnership to further its work on measuring the impact of information and communication technologies, particularly in developing economies, by creating practical guidelines, methodologies and indicators.
They encourage governments to collect relevant data at the national level on ICTs, to share information about country case studies and to collaborate with other countries in capacity-building exchange programmes.

The 2013 resolution (draft) encourages member 5 For more information on the Geneva and Tunis phases of the World Summit on the Information Society, see ITU (2005).
Manual for Measuring ICT Access and Use by Households and Individuals states to provide information to the Partnership, so as to contribute to its final assessment report on the achievement of the WSIS targets.6 Chapter 1.

Introduction 5 Box 1.

The Partnership on Measuring ICT for Development Launched: June 2004 at UNCTAD XI (Sao Paulo, Brazil).
Current members: ITU, OECD, Eurostat, UNCTAD, UIS, four UN Regional Commissions (UNECLAC, UNESCWA, UNESCAP, UNECA), the World Bank, UNDESA, UNEP/Secretariat of the Basel Convention, and the United Nations University Institute for Sustainability and Peace (UNU-ISP).
Objectives: Defining a core list of ICT indicators and methodologies to collect these indicators; Helping developing economies collect ICT statistics, particularly through capacity building and hands-on training for national statistical offices; and Collecting and disseminating information society statistics in a number of formats, including global reports and databases.
Memorandum of Understanding: Signed by all partners in order to further strengthen their commitment and to provide guidelines to potential new members.

Structure: A Steering Committee (currently consisting of ITU, UNCTAD and UNECLAC) plus task groups (on e- government indicators, gender, trade in ICT services and ICT-enabled services, measurement of the WSIS targets and measuring e-waste).

Some task groups have members that are not members of the Partnership.
Core indicators: A first edition of the core list of ICT Indicators was released during the Tunis phase of the World Summit on the Information Society (WSIS) in 2005.

It was the result of an intensive consultation process with statistical agencies and policy-makers that was facilitated by members of the Partnership.

The core list was composed of 41 ICT indicators on infrastructure, access and use by households and businesses, the ICT (producing) sector and trade in ICT goods (Partnership, 2005).
The list has been revised and added to over time.

A first revision, to reflect changes in technologies and to add new indicators on education, was presented as an “item for information” to the United Nations Statistical Commission’s 2009 meeting and published in 2010 (Partnership, 2010).

A subsequent revision extended the list to include a set of indicators on e-government.

In addition, there were revisions to some definitions and to a number of response categories.
The third revision updates the ICT household indicators and is presented in this manual.

The revisions have been made by the Expert Group on ICT Household Indicators (EGH);7 the complete revised core list can be found at Annex 1.

Capacity building: The capacity-building work of the Partnership is undertaken by its members independently but coordinated through the Partnership.
Activities include the conduct of training courses and workshops, as well as the production of technical material (of which this manual, as well as its previous edition of 2009, are examples).

Other methodological manuals include those on statistics of the Information Economy (UNCTAD, 2007 and 2009), e-government (Partnership and UNECA, 2013), use of ICT in education (UIS, 2009).

OECD (2011) and Eurostat (2013) cover broader areas of information society measurement.
More information on the Partnership, its members and its activities can be found at http://www.itu.int/ITU- D/ict/partnership/index.html.

19.

In addition to establishing a core list of indicators, the Partnership and its members are involved in a number of activities that support their mission of achieving internationally comparable and reliable ICT statistics.
These include the dissemination of national ICT data, development of statistical manuals and the provision of capacity-building services (training and technical assistance missions) to enable statistical agencies to collect the data necessary to compile the core indicators.
6 For more information on all ECOSOC’s resolutions related to the “Assessment of the progress made in the implementation of and follow-up to the outcomes of the World Summit on the Information Society”, see http://www.un.org/en/ecosoc/docs/docs.shtml.

7 The revisions were finalized and agreed upon during the 1st Meeting of the EGH in São Paulo, Brazil, on 4-6 June 2013.

The final report of the meeting is available at: http://www.itu.int/en/ITU-D/Statistics/Pages/events/brazil2013/default.aspx.
Manual for Measuring ICT Access and Use by Households and Individuals 6 Chapter 1.

Introduction 20.

The Partnership ensures that the competencies of each partner organization are used and overlaps are avoided.

The work of Partnership members in the area of ICT measurement is described below.

International Telecommunication Union 21.

The International Telecommunication Union (ITU) has a long history in setting standards for telecommunication statistics.
Of most relevance to the Manual is the important role played by ITU in standardizing definitions of telecommunication/ICT indicators.

Over 80 ICT indicators produced by ITU are defined in the Handbook for the Collection of Administrative Data on Telecommunications/ICT (2011), which is updated and reviewed regularly.

ITU reviews these indicators through the Expert Group on Telecommunication/ICT Indicators (EGTI),8 which was created in May 2009.
The EGTI has a mandate to revise the list of ITU supply-side indicators, as well as to discuss outstanding methodological issues and new indicators.

EGTI is open to all ITU members and experts in the field of ICT statistics and data collection.

It works through an online discussion forum and occasional face-to-face meetings.

EGTI reports back periodically to the World Telecommunication/ICT Indicators Symposium (WTIS).
Some of the definitions in the Handbook are used for many of the technical terms (mobile cellular network, Internet access technologies, etc.)

used in the Partnership’s core indicators on access to, and use of, ICT by households and individuals.

22.
In 2003, closely linked to the WSIS and the recognized need to measure the information society, ITU expanded its statistical work from defining and collecting (primarily administrative) data in the area of telecommunication and ICT infrastructure from regulatory authorities, into the area of household statistics and started to collect data on household ICT indicators from national statistical offices.9 As an active member of the Partnership,10 ITU has contributed to the development of the core list of ICT household indicators, including their definitions, consultations with stakeholders and the preparation of relevant methodological documents.
23.

This manual is a further contribution by ITU towards the availability of comparable ICT household statistics based on internationally agreed standards.

Revisions to the indicators included in the Manual were discussed in the Expert Group on ICT Household Indicators (EGH).

11 The EGH was established in May 2012 to review the statistical indicators for measuring ICT access and use by households and individuals.
It is open to all ITU members, and to ICT experts and statisticians familiar with data collection on these indicators.

EGH works through an online discussion forum and holds occasional face-to-face meetings.

Reports of the EGH will be presented periodically to the World Telecommunication/ICT Indicators Symposium (WTIS).

24.

Based on the Handbook and the Manual, ITU assists governments in developing economies in their ICT data collection and dissemination efforts.
Support is provided for the production of statistics in the areas of ICT infrastructure, access, and use by household and individuals.

Technical workshops are carried out at the national and regional levels to exchange experiences and discuss methodologies, definitions, survey vehicles and other issues related to the collection of ICT statistics.

25.
25.

As part of the global statistical system of the UN, ITU collects statistics covering the telecommunication/ICT sector for about 200 economies worldwide, in line with other specialized agencies that produce statistics covering their respective fields of operations.

ITU 8 9 See http://www.itu.int/ITU-D/ict/ExpertGroup/default.asp.

The first ITU questionnaire on access to, and use of, ICT by households and individuals was sent to all national statistical offices in October 2005.
10 11 Including a member of the Partnership Steering Committee.

See http://www.itu.int/net4/ITU-D/forum/expertgrouponhouseholds/forum/yaf_login.aspx?returnurl=%2fnet4%2fITU- D%2fforum%2fexpertgrouponhouseholds%2fforum%2f.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 1.
Introduction 7 statistics include indicators outlined in the Handbook and are usually collected from national telecommunication regulatory agencies, ministries or specialized agencies by means of annual questionnaires.

Indicators on access to and use of ICTs by households and individuals are also collected annually, through a questionnaire sent to national statistical offices.

26.

ITU disseminates the data that it collects in a number of forms.
The Yearbook of Statistics, has been published annually for almost three decades.

The electronic database, World Telecommunication/ICT Indicators (WTI) database, available both in a user-friendly CD-ROM and by electronic download, provides an important historical perspective of the ICT industry, with annual time series dating back to 1960 and extending until 2012.
The database includes over 140 indicators, covers about 200 economies and is widely respected as the world ’ s leading source of ICT statistics.

The annual flagship report, Measuring the Information Society (MIS) (for example, ITU, 2013a), features the ITU ICT Development Index (IDI) and the ICT Price Basket (IPB) – two benchmarking tools to measure the information society.

The IDI captures the level of advancement of ICT in countries worldwide and compares progress made between two years.
It also measures the global digital divide and examines how it has developed in recent years.

The IPB combines fixed telephone, mobile cellular and fixed broadband prices into one measure and compares countries over time.

The MIS report is complemented by a series of statistical tables providing country-level data for all indicators included in the IDI and IPB.
Lastly, a wealth of information is provided for free at http://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx on popularly requested telecommunication/ICT statistics.

United Nations Conference on Trade and Development 27.

The United Nations Conference on Trade and Development (UNCTAD) has collected data from developing economies since 2004 on the use of ICT by businesses and on the ICT (producing) sector, based on the core list of ICT indicators.
UNCTAD has contributed to the development of the core list of ICT business indicators, including their definitions, consultation with stakeholders and preparation of methodological documents.

The measurement of ICT demand by businesses and of ICT supply is outlined in the UNCTAD 2009 Manual for the Production of Statistics on the Information Economy (UNCTAD, 2009).
The results from the data collection of UNCTAD are used in their research and analysis, such as the Information Economy Report series (http://unctad.org/ier), and is published at UNCTAD's statistics portal (http://unctadstat.unctad.org/).

UNCTAD has also started working on the measurement of ICT services and the development of gender-related ICT indicators.
UNCTAD provides technical assistance to developing economies on the measurement of ICT in business and the ICT sector, including through training courses and advisory services.

UNESCO Institute for Statistics 28.

The UNESCO Institute for Statistics (UIS) is responsible for developing and collecting indicators on ICT use in education.
UIS has led the work of developing the core list of ICT indicators in education, including definitions and preparation of methodological documents, particularly the Guide to Measuring Information and Communication Technologies (ICT) in Education (UIS 2009).

UIS has piloted data collection on ICT in education in Latin America and the Caribbean and in five Arab states, to gather internationally comparable data.
The surveys were developed with the International Working Group on ICT Statistics in Education (WISE), which was established by the UIS.

The working group provides invaluable insight into the design and implementation of the survey instruments and related methodologies.

This work also entails close collaboration with UNESCO’s Communication and Information Sector and other strategic institutional partners.

Manual for Measuring ICT Access and Use by Households and Individuals 8 Chapter 1.
Introduction Organisation for Economic Co-operation and Development 29.

The work of the Organisation for Economic Co-operation and Development (OECD) on ICT indicators is mainly carried out through its Working Party on Indicators for the Information Society (WPIIS).12 The Working Party has a mandate to: (i) Ensure the continued improvement of the methodology for the collection of internationally comparable data for measuring the supply of, demand for, and impacts of, ICTs.
This includes developing and maintaining standards for measurement of the ICT sector, ICT goods and services, electronic commerce, digital content and diffusion of ICT to organisations and individuals; (ii) Compile ICT statistics according to these standards and assist in developing and interpreting statistical indicators which aid formulation of ICT and related policies, and monitoring progress; and (iii) Carry out empirical analysis, based on official statistics, of the impacts of new information technologies on the economy.
OECD has developed standards covering a number of aspects of information society measurement.

In respect of households and individuals, WPIIS has developed model surveys for measuring ICT access and use by households and individuals (OECD, 2011).

13 The model survey of 2005 (OECD, 2005) is currently under revision (OECD, 2013).

Eurostat 30.
Eurostat 30.

The Statistical Office of the European Union (Eurostat) works closely with information society statisticians from its Member States, and other participating countries, to develop and run the annual EU surveys on ICT usage in households and by individuals (as well as surveys on ICT usage and e-commerce in enterprises).

The harmonized approach based on a common legal instrument is very effective and provides detailed and highly comparable datasets.
Eurostat produces model questionnaires and methodological manuals dealing with measurement of ICT access and use (for example, Eurostat, 2013a,b).

Between 2006 and 2013, Eurostat carried out several comparative studies with NSOs to analyse the impact of ICT on the economy through the linking of microdata from different surveys, that is, ICT, innovation and structural business surveys (Eurostat, 2008).

United Nations Department of Economic and Social Affairs 31.
The UN Department of Economic and Social Affairs (UNDESA), since 2003, has collected data on the use of ICT by governments in the provision of e-services.

UNDESA tracks and monitors the progress in e-government by 193 member states and publishes the findings biennially as the UN E-government Survey (for example, UNDESA, 2012).

UNDESA also contributes its expertise in the area of e-government measurement through the Partnership Task Group on e-Government (TGEG), discussed below.
United Nations Environment Programme Secretariat of the Basel Convention 32.

The UNEP Secretariat of the Basel Convention (UNEP/SBC) provides expertise on e- waste issues.

UNEP/SBC leads the Partnership Task Group on Measuring E-waste (TGEW), which aims to support the compilation of reliable data on e-waste as a basis for political decision making and further action on the environmentally sound management of used and end-of-life ICT equipment.
It is currently developing a framework document for monitoring e- waste based on internationally defined indicators.

12 Most members of the WPIIS are information society statisticians from national statistical offices of OECD member countries.

Other international organizations, including Eurostat and ITU, are also members.

13 See www.oecd.org/sti/measuring-infoeconomy/guide and http://www.oecd.org/sti/scienceandtechnologypolicy/43281062.pdf (2009 version).
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 1.

Introduction 9 United Nations University 33.

The United Nations University (UNU) has been addressing issues associated with the production, usage and final disposal of ICT since 2000.

Its Institute for Sustainability and Peace (UNU-ISP) has a special focus on e-waste related issues.

UNU-ISP has conducted a number of detailed and standardized studies to qualify and quantify e-waste arising in various countries.
Moreover UNU hosts the multistakeholder initiative Solving the E-waste Problem (StEP).

World Bank 34.

The World Bank’s work on ICT indicators is mainly carried out through its ICT Sector Unit and Development Data Group.

It consolidates ICT indicators from ITU and other sources, including various household and business surveys conducted by the World Bank, and publishes ICT at-a-glance tables in partnership with ITU.

These provide country specific key ICT data (about 30 indicators) and indices.
ICT indicators are also featured in the World Bank's triennial report series Information and Communications for Development.

The World Bank contributed to the work of the Partnership through the Task Group on Database Development, which looked at the dissemination of data for the core list of ICT indicators collected by different members of the Partnership.

United Nations Regional Commissions 35.


The UN Regional Commissions have the mandate to promote a regional perspective to global discussions while introducing global concerns at the regional and subregional levels.

UN Regional Commissions contribute to the Partnership with their strengths, such as ground presence, knowledge about regional particularities and close relationships with their member countries.
In addition, they coordinate statistical activities in their respective regions and liaise directly with NSOs.

UN Economic Commission for Africa 36.

UNECA is the regional coordinator of statistical activities in Africa and in 1990 launched the Addis Ababa Statistical Action Plan for Africa.

It also hosts the secretariat of the Advisory Board for Statistics in Africa (ABSA) made up of representatives from member states, regional organizations and partners working on statistics in Africa.
Through the African Information Society Initiative (AISI), UNECA in cooperation with the International Development Research Centre (IDRC) of Canada, the European Union (EU) and the Norwegian Agency for Development Co-operation (NORAD) launched the SCAN ICT project in 2000.

The project’s aim is to measure the penetration and impact of the information society in key sectors of African economies.
The project, initially piloted in six African countries is being expanded, in close cooperation with NSOs, to other African countries.

37.

More recently, the UNECA led the Partnership Task Group on e-Government (TGEG), which developed and released the e-government core indicators, in Framework for a set of e- government core indicators (Partnership and UNECA, 2012).

The Framework and the forthcoming manual (Partnership and UNECA, 2013).
can be used by countries when collecting data for the e-government core indicators.

UN Economic Commission for Latin America and the Caribbean 38.

UNECLAC acts as the secretariat of the Statistical Commission of the Americas and technical secretariat of the Action Plan for the Information and Knowledge Society in Latin America and the Caribbean (eLAC2015).
ECLAC assists its member countries in the compilation, analysis and dissemination of data and indicators on access to, and use of, Manual for Measuring ICT Access and Use by Households and Individuals 10 Chapter 1.

Introduction ICTs, through capacity building, technical assistance and the provision of conceptual frameworks.

This has promoted the harmonization of statistics and facilitated monitoring ICT policies in Latin America and the Caribbean.

UN Economic and Social Commission for Western Asia 39.
UNESCWA is acting as the secretariat of the Statistical Commission for Western Asia.

The Information and Communication Technology Division (ICTD) at ESCWA plays a major role with member countries in measuring the information society and their transformation towards a knowledge-based society.

In this regard, ICTD produces periodical profiles of the information society for each of the member countries and for Western Asia as a whole.
This is substantiated by a web-enabled database of ICT indicators that allow comparative analysis at the regional and global levels.

In addition, the ICT and Statistics divisions assist member countries with methodological work related to collecting ICT statistics using household and business surveys, capacity building and technical cooperation in ICT statistics.

UN Economic and Social Commission for Asia and the Pacific 40.
UNESCAP is the regional coordinator of statistical activities and is committed to a resilient Asia and the Pacific founded on shared prosperity, social equity and sustainability.

The concept of an information society potentially interacts with all these themes.

In order to respond efficiently to the challenge of measuring ICT and the information society in the region, several actors within ESCAP have joined their efforts.
ESCAP supports its members in the ICT field by providing advisory services in the formulation of ICT policies.

It also works with members of the Partnership in advocating and promoting ICT measurement, as well as through capacity-building initiatives in the field of measuring ICT and the information society.

More general work by international organizations in standard setting 41.

A number of international organizations are active in developing standards for household surveys more generally.
These are detailed in Table 1 and are likely to be relevant to countries measuring ICT household statistics.

Some refer to standardized methodologies and survey vehicles, while others refer to major classifications on which ICT household classifications are based.

42.
42.

At the international level, the coordination of the statistical work of agencies has been facilitated since 2002 by the Committee for the Coordination of Statistical Activities (CCSA).14 Among other things, it maintains a Global Inventory of Statistical Standards, which includes those on ICT statistics.

Scope and structure of the Manual 43.


The Manual focuses on the core list of ICT indicators on household ICT access and use developed by the Partnership and collected by ITU at the international level, in particular those produced by NSOs through household surveys.

All the core indicators can be found in Annex 1.

14 http://unstats.un.org/unsd/accsub-public/workpartner_ccsa.htm.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 1.

Introduction 11 Table 1.
Reference material for household surveys and standards Publishing entity Title Short description United Nations Statistics Division (2005a) Household Sample Surveys in Developing and Transition Countries 15 United Nations Statistics Division (UNSD, 2005b) Designing Household Survey Samples: Practical Guidelines 15 United Nations Statistics Division (UNSD, 2008a) Principles and Recommendations for Population and Housing Censuses Revision 2 The International Household Survey Network (IHSN, 2013)17 World Bank (2013) Living Standards Measurement Study (LSMS) Surveys International Labour Organization (ILO, 1993, 2013) International Standard Classification of Occupations (ISCO) International Classification of Status in Employment (ICSE) 19 United Nations Educational, Scientific and Cultural Organization (UNESCO, 2011) International Standard Classification of Education (ISCED) 20 Guidance on conducting household surveys in developing and transition economies, including sample design, survey implementation, non-sampling error, survey costs and data analysis.
Provides a practical reference tool for those involved in designing and implementing household sample surveys.

Information on statistical standards as well as on the conduct of population censuses.

In particular, it recommends the collection of statistics on household access to ICT as a ‘core topic’.16 Maintenance of a catalogue of developing economies’ household surveys, and the development of tools for metadata management.
The LSMS provides survey tools that are applicable to any complex household survey.

The LSMS has a broad objective of improving the quality of household statistics in developing economies, with a more specific goal being to develop methods to monitor progress in raising living levels in developing economies.18 ISCO is a classification that organizes jobs into a clearly defined set of groups according to the tasks and duties undertaken in the job.
ICSE classifies jobs held by persons, with respect to the type of explicit or implicit contract of employment of the person with other persons or organizations.

ISCED is a classification that describes the educational attainment of individuals.

The current version (ISCED, 2011) organizes educational attainment into eight levels from early childhood education to doctoral level.

15 16 See http://unstats.un.org/unsd/demographic/sources/surveys/default.htm.
Including household access to radio, TV, fixed line telephone, mobile cellular telephone, personal computer and Internet access.

These correspond to the household access core ICT indicators (HH1-HH4 and HH6).

Note that the UNSD also recommends collection of data on households accessing the Internet elsewhere (other than home).

This refers to any member of the household and is not a core ICT indicator.
The Partnership recommends that such information is collected from individuals (note that the results are not equivalent).

The UNSD publication can be found here: http://unstats.un.org/unsd/demographic/sources/census/2010_PHC/default.htm.

17 The International Household Survey Network (IHSN) is a partnership of international organizations.
Its mission is “to improve the availability, accessibility, and quality of survey data within developing economies, and to encourage the analysis and use of this data by national and international development decision makers, the research community, and other stakeholders”.

(IHSN, 2013).

For further information, see http://www.surveynetwork.org/home.

18 See http://www.worldbank.org/LSMS/ (World Bank, 2013).
See http://www.ilo.org/public/english/bureau/stat/isco/index.htm (ILO, 2013) and http://www.ilo.org/global/statistics-and-databases/statistics- 19 overview-and-topics/status-in-employment/current-guidelines/lang--en/index.htm (ILO, 1993).

20 http://www.uis.unesco.org/Education/Documents/UNESCO_GC_36C-19_ISCED_EN.pdf (UNESCO, 2011).

Manual for Measuring ICT Access and Use by Households and Individuals 12 Chapter 1.

Introduction 44.
Introduction 44.

Many aspects of survey design and processing are not specific to ICT household statistics.

While this manual broadly covers those aspects, it leaves it for other publications to provide detailed methodological advice for conducting household surveys or including ICT- related questions in Population and Housing Censuses.
References are provided to such publications, the main ones being from the United Nations Statistics Division and the World Bank:21 • • • • Household Sample Surveys in Developing and Transition Countries (UNSD, 2005a); Designing Household Survey Samples: Practical Guidelines (UNSD, 2005b); Living Standards Measurement Study (LSMS) Surveys (World Bank, 2013); and Principles and recommendations of population and housing census (UNSD, 2008a) Rev 2.22 45.
Following the recommendations of the 10th World Telecommunications/ICT Indicators Meeting (WTIM-12), Chapter 2 of the Manual focuses on the coordination of the compilation of ICT household statistics at the national level, which is considered a major issue for the development of ICT statistics.

The chapter looks at the roles of data producers, users and providers/respondents in a national context and presents models and mechanisms for their coordination.

46.
46.

Chapter 3, Planning and preparation for ICT household surveys, describes the range of preparatory activities for the measurement of access to and use of ICT, especially using sample surveys.

It explains planning, budgeting and other preparatory work.

47.

Chapter 4, Statistical standards and measurement topics for ICT household statistics, addresses statistical standards for ICT household statistics.
It introduces the core ICT household indicators and associated classificatory variables that describe household and individual characteristics.

In order to assist countries that wish to collect statistics beyond the core list, the chapter considers other ICT household measurement topics, such as e- commerce, trust in the online environment, child online protection, impacts of ICT access and use, and gender-sensitive indicators.
It also discusses time-related issues such as survey frequency, reference periods and the value of time series.

48.

Chapter 5, Data sources and collection techniques for ICT household statistics, provides information on the types of surveys and data collection techniques that statistical agencies may use to measure access to, and use of, ICTs by households and individuals.

49.
49.

Chapter 6, Question and questionnaire design for ICT household surveys, explores the principles of good question and questionnaire design and issues relevant to ICT household measurement.

It presents model questions for the core indicators and a logical structure for a stand-alone questionnaire or a module of questions for measuring the core indicators to be inserted in a broader household survey.

50.
50.

Chapter 7, Sampling for ICT household surveys, considers issues of survey scope and coverage, target populations and survey frames, statistical units to be used, and sample design and selection.

51.

Chapter 8, Data processing for ICT household statistics, deals with the conduct of surveys and processing of survey data, including data entry, editing, imputation and data weighting.

It also discusses how the core ICT household indicators are calculated.
21 In addition, the International Household Survey Network (http://www.ihsn.org/home/index.php?q=tools/overview) provides methodological materials for different social surveys across the world.

22 See http://unstats.un.org/unsd/demographic/sources/census/docs/P&R_%20Rev2.pdf.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 1.

Introduction 13 52.
Introduction 13 52.

Chapter 9, Data quality and evaluation for ICT household statistics, discusses issues relating to data quality, including sampling and non-sampling error, data quality assurance frameworks, reporting and evaluation.

53.

Chapter 10, Dissemination of ICT household data and metadata, looks at dissemination of ICT household data and metadata and presents basic tabulation plans.

It also describes the data collection and dissemination efforts of ITU.

54.
54.

There are five annexes as follows: • • • • • Annex 1 provides the entire Partnership’s core list of ICT indicators (as revised in 2013).

Annex 2 presents the ITU model questionnaire (for a stand-alone survey or a module in an existing household survey) for collecting statistics for the core indicators on household access to, and individual use of, ICT.

Annex 3 provides examples of imputation and weighting, and complements Chapter 8.
Annex 4 provides an extract from the questionnaire ITU sends to countries to report on the core ICT household indicators.23 Annex 5 is a glossary of terms and abbreviations.

55.

The Manual concludes with a bibliography, including references to online documents and websites.

23 Updated as of 2013.

Manual for Measuring ICT Access and Use by Households and Individuals 14 Chapter 2.

Coordination among national stakeholders in ICT measurement 15 Chapter 2.
Coordination among national stakeholders in ICT measurement 56.

This chapter considers the roles of stakeholders in the national statistics system and issues relating to coordination and planning of ICT surveys at the national level.

It then describes models and mechanisms for coordination that have been used in different national statistical systems.

57.

Given the cross-cutting nature of ICTs, permeating all sectors of society, statistical data collection and dissemination may be fragmented.
Because of the variety of existing ICT data sources, coordination and cooperation among data producers are fundamental to the production of high-quality official ICT statistics.

Otherwise, there is a risk that published data will be inaccurate or inconsistent, leading to incorrect policy decisions.

Other benefits of coordination include reduction of the overall response burden for data providers, avoidance of duplication of effort and optimization of the efficient use of resources.
It also helps to identify existing data gaps, to harmonize objectives and priorities between the different stakeholders, and to improve monitoring and evaluation of the ICT statistical production process.

Coordination among statistical agencies within countries is one of the ten Fundamental Principles of Official Statistics,24 adopted by the UN Statistical Commission in 1994.
The objective of this chapter is to describe ways and means of establishing a national coordination mechanism to ensure the efficient and timely production of ICT indicators.

Stakeholders in the national statistics system and coordination of the production of statistics 58.

This section describes the different stakeholders in the national ICT statistics system, more generally, and in particular on ICT household statistics.
It considers the types of mechanisms that could be put in place for ensuring coordination, including planning statistical activities.

59.

Coordination occurs among producers of ICT statistics, between producers and users, and between producers and data providers who are the source of primary information.

The first group (data producers) is the main audience for this manual.

60.

ICT household statistics are demanded by a variety of users.
Since survey-based ICT statistics is a relatively new field in most developing economies, the initiative to produce ICT data often originates from a demand by policy-makers such as ministries responsible for ICT and telecommunication regulation agencies.
Government policy-makers responsible for telecommunications and ICT policy will usually be the most influential data users, although users from business, the non-profit sector and academia may also have important input and their experience should be taken into consideration.

Mapping the users (i.e.

identifying the different users and their needs) is a fundamental step in planning for data collection.

In line with the Fundamental Principles of Official Statistics, the 10th World 61.
Telecommunication/ICT Indicators Meeting (2012) 25 recognized that coordination among statistical agencies (NSOs) and other stakeholders within countries is crucial in improving the availability and quality of ICT statistics.

Coordination should cover the phases of planning, producing and disseminating ICT statistics.
In particular, coordination among NSOs, telecommunication regulatory authorities and ministries responsible for ICT policies is a 24 25 See http://unstats.un.org/unsd/methods/statorg/FP-English.htm.

See http://www.itu.int/en/ITU-D/Statistics/Pages/events/wtim2012/default.aspx.

Manual for Measuring ICT Access and Use by Households and Individuals 16 Chapter 2.

Coordination among national stakeholders in ICT measurement prerequisite for the development of a quality ICT household statistics system.
Other institutions dealing with social issues (such as education and health) should be involved where necessary for developing sector policies based on the adoption and use of ICT.

In a national context, there are three main groups of stakeholders involved in the ICT 62. statistics system (see Figure 2).
They are: • • • data producers, especially NSOs, but in some countries also the national telecommunication regulatory authorities, sector ministries, and non-official sources such as private companies, universities and research centres; data users, including policy-makers from sector ministries and regulatory authorities dealing with ICT and/or telecommunications, and other users, such as international organizations, private businesses, academia, media and the general public; and data providers/respondents, mainly individuals from sampled households for the purposes of this manual.
Figure 2.

Stakeholders in the ICT statistics system Statistics producers Statistics users Sector ministries Academia Consultants Media, journalists General public National regulatory agencies National statistical offices Private users ICT industry Other business Policy-makers NRAs International organizations Information providers Households, individuals, businesses, schools, government institutions, etc.

63.
63.

The multiplicity and diversity of producers of ICT statistics require strong coordination among them.

In addition, users may face problems in assessing the relative merits of different sources, therefore, the establishment of relationships with users is another important component of the national coordination system.

Finally, the relationship with information providers (individuals and households) is to be considered.
The main topics relating to coordination among stakeholders are: • • • the coordination between data producers covering legal, technical and resource allocation aspects; the responsiveness of producers to users’ needs for information, ensured by user consultation, established user-producer relationships and forums, user-orientated dissemination policies (mainly of NSOs), and efficient techniques; and the concern of data producers for a sound relationship with information providers (households and individuals), with respect to their privacy and minimization of response burden.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 2.

Coordination among national stakeholders in ICT measurement 17 64.

National statistical offices (NSOs) play a central role in the production of official statistics in all countries.

They are generally entitled by law to collect primary information from individuals, households, business and other organizations for the production of statistics, subject to scientific principles and legal requirements of confidentiality.
In the area of ICT statistics, they usually collect data through household and business sample surveys, occasionally through population and economic censuses, or from administrative data provided by other institutions.
NSOs operate under statistical legislation which sets up governance of the national statistical system, providing for mechanisms for coordination, the the obligation of response, and establishing a survey protection of confidentiality, programme, which may run over a number of years (referred to in this manual as a ‘multiyear programme’).
In most countries, NSOs adhere to the UN Fundamental Principles of Official Statistics.26 NSOs have different levels of resources, but in general, they have the necessary expertise for data collection and analysis, and often possess a network of field offices with the capacity for mobilizing enumerators and supervisors for the implementation of large, nationwide surveys.

telecommunication regulatory agencies for 65.

National authorizing operating licenses for the telecommunication sector.
In many countries, they are mandated to analyse and monitor the sector, thus explaining their interest in the production and dissemination of ICT indicators.

NRAs maintain a register of licenses that can be used to identify sources of telecommunication/ICT indicators (e.g.

service providers).

In general, data are collected for administrative purposes, but in some countries, NRAs have carried out ICT surveys (with varying levels of coordination with NSOs).
These institutions have substantial expertise in technical matters related to the telecommunication sector.

(NRAs) are responsible 66.

Sector ministries (or sector government agencies and multistakeholder organizations in some countries) responsible for telecommunications, science and technology, or innovation collect administrative data in different areas, and may be a source for ICT indicators.
As with NRAs, in some countries they have carried out ad hoc surveys of businesses and households on access to and use of ICT, with different levels of coordination with the NSO.

These institutions may have substantial expertise in technical matters related to ICT, but in general they will be more focused on the analysis and use of information.

67.

Other line ministries may also have an interest in collecting ICT-related indicators.
They include ministries of education (statistics on ICT in education and ICT skills), ministries of labour (statistics on ICT sector production and employment) and ministries of health (statistics on ICT in health).

So far, data collection in those areas is limited, particularly in developing economies, while at the same time demand for data is growing.

68.

In most cases, NRAs and ministries of ICT can be considered as users but also as producers of ICT data.
The coordination with the NSO is of the utmost importance.

In some countries, specific agencies other than the ones mentioned above have been mandated or created to collect and disseminate national ICT statistics.

This could be the case where NSOs have little subject matter experience, where resources from other sources are available, or where countries have a particularly strong interest in monitoring their ICT development.

Examples include Brazil (see Box 7).


These agencies have various levels of cooperation and coordination with NSOs.

69.

Other potential producers of ICT statistics and indicators include private companies (in the ICT sector or providing market analyses) and research centres and universities.
While private organizations are often very successful in publishing results and receiving the attention of the media, they do not always adhere to the principles of official statistics, to international statistical standards or may not have the capacity to carry out nationally 26 http://unstats.un.org/unsd/methods/statorg/FP-English.htm.

Manual for Measuring ICT Access and Use by Households and Individuals 18 Chapter 2.
Coordination among national stakeholders in ICT measurement representative large surveys.

Universities and research centres may suffer the same limitation, but are well placed to provide in-depth analysis of the data.

Issues in coordination among producers 70.

The role of different government agencies in data collection is generally established by national statistical legislation, which also sets up the processes of planning the statistical activity.
In most countries, there is a multiyear statistical programme that specifies which operations are to be carried out in the medium-term (generally, 4 or 5 years) and which government institutions (NSO or other) are responsible for their implementation.

71.

The distribution of activities in ICT data collection is generally related to access to respondents and the responsibilities of the involved institutions.
Indicators on ICT infrastructure, tariffs and subscriptions are often provided by NRAs, which have access to administrative data from operators.

Statistics compiled from survey data from businesses and households are usually produced by NSOs, but in some countries they have also been produced by other institutions such as NRAs, ministries for ICT, or other entities charged with this task.
Data on access to and use of ICT in schools or health facilities may be collected by ministries of education or health respectively.

72.

In some countries, ICT data collection has been initiated by government institutions other than NSOs, for instance, ministries or other governmental agencies that promote ICT uptake, and regulatory agencies.
While these institutions may have technical expertise on the subject matter, their ability to conduct a household survey based on sound methodology is likely to be limited unless they closely collaborate with NSOs, which are likely to have access to statistical infrastructure, such as a master sample frame (e.g.
a list of randomly selected households that is representative of the whole population), access to a country-wide network of experienced interviewers, skilled staff with expertise in data treatment and analysis, and the legal mandate for these types of activities.
In addition, there is uncertainty regarding the sustainability of data collection if conducted by the regulator or ministry, as it is not usually included in their regular programme of work and often done just to gauge the size of the market at one point in time.

The risk of obtaining low quality and non-comparable statistics (with international data or with other national household surveys) should not be underestimated.

In addition, coordination in such cases can cover the dissemination phase (e.g.
joint publications) and the use of resources (joint funding, data collection network, IT equipment, etc.).

Box 2 describes the cooperative arrangements for collecting data on access to and use of ICT by businesses, households and individuals in the Sultanate of Oman.

Box 2.
Box 2.

Cooperation between the Information Technology Authority and the National Centre for Statistics and Information in the Sultanate of Oman The Information Technology Authority (ITA) of Oman has established a collaboration protocol with the National Centre for Statistics and Information (NCSI) to implement surveys on access to and use of ICT by businesses (2011) and households and individuals (2013).
In both cases, the samples are extracted from the business register or the enumeration area listing provided by the NCSI, while the questionnaire is designed by ITA.

Data collection is carried out either by staff of the NCSI or by an external contractor, under the supervision of ITA.

Data processing is partially carried out with resources from the NCSI (data cleaning, calculation of sample weights) and from ITA (data analysis and tabulation).

Dissemination is carried out by ITA.


International comparability is ensured by the use of international standards in the preparation of the questionnaire and the compilation of indicators, which include the core ICT indicators developed by the Partnership on Measuring ICT for Development.

Source: ITA Oman, http://www.ita.gov.om/ITAPortal/MediaCenter/Document_detail.aspx?NID=66.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 2.
Coordination among national stakeholders in ICT measurement 19 It is therefore strongly recommended that ICT statistics are collected by NSOs (defined 73. to include all government statistical agencies, as described in Chapter 1) or in close collaboration with them.

There are numerous benefits to this, including the capacity of NSOs to carry out nationwide, representative household surveys and their links with national and international statistical systems, some of which may include ICT questions.
Most NSOs are also supported by legislation designed to protect data and, in many cases, to mandate provision of data, thereby enhancing response rates.

They have the necessary technical experience in data collection and generally provide credibility of the official statistics they produce.

In some countries, NSOs will also have a coordination role that confers advantages in terms of technical and legal coordination, as well as resource allocation.
In addition, like other sectoral statistics, ICT data collection could be integrated in regular household surveys, thereby ensuring sustainability of data collection.

74.

The expertise available in ministries of ICT and other agencies should be taken into account when designing data collection instruments.
In particular, decisions on inclusion of ICT topics, the adaptation of international recommendations to national standards (such as the types of Internet connection available in the country), and the analysis of results should be carried out in close collaboration with specialized agencies.

Models and mechanisms for coordination 75.

This section presents models and mechanisms for coordination among producers, between users and producers, and between producers and informants.
The main mechanisms introduced are: inter-institutional commission or working groups, multiyear programming mechanisms and mechanisms for consultation with users.

With respect to the relationship between ICT statistics producers and informants, the issues of data protection and confidentiality, and response burden reduction are addressed.

76.

National statistical legislation may provide for coordination mechanisms among data producers.
These could include: formal inter-institutional commissions, technical working groups, bilateral arrangements for the distribution of tasks, multiyear planning of statistical operations and arrangements for funding the production of ICT statistics.

In some countries, more informal arrangements can work, especially in the initial phases of collection of ICT statistics.

Examples of informal arrangements can include conversations between technical staff, or joint work on specific phases of the design.

77.
77.

In many countries, a national statistical council (or equivalent) has been established by statistical legislation, with representatives of all ministries and statistical agencies, where the methodology and quality of statistical operations are discussed together with general aspects such as statistical ordinances, legislation and arrangements for data exchange between administrations, protection of confidentiality and response burden.
27 With respect to ICT statistics, the national statistical council: • • could provide a forum to discuss the major needs in ICT statistics and the distribution of tasks among the different statistics producers.

For this, a subject matter working group may be established, where possible under the umbrella of the national statistical council, and detailed methodological aspects of ICT statistics discussed.
The working group could include representatives of the NSO, the ministry responsible for ICT, the telecommunication regulation agency – as both producers and users of ICT statistics – and possibly researchers and experts in ICT issues.

should ensure that an appropriate legal framework enables the collection of ICT statistics, ensures their status as official data and ensures their funding.

27 See Box 4 for the case of the Philippines.


Manual for Measuring ICT Access and Use by Households and Individuals 20 • Chapter 2.

Coordination among national stakeholders in ICT measurement should review the multiyear programming of surveys, to accommodate ICT questions in planned surveys when possible, or provide for the implementation of specific ICT surveys (see below).

78.
78.

When a national statistical council (or equivalent) does not exist or is not operational (for administrative or other reasons), an inter-institutional task force or working group may play the role, at a more technical level, of a forum to discuss implementation details for ICT statistics.
This working group may be attached to the NSO, or if this institution does not have the main responsibility in producing ICT statistics, to a high-level administrative unit in the government (such as the ministry responsible for ICT or the presidential office).

See Box 3 for an example of this type of entity in Lebanon.

Box 3.
Box 3.

Inter-institutional collaboration in Lebanon for ICT statistics The Ministerial Committee for Information and Communication Technology (ICT) for Lebanon was established based on a resolution issued by the President of the Council of Ministers.

In 2010, an ICT Unit was formed at the Presidency of the Council of Ministers with the aim of coordinating the implementation of the national ICT strategy and liaising between various stakeholders to collect Lebanon ICT indicators for the year 2011.
The ICT Unit developed, with the Central Administration for Statistics (CAS), the framework for ICT indicators that consisted of the minimum set of statistics that Lebanon has to compile in order to measure the digital economy.

This framework was approved by various private and public stakeholders at a workshop.
The framework was based on the recommendations of the Partnership on Measuring ICT for Development and its goals are to measure the policy effect of the e-strategy on the ICT sector and the economy at large, and to address ICT investments throughout the economy, the size of the ICT sector, e-government, and R&D.

It was recommended that the ICT indicators be populated once a year, and that results be disseminated to stakeholders and to international organizations.
The ICT Unit collected the indicators from the Telecommunication Regulatory Authority (TRA), the Office of the Minister of State for Administrative Reform (OMSAR), the National Council for Scientific Research, and the Center for Educational Research and Development.

The ICT Unit commissioned national stakeholders to conduct ICT surveys.
Two surveys were conducted in 2011 to compile ICT indicators for household and individual use, and ICT indicators for the business sector; and one survey was conducted for ICT indicators for the education sector.

All surveys were based on international methodologies.

Source: Presidency of the Council of Ministers, Lebanon.

Communication to the 10th WTIM.

79.
At the technical level, the following issues may be discussed among statistical producers: • • • • establishment of common definitions of ICT indicators and relevant classifications, based on international standards but adapted whenever necessary to national conditions; establishment of population frames for households and business surveys; agreements on procedures for the preparation and dissemination of data and metadata, including appropriate joint publications; and time scheduling of different data collections in order to optimize the use of resources and reduce response burden.
Multiyear planning as a mechanism for coordination 80.

Most national statistical systems are governed by a multiyear programme for the production and dissemination of official statistics.

Such a programme should include and describe the implementation arrangements for ICT statistics.
The range of statistical operations should cover the different domains, such as ICT infrastructure statistics, surveys of businesses and households (alternatively the inclusion of ICT access and use modules in Manual for Measuring ICT Access and Use by Households and Individuals Chapter 2.

Coordination among national stakeholders in ICT measurement 21 other surveys).

See Box 4 for an example of multiyear programming of ICT statistics in the Philippines.

81.
81.

Many developing economies are still in the process of preparing National Strategies for the Development of Statistics (NSDS), 28 which are short-term or medium-term programming instruments in the national statistical system.

Countries in this situation should consider the explicit inclusion of ICT surveys in NSDS in order to ensure coordination with other household surveys and sustainability over time.

Box 4.
Box 4.

Information society statistics in the Philippines The improvement of the state of ICT in the country is part of the Philippine Development Plan (PDP) 2011– 2016.

ICT development strategies have been designed primarily to support the economic sectors and enable equitable access to infrastructure and social services.
More specifically, the PDP has been set to develop ICT infrastructure that spurs social and economic activities and encourages innovation to support achievement of inclusive growth and reduced poverty.
The national statistical system of the Philippines is coordinated by the National Statistical Coordination Board (NSCB), which, among other activities, spearheads the formulation of multiyear programming of statistical development activities – called the Philippine Statistical Development Program (PSDP), of which the latest version is for 2011–2017.
Under the NSCB, is the Inter-Agency Committee on ICT Statistics, composed of representatives of the National Economic and Development Authority, the Department of Budget and Management, the Department of Science and Technology, the Central Bank, the National Statistics Office,29 the National Telecommunications Commission, the National Computer Center, the Trade Union Congress of the Philippines, the Business Processing Association of the Philippines, the IT Foundation of the Philippines, and the NSCB.
The compilation of comprehensive and coherent information society statistics in the Philippine Statistical System is still a work in progress.

The previous PSDP 2005–2010 included a full chapter on ICT statistics.

It linked the production of statistics to the existence of national strategies for ICT and broader national development plans, and established a framework that built on international experiences (OECD, ASEAN) in selecting the main indicators.
For access and use by households, the PSDP recalled some core indicators, plus other relevant ones for national policies.

While no specific ICT household survey was planned, the plan identified sources for relevant ICT indicators, such as: • The Census of Population and Housing (CPH) can provide, every 10 years, the number of households with radio, TV, fixed/mobile telephone, computer, ICT related occupation and educational status of household members.
• The Family Income and Expenditure Surveys can provide, every 3 years, expenditures on telephone bills and Internet subscriptions, as well as the same indicators mentioned above for the CPH.

• The Labor Force Survey provides data on labour and employment for ICT-related industries on a quarterly basis.
A number of key developments in ICT statistics in the PSDP 2005–2011 included institutional, methodological and implementation activities, as follows: • institutional activities: establishing the Interagency Committee on ICT Statistics and conducting a Consultative Workshop on the Definition, Framework and Indicators for the Measurement of e- Commerce; • methodological activities: defining standards for concepts to be measured; and • implementation of surveys and compilation of indicators: Survey on Information and Communications Technology, Survey of IT-Business Process Outsourcing Services, household data on ICT-related indicators and e-government indicators.
Source: Philippine Statistical Development Program 2011–2017 Volume 1, http://www.nscb.gov.ph/pss/psdp/20112017/; Philippine Statistical Development Program 2005–2010, http://www.nscb.gov.ph/pss/psdp/20052010/PSDP%202005-2010.pdf; Annual Report 2009 of the National Statistical Coordination Board, http://www.nscb.gov.ph/download/NSCB2009AnnualReport.pdf.

82.

A multiyear plan should specify which institutions are responsible for each statistical operation.
The distribution of tasks with respect to ICT statistics can be based on the domain 28 For a more complete description and materials for the preparation of a NSDS, please see the dedicated PARIS21 website at http://paris21.org/NSDS.

29 The National Statistics Office (NSO) is the major statistical agency responsible for collecting, compiling, classifying, producing, publishing, and disseminating general-purpose statistics as provided for in Commonwealth Act (CA) No.

591.
591.

More specifically, the NSO is tasked to prepare for and undertake all censuses on population, agriculture, commerce, and industry (Section 2, C.A.

591; Section 1, Batas Pambansa Blg.

72); and conduct statistical surveys.

Manual for Measuring ICT Access and Use by Households and Individuals 22 Chapter 2.

Coordination among national stakeholders in ICT measurement of interest (households, businesses, price statistics, etc.)
or on the type of operation (statistics from administrative registers, surveys, censuses).

It is important that definitions and concepts are as coherent as possible across statistical operations, even if the institutions responsible are different.

83.
83.

The planning process for the collection of statistics on the access and use of ICT by households and individuals should take into account a time frame based on the programming of household surveys, population and housing censuses and business surveys: • • • Population and Housing Censuses (PHC) are generally carried out only once in every decade, due to their high cost.
They are necessary to update population distribution figures, as well as the statistical infrastructure for household surveys in terms of geographical distribution of the population and exhaustive listing of dwellings.

The use of PHC for collecting ICT statistics has limitations due to low frequency and a small number of possible questions.
Large household surveys that take place with low frequency (such as income and expenditure surveys) require intensive labour input from NSOs and may absorb most human resources, especially in low-resource NSOs.

They may include modules on the access and use of ICT (see Chapter 5 for a comparison between stand-alone surveys and modules in existing surveys).
Smaller household surveys with higher frequency (such as living conditions surveys or labour force surveys) may provide a good vehicle to investigate rapidly changing phenomena such as ICT adoption.

84.

For other ICT statistics, a multiyear programme should consider the frequency and coverage of existing statistical operations (such as business surveys), the expertise and competencies of different institutions and the resources available.
In any case, NSOs should avoid implementing ICT-related statistical operations without properly programming their implementation in the frame of a programme that takes into consideration the needs of ICT statistics users, in particular, policy-makers.

In addition to multistakeholder mechanisms, bilateral agreements should be arranged between producers (e.g.

between the NSO and the NRA/Ministry of ICT) for detailed implementation aspects of the survey, including the funding of operations.
Different survey activities could be undertaken by different actors.

For instance, data collection may be undertaken and supervised by the NSO using external funding, while questionnaire design, testing and sample design could be directly provided by the NSO.
Mechanisms for user consultation It is recommended that representatives of data users work closely with data collection 85. agencies (NSOs and others) to ensure the relevance of ICT statistics programmes, that is, that they satisfy users’ needs and are useful for decision-making, Relationships between users and producers should be explicitly considered in national statistical coordination mechanisms.

86.

Users from the government sector (e.g.


ministries for telecommunication/information society) should take into account their information and data needs when drafting national ICT strategies.

This would allow statistics producers to better identify the needs of institutional users.

87.
87.

In order to identify users, especially from the private sector, it may be useful for data collection agencies to make a list of existing business associations with an interest in ICT, such as: Manual for Measuring ICT Access and Use by Households and Individuals Chapter 2.
Coordination among national stakeholders in ICT measurement 23 • • • ICT sector associations (for instance, ICT manufacturing industry associations, telecommunication associations); ICT market studies providers; and organizations with a more general profile (such as chambers of industry and commerce).

88.

The dialogue with users can be implemented in stages, first establishing the purpose and the process, then clarifying the information demand.
Issues that may be relevant in a detailed dialogue with users include the definition of target populations, level of data disaggregation, level of accuracy needed, frequency of data collection and timeliness.

Mechanisms for the coordination between users and producers can have different degrees of formalization.

In countries where ICT data collection is new, the mechanisms may be rather informal in the first phase.

As ICT data production becomes more regular, more formal mechanisms could be put in place.
89.
Informal mechanisms for consultation with users that can be considered are: • • • organizing open events to present survey plans and results (when available) to motivate users to provide feedback for the next surveys; carrying out user needs and satisfaction surveys, asking about specific dimensions of data quality, such as, topics and concepts, detail of breakdown, timeliness and access; and participating in ICT sector and academic events to present, promote and get feedback on statistical plans with respect to the issues discussed.
90.

Formal mechanisms for consultation with users can be set up at the high, decision- making level, or at the technical level.

At the decision-making level, in most countries, a national statistical council comprising representatives of statistical producer agencies and a variety of users (such as academia, chambers of commerce, business associations, trade unions, NGOs and the media) is established by statistical legislation and has a consultative role within the national statistical system.
ICT household statistics may be discussed in the framework of the national statistical council (probably together with other ICT statistics).

91.

At the technical level, and particularly with users from government institutions (sector ministries, NRA), a useful mechanism for coordination is the establishment of a working group to discuss technical issues that may affect the future use of statistics.
These could include survey scope and coverage, level of disaggregation and accuracy, and dissemination formats and channels.

Participants to this type of working group may also include representatives from research centres, universities and the ICT sector (ICT market analysts in particular).

92.

A useful tool for informing users about the quality of ICT statistics is the dissemination of quality reports; this is discussed in Chapters 9 and 10.

93.
93.

In some countries, a national observatory for the information society has been established (see Spanish and Moroccan experiences described in boxes 5 and 6).

This type of entity collects and collates data from different sources, prepares specific publications (such as sector reports) and disseminates ICT indicators via a centralized website.

The arrangements for such an observatory may include the participation of users and producers in its governing or advisory bodies.
Other examples include the Brazilian Center of Studies on Information and Communication Technologies (CETIC), which holds regular consultation meetings with data users before planning and designing future ICT surveys (see Box 7).

Manual for Measuring ICT Access and Use by Households and Individuals 24 Chapter 2.

Coordination among national stakeholders in ICT measurement Box 5.
National Observatory of the Telecommunications and the Information Society in Spain Spain has established the National Observatory of the Telecommunications and the Information Society (ONTSI) under the auspices of the Ministry of Industry, Tourism and Trade.
ONTSI elaborates reports, collects and disseminates data from private and public sources on different topics (citizens and households, the business sector, education, digital content, health, city planning, public administration, the ICT sector, etc.).
The main statistical sources for information include the surveys on ICT access and use in households and in businesses carried out by the National Statistical Institute (INE), economic data from telecommunication operators collected by the said Ministry, price information collected by the National Telecommunication Commission (the regulatory agency), telephone network and broadband coverage data from the State Secretary for Telecommunications and the Information Society, as well as ad hoc studies by ONTSI.
Source: Contribution document to the 10th World Telecommunication/ICT Indicators meeting: http://www.itu.int/ITU-D/ict/wtim12/documents/cont/005-E_doc.pdf.

Box 6.

Moroccan Observatory of Information Technology and Communication (OMTIC) The National Strategy for the Information Society and Digital Economy (Morocco 2013) aims to place Morocco in the global knowledge economy.
State administrations, businesses and citizens, are focused on the definition of priorities and actions having high impact and have set ambitious goals to achieve by 2013.

The Ministry of Industry, Commerce and New Technology has established a Statistics Directorate, which, through its Moroccan Observatory of Information Technology and Communication (OMTIC), has become a key mechanism to achieve its missions.
The OMTIC aims to be a tool for: • unifying the various observatories and surveys conducted by its partners, either within the government or professional associations; • monitoring and evaluating sector strategies; and • anticipating and monitoring changes in the ICT environment.
The OMTIC is responsible for: • defining, in collaboration with its partners, quantitative and qualitative indicators of the sector; • collecting, aggregating and analyzing indicators; • generating statistics and conducting thematic and sectoral studies for indicators not produced by the partners; • disseminating and publishing statistics and aggregated indicators and the results of surveys and studies, dashboards, information newsletters and annual diagnostics on ICT; • coordinating statistical data and contributing to the statistical system of the sector; • managing the register of businesses and establishments in this sector; • managing and operating the statistical databases on the sector; and • providing business intelligence, monitoring and evaluation of strategies in this sector.
Source: http://www.omtic.gov.ma/OMTIC/Pages/Apropos.aspx.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 2.

Coordination among national stakeholders in ICT measurement 25 Box 7.
The Brazilian Center of Studies on Information and Communication Technologies (CETIC.br) The Centre of Studies on Information and Communication Technologies (CETIC.br), a department of the Brazilian Network Information Centre (NIC.br), was created in 2005 to tackle the challenge of periodically producing, organizing, analyzing and publishing data on the access and use of the Internet in Brazil.
NIC.br is a private non-profit organization, created to implement decisions from the Brazilian Internet Steering Committee (CGI.br).

Comprised of members from the government, the corporate sector, non-profit organizations and the academic community, the CGI.br represents a unique Internet governance model for the effective participation of society in decisions involving network implementation, management and use.
CETIC.br conducts regular national surveys on the following topics: ICT Households; ICT Enterprises, ICT Kids Online Brazil, ICT in Education, ICT in Health, ICT e-Government, ICT Providers and ICT Non-profit Organizations.
In the process of collecting, organizing and disseminating information about ICTs, CETIC.br follows the standards and recommendations from the Partnership on Measuring ICT for Development, including methodological references and data collection instruments from ITU, Eurostat, OECD and UNCTAD.
The ICT Survey process at CETIC.br follows the principles of multilateralism, participation and transparency by fostering the participation and collaboration of an extensive network of academics and experts from government, the corporate sector and non-profit organizations who are renowned not only for their excellence in research methodology, but also for their expertise regarding the study of the use and impacts of ICTs.
Each ICT survey relies on a specific group of experts from different segments of society who specialize in the theme of the survey.

This group usually meets twice during the survey process, once during the planning phase, in order to validate methodology, indicators and questionnaires; and later again during the stage of data analysis to provide input for interpreting results.
The results of the surveys and their microdata base are made available to the expert groups under a confidentiality and ethical use agreement for data use.

Engaging different stakeholders in the surveys conducted by CETIC.br reflects the multistakeholder model for Internet Governance in Brazil at CGI.br and is considered key to granting legitimacy of the survey process.

For more information on CETIC.br surveys and publications, see http://www.cetic.br/english/.

Relationships with data providers 94.


Data providers (respondents) are very important players in the statistical system.

In the ICT household statistics system, respondents are individuals in households.

Without their cooperation, data would be inadequate in terms of either/both quality and quantity.

It is important that NSOs recognize the contribution of respondents and put the necessary effort into gaining their trust and cooperation, by developing close collaborative relationships with them.
At the most obvious level, this entails making the respondent’s job easier for them by providing coherent and understandable survey material, including questionnaires and instructions.

This is further discussed in Chapter 6.

95.

The three main issues with respect to data providers, which data producers should take into account, are: cooperation in providing response, reduction of response burden and protection of confidentiality.
As the response burden decreases, the probability of non- response will also decrease, thus improving the quality of the aggregated data by reducing possible biases due to non-response.

96.
Examples of actions that can improve the cooperation of respondents in providing responses are the following: • • providing public (and, whenever possible, personalized) information to respondents before the interview on the objectives and importance of the survey, and the future use of the results (for instance, where the first stage of sampling is by geographic area, there could be localized advertising in areas that have been selected in a household survey); carefully designing the interview process in terms of questionnaire design, filter questions, language used; Manual for Measuring ICT Access and Use by Households and Individuals 26 Chapter 2.
Coordination among national stakeholders in ICT measurement • • training interviewers in the subject matter (ICT issues) so that concepts are clearly transmitted while minimizing the risk of interviewer bias; and carefully planning the timing of interviews, asking for the most suitable schedule for visiting the household.

97.

As a rule, it is important to minimize the burden on respondents of surveys.

The potential benefits to NSOs of doing this include higher response rates and better data quality.
This issue is also addressed in Chapter 6.

Examples of actions that can reduce the burden of response are the following: • • • • carefully selecting the sample of households so that samples for different surveys do not overlap; limiting questionnaires to content that reflects the requirements of data users; controlling the duration of interviews; and using auxiliary information whenever possible (such as administrative registers).

98.
98.

While many NSOs work in a legal framework that makes provision of statistical data mandatory,30 cooperation may be better if such legislation is used sparingly.

99.

The legal framework of NSOs will also generally ensure the confidentiality of data provided by individuals.

It is very important that protection of individual statistical data is assured and is communicated to respondents.

100.
100.

Measures to protect confidential data include the confidentialization of survey registers and their secure storage, as well as legal measures to ensure adherence to confidentiality requirements by the staff of data producer institutions (e.g.

formal commitment, sanctions in case of breach).

30 The legal basis of a large number of NSOs can be found here: http://unstats.un.org/unsd/dnss/kf/LegislationCountryPractices.aspx.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 3.

Planning and preparation for ICT household surveys 27 Chapter 3.

Planning and preparation for ICT household surveys 101.

Survey planning and preparation is an obvious prerequisite to survey success and cost minimization.
As discussed in the previous chapter, widespread and extensive consultation and coordination with policy-makers and other stakeholders (users and producers of statistics) will help to ensure that the final product is of optimum relevance to users’ needs.

It will also help build support for the project that may assist with fund-raising or publicity.

102.

This chapter looks at planning considerations, budget and cost issues, and other preparatory activities.
More detailed information about planning household surveys can be found in the UNSD handbook Household Sample Surveys in Developing and Transition Countries (UNSD, 2005a).

For a useful checklist of quality aspects of the survey planning process, readers can consult the European Self Assessment Checklist for Survey Managers (DESAP).

31 This chapter focuses more on specific aspects of ICT household survey preparation.

103.
103.

A useful model for considering all the phases of a statistical operation is given by the UNECE Generic Statistical Business Process Model (GSBPM, see Figure 3).32 The GSBPM is intended to guide the planning of surveys and other statistical operations by systematically considering all processes and the workflow from initial preparatory steps to dissemination, documentation and archiving.

Preparatory activities include the specification of needs and the establishment of survey procedures.

Figure 3.
Figure 3.

Scheme of the Generic Statistical Business Process Model (GSBPM) PLANNING OPERATION EVALUATION Specify survey contents Establish survey procedures Check survey outputs Evaluate feedback metadata Frame creation Sampling Measurement Data preparation Observation and register creation Estimation and analysis Presentation and dissemination Source: Information Systems Architecture for National and International Statistical Offices – Guidelines and Recommendations, United Nations, 1999.

104.
104.

The broad assumption made in this manual is that ICT household surveys will generally be conducted by NSOs (broadly defined to include all government agencies that collect official statistics).

NSOs will generally be more experienced in conducting household surveys than other organizations and will have access to the statistical infrastructure required 31 32 See http://epp.eurostat.ec.europa.eu/portal/page/portal/quality/documents/desap%20G0-LEG-20031010-EN.pdf.
http://www1.unece.org/stat/platform/display/metis/The+Generic+Statistical+Business+Process+Model.

Note that the terminology used in this model is not necessarily the same as used in this manual, but the areas covered are similar.

Manual for Measuring ICT Access and Use by Households and Individuals 28 Chapter 3.

Planning and preparation for ICT household surveys (including skilled staff, survey frame information, conceptual and methodological knowledge and computer systems).
ICT household survey planning 105.

A worthwhile discipline in planning any statistical survey is to constantly review the purpose for which the eventual results will be used and what types of public policy or other decisions will rely on the results.

As it is common for the release of statistics to trigger further demand for data, planners need to contemplate whether, and when, they are prepared to undertake follow-up data collection.
Given the rapid change in the state of ICT, there is likely to be a demand for regular surveys (whether stand-alone ICT household surveys or questions included in other household surveys), 33 and this should be considered in the context of a multiyear work programme (see Chapter 2).

106.

A likely outcome of the planning stage is that priorities will be reassessed and changes made to aspects of the survey, such as its purpose and objectives, and subsequent stages such as survey design.

107.
107.

A household survey is generally a complex and costly undertaking.

Good planning will almost certainly lead to a better result – in terms of data quality, cost and timeliness.

Broad areas to consider early in the planning stage are: • • • • • Mechanisms for cooperating with policy-makers and other data users.
As discussed in Chapter 2, close cooperation with policy-makers and other data users is strongly recommended in order to improve the relevance of the survey results and to optimize survey questions by determining the purpose of the survey (see below).

Consultation mechanisms (such as a national working group on ICT statistics) may already exist in the area of ICT statistics.

If they do not, then they should be considered at the planning stage.

Possible mechanisms were introduced in Chapter 2.


Establishment of a management and planning structure, for example, using an interdisciplinary survey team.

Team members may include external representatives from consultative bodies or equivalent.

Purpose and data content of the survey.

It is important to always have the purpose of the survey in mind and to review it if necessary.
It is assumed that the purpose of the survey will be formulated with the input of policy-makers and other major users and will be centred on the most important, and measurable, needs of policy-makers.

The purpose will lead on to data specifications and may extend to proforma data tabulations.

Whatever the detail, the purpose needs to be clear – and clearly understood – by the statisticians and data users involved in the survey.
It may also be communicated to respondents in some form in order to gain their cooperation, for example at the time of interview or in publicity material before and during the survey implementation.

Availability of alternative sources of data.

A survey is a costly statistical operation.

Before planning a specific survey on ICT, or including ICT-related questions in an existing survey, alternative potential data sources should be investigated.
For instance, if topics on household ICT were included in a recent household living conditions survey, it may be unnecessary to collect information about them.

Estimation of resources required.

Significant resources (human and financial) are required to implement a survey.

The budget available to conduct a survey may be a constraining factor that needs to be considered early in the planning stage.
The 33 These may be in the form of distinct question modules or questions distributed throughout a questionnaire.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 3.

Planning and preparation for ICT household surveys 29 possibility of obtaining additional budget from users interested in particular topics should be ascertained early in the process as it might affect the development of the survey.
For example, if one user is very interested in use of ICT by people in a particular region, then that user may provide funds to boost the sample in that region and therefore enable more detailed output.

Survey budgeting is discussed in more detail below.

With respect to human resources, the need for trained field staff (in ICT concepts besides their general training as interviewers) and skilled statisticians may represent further constraints.

Training issues are also discussed below.

108.


The result of the above steps could be a business case seeking approval and possibly funding by the relevant authorities (e.g.

a national statistical council or a coordination board) for an ICT household survey to be conducted or included in a national statistical plan.

109.

More detailed planning will include consideration of procedures and outputs of the data collection, including the choice of data collection and processing methodologies.
Issues to be considered here with respect to ICT household surveys are: • • • • • Available survey vehicle.

A decision needs to be taken fairly early in the planning stage on the survey vehicle to be used.

The options are to include a modest set of questions in an existing multipurpose household survey or to conduct a stand-alone ICT household survey (also known as a ‘dedicated’ survey).

There are various advantages of each and these are explored in Chapter 5.
Adherence to existing statistical standards.34 A major focus of this manual is the core list of ICT household indicators (see Chapter 4 and Annex 1).

Those indicators have associated statistical standards and statisticians are strongly encouraged to use those standards so that resulting output is internationally comparable as well as consistent over time in a national context.
The core indicator standards also incorporate other international statistical standards, for example, the classification of occupations, labour force status and educational attainment.

Statistical standards are described in Chapter 4.

Timetable.

The release of data should generally occur as quickly as possible after the date of the survey and the reference period (without compromising data quality), particularly given rapid developments in the area of ICT.
Statistical resources, such as interviewers and other staff, may only be available in a specified time frame and will have costs associated with the time they are employed on the survey.

For these reasons, it is very important that the planning stage includes a detailed timetable of activities involved in the survey cycle and that milestones are adhered to.
An example of a broad timetable that could be adapted can be found in Chapter 2 of Designing Household Survey Samples: Practical Guidelines (UNSD, 2005b).35 Legal and related issues.

There could be a range of legal and related issues that need to be considered.

These include legal obligations of the data collection agency (which may include confidentiality constraints on data release, for example, a prohibition on release of data identifying individuals); respondents’ legal obligations (e.g.
to take part in the survey); and practices that may not be prescribed in law but are policy of the data collection agency (e.g.

minimization of respondent burden).

The survey scope (the ‘target population’ of interest) and units.

When planning a survey, it is important to define the target population to be covered.

For instance, is information required for both urban and rural areas?
In some countries, ICT penetration is very low in rural areas and therefore collecting ICT data may not be 34 35 The word ‘standards’ is used here in a broad context covering topics, questions, concepts, classifications and definitions.

Time-table of Household Survey Activities for Country X; the same chapter has a cost worksheet that may also be useful in outlining the steps in the survey process.

Manual for Measuring ICT Access and Use by Households and Individuals 30 Chapter 3.
Planning and preparation for ICT household surveys cost-effective.36 It may be very expensive to survey some populations, for instance, those living in remote locations, so decisions need to be made at the planning stage about such populations.

37 In respect of there age scope considerations, for instance, is there a particular interest in children – or older people?

Chapter 7 covers scope and units in some detail.

individuals, are Classificatory data required.


In general, users require detailed breakdowns by particular characteristics (e.g.

age of individuals, geographic area, labour force status, sex or educational attainment).

These should be established at the planning stage as they may have implications for sample design and size (and therefore cost).

Classifications are considered in Chapter 4.

Survey design.
Survey design.

Survey design issues and procedures include statistical standards to be used, the availability or development of a survey frame, data sources, data collection techniques, sample design according to the available budget and output requirements, and questionnaire design and testing.

These issues are examined in chapters 5, 6 and 7.

Survey implementation.


Survey implementation issues and procedures include data collection, data processing requirements (such as editing and estimation), development and testing of computer systems, and consideration of skills and training required.

Data processing is covered in chapter 8.

Post-survey processes.

Post-survey processes tabulation and dissemination, metadata dissemination, archiving, documentation and evaluation.
These are very important elements of the survey process, especially as they are the most visible to users.

Post-survey processes are mainly covered in chapters 9 and 10. include data • • • • Budget and management issues 110.

It is rarely possible to achieve good results without significant cost but it is certainly possible to incur significant costs and yet obtain poor quality results if the survey is not well planned.
Having an experienced and knowledgeable project manager and paying careful attention to planning for every phase before commencing operations will generally be very cost effective.

The project manager position would usually be full-time and would cover all phases of the survey (design, implementation and dissemination).

111.

Costs include wages and salaries, ICT costs and administrative costs.
Depending on the costing policy of the organization carrying out the survey, overhead costs (fixed and/or variable), may need to be added to the budget.

112.

It is necessary, at the outset, to itemize and estimate costs associated with the survey.

A draft budget sheet has been developed by UNSD 38 and could be adapted by countries based on their own costing data.

113.
113.

Budgeting needs to be carried out carefully in order to avoid the most common difficulties, which include: • underestimating known costs (for instance, because allowance is not made for things going wrong and therefore staff resources required are underestimated); 36 37 If electricity is not available, it is unlikely that most ICTs are widely used there (the possible exception to this is the mobile telephone).
However, note the importance of providing available data and metadata in relation to the non-availability of ICT services in unsurveyed areas.

Some data dissections, such as urban/rural, are important for measuring the digital divide and where a survey measure is not available, an alternative based on other data (for instance, infrastructure data) could be included in the data dissemination.

It is also very important to document any scope limitations so that users are able to make relevant comparisons.
This subject is further dealt with in Chapter 10.

38 See UNSD (2005a, Chapter IV).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 3.

Planning and preparation for ICT household surveys 31 • • omitting some costs (e.g.

costs of unexpected publicity); and ignoring or underestimating overhead costs (these can be significant and will include direct and indirect overhead costs).39 114.
Given the likelihood of delays, it is useful to include some extra budget (and other resources such as staff time) for unforeseen events or delays.

115.

Often trade-offs are required to fit the survey to the available financial and other resources.

Trade-offs could include a reduction in sample size (usually resulting in larger sampling error), removal of some level of detail, or removal of some questions or topics.
Ideally, such decisions would be made together with policy-makers and other major data users to ensure that their data needs are still adequately addressed.

116.

Mechanisms to reduce costs should be considered and include: • • • Use of ‘economies of scale’, for instance, including ICT questions in a larger survey (the marginal cost is likely to be lower than the cost of running a stand-alone survey).
Use of technology to reduce costs, for instance, the integration of computer-based quality control 40 into fieldwork should be considered.

This includes the use of computer assisted personal or telephone interviewing for data collection, and computer assisted data entry while in the field (in the case of pen and paper interviews).

Such techniques are important for improving data quality and should also reduce costs by reducing or eliminating further data editing.
Careful consideration of other factors is necessary, for instance, the costs of computer systems development and maintenance.

international organizations Use of standard tools provided (generally for free) by international organizations for the dissemination and documentation of ICT household data and indicators.
Examples of such tools are DevInfo41 (currently used by a large number of countries as well as by some to disseminate Millennium Development Goal indicators, including Internet users, mobile cellular subscriptions and fixed-telephone subscriptions per 100 inhabitants), NADA (National Data Archive,42 used to document surveys and provide access to microdata), PC-AXIS43 (developed by a consortium of NSOs led by Statistics Sweden, to disseminate aggregate data and geographical information) and REDATAM 44 (mainly used by Latin American countries to disseminate population and housing census data, including some ICT variables: presence of computer, access to Internet, access to fixed and mobile telephone).
Other general preparatory work 117.

Preparatory work covers a range of activities and arguably continues throughout the survey cycle.

Planning and budget issues were discussed above.

In subsequent chapters, we will look at data sources, collection methods, questionnaire design and survey design.

In this chapter, we look at staff training which is only discussed briefly in other parts of the Manual.

39 Direct overhead costs are those that are proportional to units used (e.g.
staff salary overheads such as contributions to pension funds).

Indirect overhead costs are those that are not proportional to units used but may be significant at a ‘whole of organization’ level.

They include things like building costs.

40 Computer-based quality control will be discussed in Chapter 8. www.devinfo.org.

http://www.ihsn.org/nada/.

http://www.scb.se/Pages/StandardNoLeftMeny____314045.aspx.

See http://www.cepal.org/redatam/ for the main page.
Some census data are available online for Latin America, Caribbean, Asian and African 41 42 43 44 countries.

Manual for Measuring ICT Access and Use by Households and Individuals 32 Chapter 3.

Planning and preparation for ICT household surveys Staff training and selection 118.

It can be seen from the information presented above that staff with diverse skills and expertise will be required for different aspects of the survey.
Skills relevant to the following areas will be required: survey management, survey design, computer systems development, interviewing, data entry, data editing and coding, data imputation and estimation, data analysis, survey documentation, archiving and dissemination (including publication writing).45 Although field work managers and computer programmers may belong to different departments within the organization, they would ideally be recognized as members of the survey team.

119.
119.

Staff selection and training will run parallel with survey planning, questionnaire design and sample selection.

It will often be a phased activity, for instance, staff involved in survey planning and development are likely to be employed first.

While specialized staff may be available in an organization, they will usually need to be trained on the specifics of the survey.

120.

It is better to make training an inclusive activity.
For instance, interviewers and their supervisors often have valuable ideas for the operational phases of the survey and will be more committed to a quality result if they have had some involvement in documentation and the setting of field procedures.

121.

While many staff involved in a particular survey will be skilled and will require minimal training, others may need significant training.

Of particular importance is the training of interviewers, some of whom may be inexperienced.
An important cause of bias is poor handling of respondents by interviewers, for instance, asking leading questions or suggesting some judgement of responses (for instance, by their tone of voice or facial expression).

Training and briefings, as well as survey material, should be focused on avoiding such problems.

Elements of training may include classroom training, interviewer manuals and field work in the presence of experienced interviewers or supervisory staff.
Training is perhaps the most underestimated component of survey implementation.

Although it is difficult to provide specific recommendations on the minimum time needed for training, it should probably be measured in weeks and not in days.

122.

It is important that staff involved in a particular process (e.g.

data collection) receive the same, or similar, training to avoid bias.

Providing sufficient time for training is also key to ensuring high quality information.

123.
123.

The performance of all staff should be monitored closely, especially in the early stages of the survey.

Any instances of underperformance, or behaviour that might induce statistical bias, need to be addressed as quickly as possible.

Box 8 illustrates a particularly relevant problem in supervision.

45 The last is quite a specialized skill, needing general writing ability as well as an understanding of data and an ability to describe and interpret data clearly and unambiguously.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 3.

Planning and preparation for ICT household surveys 33 Box 8.

An example of supervision and monitoring in ICT household surveys A typical problem of questionnaire design and supervision is found when a positive answer to a question triggers other questions.

This situation could encourage the interviewer (and possibly the interviewee) to provide a negative answer.
For instance, question 20 in the model questionnaire for measuring ICT access and use by households and individuals (Annex 2) may represent such a case.

It refers to the use of the Internet and, if answered positively, requires that questions 21 to 23 (which are important for monitoring characteristics of Internet use) are answered as well.

Otherwise, the interview is over after question 20.

The only way to solve this problem is to increase the level of supervision and monitoring.
There are no possible solutions within the questionnaire design.

Supervision implies random control visits in which certain questions are asked again in a randomly chosen subset of the households.

It is generally considered good practice to perform this kind of supervision in around 15–20 per cent of households in the sample, although unfortunately the levels actually found in practice are usually much lower.

As mentioned, question 20 is a natural candidate for this kind of supervision.
Monitoring can be performed through tabulation of the data while interviews are being performed in the field.

Odd trends can be detected, such as a particular interviewer whose questionnaires have noticeably low rates of Internet use (that is, with a tendency to insert “No” as the answer to question 20).

124.
124.

Given that some questions on ICT access and use are somewhat technical, it could be advantageous to employ people who are more attuned to ICT, for instance young adults and people with proven ICT skills.

Clearly also, it is important to provide training in the ICT concepts and terms used in questionnaires.46 125.

A most important prerequisite for training is the availability of training and/or procedures manuals for each broad class of staff, including interviewers, supervisors and data entry staff.
Such manuals should ideally be prepared before the survey commences and may continue to be useful references during the survey.

Training manuals should clearly explain the purpose of the survey and be quite explicit about tasks to be performed by staff.47 126.

Training resources that can be used before undertaking a household ICT survey include: • • • this manual (available in the UN official languages), short e-learning course on the Manual,48 and face-to-face training courses organized by ITU.
46 47 48 Technical definitions are included with the core indicators.

UNSD (2005a, Chapter IV) discusses this in more detail.

http://www.itu.int/ITU-D/ict/capacitybuilding/material/player.asp.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 35 Chapter 4.

Statistical standards and measurement topics for ICT household statistics 127.
Survey planning can be simplified, and output improved, by the use of national and international standards covering definitions of indicators, model questions, concepts, units, scope and classifications.

In respect of ICT household statistics, the standards described in this manual are both specific and general.

Specific standards are those recommended by the Partnership on Measuring ICT for Development and endorsed by the United Nations Statistical Commission (UNSC).
General standards include definitions and classifications of labour force status, occupation, educational attainment and age.

128.

Adherence to both specific and general standards governing ICT statistics should be a primary aim and will ensure that collected data have maximum usefulness and are as comparable as possible with the output of other countries.

In a national context, use of standards may enable comparability with other datasets and enhance comparability with historical data.
In this chapter, we will consider specific standards pertaining to ICT household 129. statistics and relevant international classifications.

Methodological standards, such as survey procedures, scope and statistical units are discussed in the following chapters.

Core ICT household indicators 130.

The core list of indicators was formally released by the Partnership in 2005 as Core ICT Indicators (Partnership, 2005).
The list was later revised and expanded to improve international comparability and relevance (Partnership, 2010; UNSC, 2012).

The Partnership and its members are continuously improving the core list, in consultation with member countries, based on data collection experiences and in light of technological change.
In 2012, following a recommendation of the 9th World Telecommunication/ICT Indicators meeting (WTIM-11), the Expert Group on ICT Household Indicators (EGH) was established by ITU to revise the core list of household indicators and the previous version of this manual.

As a first result of its work, EGH has agreed on some methodological changes as well as the addition of four new indicators in 2013.49 The list of household indicators is shown in Table 2.
The complete core list of indicators can be found in Annex 1.

131.

There are 16 ICT household indicators in the core list.

The reference indicator (HHR1, Proportion of households with electricity) was dropped from the core list and is referred to in this manual as a useful variable to cross-tabulate ICT access indicators.

The main purpose of the core list is to assist countries to produce high quality and internationally comparable ICT household statistics.
As we have seen, the indicators have associated standards and metadata including definitions, model questions, classificatory variables, scope and statistical units.

132.

The new core indicators agreed by the EGH in 2013 are the following: Proportion of households with multichannel television, by type (HH13), Barriers to household Internet access (HH14), Individuals with ICT skills, by type of skills (HH15) and Household expenditure on ICT (HH16).
Indicators on other important topics (namely Individuals using the Internet by type of portable device and network used to access the Internet, Internet security, and Children and youth online protection) were discussed by the EGH but were not adopted at this time.

Further discussion by the EGH on these issues is expected.

49 See the final report at http://www.itu.int/en/ITU-D/Statistics/Documents/events/brazil2013/Final_report_EGH.pdf.
Manual for Measuring ICT Access and Use by Households and Individuals 36 Chapter 4.

Statistical standards and measurement topics for ICT household statistics Table 2.
List of core indicators on access to, and use of, ICT by households and individuals HH1 HH2 HH3 HH4 HH5 HH6 HH7 HH8 HH9 HH10 HH11 HH12 HH13 HH14 HH15 HH16 Proportion of households with a radio Proportion of households with a television Proportion of households with telephone Proportion of households with a computer Proportion of individuals using a computer Proportion of households with Internet Proportion of individuals using the Internet Proportion of individuals using the Internet, by location Proportion of individuals using the Internet, by type of activity Proportion of individuals using a mobile cellular telephone Proportion of households with Internet, by type of service Proportion of individuals using the Internet, by frequency Proportion of households with multichannel television, by type Barriers to household Internet access Individuals with ICT skills, by type of skills Household expenditure on ICT 133.
To simplify understanding, the following discussion of the indicators distinguishes the access indicators applying at the household level, the household ICT expenditure indicator (HH16) and the use indicators applying to individuals.

Household ICT access core indicators 134.

Indicators HH1–HH4, HH6, HH11, HH13 and HH14 refer to household access (and barriers to access) to ICT equipment and services, not to use of those products by individual household members.
In order for a household to have access to ICT equipment or services, it should be able to be used, that is, equipment is in working condition at the time of interview and ICT services are in operation.

135.

In order for a household to have access to ICT equipment or services, the equipment/service should generally be available for use by all members of the household at any time, regardless of whether it is actually used.

ICT equipment may or may not be owned by the household.
Household surveys traditionally ask about the availability of assets in the household, including TV, electricity, refrigerator, piped water, etc.

A similar principle has been adopted for ICT equipment and services, that is, they should be available for use by household members at home, regardless of whether they are used.

They can be taken away from home occasionally, but the basic principle is that they are usually available for use by all household members at home.

136.
136.

The access indicators are presented as the proportion of households with [equipment, service].50 With the exception of HH14, indicator values are calculated by dividing the number of in-scope households with [equipment, service] by the total number of in-scope households.

For HH11 (Internet access by type of service), output for each type of Internet 50 Note that ITU collects the data as numbers, not proportions, and then prepares the indicators in the form of proportions (percentages).
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 37 service category can also be presented as the proportion of households with Internet.

Similarly, for HH13 (multichannel TV by type of service), output for each type of service category can also be presented as the proportion of households with TV.
For HH4, where countries ask about the type of computer, output for each type of computer category can be presented as the proportion of households with computer.

For HH14 (barriers to household Internet access), output for each type of barrier category should be presented as the proportion of households without Internet.

137.

Subindicators can be constructed using the classificatory variables, household composition and size.

These are detailed later in this chapter.


Household ICT expenditure core indicator 138.

Indicator HH16 (Household expenditure on ICT) is intended to measure the expenditure undertaken by households on ICT equipment and ICT services.

HH16 can be presented as the amount, or proportion, of household expenditure spent on ICT.

For international comparison, HH16 may be presented together with other economic indicators such as the distribution of household income or per capita income.
Demographic indicators such as the number of households or average household size should be considered for the analysis of this indicator.

139.

When broken down by socio-economic classificatory variables, HH16 can provide information on differences in ICT consumption patterns of households.

As with other consumption indicators, the analysis of the distribution of the variable provides more information than summary statistics (such as the mean or the median).

140.
140.

Product and service classifications used to classify household expenditure should be used.

For this purpose, the UN COICOP classification (Classification of Individual Consumption According to Purpose) (UNSD, 1999) is recommended.

However, it is recognized that the boundary between communication and audio-visual, photographic and information processing equipment is problematic.
Other difficulties include: • • the measurement of expenditure when products in different categories are bundled (sold as a package for a discounted price); and the treatment of television services, which are included in COICOP 09.4.2 – Cultural services.

Where countries are able to collect data separately on television services, they should include them in ICT services and note the inclusion in metadata.

141.
141.

Table 3 presents a proposal for use of the COICOP classification for ICT equipment and services for the purposes of measuring ICT expenditure.

Individual ICT use core indicators 142.

Indicators HH5, HH7–HH10 and HH12 refer to use of ICT equipment and services by individual household members.

HH15 measures the skills of individuals by examining the computer-related activities they have carried out.
The suggested reference period,51 which has been revised from the previous edition of this manual, is the last three months.

143.

Four individual use indicators (HH5, HH7, HH10 and HH15) are presented as the proportion of individuals using [equipment, Internet].

The other three use indicators (HH8, HH9 and HH12) break down Internet use (by location, Internet activities undertaken and frequency of use respectively).
51 Reference period is the time period referred to in the survey when asking about individual use of ICT.

The core ICT indicators standards and the Manual recommend a 3-month reference period, instead of 12 months as in the previous edition.

Country practices vary, but ideally, reference periods should be aligned in order to obtain comparable data.

Manual for Measuring ICT Access and Use by Households and Individuals 38 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Table 3.

Classification of ICT equipment and services, based on COICOP52 COICOP code ICT equipment and services categories 08 Communication Telephone and telefax equipment (08.2.0) • Purchases of telephones, radio-telephones, telefax machines, telephone- answering machines and telephone loudspeakers.

• Repair of such equipment.


Telephone and telefax services (08.3.0) • Installation and subscription costs of personal telephone equipment; includes telephone calls (from any location), information transmission services, Internet connection services, hire of telephones.
09.1 Audio-visual, photographic and information processing equipment Equipment for the reception, recording and reproduction of sound and picture (09.1.1) • Television sets, video cassette players and recorders, television aerials of all types; radio sets, car radios, radio clocks, two-way radios, amateur radio receivers and transmitters; gramophones, tape players and recorders, cassette players and recorders, CD-players, personal stereos, stereo systems and their constituent units (turntables, tuners, amplifiers, speakers, etc.
), microphones and earphones.

Information processing equipment (09.1.3) • Personal computers, visual display units, printers and miscellaneous accessories accompanying them; computer software packages such as operating systems, applications, languages, etc.

; calculators, including pocket calculators; typewriters and word processors.

• Also includes laptops, tablets, e-book readers.


Repair of audio-visual, photographic and information processing equipment (09.1.5) Source: Classification of Individual Consumption According to Purpose (COICOP), UNSD, http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=5.

144.

Indicator values for HH5, HH7 and HH10 are calculated by dividing the number of in- scope individuals using [equipment, Internet] by the total number of in-scope individuals.
For HH8 (location of use), HH9 (Internet activities undertaken) and HH12 (frequency of use), output may be calculated as both the proportion of in-scope individuals and the proportion of individuals using the Internet.

HH15 (ICT skills) should be calculated as the proportion of individuals using computers.

Classifications for ICT household statistics 145.

Specific subpopulations are generally of more interest to policy-makers than the whole population.
Classifications of units are therefore generally part of a statistical framework.

This section discusses the classifications recommended for use with the core indicator statistical units, households and individuals.

146.

It is unlikely that small subpopulations will be sufficiently well represented in a sample survey to enable reliable estimates.

It will therefore be difficult to obtain ICT indicators for these subpopulations from sample surveys unless they are specifically designed to cover them.
In some household surveys, limitations to scope may also exclude certain subpopulations, for example, those in remote areas.

Where ICT indicator data are collected 52 COICOP is now reasonably out of date in respect of ICT equipment and services.

While the COICOP categories have been used in Table 3, some suggestions have been made regarding the inclusion of more recent examples, such as tablets and e-book readers.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 39 from a census, then small subpopulations are likely to be covered, unless there are scope limitations that exclude them.

Individual characteristics 147.

In terms of ICT policies, the following information about individuals may be of interest: children and youth, the elderly, persons with disabilities and groups with certain ethno- cultural characteristics.
The latter includes those using a particular language, nomads or persons living in areas to which access is difficult, immigration status (e.g.

temporary migrant workers), level of education, labour force status and occupation.

In addition, the gender perspective is increasingly considered in all social and economic topics, and recommended in particular for studies on access to, and use of, ICT.

148.
148.

Standard questions on age and sex used as classificatory variables allow dissection of indicators on the use of ICT by individuals, identifying groups such as children, youth, the elderly and women.

Data for these classificatory variables are usually collected in the survey that collects ICT data or, less commonly, are available from the survey frame.

149.

For many developing economies, there are socio-economic problems that create barriers to use of ICT by individuals.
These problems are diverse and broadly cover lack of opportunity and lack of ability.

They include illiteracy and other linguistic limitations, socio- cultural barriers, lack of ICT and other skills, lack of confidence or awareness and low income.

Some classificatory variables that might address these issues include level of education, status in the labour force and occupation.

150.
150.

There are several individual characteristics classifications recommended by this manual; they are: sex, age, highest education level attained, labour force status and occupation.

Classifications for these categories are based on international standards and are described below.

Sex 151.

Sex (male or female) of every individual should be recorded, as sex disaggregation of data is a fundamental requirement for gender statistics and in particular for the analysis of the gender gap in the use of ICT.
For policy purposes, all core ICT use indicators should be broken down by sex, in order to maximize information on any digital gender gap.

Age 152.

Age is a strong determinant of ICT use so a common age cut-off and categories are important.

It is recommended that countries use the following ranges: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.

53 Countries are particularly encouraged to collect data for children, where this is feasible.

153.
153.

The above age ranges are consistent with UNSD recommendations on age ranges of individuals, which are: under 1; 1–4; 5–9; 10–14; 15–19; 20–24; 25–29; 30–34; 35–39; 40– 44; 45–49; 50–54; 55–59; 60–64; 65–69; 70–74; 75–79; 80–84; 85–89; 90–94; 95–99; and 100 and over.54 53 The ‘youth’ age standard as specified in 2005 (in Partnership, 2005) was 16-24 years per recommendations made by OECD and Eurostat for their model surveys.
This was revised to conform to UN standards and the practices of a number of countries for the 2010 revision (Partnership, 2010).

Countries which use 16 (or, less commonly, 18) as their lowest age should report on that basis but note it in survey metadata.

54 Principles and Recommendations for Population and Housing Censuses Revision 2 (UNSD, 2008a).

Manual for Measuring ICT Access and Use by Households and Individuals 40 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Highest education level attained 154.

Categories are based on the United Nations Educational, Scientific and Cultural Organization (UNESCO) International Standard Classification of Education, the latest revision of which occurred in 2011 (UNESCO, 2011).
ISCED codes are defined for educational programmes (ISCED-P) and for educational attainment (ISCED-A), providing parallel classifications of levels of an education programme and of educational attainment (i.e.

highest educational level that the individual has completed).

Categories at the first-digit levels for educational attainment can be found below.
In general, countries have adapted the classification and created correspondence tables between ISCED and their national educational level classifications.

155.
155.

ISCED-A 2011 levels are as follows: 55 • • • • • • • • • level 0: Less than primary, level 1: Primary education, level 2: Lower secondary education, level 3: Upper secondary education, level 4: Post-secondary non-tertiary education, level 5: Short-cycle tertiary education, level 6: Bachelor or equivalent, level 7: Master or equivalent, level 8: Doctoral or equivalent.

156.
156.

This manual recommends that the ISCED level categories are aggregated for reporting and comparison purposes as follows: • • • • • primary education or lower (ISCED levels 0, 1), lower secondary education (ISCED level 2), upper secondary education or post-secondary non-tertiary education (ISCED levels 3,4), tertiary education (ISCED levels 5, 6), and post-tertiary education (ISCED levels 7, 8).

157.
157.

When analyzing the use of ICT by educational level, it may be relevant to cross- classify data by age group.

Where official age ranges are defined for educational levels (e.g.

6–12 for primary education in some countries), these should be considered in the analysis at the national level.

For international comparability purposes, presenting ICT indicators by ISCED level and age group may provide a better understanding of ICT use according to education (e.g.
the proportion of Internet users among children aged 10–14 with primary education may be much higher than that of those aged 40–44 with the same educational attainment).

It is not recommended that countries calculate estimates for each combination of age interval and educational level, unless the sample is large enough to provide for accurate estimates (e.g.
Eurostat disseminates data on the proportion of persons with lower secondary education attainment only for those aged 15 or more, and with tertiary education attainment only for those aged 20 and more).

55 See http://www.uis.unesco.org/Education/Documents/UNESCO_GC_36C-19_ISCED_EN.pdf (UNESCO, 2011) for details.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 41 Labour force status 158.
Categories for labour force status used to break down ICT indicators at the individual level are based on the International Labour Organization (ILO) International Classification of Status in Employment (ICSE-93),56 with additional categories for those who are unemployed or outside the labour force.
The categories are: • • • • • employee; self-employed (includes the four categories: employers, own-account workers, members of producers' cooperatives, and contributing family workers); workers not classifiable by status (for whom insufficient relevant information is available, and/or who cannot be included in the preceding categories); unemployed; and outside the labour force.

159.

The ICSE-93 categories map to ICT indicators categories for those in the labour force.
The additional labour force categories recommended by this manual are Unemployed and Outside the labour force (which includes individuals who are not economically active, that is those who are neither employed nor unemployed).

For policy purposes, it may be relevant to further break down the Outside the labour force category to differentiate those attending an educational institution (students) from others (such as, those performing household duties, retired, or not active for reasons such as illness).
Occupation 160.

For those in the labour force, occupation categories should be based on ISCO major groups where possible.57 The major groups for the 1988 and the 2008 versions of ISCO are shown in Table 4.

ISCO is the International Standard Classification of Occupations and is maintained by the ILO.

According to the ILO, “ISCO is a tool for organizing jobs into a clearly defined set of groups according to the tasks and duties undertaken in the job”.58 ISCO-88 is being replaced by ISCO-08.
There have been some changes at the level of interest for ICT statistics (the major group level).59 161.

Occupation will not be relevant for some age groups (those likely to be under and over the usual working age range) and those outside the labour force.

A ‘not applicable’ category would therefore be a useful addition to tables showing occupation.

Other individual characteristics 162.

Additional individual classifications on socio-demographic/cultural characteristics might also be of interest.
They include level of literacy, ethnicity, languages spoken, language skills and disability status.60 The revised ICT household indicators include HH15, Individuals with ICT skills, by type of skills.

It will therefore be possible to cross-classify the individual use indicators by ICT skill level.

56 ILO (1993).
56 ILO (1993).

The ICSE-93 consists of the following six categories: employees; employers, own account workers, members of producers’ cooperatives, contributing family workers; and workers not classifiable by status.

The ICSE categories refer to work for pay or profit, per decisions made by the 19th International Conference of Labour Statisticians in October 2013, http://www.ilo.org/global/statistics-and-databases/meetings- and-events/international-conference-of-labour-statisticians/19/lang--en/index.htm.
57 For more information on ISCO, see http://www.ilo.org/public/english/bureau/stat/isco/index.htm..

According to the ILO, the basic criteria used to define the system of major, sub-major, minor and unit groups are the skill level and skill 58 specialization required to competently perform the tasks and duties of the occupations.

59 Correspondence tables are available from ILO, http://www.ilo.org/public/english/bureau/stat/isco/isco08/index.htm.
60 Of particular interest is the use of such categories to identify non-users.

According to UNECLAC, variables like ethnicity and language spoken are relevant for ICT access discrimination in some Latin American countries.

Countries with a very high proportion of non-national migrant workers (such as those in the Persian Gulf) distinguish between national and non-nationals in their questionnaires.

Manual for Measuring ICT Access and Use by Households and Individuals 42 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Table 4.
ISCO major groups: 1988 and 2008 Major group 1988 (ISCO-88) 2008 (ISCO-08) 0 Legislators, senior officials and managers Managers Professionals Professionals Technicians and associate professionals Technicians and associate professionals Clerks Service workers and shop and market sales workers Skilled agricultural and fishery workers Clerical support workers Service and sales workers Skilled agricultural, forestry and fishery workers Craft and related trades workers Craft and related trades workers Plant and machine operators and assemblers Plant and machine operators, and assemblers Elementary occupations Elementary occupations Armed forces Armed forces occupations Source: ILO, http://www.ilo.org/public/english/bureau/stat/isco/intro.htm.
Household characteristics 163.

There are two household characteristics classifications recommended by this manual.

They are: • • household composition (households with children under 15 and households without children under 15) and household size (number of household members, including those outside any age scope imposed).

164.

Household composition is relevant to measuring the digital divide in households with children – who are ‘digital natives’ in many countries (see Chapter 4 of ITU, 2013a).

165.
165.

Of particular interest, countries that have a notable rural/urban divide or a strong regional structure (e.g.

federal states) may be interested in using a geographical classification.
Note that there is no internationally comparable definition of rural or urban, and countries have their own definitions based on the size, density or administrative status of localities.61 The complexity of geographic classifications is illustrated by the approach in India (see Box 9), which combines geographic, demographic, administrative and socio-economic criteria to define urban and rural areas.

166.

Other characteristics may be derived from those of the household ‘head’ or ‘reference person’.
These include sex, level of education, status in the labour force and occupation, which have a high explanatory role in socio-economic status, and therefore, may be useful for analysing the conditions for household access and of individual use of ICT within the household.

61 See the UNSD Recommendations for Population and Housing Censuses (UNSD,2008), Chapter VI, Section D, par.

2.81 to 2.88.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 43 Box 9.

India: definition of rural and urban areas The Ministry of Statistics and Programme Implementation of India uses several demographic, administrative and socio-economic variables to define urban and rural areas.
Urban areas are defined as (a) all places with a Municipality, Corporation of Cantonment and places notified as town area, (b) all other places that satisfy the following criteria: a minimum population of 5000, at least 75 per cent of the male working population is non-agriculturist and (iii) a density of population of at least 400 per square kilometer.

However, there are urban areas which do not possess all the above characteristics uniformly.
Certain areas are treated as urban on the basis of their possessing distinct urban characteristics, overall importance and contribution to the urban economy of the region.

The rural sector covers areas other than the urban areas.

The rural areas are composed of whole villages as well as part of villages.
The lists of census villages as published in the Primary Census Abstracts constitute the rural areas, and the lists of cities, towns, cantonments, non-municipal urban areas and notified areas constitute the urban areas.

Source: Ministry of Statistics and Programme Implementation.

http://mospi.nic.in/Mospi_New/upload/nsso/concepts_golden.pdf?status=1&menu_id=49.

Cross-classification of data 167.


In terms of output, many countries will want to cross-classify some of the above variables (for instance, age by sex62).

This can produce information that is very useful for analytical purposes.

However, it should be noted that cross-classified output is usually quite detailed and would therefore generally require higher sample sizes to support reliable estimates.
Cross-classification is more likely to be feasible for higher-level indicators, such as individual use of the Internet.

When disseminating the results of cross-classification of ICT indicators, sample sizes and accuracy measures should also be included (see Chapter 9 for more information on quality indicators).

168.
168.

The questionnaire used by ITU to collect data from countries (see extract in Annex 4) proposes the following cross-classifications: • • • • • • household composition by rural/urban, rural/urban by sex, age by sex, educational attainment by sex, status in the labour force by sex, and occupation by sex.

Other classificatory variables 169.

For many countries, an income variable will also be of interest.
Because both variables household income and individual income are problematic from a collection and international comparability viewpoint, they are not included as recommended classificatory variables for the ICT indicators.

However, because of their policy relevance, they are described in this manual.

They are regarded as important classificatory variables because of the strong correlation between income and access to/use of ICT.
To overcome the difficulty of measuring them, there is a diversity of approaches typically used by statistical agencies (household/individual, monthly/annual, gross/net etc.).

Eurostat adopted a quartile approach for measuring household income from 2006.

It entails either collecting income in ranges corresponding to quartiles (based on other survey data) or collecting income data in other ways and converting them to quartiles for output purposes.
It is expected that the quartile 62 For examples of such cross-classifications, see ITU (2008).

Manual for Measuring ICT Access and Use by Households and Individuals 44 Chapter 4.

Statistical standards and measurement topics for ICT household statistics approach would allow better comparability between countries choosing to use this classificatory variable (and within a country, possibly better comparability over time).
UNECLAC has adopted quintiles of household per capita income for surveys by countries of Latin America and the Caribbean (LAC).

63 As most of the LAC household surveys that include ICT questions have also collected information on household income, it is possible to compare differences in the domestic income divide.64 Detailed information on core ICT household indicators 170.
Table 5 presents the core indicators on access to, and use of, ICT by households and individuals along with standards that countries should apply to their compilation.

The ICT concepts that are used in the definition of indicators are standardized with ITU definitions and UNSD recommendations.

171.
171.

The detailed information for each indicator included in Table 5 includes: • • • • • • definitions, clarifications and methodological issues, suggested model question/s, relevant disaggregations and classifications enabling subindicators, the construction of method of calculation, and notes on policy relevance.

172.

Considerations for questionnaire design are discussed in Chapter 6.

173.

This edition of the Manual includes a new item on policy relevance for each indicator.
The policy relevance of each indicator is a key element, not only because it helps to justify the need for collecting statistics to compile the indicator, but also because it helps in understanding the importance of the indicator in identifying and monitoring aspects of the digital divide.

63 64 UNECLAC (2007).

See OSILAC ICT Statistical Information System (www.cepal.org/tic/flash).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 45 Table 5.

Detailed information on core indicators on access to, and use of, ICT by households and individuals: HH1 to HH16 Indicator HH1: Proportion of households with a radio Definitions: This is the proportion of households that have a radio.
A radio is defined as a device capable of receiving broadcast radio signals, using common frequencies, such as FM, AM, LW and SW. A radio may be a stand-alone device, or it may be integrated with another device, such as an alarm clock, an audio player, a mobile telephone or a computer.

Clarifications and methodological issues: ‘Household with a radio’ means that a radio is generally available for use by all members of the household at any time, regardless of whether it is actually used.
The radio may or may not be owned by the household, but should be considered a household asset.

Household is defined in Chapter 7.

With respect to the previous edition, more devices with radio functionality are now included in the definition.

For time series compatibility, countries may want to split the question to include more than one response category.

Equipment should be in working condition at the time of the survey.

Model question: Does this household have a radio?


Yes/No Disaggregation and classification: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.
• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.

Calculation: The number of in-scope households with a radio is calculated by aggregating the weighted responses (see Chapter 8).
The proportion of households with a radio is expressed as a percentage and is calculated by dividing the number of in-scope households with a radio by the total number of in-scope households, and then multiplying the result by 100.

• HH1% = [(number of in-scope households with a radio) / (total number of in-scope households)]*100 Policy relevance: Radio and television are the most widespread ICTs in the world.
They are generally reliable and are particularly useful for those parts of the world where Internet-based ICTs are not affordable, or available.

For many people, especially in developing economies, radios, while an ‘old ICT’, remain the only communication device.

Their importance as an affordable and accessible mass medium for rural and marginalized urban communities has been highlighted.
Radios are largely able to overcome literacy and language barriers and, according to UNESCO, radio is the medium that reaches the widest audience worldwide – radios remain “widely accessible, relatively cheap and very simple to use” and radio is “the medium that can carry any message to any place at any time – even without electricity.

In situations of conflict and natural disaster, shortwave radio provides a lifeline of information that can save lives”.
Especially where Internet access is not available or affordable, radios play a very important role in delivering education or services in the areas of agriculture and health.

Country projects that rely on the availability of radios in households will find the information provided by this indicator very useful.

Manual for Measuring ICT Access and Use by Households and Individuals 46 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Indicator HH2: Proportion of households with a television Definitions: This is the proportion of households that have a television (TV).

A television (TV) is a device capable of receiving broadcast television signals, using popular access means such as over-the-air, cable and satellite.

A television set is typically a stand-alone device, but it may also be integrated with another device, such as a computer or a mobile telephone.
Clarifications and methodological issues: ‘Household with a television’ means that a TV is generally available for use by all members of the household at any time, regardless of whether it is actually used.

The TV may or may not be owned by the household, but should be considered a household asset.

Household is defined in Chapter 7.

With respect to the previous edition, TV functionality integrated in other devices is now included in the definition.
For time series compatibility, countries may want to split the question to include more than one response category, such as ‘stand-alone TV’ or ‘TV embedded in another device’.

Equipment should be in working condition at the time of the survey.

Model question: Does this household have a television?

Yes/No Disaggregation and classification: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.
• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.

• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.

Breakdown by type of TV service is considered in a new indicator, HH13.
Calculation: The number of in-scope households with a TV is calculated by aggregating the weighted responses (see Chapter 8).

The proportion of households with a TV is expressed as a percentage and is calculated by dividing the number of in-scope households with a TV by the total number of in-scope households, and then multiplying the result by 100.
• HH2% = [(number of in-scope households with a TV) / (total number of in-scope households)]*100 Policy relevance: Televisions are sometimes referred to as an ‘old’ ICT but remain important as a source of information, and as a means of expressing national identity.

Moreover, they are widely available globally: ITU estimates that at the end of 2012, almost 80 per cent of households globally had a TV, compared with only 37 per cent of households having Internet access.
This is a meaningful comparison, since both require access to electricity in order to function properly, and both represent an expense for household budgets in acquiring the equipment/service and/or for any subscription charges.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 47 Indicator HH3: Proportion of households with telephone Definitions: This is the proportion of households that have a telephone.

A fixed telephone line refers to a telephone line connecting a customer's terminal equipment (e.g.

telephone set, facsimile machine) to the public switched telephone network (PSTN) and which has a dedicated port on a telephone exchange.
This term is synonymous with the terms main station or Direct Exchange Line (DEL) that are commonly used in telecommunication documents.

It may not be the same as an access line or a subscription.

A mobile (cellular) telephone refers to a portable telephone subscribing to a public mobile telephone service using cellular technology, which provides access to the PSTN.

This includes analogue and digital cellular systems and technologies such as IMT-2000 (3G) and IMT-Advanced.
Users of both postpaid subscriptions and prepaid accounts are included.

Clarifications and methodological issues: ‘Household with a mobile telephone’ means that the mobile telephone is generally available for use by all members of the household at any time, regardless of whether it is actually used.

The mobile telephone may or may not be owned by the household but should be considered a household asset (as has traditionally been the case for fixed telephone).

Household is defined in Chapter 7.


A household can be considered as having access to a mobile telephone when it is able to receive and make calls from inside, or within the near vicinity of, the house (for example, the garden of the house).

Equipment should be in working condition at the time of the survey.

Model questions: For fixed telephone: Does this household have a fixed telephone line?

Yes/No For mobile telephone: Does this household have a mobile telephone?
Yes/No Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.

• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.
• Disaggregation by type of mobile telephone, for example, smartphone.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.
Calculation: The following subindicators can be calculated: • Proportion of households with a fixed telephone (regardless of whether they have a mobile telephone) • Proportion of households with a mobile telephone (regardless of whether they have a fixed telephone) • Proportion of households with any telephone (fixed and/or mobile) • Proportion of households with a fixed telephone only • Proportion of households with a mobile telephone only • Proportion of households with both fixed and mobile telephone.
The number of in-scope households with a given type of telephone is calculated by aggregating the weighted responses for each case (see Chapter 8).

Separate variables in the micro database need to be created for calculating each subindicator using the two questions included in the survey questionnaire.
Subindicators are calculated as follows: • The proportion of households with a fixed telephone is calculated by dividing the number of in-scope households with a fixed telephone by the total number of in-scope households.

The result is then multiplied by 100 to be expressed as a percentage.

• The proportion of households with a mobile telephone is calculated by dividing the number of in-scope households with a mobile telephone by the total number of in-scope households.
The result is then multiplied by 100 to be expressed as a percentage.

• The proportion of households with any telephone is calculated by dividing the number of in-scope households with access to any telephone (fixed and/or mobile) by the total number of in-scope households.

The result is then multiplied by 100 to be expressed as a percentage.
• The proportion of households with fixed telephone only is calculated by dividing the number of in-scope households with a fixed telephone only by the total number of in-scope households.

The result is then multiplied by 100 to be expressed as a percentage.

Manual for Measuring ICT Access and Use by Households and Individuals 48 Chapter 4.
Statistical standards and measurement topics for ICT household statistics • The proportion of households with mobile telephone only is calculated by dividing the number of in-scope households with a mobile telephone only by the total number of in-scope households.

The result is then multiplied by 100 to be expressed as a percentage.
• The proportion of households with both fixed and mobile telephone is calculated by dividing the number of in-scope households with both a fixed and mobile telephone by the total number of in-scope households.

The result is then multiplied by 100 to be expressed as a percentage.
The subindicators are expressed algebraically as follows: • HH3%fixed = [(number of in-scope households with a fixed telephone) / (total number of in-scope households)]*100 • HH3%mobile = [(number of in-scope households with a mobile telephone) / (total number of in-scope households)]*100 • HH3%any = [(number of in-scope households with a fixed and/or mobile telephone) / (total number of in- scope households)]*100 • HH3%fixed only = [(number of in-scope households with a fixed telephone only) / (total number of in-scope households)]*100 • HH3%mobile only = [(number of in-scope households with a mobile telephone only) / (total number of in- scope households)]*100 • HH3%both fixed and mobile = [(number of in-scope households with both fixed and mobile telephone) / (total number of in-scope households)]*100 Policy relevance: A telephone provides shared, two-way communication services to a household and therefore allows members of a household to be reached, or to make a call, without having to travel any distance.
It is an important basic device to stay in contact with people and to make calls in the case of an emergency.

Basic telephone services remain relatively affordable and are usually free for incoming calls, which makes them relatively accessible to low income households.

At the same time, almost anyone can use a telephone since it does not require specific literacy or ICT skills.

Mobile cellular telephones are becoming the predominant method of communication in many countries.
Although fixed telephone lines have now been surpassed by mobile telephony globally, they are still an important affordable communication medium.

Furthermore, they provide a basis for Internet access in most economies, whether through dial-up, Integrated Services Digital Networks (ISDN), or Digital Subscriber Line (DSL) services.

HH3 will help monitor trends in fixed and mobile telephony over time.
In developing economies, while fixed- telephone networks are often limited to urban areas, mobile-cellular network coverage has reached about 91 per cent of their population, effectively overcoming a major infrastructure barrier.

Many countries have identified specific goals for the delivery of universal service, which refers to the availability of basic telecommunication services for every household.
To achieve universal service, many governments have set up universal service funds and identified universal service obligations, which oblige operators to provide basic services (often at set or limited prices) to a certain percentage of households, and in particular those in rural and remote areas, or to households with low income levels.
Examples include the 2002 Universal Service Obligation in India65 and the 1997 United States Universal Service Fund.66 65 66 See http://www.itu.int/ITU-D/treg/related-links/links-docs/USOF-India.pdf.

See http://www.fcc.gov/encyclopedia/universal-service.

Since the 1997 USF, the FCC has made changed the USF to include the financing of access to broadband.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 49 Indicator HH4: Proportion of households with a computer Definitions: This is the proportion of households that have a computer.

A computer refers to a desktop computer, a laptop (portable) computer or a tablet (or similar handheld computer).

• Desktop: a computer that usually remains fixed in one place; normally the user is placed in front of it, behind the keyboard.
• Laptop (portable) computer: a computer that is small enough to carry and usually enables the same tasks as a desktop computer; it includes notebooks and netbooks but does not include tablets and similar handheld computers.

• Tablet (or similar handheld computer): a tablet is a computer that is integrated into a flat touch screen, operated by touching the screen rather than (or as well as) using a physical keyboard.
It does not include equipment with some embedded computing abilities, such as smart TV sets, and devices with telephony as their primary function, such as smartphones.

Clarifications and methodological issues: HH4 has been revised since the last edition of this manual and now includes tablets (and similar), which are more recent devices.

‘Household with a computer’ means that the computer is generally available for use by all members of the household at any time, regardless of whether it is actually used.
The computer may or may not be owned by the household, but should be considered a household asset.

Household is defined in Chapter 7.

For time series compatibility, countries may want to split the question to include more than one response category, such as desktop computer, laptop (portable) computer and tablet (or similar handheld computer).

Equipment should be in working condition at the time of the survey.

Model question: Does this household have a computer (desktop, laptop, tablet or similar)?
Yes/No Note that if the question is split by type of computer, respondents should select all that apply.

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.
• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.

• Disaggregation by type of computer: desktop, laptop, tablet or similar.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.
Calculation: The number of in-scope households with a computer, or a given type of computer, is calculated by aggregating the weighted responses (see Chapter 8).

The proportion of households with a computer is expressed as a percentage and is calculated by dividing the number of in-scope households with a computer (or a given type of computer) by the total number of in-scope households and then multiplying the result by 100.
• HH4% = [(number of in-scope households with a computer) / (total number of in-scope households)]*100 • HH4%desktop = [(number of in-scope households with a desktop computer) / (total number of in-scope households)]*100 • HH4%laptop = [(number of in-scope households with a laptop computer) / (total number of in-scope households)]*100 • HH4%tablet = [(number of in-scope households with a tablet or similar) / (total number of in-scope households)]*100 Alternatively, percentages can be also presented for each type of computer as the percentage of in-scope households with a computer by type of computer, that is, the denominator is the total number of households with a computer of any type.
Manual for Measuring ICT Access and Use by Households and Individuals 50 Chapter 4.

Statistical standards and measurement topics for ICT household statistics Policy relevance: The availability of a computer at home allows people to carry out basic computing tasks, and store and process information, including word processing.

The availability of a computer at home is also important for household members to improve their ICT skills.
A computer is also an important device to access and use the Internet, in particular advanced applications and services (which are usually more difficult to use on a smartphone).

Moreover, there is growing evidence of the strong association between school performance and home access and use of computers.67 Information on the proportion of households with a computer is critical in identifying households without a computer.
Classificatory variables – such as ‘household income’, ‘rural/urban’ and other geographical classifications – can provide data to inform policies targeting households without a computer (e.g.

computer subsidy schemes).68 Such detailed information at household level is unavailable through other data sources.

This indicator is included in the ICT Development Index,69 and thus considered a key metric for international comparison of ICT developments.

67 68 See, for instance, OECD (2010).


Recognizing the potential of connecting more households with a computer and Internet access, a number of governments, including Brazil, Uruguay and Peru, have subsidized the purchase of a computer for low-income families.

For example, Uruguay has a national ‘one laptop per child’ programme in public schools (100 per cent of students have their own laptop and over 95 per cent of public schools have Internet access).
An impact of this program is a narrowing of the digital divide between high- and low-income households to only 6 per cent (in 2012).

See http://www.itu.int/ITU-D/sis/newslog/2010/02/08/UruguaysAmbitiousPlanCeibal.aspx 69 The ICT Development Index (IDI) is ITU’s composite index to monitor and compare developments in information and communication technology (ICT) across countries.

For more information on the IDI, see Chapter 2 and Annex 1 in ITU (2013a).
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 51 Indicator HH5: Proportion of individuals using a computer Definitions: This is the proportion of individuals who used a computer from any location in the last three months.

A computer refers to a desktop computer, a laptop (portable) computer or a tablet (or similar handheld computer).
• Desktop: a computer that usually remains fixed in one place; normally the user is placed in front of it, behind the keyboard.

• Laptop (portable) computer: a computer that is small enough to carry and usually enables the same tasks as a desktop computer; it includes notebooks and netbooks but does not include tablets and similar handheld computers.
• Tablet (or similar handheld computer): a tablet is a computer that is integrated into a flat touch screen, operated by touching the screen rather than (or as well as) using a physical keyboard.

It does not include equipment with some embedded computing abilities, such as smart TV sets, and devices with telephony as their primary function, such as smartphones.
Clarifications and methodological issues: HH5 has been revised since the last edition of this manual and now includes tablets (and similar), which are more recent devices.

This indicator refers to use of a computer by individual household members.

The suggested reference period is the last three months.

Country practices vary, but ideally, reference periods should be aligned in order to obtain comparable data.

Note that this represents a change since the last edition of this manual.
Countries changing their reference period may wish to split the reference period in order to obtain comparable time series.

Individual is discussed in Chapter 7.

As for HH4, for time series compatibility, countries may want to split the question to include more than one response category, such as desktop computer, laptop (portable) computer and tablet (or similar handheld computer).

Model question: Have you used a computer (desktop, laptop, tablet or similar) from any location in the last three months?
Yes/No Note that if the question is split by type of computer, respondents should select all that apply.

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Classification by sex.

• Classification by age: countries can use the following age groups for reporting on individuals’ age: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.
• Classification by highest education level attained: countries can use the ISCED 2011 classification for reporting on individuals’ level of education: primary education or lower (ISCED 0,1); lower secondary education (ISCED 2); upper secondary or post-secondary non-tertiary education (ISCED 3, 4); tertiary education (ISCED 5, 6); and post-tertiary education (ISCED 7, 8).
• Classification by labour force status: countries can use the following categories for reporting on individuals’ labour force status: employee; self-employed; workers not classifiable by status, unemployed; and outside the labour force.
• Classification by occupation: countries should use the ISCO 2008 categories where these are in use (if not, use ISCO-88 per Table 4 earlier in this chapter) for reporting on individuals’ occupation: managers; professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators, and assemblers; elementary occupations; and armed forces occupations.
(However, note that armed forces personnel may be out of scope of household surveys.)

• By type of computer: desktop, laptop, tablet or similar.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as individual income.

Manual for Measuring ICT Access and Use by Households and Individuals 52 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Calculation: The number of in-scope individuals using a computer is calculated by aggregating the weighted responses (see Chapter 8).

The proportion of individuals using a computer is expressed as a percentage and is calculated by dividing the total number of in-scope individuals using a computer by the total number of in-scope individuals, and then multiplying the result by 100.
The indicator can be split by type of computer, similarly to HH4.

• HH5% = [(number of in-scope individuals using a computer) / (total number of in-scope individuals)]*100 Policy relevance: Using a computer is an increasingly important life skill.

It allows people to carry out basic computing tasks, and store and process information, including word processing.

Using a computer also allows people to improve their ICT skills and become more familiar with advanced computing functionalities.
A computer is also an important means of using the Internet, in particular advanced applications and services (which are usually more difficult to use on a smartphone).

Classificatory variables for individuals using a computer – such as age, sex, education level or labour force status – can help identify digital divides, for example, a gender gap or a socio-economic divide.

This information can feed policy analysis and contribute to the design of targeted policies to overcome digital divides.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 53 Indicator HH6: Proportion of households with Internet Definitions: This is the proportion of households with Internet access at home.

The Internet is a worldwide public computer network.
It provides access to a number of communication services including the World Wide Web and carries e-mail, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer − it may also be by mobile telephone, tablet, PDA, games machine, digital TV etc.).

Access can be via a fixed or mobile network.


Clarifications and methodological issues: ‘Household with Internet access’ means that the Internet is generally available for use by all members of the household at any time, regardless of whether it is actually used.

The connection and devices may or may not be owned by the household but should be considered household assets.

Household is discussed in Chapter 7.

An Internet connection in the household should be working at the time of the survey.
Model question: Does this household have Internet?

Yes/No Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.
• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.

Calculation: The number of in-scope households with Internet is calculated by aggregating the weighted responses (see Chapter 8).
The proportion of households with Internet is expressed as a percentage and is calculated by dividing the number of in-scope households with Internet by the total number of in-scope households, and then multiplying the result by 100.
• HH6% = [(number of in-scope households with Internet) / (total number of in-scope households)]*100 Policy relevance: Having Internet at home is a key indicator of information society progress because Internet access at home allows citizens to benefit from the availability of ICT services and applications on the Internet in the privacy and security of their home.

For instance, for the delivery of e-government services it is critical knowing whether citizens have Internet access at home.
Home Internet access has some advantages over Internet access at other locations because users are free to choose the Internet activity they want to carry out.

Moreover, home Internet access is usually not limited in terms of time, or purpose, and is potentially available to all members of the household, even those lacking ICT skills (because other household members can help them, or carry out certain activities for them, for example, carrying out research or finding information).
A number of studies, including the OECD’s PISA studies (for example, OECD (2010), highlight the positive relationship between ICT access and use at home and educational performance, with those that have Internet access at home achieving higher grades and faring better academically.

The Broadband Commission has set a target that by 2015, 40 per cent of households in developing economies should have Internet access (either fixed or mobile).
A growing number of countries include Internet access (usually broadband access) as a target in their national ICT or broadband plans.

HH6 is included in the ICT Development Index, and is thus considered a key metric for international comparisons of ICT developments.

Manual for Measuring ICT Access and Use by Households and Individuals 54 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Indicator HH7: Proportion of individuals using the Internet Definitions: This is the proportion of individuals who used the Internet from any location in the last three months.

The Internet is a worldwide public computer network.
It provides access to a number of communication services including the World Wide Web and carries e-mail, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer − it may also be by mobile telephone, tablet, PDA, games machine, digital TV etc.).

Access can be via a fixed or mobile network.

Clarifications and methodological issues: This indicator refers to use of the Internet by individual household members.
The suggested reference period is the last three months.

Country practices vary, but ideally, reference periods should be aligned in order to obtain comparable data.

Note that this represents a change since the last edition of this manual.

Countries changing their reference period may wish to split the reference period in order to obtain comparable time series.

Individual is discussed in Chapter 7.

Model questions: Have you used the Internet from any location in the last three months?
Yes/No Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Classification by sex.

• Classification by age: countries can use the following age groups for reporting on individuals’ age: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.
• Classification by highest education level attained: countries can use the ISCED 2011 classification for reporting on individuals’ level of education: primary education or lower (ISCED 0,1); lower secondary education (ISCED 2); upper secondary or post-secondary non-tertiary education (ISCED 3, 4); tertiary education (ISCED 5, 6); and post-tertiary education (ISCED 7, 8).
• Classification by labour force status: countries can use the following categories for reporting on individuals’ labour force status: employee; self-employed (includes employers, own account workers, members of producers' cooperatives and contributing family workers); workers not classifiable by status, unemployed; and outside the labour force.
• Classification by occupation: countries should use the ISCO 2008 categories where these are in use (if not, use ISCO-88 per Table 4 earlier in this chapter) for reporting on individuals’ occupation: managers; professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators, and assemblers; elementary occupations; and armed forces occupations (noting that armed forces personnel may be out of scope).
• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as individual income.

Calculation: The number of in-scope individuals using the Internet is calculated by aggregating the weighted responses (see Chapter 8).
The proportion of individuals using the Internet is expressed as a percentage and is calculated by dividing the total number of in-scope individuals using the Internet by the total number of in-scope individuals, and then multiplying the result by 100.
• HH7% = [(number of in-scope individuals using the Internet) / (total number of in-scope individuals)]*100 Policy relevance: Internet user uptake is a key indicator tracked by policy-makers and analysts as an indication of a country’s progress towards becoming an information society.

Classificatory variables for individuals using the Internet – such as age, sex, education level or labour force status – can help identify digital divides in individuals using the Internet.
This information can contribute to the design of targeted policies to overcome those divides.

The proportion of Internet users is one of the three ICT-related Millennium Development Goal (MDG) indicators, and the Broadband Commission has set a target that by 2015, Internet user penetration should reach 60 per cent worldwide – 50 per cent in developing economies and 15 per cent in least developed economies.
In 2013 the Commission endorsed a new target aimed at achieving gender equality in broadband access by 2020.

This target can be monitored by HH7 classified by sex.

HH7 is included in the ICT Development Index, and thus considered a key metric for international comparisons of ICT developments.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 55 Indicator HH8: Proportion of individuals using the Internet, by location Definitions: This is the proportion of individuals who used the Internet from specified locations in the last three months.

The Internet is a worldwide public computer network.
It provides access to a number of communication services including the World Wide Web and carries e-mail, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer − it may also be by mobile telephone, tablet, PDA, games machine, digital TV etc.).

Access can be via a fixed or mobile network, including wireless access at a WiFi ‘hotspot’.

Access via a mobile device should be classified to the appropriate location or to ‘in mobility’, that is while mobile.
Locations of Internet use are defined as follows: • Home • Work: where a person’s workplace is located at his/her home, then he/she would answer yes to the home category only • Place of education: applies only to students – teachers and others who work at a place of education would report ‘work’ as the place of Internet use; where a place of education is also made available as a location for general community Internet use, such use should be reported in the Community Internet access facility category • Another person’s home: the home of a friend, relative or neighbour • Community Internet access facility (typically free of charge): Internet use at community facilities such as public libraries, publicly provided Internet kiosks, non-commercial telecentres, digital community centres, post offices, other government agencies; access is typically free and available to the general public • Commercial Internet access facility (typically not free of charge): Internet use at publicly available commercial facilities such as Internet or cybercafés, hotels, airports etc., where access is typically paid for • In mobility: Use of the Internet while mobile, via a mobile cellular telephone (including devices with mobile telephone functionality) or other mobile access devices, for example, a laptop computer, tablet or other handheld device connected to a mobile phone network.
Clarifications and methodological issues: Individuals should be asked about all locations of Internet use.

The survey question used by countries should specify multiple responses and should not, for example, ask about the most frequently used locations.

The suggested reference period is the last three months.

Country practices vary, but ideally, reference periods should be aligned in order to obtain comparable data.

Note that this represents a change since the last edition of this manual.
Countries changing their reference period may wish to split the reference period in order to obtain comparable time series.

The concept of access via a mobile device represents a change from the concept in the previous edition, which distinguished mobile access at any location from access at specified locations.

Individual is discussed in Chapter 7.

Model question: Where did you use the Internet in the last three months?

Respondents should select all locations (see above) that apply.
Countries may also ask about location of use as a series of yes/no questions, each referring to one location of use.

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Classification by sex.

• Classification by age: countries can use the following age groups for reporting on individuals’ age: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.
• Classification by highest education level attained: countries can use the ISCED 2011 classification for reporting on individuals’ level of education: primary education or lower (ISCED 0,1); lower secondary education (ISCED 2); upper secondary or post-secondary non-tertiary education (ISCED 3, 4); tertiary education (ISCED 5, 6); and post-tertiary education (ISCED 7, 8).
• Classification by labour force status: countries can use the following categories for reporting on individuals’ labour force status: employee; self-employed (includes employers, own account workers, members of producers' cooperatives and contributing family workers); workers not classifiable by status, unemployed; and outside the labour force.
• Classification by occupation: countries should use the ISCO 2008 categories where these are in use (if not, use ISCO-88 per Table 4 earlier in this chapter) for reporting on individuals’ occupation: managers; Manual for Measuring ICT Access and Use by Households and Individuals 56 Chapter 4.
Statistical standards and measurement topics for ICT household statistics professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators, and assemblers; elementary occupations; and armed forces occupations (noting that armed forces personnel may be out of scope).
• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as individual income.

Calculation: The number of in-scope individuals using the Internet from a specific location is calculated by aggregating the weighted responses for each location (see Chapter 8).
Proportions are expressed as percentages and are calculated by dividing the number of in-scope individuals using the Internet from a specific location by either the total number of in-scope individuals using the Internet (see HH7) or by the total number of in-scope individuals, and then multiplying the result by 100.
Examples: The percentage of Internet users using the Internet at home is calculated as: • HH8%Internet users home = [(number of in-scope individuals using the Internet at home) / (total number of in- scope individuals using the Internet)]*100 The percentage of in-scope individuals using the Internet at home is calculated as: • HH8%Individuals home = [(number of in-scope individuals using the Internet at home) / (total number of in- scope individuals)]*100 Policy relevance: HH8 can provide important information for policy-makers because it helps them to identify possible ways of increasing Internet access.
A country where many people rely on public Internet access facilities could, for example, ensure that these are widely available and affordable.

Conversely, if public Internet facilities exist in a country but are not much used, it could mean that there are constraints on use or that users have more convenient options.

Countries may wish to track changes in location of Internet use, such as from other locations to home Internet access.
Home Internet access is likely to be preferred where it is possible (e.g.

it is private, safer and may be less limited in terms of purpose or time).

Classificatory variables can provide useful information on differences in the location of use of the Internet by men/women, children/adults, employed/unemployed, etc.

These data may inform targeted policies to reduce digital divides within a country, such as a gender gap or a socio-economic divide in individuals using the Internet.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 57 Indicator HH9: Proportion of individuals using the Internet, by type of activity Definitions: This is the proportion of individuals who undertook one or more activities using the Internet for private (defined as non-work) purposes from any location in the last three months.
Internet activities are defined as follows: • Getting information about goods or services • Seeking health information (on injury, disease, nutrition etc.).

• Making an appointment with a health practitioner via a website • Getting information from general government organizations • Interacting with general government organizations (downloading/requesting forms, completing/lodging forms online, making online payments and purchasing from government organizations etc.)
General government organizations should be consistent with the SNA93 (2008 revision) concept of general government.
According to the SNA “… the principal functions of government are to assume responsibility for the provision of goods and services to the community or to individual households and to finance their provision out of taxation or other incomes; to redistribute income and wealth by means of transfers; and to engage in non-market production.” (General) government organizations include central, state and local government units.
• Sending or receiving e-mail • Telephoning over the Internet/VoIP (using Skype, iTalk, etc.

; includes video calls via webcam) • Participating in social networks (creating user profile, posting messages or other contributions to Facebook, Twitter etc.)
• Accessing chat sites, blogs, newsgroups or online discussions • Purchasing or ordering goods or services (purchase orders placed via the Internet whether or not payment was made online; excludes orders that were cancelled or not completed; includes purchasing of products such as music, travel and accommodation via the Internet) • Selling goods or services (via eBay, Mercado libre, Facebook etc.)
• Using services related to travel or travel-related accommodation • Internet banking (includes electronic transactions with a bank for payment, transfers, etc.

or for looking up account information; excludes electronic transactions via the Internet for other types of financial services such as share purchases, financial services and insurance) • Doing a formal online course (in any subject) • Consulting wikis (Wikipedia etc.
), online encyclopaedias or other websites for formal learning purposes • Listening to web radio (either paid or free of charge) • Watching web television (either paid or free of charge) • Streaming or downloading images, movies, videos or music; playing or downloading games (either paid or free of charge) • Downloading software or applications (includes patches and upgrades, either paid or free of charge) • Reading or downloading online newspapers or magazines, electronic books (includes accessing news websites, either paid or free of charge; includes subscriptions to online news services) • Looking for a job or sending/submitting a job application (includes searching specific web sites for a job; sending/submitting an application online) • Participating in professional networks (professional networks are also seen in the broader context of social networking and have the same requirement of profile creation, contributing through messaging or chat, or uploading text or audio-visual content files; examples of professional or business networks are LinkedIn and Xing) • Managing personal/own homepage • Uploading self/user-created content to a website to be shared (text, images, photos, videos, music, software, etc.)
• Blogging: maintaining or adding contents to a blog • Posting opinions on civic or political issues via websites (blogs, social networks, etc.)

that may be created by any individual or organization • Taking part in online consultations or voting to define civic or political issues (urban planning, signing a petition etc.)

• Using storage space on the Internet to save documents, pictures, music, video or other files (e.g.
Google Drive, Dropbox, Windows Skydrive, iCloud, Amazon Cloud Drive) • Using software run over the Internet for editing text documents, spreadsheets or presentations Clarifications and methodological issues: Note that these activities are restricted to private purposes and therefore exclude activities such as purchasing over the Internet undertaken as part of a person’s job or teleworking.

Individuals should be asked about all Internet activities.
The survey question used by countries should specify multiple responses and should not, for example, ask about the most frequent activities undertaken.

Activities are not mutually exclusive, that is, there is overlap between some categories.

When collecting data on these activities, some of them may need rewording and examples provided according Manual for Measuring ICT Access and Use by Households and Individuals 58 Chapter 4.
Statistical standards and measurement topics for ICT household statistics to the local context.

The suggested reference period is the last three months.

Country practices vary, but ideally, reference periods should be aligned in order to obtain comparable data.

Note that this represents a change since the last edition of this manual.

Countries changing their reference period may wish to split the reference period in order to obtain comparable time series.

Individual is discussed in Chapter 7.


Countries may wish to extend activities to some non-private purposes, such as teleworking (working from one’s home either as an employee or as a self-employed person).

Model question: For which of the following activities did you use the Internet for private purposes (from any location) in the last three months?’ Respondents should select all activities (see above) that apply.
Countries may ask about activities as a series of yes/no questions, each referring to one activity.

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Classification by sex.

• Classification by age: countries can use the following age groups for reporting on individuals’ age: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.
• Classification by highest education level attained: countries can use the ISCED 2011 classification for reporting on individuals’ level of education: primary education or lower (ISCED 0,1); lower secondary education (ISCED 2); upper secondary or post-secondary non-tertiary education (ISCED 3, 4); tertiary education (ISCED 5, 6); and post-tertiary education (ISCED 7, 8).
• Classification by labour force status: countries can use the following categories for reporting on individuals’ labour force status: employee; self-employed (includes employers, own account workers, members of producers' cooperatives and contributing family workers); workers not classifiable by status, unemployed; and outside the labour force.
• Classification by occupation: countries should use the ISCO 2008 categories where these are in use (if not, use ISCO-88 per Table 4 earlier in this chapter) for reporting on individuals’ occupation: managers; professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators, and assemblers; elementary occupations; and armed forces occupations (noting that armed forces personnel may be out of scope).
• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as individual income.

Calculation: The number of in-scope individuals using the Internet for a specific activity is calculated by aggregating the weighted responses for each activity (see Chapter 8).
Proportions are expressed as percentages and are calculated by dividing the number of in-scope individuals using the Internet for a specific activity by either the total number of in-scope individuals using the Internet (see HH7) or by the total number of in-scope individuals, and then multiplying the result by 100.
Examples: The percentage of Internet users who undertook Internet banking is calculated as: • HH9%Internet users banking = [(number of in-scope individuals who used the Internet for banking) / (total number of in-scope individuals who used the Internet)]*100 The percentage of in-scope individuals using the Internet for Internet banking is calculated as: • HH9%Individuals banking = [(number of in-scope individuals who used the Internet for banking) / (total number of in-scope individuals)]*100 Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 59 Policy relevance: The indicator on the types of Internet activities undertaken by individuals is a key indicator in tracking the information society because it allows policy-makers, businesses and analysts to understand how Internet access is changing the way that people do business, learn, buy, communicate and interact with others, including governments.
This indicator is important for the formulation of policies since it is an indication of the demand for certain online services and applications.

For example, it helps government organizations understand the demand for e- government information and services.

Questions on e-goods and services will help businesses and others understand the degree to which users are adopting e-commerce, etc.
HH9 also provides useful information on the sophistication of Internet use and the degree of ICT skills that Internet users have.

Classificatory variables can provide further information on differences in the Internet activities undertaken by men/women, children/adults, employed/unemployed, etc.
This information may be used, for instance, to design policies to promote e-commerce and extend e-government services to particular target groups, in order to ensure transition towards an inclusive information society.

Manual for Measuring ICT Access and Use by Households and Individuals 60 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Indicator HH10: Proportion of individuals using a mobile cellular telephone Definitions: This is the proportion of individuals who used a mobile telephone in the last three months.

A mobile (cellular) telephone refers to a portable telephone subscribing to a public mobile telephone service using cellular technology, which provides access to the PSTN.
This includes analogue and digital cellular systems and technologies such as IMT-2000 (3G) and IMT-Advanced.

Users of both postpaid subscriptions and prepaid accounts are included.

Clarifications and methodological issues: This indicator refers to the use of a mobile telephone by individual household members for communication (therefore, not only as a clock, playing games or listening to music).
Use of a mobile telephone does not necessarily mean that the telephone is owned or paid for by the individual but should be reasonably available through work, a friend or family member, etc.

It excludes occasional use, for instance, borrowing a mobile telephone to make a call.

The suggested reference period is the last three months.

Country practices vary, but ideally, reference periods should be aligned in order to obtain comparable data.
Note that this represents a change since the last edition of this manual.

Countries changing their reference period may wish to split the reference period in order to obtain comparable time series.

Individual is discussed in Chapter 7.

Model question: Have you used a mobile telephone in the last three months?

Yes/No Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.
• Classification by sex.

• Classification by age: countries can use the following age groups for reporting on individuals’ age: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.
• Classification by highest education level attained: countries can use the ISCED 2011 classification for reporting on individuals’ level of education: primary education or lower (ISCED 0,1); lower secondary education (ISCED 2); upper secondary or post-secondary non-tertiary education (ISCED 3, 4); tertiary education (ISCED 5, 6); and post-tertiary education (ISCED 7, 8).
• Classification by labour force status: countries can use the following categories for reporting on individuals’ labour force status: employee; self-employed (includes employers, own account workers, members of producers' cooperatives and contributing family workers); workers not classifiable by status, unemployed; and outside the labour force.
• Classification by occupation: countries should use the ISCO 2008 categories where these are in use (if not, use ISCO-88 per Table 4 earlier in this chapter) for reporting on individuals’ occupation: managers; professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators, and assemblers; elementary occupations; and armed forces occupations (noting that armed forces personnel may be out of scope).
• By type of mobile telephone, for example, to distinguish smartphone use.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as individual income.

Calculation: The number of in-scope individuals using a mobile cellular telephone is calculated by aggregating the weighted responses (see Chapter 8).
The proportion of individuals using a mobile telephone is expressed as a percentage and is calculated by dividing the total number of in-scope individuals using a mobile telephone by the total number of in-scope individuals, and then multiplying the result by 100.

• HH10% = [(number of in-scope individuals using a mobile cellular telephone) / (total number of in-scope individuals)]*100 Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 61 Policy relevance: The proportion of individuals who use a mobile telephone is an important indicator to measure the uptake of mobile cellular technology.
The indicator complements the widely available indicator on the number of mobile cellular subscriptions and does not have the same shortcomings as the latter: HH10 provides information on the number and type of people who use a mobile telephone, whereas the mobile cellular subscription indicator measures the number of subscriptions.

HH10 is particularly useful for developing economies, where ICT access and use remains limited.
Classificatory variables for individuals using a mobile telephone – such as age, sex, education level or labour force status – can help identify digital divides, for example, a gender gap or a socio-economic divide.

This information can feed policy analysis and contribute to the design of targeted policies to overcome those divides.

Manual for Measuring ICT Access and Use by Households and Individuals 62 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Indicator HH11: Proportion of households with Internet, by type of service Definitions: This is the proportion of households with access to the Internet, by type of service.

The Internet is a worldwide public computer network.
It provides access to a number of communication services including the World Wide Web and carries e-mail, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer − it may also be by mobile telephone, tablet, PDA, games machine, digital TV etc.).

Access can be via a fixed or mobile network.
The broad types of Internet services to be identified are the following: • Fixed (wired) narrowband network: includes analogue modem (dial-up via standard telephone line), ISDN (Integrated Services Digital Network), DSL (Digital Subscriber Line) at advertised download speeds below 256 kbit/s, and other forms of access with an advertised download speed of less than 256 kbit/s • Fixed (wired) broadband network: refers to technologies at advertised download speeds of at least 256 kbit/s, such as DSL, cable modem, high speed leased lines, fibre-to-the-home/building, powerline and other fixed (wired) broadband • Terrestrial fixed (wireless) broadband network: refers to technologies at advertised download speeds of at least 256 kbit/s, such as WiMAX, fixed CDMA • Satellite broadband network (via a satellite connection), at advertised download speeds of at least 256 kbit/s • Mobile broadband network (at least 3G, e.g.
UMTS) via a handset • Mobile broadband network (at least 3G, e.g.

UMTS) via a card (e.g.

integrated SIM card in a computer) or USB modem Clarifications and methodological issues: As households can use more than one type of access service, multiple responses are possible.

Household is defined in Chapter 7.

Proposed categories and technical terms will probably not be used directly in household questionnaires.

They are recommended for reporting purposes and international data harmonization.
The questions and response categories at the country level (in the household questionnaire) need to be adapted according to plans and services offered by operators and terminologies that are more familiar to users.

Furthermore, according to local context, additional information could be collected to better identify the correct type of access.

WiFi access available inside the home to redistribute a fixed (wired) broadband signal is categorized as fixed (wired) broadband.
If information is collected by access technology (e.g.

cable modem, DSL, fibre-to-the- home/building, other fixed (wired) broadband), then WiFi should be classified to the type of technology available in the household.

The Internet connection(s) selected should be working at the time of the survey.

Model question: What type/s of Internet services are used for Internet access at home?

Respondents should select all that apply (see above).
Countries may ask about services as a series of yes/no questions, each referring to one type of service.

This question can present difficulties for both respondents and interviewers.

The response options should be based on the commercial packages or plans offered in the country at the time of the interview – possibly using the brand names used by service providers, where these can be recoded to the different types of networks.
Grouping into the above categories should be done by specialists during the coding phase of data processing.

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: Disaggregation by household characteristics: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.
• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 63 Calculation: The number of in-scope households with Internet access by a given type of access is calculated by aggregating the weighted responses for each type of access (see Chapter 8).
Proportions are expressed as percentages and are calculated by dividing the number of in-scope households with a given type of Internet access by either the total number of in-scope households with Internet access (HH6) or by the total number of in-scope households, and then multiplying the result by 100.
Examples: The percentage of households with Internet access using a fixed (wired) broadband network should be calculated as: • HH11%households with access, fixed broadband = [(number of in-scope households with fixed (wired) broadband Internet access) / (total number of in-scope households with Internet access)]*100 The percentage of in-scope households accessing the Internet via a fixed broadband network should be calculated as: • HH11%all households, fixed broadband = [(number of in-scope households with fixed (wired) broadband Internet access) / (total number of in-scope households)]*100 Policy relevance: Information on the type of Internet access that households use enables monitoring of the uptake of broadband Internet access.
It is also important in tracking the transition from fixed (wired) Internet access, to wireless access.

Fixed–mobile substitution has an impact on the definition and regulation of broadband markets, because it determines to a great extent the competitive forces acting in the market.

Quantitative data on fixed– mobile substitution is becoming an increasingly significant input for evidence-based market regulation.
The breakdown by technology allows policy-makers to evaluate the speed and the quality of Internet connection, as each technology has different characteristics and offers different speeds.

Linked to the difference in speed and quality, this will also allow for an evaluation of the differences in the potential of these technologies and what types of activities can/cannot be carried out over the Internet.
For example, some countries are trying to increase the number of households that are connected via ftth since fibre offers particularly high speeds and quality, including for future applications and services.

Manual for Measuring ICT Access and Use by Households and Individuals 64 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Indicator HH12: Proportion of individuals using the Internet, by frequency Definitions and notes: This is the frequency of Internet use by individuals who used the Internet from any location in the last three months.

The Internet is a worldwide public computer network.
It provides access to a number of communication services including the World Wide Web and carries e-mail, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer − it may also be by mobile telephone, tablet, PDA, games machine, digital TV etc.).

Access can be via a fixed or mobile network.


Frequency of use categories are as follows: • At least once a day: once a working day for respondents who only (or most frequently) use the Internet from work or school etc.

• At least once a week but not every day • Less than once a week.
Clarifications and methodological issues: It is recommended that countries collect this information in respect of a typical period; therefore, respondents should ignore weekends (if they only use the Internet at work or school etc) and breaks from their usual routine, such as holidays.

Multiple responses are not possible.

The suggested reference period is the last three months.

Individual is discussed in Chapter 7.


Model question: How often did you typically use the Internet during the last three months (from any location)?

Respondents can only respond to one category (see above).

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Classification by sex.


• Classification by age: countries can use the following age groups for reporting on individuals’ age: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.
• Classification by highest education level attained: countries can use the ISCED 2011 classification for reporting on individuals’ level of education: primary education or lower (ISCED 0,1); lower secondary education (ISCED 2); upper secondary or post-secondary non-tertiary education (ISCED 3, 4); tertiary education (ISCED 5, 6); and post-tertiary education (ISCED 7, 8).
• Classification by labour force status: countries can use the following categories for reporting on individuals’ labour force status: employee; self-employed (includes employers, own account workers, members of producers' cooperatives and contributing family workers); workers not classifiable by status, unemployed; and outside the labour force.
• Classification by occupation: countries should use the ISCO 2008 categories where these are in use (if not, use ISCO-88 per Table 4 earlier in this chapter) for reporting on individuals’ occupation: managers; professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators, and assemblers; elementary occupations; and armed forces occupations (noting that armed forces personnel may be out of scope).
• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as individual income.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 65 Calculation: The number of in-scope individuals using the Internet with a specific frequency is calculated by aggregating the weighted responses for each frequency (see Chapter 8).
Proportions are expressed as percentages and are calculated by dividing the number of in-scope individuals using the Internet with a specific frequency either by the total number of in-scope individuals using the Internet (see HH7) or by the total number of in-scope individuals, and then multiplying the result by 100.
Examples: The percentage of Internet users who used the Internet at least once a day is calculated as: • HH12%Internet users at least once a day = [(number of in-scope individuals using the Internet at least once a day) / (total number of in-scope individuals who used the Internet)]*100 The percentage of in-scope individuals using the Internet at least once a day is calculated as: • HH12%Individuals at least once a day = [(number of in-scope individuals who used the Internet at least once a day) / (total number of in-scope individuals)]*100 Policy relevance: HH12 provides policy-makers with an understanding of the pervasiveness of the information society as it will help them distinguish between occasional Internet users and those who use the Internet intensively.
Measuring intensity of use is becoming more relevant as Internet access spreads, and the policy focus shifts from “what proportion of people use the Internet?” to “how much are people using the Internet?”.

The indicator is also useful in tracking progress over time and monitoring the evolution of Internet behavior.

Classificatory variables can provide further information on differences in the intensity of Internet use among men/women, children/adults, employed/unemployed, etc.
These data may inform targeted policies to promote Internet use among low-usage groups, and thus contribute to a more inclusive information society.

Manual for Measuring ICT Access and Use by Households and Individuals 66 Chapter 4.

Statistical standards and measurement topics for ICT household statistics Indicator HH13: Proportion of households with multichannel television, by type Definitions: This is the proportion of households with multichannel television (TV) and by type of multichannel service.
Multichannel TV services are as follows: • Cable TV (CATV): multichannel programming delivered over a coaxial cable for viewing on television sets • Direct-to-home (DTH) satellite services: TV services received via a satellite dish capable of receiving satellite television broadcasts • Internet-protocol TV (IPTV): multimedia services such as television/video/audio/text/graphics/data delivered over an IP-based network managed to support the required level of quality of service, quality of experience, security, interactivity and reliability; it does not include video accessed over the public Internet, for example, by streaming.
IPTV services are also generally aimed at viewing over a television set rather than a personal computer.

• Digital terrestrial TV (DTT): the technological evolution from analogue terrestrial television, providing capability for significantly more channels Clarifications and methodological issues: National questionnaires should reflect services available in the country and describe them using local terminology, such as brand names.
As households can use more than one type of multichannel TV service, multiple responses are possible.

Household is discussed in Chapter 7.

The TV service(s) selected should be working at the time of the survey.

Model question: Does this household have any of the following television services?

Respondents should select all services (see above) that apply.

Countries may ask about multichannel services as a series of yes/no questions, each referring to one service.
Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.

• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.
• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.

Calculation: The number of in-scope households with any type of multichannel TV service is calculated by aggregating the weighted responses for any multichannel TV service (see Chapter 8).
The proportion of households with any type of multichannel TV service is expressed as a percentage and is calculated by dividing the number of in-scope households with multichannel TV (of any type) by either the total number of in-scope households with TV (from HH2) or by the total number of in-scope households, and then multiplying the result by 100.
The number of in-scope households with a given type of multichannel service is calculated by aggregating the weighted responses for each multichannel TV service (see Chapter 8).

Proportions are expressed as percentages and are calculated by dividing the number of in-scope households with a given type of multichannel TV service by either the total number of in-scope households with TV (from HH2) or by the total number of in-scope households, and then multiplying the result by 100.
Examples: Percentage of households with a TV having cable TV: • HH13%households with TV, cable = [(number of in-scope households with cable TV) / (total number of in-scope households with a TV)]*100 Percentage of in-scope households with cable TV: • HH13%all households, cable TV = [(number of in-scope households with cable TV / (total number of in-scope households)]*100 Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 67 Policy relevance: This indicator is useful in tracking the move from analogue to digital TV and the adoption of multichannel services.

Since some multichannel and digital TV services do not require a subscription (e.g.
free-to-air satellite services and most digital terrestrial television broadcasts), nationally representative household surveys and censuses are the main vehicles for obtaining reliable data on multichannel and digital TV adoption.

For instance, countries doing the digital terrestrial television switchover use household surveys as a means of monitoring the process – because they can keep track of households equipped with set-top boxes or digital TVs.
Similar data cannot be captured from subscription-based administrative data sources.

A distinction of technologies will further allow policy-makers to monitor the current regulation of different TV platforms, particularly in view of convergence.

Indeed, because of the historical development of TV platforms, several technologies currently competing in the same TV markets may be subject to different regulation.
Reliable data on the evolution and uptake of new TV platforms will provide insights about the extent to which these platforms are complementing or substituting traditional TV services.

Hence, these data will be a relevant input for future revisions of the audiovisual regulatory framework.

Manual for Measuring ICT Access and Use by Households and Individuals 68 Chapter 4.
Statistical standards and measurement topics for ICT household statistics Indicator HH14: Barriers to household Internet access Definitions: This measures the barriers to Internet access for households without Internet access.

It is expressed as a proportion of households without Internet access.
Barriers (that is, reasons for not having Internet) are: • Do not need the Internet (not useful, not interesting, lack of local content) • Have access to the Internet elsewhere • Lack of confidence, knowledge or skills to use the Internet • Cost of the equipment is too high • Cost of the service is too high • Privacy or security concerns • Internet service is not available in the area • Internet service is available but it does not correspond to household needs (e.g.
quality, speed) • Cultural reasons (e.g.

exposure to harmful content) Clarifications and methodological issues: Household is defined in Chapter 7.

As households can have more than one barrier (reason for not having Internet), respondents should select all that apply.

Model question: Why does this household not have Internet access?

Respondents should select all reasons (see above) that apply.

Some countries may ask about barriers as a series of yes/no questions.
This question should be asked of households with no access to Internet at home.

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.
• Breakdown by characteristics of the head of the household/household reference person, such as sex, level of education, occupation or status in the labour force.

• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as household income.

Calculation: The number of in-scope households with a given barrier to Internet access is calculated by aggregating the weighted responses for each TV service (see Chapter 8).
Proportions are expressed as percentages and are calculated by dividing the number of in-scope households with a given barrier by the total number of in-scope households without Internet access, and then multiplying the result by 100.
Example: Percentage of households without Internet access for which cost of equipment is too high: • HH14%cost too high = [(number of in-scope households for which cost of equipment is too high) / (total number of in-scope households without Internet access)]*100 Policy relevance: HH14 is useful in countries where home Internet access is relatively low because it will help policy-makers to identify policy tools to overcome barriers to higher penetration rates.
If, for example, many citizens feel that the cost of the equipment or services is too high, specific actions could be taken to reduce costs.

If Internet services are not used because they are not available, more efforts can be made to expand Internet infrastructure.

Other specific programmes could tackle the awareness of the benefits of the Internet, the creation of local content or the development of ICT skills.
In countries where Internet access is high, this indicator is also relevant because barriers to household Internet access may be less evident and thus require detailed data (in some cases collected at subnational level) to inform policy-makers.

Indeed, connecting the last subscribers usually requires more targeted policies than those aiming at larger shares of the population.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 69 Indicator HH15: Individuals with ICT skills, by type of skills Definitions: This refers to ICT skills, defined for the purpose of this indicator as having undertaken certain computer-related activities in the last three months.
Computer-related activities to measure ICT skills are as follows: • Copying or moving a file or folder • Using copy and paste tools to duplicate or move information within a document • Sending e-mails with attached files (e.g.

document, picture, video) • Using basic arithmetic formulae in a spreadsheet • Connecting and installing new devices (e.g.
a modem, camera, printer) • Finding, downloading, installing and configuring software • Creating electronic presentations with presentation software (including text, images, sound, video or charts) • Transferring files between a computer and other devices • Writing a computer program using a specialized programming language Clarifications and methodological issues: Individual is discussed in Chapter 7.
Most individuals will have carried out more than one activity and therefore multiple responses are expected.

The tasks are broadly ordered from less complex to more complex, although there is no requirement for a respondent to select simpler tasks before selecting a more complex task.

It may be possible to construct a metric based on the number of tasks individuals have performed.
For example, Eurostat (2012) categorized individuals into low, medium and high levels of computer skills depending on how many tasks had been ticked (the level of difficulty of tasks is not taken into account).

However, as at 2012, that categorization was under review.

Model question: Which of the following computer-related activities have you carried out in the last three months?

Respondents should select all that apply (see above).

Some countries may ask about tasks as a series of yes/no questions.
This question is asked of individuals having used a computer in the last three months.

Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Classification by sex.

• Classification by age: countries can use the following age groups for reporting on individuals’ age: under 5; 5–9; 10–14; 15–24; 25–34; 35–44; 45–54; 55–64; 65–74 and 75 and over.
• Classification by highest education level attained: countries can use the ISCED 2011 classification for reporting on individuals’ level of education: primary education or lower (ISCED 0,1); lower secondary education (ISCED 2); upper secondary or post-secondary non-tertiary education (ISCED 3, 4); tertiary education (ISCED 5, 6); and post-tertiary education (ISCED 7, 8).
• Classification by labour force status: countries can use the following categories for reporting on individuals’ labour force status: employee; self-employed (includes employers, own account workers, members of producers' cooperatives and contributing family workers); workers not classifiable by status, unemployed; and outside the labour force.
• Classification by occupation: countries should use the ISCO 2008 categories where these are in use (if not, use ISCO-88 per Table 4 earlier in this chapter) for reporting on individuals’ occupation: managers; professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators, and assemblers; elementary occupations; and armed forces occupations (noting that armed forces personnel may be out of scope).
• Other breakdowns or classifications, where relevant variables or questions are used in the questionnaire, such as individual income.

Manual for Measuring ICT Access and Use by Households and Individuals 70 Chapter 4.

Statistical standards and measurement topics for ICT household statistics Calculation: Indicator HH15 is calculated as the proportion of in-scope computer users (HH5) who have carried out each computer-related activity.

The indicator is expressed as a percentage.


For instance, the percentage of individual computer users having copied or moved a file or folder can be calculated as: • HH15copied or moved a file= [(number of in-scope individuals who copied or moved a folder or file) / (number of in-scope individuals who used a computer)]*100 Policy relevance: ICT skills determine the effective use that is made of ICTs.

The information from HH15 may therefore assist in making the link between ICT usage and impact.
Currently, there is little data available for measuring ICT- specific skills, and hence researchers and policy-makers must rely on proxy indicators to measure this important enabler of ICT development.

HH15 is an appropriate way to measure and track the level of proficiency of computer users.
This information could be used, for example, to adapt ICT literacy courses in schools, identify barriers to certain uses of computers as well as potential applications and services that could be accessed over the Internet.

Classificatory variables can provide further information on the differences in ICT skills among men/women, children/adults, employed/unemployed, etc.

These data may be used to inform targeted policies to improve ICT skills, and thus contribute to an inclusive information society.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 71 Indicator HH16: Household expenditure on ICT Definitions: This measures the percentage of total household expenditure that is expended on ICT goods and services as follows: • Telephone and telefax equipment (COICOP 08.2.0): Purchases of telephones, radio-telephones, telefax machines, telephone-answering machines and telephone loudspeakers; repair of such equipment.
• Telephone and telefax services (COICOP 08.3.0): Installation and subscription costs of personal telephone equipment; includes telephone calls (from any location), information transmission services, Internet connection services, hire of telephones.
• Equipment for the reception, recording and reproduction of sound and picture (COICOP 09.1.1): Television sets, video cassette players and recorders, television aerials of all types; radio sets, car radios, radio clocks, two-way radios, amateur radio receivers and transmitters; gramophones, tape players and recorders, cassette players and recorders, CD-players, personal stereos, stereo systems and their constituent units (turntables, tuners, amplifiers, speakers, etc.

), microphones and earphones.


• Information processing equipment (COICOP 09.1.3): Personal computers, visual display units, printers and miscellaneous accessories accompanying them; computer software packages such as operating systems, applications, languages, etc.

; calculators, including pocket calculators; typewriters and word processors.

(Also includes laptops, tablets, e-book readers.)


• Repair of audio-visual, photographic and information processing equipment (COICOP 09.1.5) Clarifications and methodological issues: The 1999 UN Classification of Individual Consumption According to Purpose (COICOP) is used as the basis of the classification presented above and to define the scope of ICT goods and services.

It is expected that data would be collected from a household budget survey.
Ideally, the reference period would be a year, but this is likely to vary depending on the nature of countries’ existing budget surveys.

Note that television services are included in COICOP 09.4.2 – Cultural services.

Where countries are able to collect data separately on television services, they should include them in ICT services and note the inclusion in metadata.

Model question: As this indicator will usually be derived from household budget survey, no model question is proposed.
Disaggregation and classifications: If data allow breakdown and disaggregation, the following can be considered: • Breakdown by region, such as geographical areas, urban/ rural.

• Breakdown by household characteristics, such as household composition and size, and whether the household has access to electricity.

• Breakdown by household income, for example, by income quintile or quartile, according to the practices of the country.
Calculation: The indicator is calculated as the percentage of total household expenditure that is expended on ICT goods and services as defined above.

Policy relevance: Information on the percentage) of income that households spend on ICT can be compared to expenditure on other services (such as electricity, food, etc.).

The indicator provides an indication of the importance of ICTs because it shows how much households are prepared to spend on ICT.
At the same time, it can be linked to the price of ICT equipment and services and help governments identify ways of reducing the cost and increasing the affordability of ICT.

Other measurement topics related to ICT household statistics 174.

The core list of household indicators is a starting point for collection of data on ICT.

Many countries will have information needs for policy purposes that are not satisfied by the Partnership indicators alone.

175.
175.

Besides the core list of indicators, countries may wish to collect other statistics which are relevant to their ICT policies.

The inclusion of ICT-related questions in existing surveys (such as labour force or income and expenditure surveys) can provide interesting breakdowns and cross-tabulations.

This is discussed in Chapter 5.

Manual for Measuring ICT Access and Use by Households and Individuals 72 Chapter 4.

Statistical standards and measurement topics for ICT household statistics 176.
A number of other topics of interest for policy purposes are being discussed by the Expert Group on ICT Household Indicators (EGH): Use of portable devices to access the Internet by individuals, Internet security, Children and youth online protection, Green ICTs, Mobile telephone activities, Gender-relevant ICT indicators and ICT for people with disabilities.

177.
177.

A glance at the OECD and Eurostat model questionnaires (OECD, 2005, 2013; Eurostat 2013b), shows that there are many topics of interest beyond those covered by the core indicators.

This section outlines additional topics that countries may wish to measure in addition to those required to construct the core indicators.
The discussion in this section is based on work by the OECD’s Working Party on Indicators for the Information Society (OECD, 2011), the manuals for the Eurostat model surveys, 70 ITU’s Child Online Protection Statistical Framework and Indicators (ITU, 2010b) and discussions held by the EGH and the Partnership.

E-commerce 178.

For individual members of households, e-commerce presents an alternative method of purchasing (and increasingly selling) goods and services for private use.
According to the long-standing OECD statistical standard for measuring e-commerce, it is the method by which an order is placed or received, rather than the payment or channel of delivery, which determines whether a transaction is an e-commerce transaction.

OECD member countries have endorsed narrower (Internet) and broader (other computer-mediated networks) definitions of e-commerce.

179.
179.

The main interest in e-commerce measurement for the household sector is in use of the Internet for purchasing rather than selling transactions.

This can provide useful information on, for example, business-to-consumer e-commerce, often not obtained through business surveys.
While indicator HH9 includes the activities of purchasing and selling of goods or services, surveys of ICT use in households may collect additional information, including the nature of goods and services purchased or sold, the monetary value of those purchases or sales, the monetary value of online payments and/or barriers to purchasing or selling over the Internet.

Box 10 describes the e-commerce data collected by Brazil in 2011.

180.
180.

There are both conceptual and data collection challenges associated with e-commerce measurement.

For example, in respect of individuals reporting the value of Internet purchases, there are issues of understanding the definition of e-commerce (for instance, distinguishing purchases from payments71) and the relatively small volume of e-commerce activity, which has implications for the size of sampling error.
In addition, there are recall issues for respondents in relation to the value of e-commerce purchases (that is, they may not be able to report reliable information on the value of those purchases).

Indeed, as such Internet transactions become more common, the recall problem is likely to worsen.

72 70 71 Available for various years in http://epp.eurostat.ec.europa.eu/portal/page/portal/information_society/methodology.
Following the OECD definition, an e-commerce purchase occurs where an individual buys or orders a good or service online, irrespective of the method of payment (and whether the payment is made online or offline).

A payment that occurs online without the ordering of a good or service (e.g.

e-banking) is not regarded as e-commerce.


72 OECD countries vary in their collection efforts in this area, with an obvious trend being that fewer are collecting the value of Internet purchases (driven, in large part, because of changes to Eurostat’s model household survey of 2006, where the question on value of Internet purchases was removed).
The 2005 OECD model survey nominated the value of Internet purchases as a non-core question, reflecting both the direction of Eurostat and the difficulty respondents have to recall the value of purchases.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 73 Box 10.
Brazil: measuring e-commerce The survey on the use of ICT in households carried out by CETIC.br in Brazil in 2011 collected various items related to e-commerce.
These enable the production of indicators including the following (response categories in brackets): • the percentage of individuals who researched prices of products or services on the Internet; • the percentage of individuals who had purchased products or services via the Internet; • the types of products and services acquired through the Internet (electronic equipment, household products/appliances, clothing/footwear/sporting gear and accessories, computers and IT equipment, books/magazines or newspapers, travel (flight and hotel bookings), films/songs/ringtones, tickets for events, software, e-learning materials, computer games or videogames, medicines, food products, financial services/insurance, lottery and betting, flowers); • the method of payment (credit card, bank payment slip, online debit/electronic transfer, payment on delivery, financing, not paid/free); • the percentage of individuals who had problems purchasing through the Internet; • reasons not to shop through the Internet (prefers purchasing in person/likes to see the product, no need or interest, privacy and security concerns, does not trust the product that will be delivered, force of habit/usually shops in the same places, lack of Internet skills, delivery takes too long/problems in receiving products at home, unable to pay via the Internet, more expensive than traditional purchases, unable to return products or file complaints, desired products and services are not available on the Internet, could not complete the purchase); and • the percentage of individuals who have advertised or sold goods or services via the Internet.
Source: ICT Households and Enterprises 2011, Brazilian Center of Studies on Information and Communication Technologies (CETIC,br).

E-security: trust in the online environment and child online protection 181.

The question of trust in the online environment is an important one from a policy point of view, as lack of trust potentially impedes the uptake of ICT by individuals and other entities, such as businesses.
Both the OECD and Eurostat have made attempts to measure trust via their model surveys of household ICT access/use and the efforts of member countries.

73 However, evidence indicates that the topic presents difficult measurement challenges.

Problems include the difficulties of asking individuals about IT security in terms of: the incidents they have encountered, what action they take to protect themselves and whether the computer or similar device they use at home is protected.
Anecdotal evidence indicates that respondents have difficulty responding to such technical questions.

182.

A particularly relevant issue regarding security is child online protection, which comprises topics such as awareness and attitudes, risk-prone behavior of children, incidents and children’s responses and preventive actions.

A statistical framework for measuring child online protection has been developed by ITU (ITU, 2010b).
Some of the core indicators can be considered as part of this framework by considering the relevant age breakdowns (children under 15).
These include: • • • percentage of individuals under 15 who used the Internet during the past three months (HH7); risk-prone activities, indicated by the following categories of HH9 (Internet activities undertaken by individuals): Participating in social networks; Accessing chat sites, blogs, newsgroups or online discussions; Purchasing or ordering goods or services; Streaming or downloading images, movies, videos or music; playing or downloading games; and Uploading self/user-created content to a website to be shared.
location of individual use (HH8), especially those locations where parental control is more difficult (outside the home); and 73 Several questions (and parts of questions) in the OECD 2005 model questionnaire deal with the topic of trust in the online environment.

The questions concern the issue of IT security (questions 8, 15 and 16) and privacy, security or trust as barriers (questions 5 and 23).

See OECD (2011).

Manual for Measuring ICT Access and Use by Households and Individuals 74 • Chapter 4.
Statistical standards and measurement topics for ICT household statistics frequency of individual use (HH12), as it can provide a rough indication of time spent online and potential risk of addiction.

183.

In order to be able to collect indicators about the online activities of children, the scope of relevant surveys should include individuals under 15.
This should be taken into consideration when including ICT-related questions in an existing household survey vehicle that restricts its age scope to populations over 15 (such as labour force surveys in most countries).

184.
There are two potential new indicators that are being discussed by the EGH: • • children who have been subject to forms of victimization, such as cyberbullying, exposure to a medium that might foster harmful behaviour on the part of children, exposure to pornography, child solicitation or grooming, online encounters resulting in offline meetings and actions taken by parents about children’s use of Internet, such as agreeing on house rules about use of Internet and personal devices, installing an Internet content filter, supervising or monitoring child(ren)’s use of Internet, allowing the child(ren) to access the Internet only from a public area in the house, and educating child(ren) about safe and appropriate Internet use.
The social and economic impacts of ICT access and use by households and individuals 185.

There has been relatively little data collection and analytical work done on the impacts of ICT access and use by households and individuals.
However, the availability of ICT has obviously changed – and will continue to change – the types of jobs people do, how they work (for instance, teleworking), how they communicate with others, how they access commercial and government services, and what they do in their leisure time.

In respect of social statistics, the following ideas for impact measurement have been 186. suggested (OECD, 2007): • • • include perception questions in social surveys (e.g.
asking people how the Internet has affected their lives); use of standard time use and household expenditure survey methodologies and classifications in the area of ICT measurement, in order to find out how much time people are spending using ICT (and how this is changing) and how much money they are spending on ICT compared with other goods and services;74 and collection of statistics on ‘teleworking’ and other changes in work patterns that are driven by ICT; such data may be collected from specific ICT use surveys or via labour force surveys.
Barriers to ICT use 187.

For many developing economies, there are significant barriers to access to, and use of, ICT.

The current version of the core indicators includes barriers to Internet access by households.

Consideration could also be given to including other household and/or individual barriers questions in ICT household questionnaires.

For example, countries may be interested in investigating the reasons why households do not have computers.
Box 11 shows the reasons included in the ICT Household Survey of Oman, 2013.

Box 12 shows Eurostat’s 2007 model questions on barriers to more extensive use of ICT by individuals (for Internet users).

In developing economies, barriers such as lack of electricity, poor or 74 Note that the new indicator HH16 addresses this issue.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.
Statistical standards and measurement topics for ICT household statistics 75 unreliable network coverage, affordability of services offered or long distance to public Internet access points may be particularly policy relevant.

Box 11.

Oman: measuring barriers to household access to a computer The Information Technology Authority of Oman included, in its 2013 questionnaire, a question on the reasons why the interviewed household does not own a computer.
The question is worded as follows: What are the reasons for the household not owning a computer?

(select all that apply) • Cannot afford one • Household members have access to computers at work, school or Internet café • Household has no need for a computer • No one in the household knows how to use a computer • Harm for health • Waste of time • Illiteracy • Need special equipment/software • Other Source: ITA (2013) questionnaire.

Box 12.
Box 12.

Eurostat 2007 model question on barriers to use of the Internet by individuals The Eurostat 2007 model included questions, limited to Internet users, on barriers to more intensive use of Internet: What are your barriers to more intensive use of the Internet?
Population: Internet users Foreign language skills are inadequate Lack of time Connection is too slow Additional connection or per-volume download cost Cost of online content Content (what is there is not interesting enough to make more use of the Internet) Lack of skills or knowledge (e.g.

sites are not user-friendly or too complicated) Security or privacy concerns None of the above Source: Methodological Manual for statistics on the Information Society (Eurostat, 2007).

Gender-sensitive indicators 188.


While all indicators related to ICT use can be disaggregated by sex, there are other gender-sensitive indicators that could be considered.

ITU, as a member of the Partnership is working together with UNCTAD and various partners in elaborating a list of core indicators to monitor gender equality and integration in the context of ICT.
There are a number of areas where further sex-disaggregated data and indicators are needed, such as on skills, content, employment, education, representation of women in ICT decision-making and impact of ICTs on women lives.

Time-related issues 189.

There are several aspects of a survey that have a time characteristic.
They are: • • survey frequency (how often a survey is conducted); reference period/s (recall period/s) used in the questionnaire, typically when asking questions of an individual’s ICT use activities; Manual for Measuring ICT Access and Use by Households and Individuals 76 Chapter 4.

Statistical standards and measurement topics for ICT household statistics • • reference date/s used in the questionnaire when asking about a given situation (e.g.
whether the household has Internet access); and time series, that is a data series derived from surveys that are sufficiently compatible to allow comparison of data over time.

190.

For a particular country, survey frequency will be determined by national priorities, available resources and the level of penetration of ICT infrastructure and use.
A country’s multiyear statistical programme should be taken as a reference to establish the frequency of inclusion of ICT-related questions in a range of household surveys.

191.

Where an annual collection is not feasible, countries should attempt to align their collection years with those of countries they wish to be compared with.

This will commonly be countries in a region or countries with the same development level.

192.
192.

Most developed economies that conduct household ICT access/use surveys do so annually.

Among developing economies, the situation is complicated by different frequencies for measuring household access and individual ICT use.

A small number of countries with strong interest in ICT issues have conducted surveys more frequently than annually (e.g.

the Republic of Korea and China).


In Latin America, most countries include questions on household ICT access annually, for instance, in multipurpose and life conditions household surveys.

However, the frequency of inclusion of questions on individual ICT use varies.

Some countries have collected the information annually, while other countries have included ICT use questions every two or three years.
Table 8 has more information on surveys used by Latin American and Caribbean countries to measure household access to, and individual use of, ICT.

193.

Reference period is the time period referred to in the survey when asking about individual use of ICT.

The core ICT indicators standards and this revised version of the Manual recommend a three month reference period instead of the 12-month period previously recommended.
Country practices vary, but ideally, reference periods should be aligned among countries in order to obtain comparable data.

75 Although longer reference periods allow the capture of more events, both ‘memory’ and the ‘telescoping’ effects (described below) are likely to increase with a longer recall period.

194.

When a respondent is asked about a particular event during a reference period, two type of difficulties can arise.
The first is the ‘memory effect’ (or ‘recall effect’): respondents tend to forget events.

The second problem is less obvious: the event is not forgotten but recall of the date of occurrence may be inaccurate.

In particular, people may report events as occurring within the reference period when they actually occurred outside of it.

This is called the ‘telescoping effect’.


Empirical evidence from the field of psychology shows that there is a tendency to ‘telescope’ particularly when an event involves activities that reveal some kind of social or economical status.

195.

As the core indicators on household access are at a reference date (‘point-in-time’ data), it is preferable to have alignment of reference dates across participating countries.
Reference dates are typically the day of interview, with questions of the type “Does this household have a computer?”.

However, they may be another date, for example, the last day of a calendar year.

75 Country practices include reference periods of 12 months, three months, one month or one week.

Some surveys (for instance, those done by Eurostat) use more than one reference period (both one year and three months).

Some surveys do not use a reference period at all, referring instead to current use.
An example is the 2003 United States ICT use survey (Computer and Internet Supplement to the Current Population Survey) that asked “Does this person use a computer at home?” without reference to a particular time period.

Compare this with the question in the Eurostat model questionnaire for 2013 “When did you most recently use a computer?

(options include Within the last 3 months, Between 3 months and a year ago, More than 1 year ago and Never used one).
See http://www.census.gov/econ/ict/ and http://epp.eurostat.ec.europa.eu/portal/page/portal/information_society/methodology.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 4.

Statistical standards and measurement topics for ICT household statistics 77 Issues related to the reference period with respect to questionnaire design are also 196. dealt with in Chapter 6.

197.
197.

Countries that are dependent on existing survey vehicles may be unable to adopt all these timing recommendations, because of constraints imposed by the timing of the vehicles used.

198.

Other time-related issues include the importance of time series data in tracking changes over time and to improve survey processes and understanding.
It is expected that the extra cost of conducting surveys on a regular basis will be offset, to some degree, by the availability of experienced staff and existing systems and procedures.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 5.

Data sources and collection techniques for ICT household statistics 79 Chapter 5.

Data sources and collection techniques for ICT household statistics 199.
This chapter considers the sources of data and the data collection methods for ICT household statistics that can be employed by statistical agencies.

Sources and methods chosen will be influenced by: • • • • • the resources and time available for the project; available survey vehicles; requirements to maintain consistency over time; infrastructure and expertise available in the statistical agency; and practicalities such as geography and language.

200.
200.

This chapter examines the advantages and disadvantages of various options.

It also looks at the practices of countries that collect ICT household data.

Data sources for social and demographic data are surveys and 201.

The main data sources administrative data.

The types of surveys considered in this manual are household sample surveys and population censuses.76 In all known cases, the ICT household indicators considered in this manual are 202. collected by surveys (including censuses).
Administrative data sources are unlikely to generate indicators on household ICT access and individual ICT use, because administrative data are generally not classifiable according to the characteristics of interest.

However, such sources are successfully used by ITU to produce statistics on available infrastructure, prices and number of subscriptions.
It is important to note that subscription77 data are not equivalent to survey data on households and individuals, but they can be very useful, especially for monitoring uptake of ICT in countries with low levels of ICT access and use.

203.

This manual will focus on the range of surveys that can be used to collect ICT household data.

Types of surveys 204.

There are various types of surveys used to collect information about households and household members.
Two main types can be distinguished for the purposes of this manual: stand-alone surveys focused on ICT, and other household surveys that may contain some questions on ICT topics.

205.

Stand-alone household surveys dealing with ICT access and use allow for more details to be collected than is usually possible in an existing survey vehicle designed for 76 The word ‘survey’ is sometimes taken to mean ‘sample survey’ although, in fact, it includes completely enumerated surveys, that is, censuses.
Surveys include those conducted by personal interview or by other means, such as mail.

77 Subscriptions may be attributable to organizations (business, government or non-profit) or individuals.

There may be more than one subscription in a household and several individuals may use the same subscription.

Subscription data do not usually include information about the subscriber, except for the location where the service is provided.
Exceptions to this are surveys of Internet service providers where providers are asked to split subscriptions by type (e.g.

household and other).

Such surveys are conducted by few countries, among them Australia (ABS, the Internet activity survey, www.abs.gov.au/ausstats/abs@.nsf/mf/8153.0) and Norway (Statistics Norway, the Internet survey, http://www.ssb.no/inet_en/).

Manual for Measuring ICT Access and Use by Households and Individuals 80 Chapter 5.
Data sources and collection techniques for ICT household statistics investigating other topics.

An ICT household survey can have a customized sample design, while the information gathered through other surveys will depend on the design of those surveys.

The advantages and disadvantages of specific ICT surveys compared to the inclusion of ICT questions in existing survey vehicles are discussed below.

206.

Surveys not specific to ICT include: • • • Multipurpose household surveys.
Multipurpose household surveys collect data on more than one subject via a single household survey.

The usefulness and the feasibility of multipurpose household surveys have been largely proven by the Living Standard Measurement Survey (LSMS) project of the World Bank78 which has been applied in many countries since the 1980s.

Despite some necessary compromises, this type of survey can be cost effective and produce timely results if the survey vehicle is ongoing.
Once collected and computerized, data can be further edited and tabulated by separate subject matter teams.

Other than the LSMS, particular surveys that are sometimes used for collecting ICT household data in developing economies include Demographic and Health Surveys (DHS), the Multiple Indicator Cluster Survey (MICS) funded by UNICEF, and other multitopic surveys carried out by national statistical offices.
Box 13 describes use of multipurpose surveys to collect ICT data in the Palestinian Authority and Costa Rica.

Box 13.

Inclusion of ICT questions in the Palestinian Housing Conditions Survey 2010 and the Multipurpose Household Survey of Costa Rica The Palestinian Central Bureau of Statistics has carried out several specific household surveys on the use of ICT by businesses (2007, 2009, 2011).
In 2010, questions related to access to ICT at the household level were included in the questionnaire of the Housing Conditions Survey: access to TV, computer, telephone line, Internet, mobile.

In Costa Rica, the National Institute for Statistics and Censuses (INEC) included in the National Household Survey (ENAHO) the questions necessary for the compilation of ICT indicators as recommended by the OSILAC.
These include access to radio, color TV, cable TV, fixed and mobile telephone, computer, Internet, as well as electricity (66 per cent in 2010) to provide a reference indicator.

Source: Palestinian CBS, Survey Catalog (http://82.213.38.42/PCBS_NADA3.1/index.php/catalog/121); Costa Rica, (http://www.inec.go.cr/Web/Home/GeneradorPagina.aspx).

Household budget surveys.


Household expenditure (budget) surveys are designed to measure household expenditure and are also used by a number of countries to identify household access to ICT equipment and services.

79 Some countries include questions on household income in their household expenditure surveys.

As we have seen above, income is a useful classificatory variable for ICT access (and use) data.
Box 14 illustrates use of household expenditure surveys by the Lao People’s Democratic Republic to collect household ICT access data.

Population censuses.

Population censuses can be used to collect a small number of ICT access and/or use data items.

Although this is usually an expensive option and population censuses are infrequent (usually once in a decade), it remains a good alternative in countries that have never collected any ICT household data and are not planning to do so in the near future.
In addition, population censuses provide very good detail about the variables collected and can provide a basis for the design of samples for future ICT-specific surveys.

UNSD (2008a) presents standards for the 78 The LSMS has a broad objective of improving the quality of household statistics in developing economies.

A more specific goal is to develop methods to monitor progress in raising of living levels in developing economies, see http://go.worldbank.org/IFS9WG7EO0.
79 The main objective of household budget surveys is to measure household consumption (expenditure) for national accounts purposes and calculation of consumer price indices.

Chapter XXIV of UNSD (2005a) discusses design and measurement issues specific to household budget surveys.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 5.

Data sources and collection techniques for ICT household statistics 81 2010 round of population and housing censuses.
The standards include ICT access as a core topic.

In particular, the following indicators were suggested for inclusion in censuses: o Household having radio o Household having television set o Household having fixed-line telephone o Household having mobile cellular telephone(s) o Household having personal computer(s) o Household accessing the Internet from home o Household accessing the Internet from elsewhere other than home, and o Household without access to the Internet.

Box 14.
Box 14.

Lao People’s Democratic Republic: use of budget surveys to collect ICT access data The Lao PDR used an interviewer-administered general household module and diary for its 1997–98 Expenditure and Consumption Survey (conducted by the National Statistical Centre of Lao People’s Democratic Republic).

Census enumeration areas were used as primary sampling units (PSUs), which were stratified by 18 provinces and within provinces by urban/rural.

A sample of 25 PSUs was allocated to each province.
A further allocation by urban/rural was implemented.

In total, there was a sample of 450 PSUs and 9,000 households.

As well as information on consumption, data were collected on the possession of durables, including TVs, radios and videos (providing data for the two core indicators, HH1 and HH2).

The latest Lao Expenditure and Consumption Survey (LECS) was conducted in 2007–08 and included a question on ownership of mobile phones.
A total of 518 villages served as primary sampling units (PSUs) or clusters.

In each village 16 households were interviewed, half of which had been surveyed in the earlier LECS III.

A total of 48,021 individuals in 8,296 households were interviewed Source: Lao Statistics Bureau, http://www.nsc.gov.la/index.php?option=com_content&view=article&id=55&Itemid=80; UNSD (2005a), http://unstats.un.org/unsd/hhsurveys/pdf/Chapter_24.pdf.

Advantages and disadvantages of using stand-alone ICT surveys 207.
Given the cost of developing and running a household survey, it is likely that developing economies would prefer not to run stand-alone household surveys on ICT access and use (or at least only infrequently).

Most developing economies that have collected ICT statistics through household surveys have included the relevant questions in multipurpose surveys (see tables 14 and 15 for examples).
In a few countries, they have been included in a different survey such as a labour force or budget survey (see Table 6).

Following UNSD recommendations, 77 countries have included at least one of the suggested questions on ICT in their Population and Housing Censuses.

See Table 7 for details.

208.

Stand-alone household surveys on ICT have been implemented mostly in developed economies,80 but also some developing economies have conducted at least one and some do it annually, such as Brazil and Qatar.
80 Defined here as an economy not belonging to OECD or not covered by Eurostat ICT household collections (that is the European Union countries plus a small number of other countries such as Norway and Turkey).

Manual for Measuring ICT Access and Use by Households and Individuals 82 Chapter 5.

Data sources and collection techniques for ICT household statistics Table 6.
Types of surveys where ICT questions have been included between 2009 and 2011 Type of survey Labour Force Survey (LFS) Multipurpose Household Survey (MPHS)/Household survey Living Standard/Conditions Survey or Budget survey ICT stand-alone survey Other types of surveys Unknown survey type Population census TOTAL Number of surveys 2009–2011 7 35 15 50 4 2 10 123 Source: ITU database (2012) as per data reported by countries to ITU.

The table refers to surveys rather than countries.

Table 7.
Inclusion of ICT related question in the last Population and Housing Census (number of countries)81 HH1 HH2 HH3fixed HH3mobile HH4 HH5 HH6 HH7 HH8 HH9 HH10 HH11 HH12 Region Africa Arab states Asia & Pacific CIS countries Europe countries The Americas Other economies 14 4 9 2 6 8 14 5 12 2 3 10 9 Total general Source: ITU, based on UNSD: http://unstats.un.org/unsd/demographic/sources/census/censusquest.htm.
209.

There are advantages to using an existing survey vehicle, apart from cost.

The main one is that a number of other data items and classificatory variables are available and these can be cross-tabulated against ICT data to produce a richer dataset.

For example, including an ICT-related module in a labour force survey would allow a breakdown of use of ICT by individuals according to their employment status and occupation.
In a household budget survey, it would allow analysis of differences in ICT access by household income groups.

It is also important for producing ICT statistics where use by sex can be cross-tabulated with variables such as income, labour force status and/or occupation.

210.

However, there are disadvantages as well.

The use of existing survey vehicles may impose constraints on applying some of the recommendations presented in this manual.
For instance, an existing labour force survey will have an established methodology and 81 Indicator references (HH1 etc) refer to the 2009 list of indicators (ITU, 2009b).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 5.

Data sources and collection techniques for ICT household statistics 83 questions.

82 These may not be optimal for collecting ICT data, nor for producing disaggregated ICT indicators.

211.
211.

Another disadvantage of using an existing survey vehicle is that ICT topics will be competing for space and time, given a likely pressure to minimize interview time in order to reduce respondent burden and cost.

This is particularly important in the case of ICT topics in a population census.

Most countries will therefore need to determine a small set of important questions.
The core list of ICT indicators developed by the Partnership is a recommended starting point, in conjunction with other information requirements of a country’s policy- makers.

212.

Countries may decide to include ICT questions in different household surveys, in order to have a more complete picture of access and use for different population segments.

Box 15 describes surveys used by Nepal in recent years to measure household access to ICT; they include a labour force survey and a living standards survey.
Similarly, Table 8 describes the range of surveys used by Latin American and Caribbean countries that include some questions on household access to, and individual use of, ICT.

Box 15.

Nepal: surveys used to collect household ICT access data The Central Bureau of Statistics of Nepal conducts several multipurpose surveys that collect ICT household data.

They are: Labour Force Survey The Nepal Labour Force Survey is generally conducted every five years; the last survey was in respect of 2007–08.
In that survey, the household head was asked about the presence in the household of radio, TV, fixed telephone, mobile telephone and computer, and also how many of each type of item were present in the household (for instance, how many radios).

The sample size for the 2007–08 survey was 16,000 households and data collection was by face-to-face personal interview with relevant individuals.

Living Standards Survey The Nepal Living Standards Survey is also generally conducted every five years.
The last survey was conducted during 2010–11 and the household head was asked about the availability in the dwelling unit of a telephone, mobile telephone, pager, cable TV, e-mail and the Internet.

This survey is particularly interesting because it was designed as a rotating panel.

Since this was the third round of the survey (the first one was in 1995–6), it is possible to study the growth in ICT access over time.

It is important to emphasize that datasets are available for researchers.
This is an example of good practice for the developing world.

Population Census, 2011 Nepal included most of the ICT access questions recommended by UNSD (2008a) in its last population census.

These are: household access to radio, TV, fixed line telephone, mobile cellular telephone and computer.

The census also included a question on household access to the Internet.

An advantage of using a census to collect this information is the potential for detailed tabulation, for instance by geographic area.
Source: UNCTAD and ITU, unpublished reports and research.

82 An example might be where the age scope of the labour force survey is limited to those of working age, whereas the age scope of an ICT household survey is usually broader than this.

Manual for Measuring ICT Access and Use by Households and Individuals 84 Chapter 5.

Data sources and collection techniques for ICT household statistics Table 8.
Surveys used by countries of the Latin American and Caribbean region to measure household access to, and individual use of, ICT Country Argentina Survey Survey on ICT access and use (ENTIC) (only urban level) Households expenditure survey Type of Survey Stand-alone ICT survey Budget expenditure survey Year 2011 2012 Module on activities by children and teenagers Special survey 2012 Quality of life Survey for elderly people Special survey 2012 Bolivia Continuous Household Survey Households survey Supplementary survey on Internet access, included in the National Survey for dwelling sample (PNAD) Multipurpose household survey Multipurpose household survey Multipurpose household survey 2003–2004 2005–2009, 2011, 2012 2001–2009, 2011, 2012 Survey on Information and Communication Technologies in Brazil Stand-alone ICT survey 2005–2012 Brazil (Brazilian Institute of Geography and Statistics, IBGE) Brazil (Brazilian Center of Studies on Information and Communication Technologies – CETIC.br) Chile 2000, 2003 2006, 2009, 2011 2001, 2006 2007–2011 National socio-economic characterization survey (CASEN) Life conditions survey Colombia Continuous Household Survey (ECH) Multipurpose household survey Integrated Large Household Survey (GEIH) Multipurpose household survey Costa Rica Cuba Quality of Life Survey (ECV) Life conditions survey 2003–2012 Multiple Purpose Household Survey (ENAHO) Multipurpose household survey National Occupation and economic conditions households Survey (ENO- ESEH) Life conditions and labour force
 survey 2000–2003, 2005–2012 2006, 2008– 2010 National Occupation Survey (ENO) Labour force survey 2011, 2012 Dominican Republic Multiple Purpose Household National Survey (ENHOGAR) Multipurpose household survey 2005, 2007, 2011, 2012 Labour force national survey Labour Force survey 2009–2011 Manual for Measuring ICT Access and Use by Households and Individuals 2000–2013 2000,2006, 2011 2002–2004, 2010–2012 2002–2010 Chapter 5.
Data sources and collection techniques for ICT household statistics 85 Ecuador Income and Expenditure Survey (only urban level) Income and Expenditure Survey 2003 Life Conditions Survey Life conditions survey 2006 Employment and Unemployment Survey Labour Force survey 2008–2012 Time use survey Time use survey 2012 El Salvador Multiple Purpose Household Survey (EHPM) Multipurpose household survey Guatemala National Life Conditions Survey Life conditions survey Honduras Mexico Labour and income survey Labour Force Survey Permanent Multiple Purpose Household Survey Multipurpose household survey Module on Information and Communication Technologies in households (ENDUTIH) ICT module attached to the labour force survey 2001, 2002, 2004–2012 National income and expenditure survey Budget expenditure survey 2006, 2008, 2010, 2012 Nicaragua Labour Measurement Household Survey Labour Force Survey 2006 National Life Conditions Survey Life Conditions Survey Panamá Multiple Purpose Household Survey Multiple Purpose Household Survey 2001, 2005, 2009 2006–2013 Life conditions survey Life conditions survey 2003, 2008 Paraguay Permanent Household Survey Life conditions survey 2000, 2002– 2011 National Household Survey (ENAHO) Life conditions survey 2000–2012 Peru Uruguay Continuous Household Survey Large National Households Survey Multipurpose household survey Multipurpose household survey National income and expenditure survey Budget expenditure survey Survey on ICT Access and Use (EUTIC) Venezuela Household Sample Survey
 Stand-alone ICT survey Multipurpose household survey 2001–2005, 2007–2013 2006 2005–2006 2010 and 2013 2003, 2005– 2013 Source: ECLAC, Observatory for the Information Society in Latin America and the Caribbean (OSILAC) and ITU.
Data collection techniques 213.

Households, and/or individuals within them, can be presented with questions in face- to-face interviews, by telephone interviews, by a self-enumerated questionnaire (posted or delivered) or by e-mail/website interaction.

Information for some members of the household can be provided by proxy if another member of the household answers questions on their behalf.

Manual for Measuring ICT Access and Use by Households and Individuals 86 Chapter 5.
Data sources and collection techniques for ICT household statistics 214.

Most countries use personal interview techniques for collecting ICT household data.

Personal interviewing includes face-to-face interviewing (generally in the respondent’s home), telephone interviewing and a combination of the two (see Box 16 for examples).
A personal interview, whether face-to-face or telephone, requires careful training and evaluation of interviewers to avoid bias (for instance, affecting the likelihood of a response option by their tone of voice).

Box 16.

Use of a combination of techniques to collect ICT household data Macao, China In 2006, Macao, China, included ICT questions on a partial census of the population (20 per cent of dwellings were included).
Questionnaires were mailed to households and later collected by enumerators who also conducted face-to-face interviews.

Computer assisted telephone interviewing (CATI) was used mainly for making appointments, although telephone interviews were conducted upon request by respondents.

In 2011, the usage of ICT was studied in a sample of the Employment Survey (aged 3 and above), which is collected by face-to-face interview.
Information on the data collection operation is provided to selected respondents, by two means: an informative letter and a specific webpage describing the identification of interviewers.

New Zealand New Zealand conducted its 2006 and 2009 Household Use of ICT Surveys as a supplement to its quarterly labour force survey.

Personal telephone interviews using CATI were conducted for the majority of respondents, with face-to-face interviews using computer aided personal interviewing (CAPI) for the minority.
This follows the methodology used for New Zealand’s labour force surveys, where households remain in the survey for eight quarters.

Newly selected households are initially interviewed face-to-face and thereafter by telephone.

Denmark The 2012 ICT household survey was conducted with a combination of self-administered web survey and CATI.

Respondents received a letter with an Internet link.
They could choose to fill out the questionnaire on the Web or await a phone call from Statistics Denmark, in which case CATI was used.

Nearly half the respondents used the Web option.

Poland The 2012 ICT household survey used face-to-face interviewing supported by CAPI.

Interviewers completed the household questionnaire together with persons able to give credible answers.

Then all members of the household aged 16–74 were interviewed by means of individual questionnaires.
Where an individual was absent, the interviewer revisited the respondents in order to complete the missing questionnaires.

However, if more convenient, paper forms were left with the respondents to complete by themselves.

Interviewers then gathered these questionnaires on a prearranged day.

Source: ITU (2009b), Eurostat survey metadata.

215.

Each data collection method has advantages and disadvantages and these are summarized below.
For a general discussion on the use of different data collection methods in household surveys, especially in developing economies, see UNSD (2005a); in particular, on the effect of the data collection mode on measurement errors, see Section C, Chapter IX.

Personal face-to-face interviews 216.

Personal face-to-face interviewing is very common in household surveys in both developed and developing economies.

217.
217.

The main advantages of face-to-face interviews are facilitation of responses by the interviewer (and therefore a higher unit and item response rate) and that the technique does not rely on having an existing survey frame of households or individuals (Chapter 7 describes sampling techniques for household surveys that include cluster sampling based on geographic sampling).
In respect of ICT access and use data, face-to-face interviewing enables better 218. explanation of technical terms by the interviewer.

It may also allow the interviewer to check aspects of the respondent’s technical set-up, such as the type of Internet connection (for Manual for Measuring ICT Access and Use by Households and Individuals Chapter 5.
Data sources and collection techniques for ICT household statistics 87 example, dial-up using analogue modem versus a broadband modem or the existence of a fixed line telephone).

It is also the most obvious data collection mode when no telephone is available or when telephone listings are incomplete.

219.

Where a number of languages or dialects are spoken, a face-to-face technique may be very effective, although it relies on being able to assign the most appropriate interviewer for a given respondent.
83 Cultural aspects should be taken into account when selecting interviewers according to language(s) spoken, sex, age, educational background etc.

220.

The main disadvantage of face-to-face interviewing as a method of data collection is that it is costly, requiring more time spent by the interviewer travelling and locating respondents (though this is offset where respondents are geographically clustered).
A relatively recent problem for many countries is the difficulty of accessing some kinds of dwellings, for instance, apartment buildings with access secured by electronic or physical locks.

While face-to-face interviews allow careful explanation of relevant topics and questions, interviewers need to be trained not to indicate (e.g.

by their facial expression) judgements of responses.

221.
221.

Face-to-face interviewing can be facilitated by ICT in the form of direct entry of responses into computers (often portable computers, PDAs or tablets, carried in the field by the interviewer) and supporting software (Computer Assisted Personal Interview software – CAPI).

Such software also provides automatic question sequencing (via a series of ‘skips’) and immediate editing of responses.

See Box 17 for an example of use of PDAs in a household survey in Lebanon.

Box 17.
Box 17.

Lebanon: use of PDAs in a multipurpose household survey The Central Administration for Statistics (CAS) used personal digital assistants (PDAs) for the collection of data for the MICS3 (Multiple Indicators Cluster Survey 2009, Round 3).

The survey had three different questionnaires (household questionnaire, women questionnaire and under-five questionnaire).
The use of PDAs facilitated the field work and improved the quality of data since it integrated consistency checks (and other types of checks) within the data collection program, developed in-house at CAS.

The use of PDAs also shortened the duration of the survey process, as there was no need to design and print paper questionnaires, nor to have a separate data entry process.

Data coding was automatically provided for most fields.
An additional advantage is related to the use of PDAs for storing and archiving paper questionnaires, since data are stored on SD cards with automatic backup on the device itself during the collection and then automatically uploaded and sent encrypted to the server in the office.

Note that the technology required a full and detailed training for enumerators and other staff on the use of the devices.

Source: CAS, http://www.cas.gov.lb/Mics3/CAS_MICS3_survey_2009.pdf.

Personal telephone interviews 222.


Telephone interviewing is less common than face-to-face interviewing but is still reasonably common, especially for developed economies.

Like face-to-face interviews, telephone interviewing can be supported by ICT.

For instance, interviews can be conducted in a call centre environment and use supporting software (Computer Assisted Telephone Interview software – CATI).

As with CAPI, CATI software also provides automatic filtering and immediate editing of responses.
Telephone interviewing may be based on a list of telephone numbers or be implemented by randomly dialing a sequence of digits that comprise a valid telephone number (called random digit dialing, RDD).

223.
223.

The main advantage of telephone interviewing is that it is relatively inexpensive compared with face-to-face interviewing and there is greater flexibility in assigning the most appropriate interviewer (for instance, in a call centre environment, staff with skill in a 83 Chapter 6 discusses questionnaire issues where a number of languages are spoken in a country.

Manual for Measuring ICT Access and Use by Households and Individuals 88 Chapter 5.
Data sources and collection techniques for ICT household statistics particular language can be quickly chosen and assigned to deal with respondents who speak that language).

224.

While response to telephone interviews is facilitated by interaction with a human interviewer, the relationship between the interviewer and respondent is likely to be less effective than in a face-to-face situation.
In addition, the response rate may be lower as it is likely to be easier to reject a telephone caller than a person who is physically present at the respondent’s dwelling.

225.

For many developing economies, there are insufficient households with a telephone connection, or a telephone directory listing, to make this method feasible.

In particular, there would be problems creating a representative sample (and making contact with selected households) if telephone is the only option.
This will apply, for instance, where telephone penetration is low or it is not possible to include mobile or unlisted subscribers.

In many cases, there are no listings of cellular phone subscribers, which are increasingly used in developing economies.

Random digit dialing (RDD) may overcome the problem of lack of directory listings but may result in an unrepresentative sample.
Frequently, quotas that broadly represent the population are set and the quotas are gradually filled as RDD telephone interviews proceed.

226.

The telephone can be a useful complementary method of interview, subsequent to face-to-face interviewing, once contact has been made and a telephone number obtained.

227.

Table 9 shows metadata on the mode of data collection, survey vehicle and response rate for a number of countries conducting the Eurostat community survey.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 5.

Data sources and collection techniques for ICT household statistics 89 Table 9.
Mode of data collection, survey vehicle and response rate for countries conducting the Eurostat community survey, 2011 Country Data collection Survey vehicle Response rate (individuals) Response rate (households) Belgium Austria Sweden Croatia Mail CATI CATI CATI Netherlands CATI Norway Finland CATI CATI LFS LFS Stand-alone + LFS Stand-alone Stand-alone n.a.

Stand-alone Denmark Web+CATI Multipurpose survey Slovenia Face-to-face+CATI n.a.
Malta Latvia Face-to-face+CATI Stand-alone Face-to-face+CATI Stand-alone Czech Rep. Face-to-face+CAPI Stand-alone Spain France Greece Iceland Face-to-face+CAPI Stand-alone CATI CATI CATI Stand-alone Stand-alone Stand-alone Lithuania Face-to-face n.a.
Italy Face-to-face Multipurpose survey Portugal Face-to-face+CAPI Stand-alone Hungary Face-to-face Stand-alone Ireland CAPI Stand-alone Bulgaria Face-to-face Stand-alone Turkey CAPI Stand-alone Romania Face-to-face Stand-alone Poland Face-to-face Stand-alone Germany Mail Stand-alone Estonia Cyprus Face-to-face+CAPI LFS Face-to-face+CAPI Stand-alone n.a.

44% 46% 50% 57% 57% 66% 66% 73% 73% n.a.

n.a.

75% 77% 74% 77% 80% 80% 80% n.a.

71%% 90% 100% n.a.

93% n.a.


98% 99% Slovak Rep. Face-to-face Stand-alone 100% Source: Eurostat metadata.

43% 64% n.a.

50% n.a.

55% n.a.

n.a.

73% n.a.

74% 74% 77% n.a.

n.a.

78% 83% n.a.

80% 82% 87% 91% 92% 93% 74% 95% 61% 96% n.a.

Manual for Measuring ICT Access and Use by Households and Individuals 90 Chapter 5.

Data sources and collection techniques for ICT household statistics Self-enumeration 228.
Logically, household surveys can also be conducted by mail, although this is rarely done (no instances are known for developing economies).

While there are cost advantages in the use of postal surveys, there are obvious potential disadvantages as well.

Some countries use mail to make initial contact and then conduct a personal interview.

229.

Self-enumerated surveys are those where respondents complete a questionnaire themselves, usually paper-based.
The questionnaire may be mailed (a postal survey) or delivered to the respondent, together with appropriate instructions.

84 Following completion, the questionnaire may be collected by field staff or posted back to the collection agency by the respondent.

Postal surveys require a current and complete sampling frame of addresses for households or individuals.
They do not involve personal interaction with the respondent, therefore technical questions on ICT use may be less well understood and questionnaire logic is likely to be more complex.

230.

Where questionnaires are delivered directly to mail boxes, there may be no need for a sampling frame of addresses.

Where questionnaires are collected by field staff, they may be able to check responses and assist with any problems the respondent has in completing the questionnaire.

231.
231.

One advantage of self-enumerated questionnaires is that bias due to interaction with interviewers is likely to be reduced or eliminated, especially for sensitive questions.

However, unit and item response rates are likely to be lower than for personal interviewing, leading to higher sampling error and likely non-response bias.
In situations where there are several languages or dialects spoken in a country, or where literacy is low, self-enumeration is likely to be ineffective, unless combined with other methods.

In addition, some ICT questions can be complicated for non-experts, for example, questions on Internet services.

232.

The need for good questionnaire design is likely to be greater for self-enumerated questionnaires as interviewers are not available to interpret the questions or manage the flow of questions.
The principles of good questionnaire design are therefore particularly important for such surveys; this is explored further in Chapter 6.

233.

Despite the potential problems outlined above, there are obvious advantages of self- enumerated surveys.

These include lower costs and the ability to ask list-based questions.

At least two OECD countries, Germany 85 and Japan, have used mailed self-enumeration questionnaires to collect ICT household data.

Internet based surveys 234.


The final method is to use the Internet to assist data collection.

This would entail either an online questionnaire, which respondents fill out on a webpage, or a questionnaire that can be e-mailed back to the agency conducting the survey.

While this form of data collection for household surveys is rare, there are some examples.
Denmark uses both a web form and CATI for its ICT household survey (see Box 16) and the Australian population census in 2011 had both a paper and a web form available for use by households.

235.

While this method of data collection may seem attractive, it is only practical as a supplementary form of data collection for household ICT access and use data.

For a start, it can only be used by respondents with Internet access and a reasonable level of ICT proficiency.
This clearly excludes a large proportion of the population of interest for ICT access/use measurement (that is, non-users).

The costs of establishing software and 84 85 These may be incorporated in the questionnaire or provided as a separate document.

See https://www.destatis.de/EN/Publications/Specialized/InformationSociety/informationtechnology.pdf?__blob=publicationFile.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 5.
Data sources and collection techniques for ICT household statistics 91 appropriate questionnaires might also be high and not cost-effective for a method that can only ever supplement other methods of data collection.

Advantages include concurrent editing while the questionnaire is being completed (although methods such as CATI and CAPI also do this), reduced actual data collection costs and perhaps novelty and convenience value for respondents that might increase response rates.

236.
236.

In summary, while there are some cost advantages to such an approach, there are a number of reasons why this method will not be feasible as a primary means of data collection, especially for developing countries.

237.

Table 10 summarizes the main advantages and disadvantages of the different data collection methods.

Table 10.
Table 10.

Summary of data collection methods86 Method Main advantages Main disadvantages Face-to-face personal interview Telephone personal interview This is the most direct method of collecting information.

It facilitates direct interaction between the interviewer and the interviewee, allowing checking and follow-up questions.

An interviewer can also assist respondents to answer complex questions and can clarify concepts such as definitions of particular ICTs.
Because the interviewer is in view, he/she can use visual prompts such as prompt cards.

In addition, face-to-face interviews are especially useful for questions about opinions or impressions, and for surveys that take a long time to complete.

Where a number of languages or dialects are spoken, it may be very effective if the interviewers are selected with the adequate linguistic skills.

The technique usually produces lower non- response rates.
Data collection can be managed efficiently with specific software (Computer Assisted Personal Interviewing – CAPI).

Although to a lesser extent than face-to-face personal interview, telephone interviewing allows direct interaction between the interviewer and interviewee.

It is a fast and relatively inexpensive way to collect information, since a small number of interviewers from a single call centre can carry out a great number of interviews.
The data collection can be managed efficiently with specific software (Computer Assisted Telephoning Interviewing – CATI).

The telephone can be a useful complementary method of interview, subsequent to face-to- face interviewing, once contact has been made and a telephone number obtained High personnel costs may be incurred (for hiring and training interviewers).
However, this could be a minor issue in developing economies where salaries of interviewers are low, or agreements are reached with certain institutions to provide part-time interviewers (such as university students).

Interviewers are part of the measurement tool and they can induce important biases if they have not received suitable training.

In developing economies with poor quality transport infrastructure, reaching households located in some remote areas may prove difficult.
Correct and comprehensive telephone numbers may not be available, particularly in developing economies where mobile telephony may be more common than fixed telephone.

Interviews must be relatively short, since a long telephone conversation can be perceived as an annoyance.

Some people also feel that it is intrusive to be interviewed by telephone.

Telephone interviews may not be suitable for collecting quantitative information, for which the interviewee may have to check records.
The non-response rate is usually larger than for face-to-face interviews (but lower than for mail-based surveys).

86 Adapted from various sources including UNCTAD (2009), ITU (2009b).

Manual for Measuring ICT Access and Use by Households and Individuals 92 Chapter 5.

Data sources and collection techniques for ICT household statistics Self-enumeration The method is likely to be relatively inexpensive and allows the respondent to complete the questionnaire at his/her convenience.
It eliminates the problem of interviewer bias, though note that interviewer follow-up (e.g.

for non-response or inconsistent answers) can potentially introduce bias if not managed properly.

Where questionnaires are delivered directly to mail boxes, there may be no need for a sampling frame of addresses.
Where questionnaires are collected by field staff, they may be able to check responses and assist with any problems the respondent has completing the questionnaire Interview assisted by computer (CAPI/CATI) (can be applied to face-to- face or telephone interviews respectively) CAPI and CATI systems can eliminate errors of flow and data consistency, and can thus improve input data quality and reduce the time for data capture and validation.
Modern IT equipment such as PDAs or tablets may present a cheap and comfortable tool for data collection.

Internet-based surveys Data editing is done concurrently with data entry, reducing the time for processing.

Novelty and convenience for some respondents may increase response rates in particular population segments difficult to reach at home (e.g.

young employed persons).

Postal surveys require a current and complete sampling frame of addresses for households or individuals.
If questionnaires are not properly designed and tested, they can introduce bias to survey results that may be difficult to detect.

In particular, because they do not involve interaction with the respondent, technical questions on ICT use may be less well understood and questionnaire logic is likely to be more complex.

Requires separate data entry unless advanced imaging technology tools (such as Optical Character Recognition, OCR) are available.
Unit and item response rates are likely to be lower than for personal interviewing, leading to higher sampling error and likely non- response bias.

In situations where there are several languages or dialects spoken in a country, or where literacy is low, self-enumeration is likely to be ineffective.

Delays in mailing back questionnaires can introduce delays in survey processing.

In developing economies with a low quality postal system, such delays may be prohibitive.
CAPI and CATI techniques require interviewers with some technical skills.

CAPI and CATI systems are usually based on commercial software that may be costly.

Skilled staff are required to adapt the software to the questionnaire.

CAPI requires that interviewers carry IT equipment, which can be damaged or stolen during field operations.

In developing economies with poor road networks, there is a risk of damaging equipment.
Internet-based surveys can only be used by respondents with Internet access and a reasonable level of ICT proficiency.

This clearly excludes a large proportion of the population of interest for ICT access and use measurement (that is, non-users).

For this reason, they are only practical as a supplementary form of data collection for household ICT access and use data.
The costs of establishing software and appropriate questionnaires might also be high and not cost-effective for a method that can only ever supplement other methods of data collection.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 6.

Question and questionnaire design for ICT household surveys 93 Chapter 6.

Question and questionnaire design for ICT household surveys 238.
This chapter considers general issues of question and questionnaire design and specific issues relating to the model questions associated with the core list of ICT indicators.

These were presented in Table 5 in Chapter 4.

239.

Poor question and questionnaire design can be a significant source of survey error.

It is therefore very important that design is undertaken carefully and that sufficient time is allowed for thorough testing.

240.
240.

There will never be a questionnaire design that works optimally for every household or individual in a survey, so it will be necessary to undertake careful research and testing to ensure an effective compromise.

Once data requirements are determined, appropriate questions can be drafted, although it usually takes quite a lot of effort to finalize the wording, establish a logical order for the questions and construct a sequence guide to fit all situations.

241.
241.

As most countries collect ICT household statistics by personal interview, the assumption made in this chapter is that questionnaires will be administered by interviewers.

However, much of to self-enumerated the material presented applies equally questionnaires.87 General principles of questionnaire design for household surveys 242.

Most household surveys are conducted by personal interview (either face-to-face or by telephone).
This enables terms to be explained and logic applied by trained interviewers.

The method of asking questions will vary with the collection methodology used, for instance, telephone interviewers will ask questions differently from face-to-face interviewers.

243.

In general, questionnaires should be designed to: • • • • Maintain respondents’ cooperation by being as short as possible; this will also generally improve the quality of responses by avoiding respondent fatigue.
A measure of the time needed for completing the questionnaire should be recorded to evaluate the response burden.

Maintain respondents’ interest and motivation to complete the form, for example, by clearly explaining the aims and methodology of the survey, starting with simple and interesting questions, and, as far as possible, avoiding complicated questions.
Appear logical by having related questions grouped (possibly into modules) and with a logical flow; if there is more than one respondent in the household, group their questions so as to use their time most efficiently.

In the paper version of a questionnaire, the layout of questions for the different household members should allow for a variable number of members.

Where a question has a number of response categories (or items), these need to be handled carefully to avoid recall problems.
For instance, if items are all read out to the respondent at once, he/she may have a clearer recollection of the last two or three items than the first few, or an impression that the order of the responses reflects their importance.

With the exception of the ‘frequency of Internet use 87 That is, a questionnaire completed by a respondent, usually as a paper form but it could also be electronic.

See previous chapter for details.


Manual for Measuring ICT Access and Use by Households and Individuals 94 Chapter 6.

Question and questionnaire design for ICT household surveys indicator’ (HH12), the response categories in the model questions are all ‘multiple responses’, that is, all instances should be reported.

This should minimize an order effect.

The model question associated with HH9 (Internet activities) has a large number of response items.
To avoid recall problems, an appropriate way to ask this question might be by showing a list (in the case of a face-to-face interview or paper questionnaire) or asking a series of ‘yes/no’ questions about each activity (in a telephone interview).

Ensure that question wording is clear, uses plain language, is unbiased and is unambiguous.
It is particularly important to avoid bias in question wording and not to ask ‘leading questions’ (that is, a question where a particular answer is implied, thus resulting in a biased response).
Avoid double-barreled questions (that is, questions that require a single answer but have actually several parts, for instance: “How often and how much time do you spend when you use the Internet?” and double-negative questions (that is, questions that include two negative terms, for instance “Do you think that using your mobile telephone while driving should not be forbidden?”).

Build trust with the respondent by avoiding sensitive questions, as far as possible, and assuring confidentiality of responses.
Questions that are sensitive could be asked at the end of the interview so that they do not affect responses to other questions.88 • • • Interviewer-administered questionnaires include prompts and skips 89 to guide the 244. interviewer through the questionnaire.

These will specify the population for each question and ensure, as far as possible, consistent conduct of the interview.
Figure 4 shows the populations that are asked each of the model ICT questions, for instance, only those who have used the Internet in the last three months are asked questions about the location, activity and frequency of Internet use.

It should be noted that an interviewer or respondent may have an incentive to answer negatively when an affirmative answer implies numerous follow-up questions.
For instance, the interviewer may be tempted to encourage a ‘no’ answer in the question on Internet use in order to avoid having to ask questions on location, activities and frequency.

245.

Past experience can often be used to refine question wording and the logic aspects of form design.

246.
246.

Where more than one language is used in a country, UNSD (2005a) strongly recommends that questionnaires be translated into all major languages spoken in order to ensure preservation of meaning and uniformity of presentation by interviewers.

They present evidence that the alternative, being an ‘on-the-spot’ translation by the interviewer, increases errors by a factor of between two and four.
Interviewers who do not speak the local language should not be used, as they may not be understood by respondents or may need to use local interpreters – another potential source of bias.

Decisions on how many languages should be represented will be a function of things like the number of people speaking only a minority language and the likelihood that their omission would bias survey results.

90 247.
90 247.

Ensuring clear wording in the original version of a questionnaire does not guarantee that it will be as clear in translated versions, especially as it is common for local languages to be spoken but not written.
An advisable practice when translating questionnaires is to translate from the original language and then back again, after which the two versions in the 88 The United States 2003 Computer and Internet Use Supplement (to the Current Population Survey) asked two questions about concerns relating to the Internet.

They were asked after the other ICT questions and were only asked of respondents on an outgoing rotation of the CPS.
89 These are instructions to interviewers that guide them through a questionnaire.

For instance, if a respondent answers ‘no’ to a question on whether they used the Internet, the enumerator would ‘skip’ to the next logical question and not ask about use of the Internet.

90 See UNSD (2005a, Chapter III).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 6.

Question and questionnaire design for ICT household surveys 95 original language are compared.
The back-translation should be done by someone who was not closely involved in the development of the questionnaire in order to avoid contaminating the translation with prior knowledge.

248.

Questions and whole questionnaires should be thoroughly tested before use in a survey.

They should always be tested with actual respondents to ascertain whether the questions can be understood and answered accurately and whether respondents have a common understanding of the meaning of the questions.
Testing can be qualitative or quantitative.

Qualitative tests include focus group tests 91 and cognitive research.

92 Quantitative testing includes pilot tests and dress rehearsals.93 249.

Box 18 provides more information on qualitative testing and an example of its use from Brazil.

Box 18.
Box 18.

Cognitive interviewing as a tool to evaluate questions: a practical case from Brazil Cognitive interviewing seeks to evaluate survey questions by use of techniques that gauge respondents’ understanding of, and response to, questions.
The techniques include: • ‘think-aloud’ interviews: the respondent speaks their thoughts while answering questions, or recalls their thoughts directly afterwards; • paraphrasing: the respondent is asked to rephrase the question in his or her own words; • probing: the interviewer asks follow-up questions after each question or group of questions to probe respondents’ interpretation of the question/s; and • definitions: the respondent is asked to explain key terms.
An important application of cognitive interviewing is evaluating the translation and adaptation of cross- national questionnaires.

In 2012, CETIC.br conducted the Kids Online Brazil Survey for the first time in order to measure risks and opportunities related to Internet use among children aged 9 to 16.

The questionnaires used in the survey were based on those developed for the EU Kids Online project and followed the framework designed by the London School of Economics.
The European questionnaires were translated into Portuguese from the master questionnaires in English and then adapted to the Brazilian context.

Cognitive interviews were carried out with the objectives of: • learning how Brazilian respondents understood the critical concepts of the survey; • testing the translation of the questionnaire; • identifying possible sensitivity of specific issues; and • checking that the questions were age appropriate.
The interviews were carried out in two different phases, allowing different aspects to be evaluated in each phase.

The respondents recruited were of different socio-demographic profiles and varied in age, sex and socio-economic status.

As a result of the cognitive interviewing process, a number of changes were made to the Brazilian version of the original questionnaires, including changes in wording of questions or response items.

Source: CETIC.br; Survey Methodology, Robert Groves et al.

(2009).
(2009).

91 92 Focus groups involve informal discussions of relevant survey issues or topics with small groups of people who are in scope of the survey.

This involves research on how potential respondents interpret questions in a questionnaire.

More information can be found in UNSD (2005a, Chapter IX).

93 A dress rehearsal is a large scale pilot test.

Manual for Measuring ICT Access and Use by Households and Individuals 96 Chapter 6.

Question and questionnaire design for ICT household surveys Figure 4.
Structure and logic of a model questionnaire/module for collecting ICT household data Section 1: Household characteristics94 Household number of members Population: all in-scope households; includes household members outside any individual age scope applied Household composition (whether there are children under 15) Population: all in-scope households; Optional questions on topics such as household access to electricity, household income, location (e.g.
urban/rural)95 includes household members outside any individual age scope applied Population: all in-scope households Section 2: Household access to information and communication technology Household with a radio (HH1) Household with a television (HH2) Population: all in-scope households Population: all in-scope households Household with multichannel television (HH13) Population: all in-scope households with a Household with a fixed telephone line (HH3) Population: all in-scope households Household with a mobile telephone (HH3) Population: all in-scope households Household with a computer (HH4) Household with Internet (HH6) Types of Internet access services used by households at home (HH11) Barriers to household Internet access (HH14) Section 3: Individual characteristics94 Population: all in-scope households Population: all in-scope households Population: all in-scope households with Internet access at home Population: all in-scope households without Internet access at home Age Sex Highest educational level attained Labour force status Occupation Population: all selected in-scope individuals Optional questions, for example, income, disability status, languages spoken/read Section 4: Individual use of information and communication technology Individual use of a mobile cellular telephone (HH10) Population: all selected in-scope individuals Individual use of a computer (any location, last three months) (HH5) Individuals with ICT skills: computer-related activities carried out in the last three months at any location (HH15) Individual use of the Internet (any location, last three months) (HH7) Location of individual use of the Internet in the last three months (HH8) Population: all selected in-scope individuals Population: all selected in-scope individuals who used a computer from any location in the last three months Population: all selected in-scope individuals Population: all selected in-scope individuals who used the Internet from any location in the last three months 94 Some or all of the household and individual characteristics information would be collected as part of a larger survey and therefore would not need to be included in a module on ICT access and use.
95 Location will often be known already, in which case it will not need to be asked of respondents.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 6.
Question and questionnaire design for ICT household surveys 97 Frequency of individual use of the Internet in the last three months at any location (HH12) Internet activities undertaken by individuals in the last three months at any location (HH9) Population: all selected in-scope individuals who used the Internet from any location in the last three months Population: all selected in-scope individuals who used the Internet from any location in the last three months 250.
Testing of a set of draft questions at an early stage can greatly assist planning as well as questionnaire design.

Such testing may be undertaken by statistical agency staff, including field supervisors.

This would serve as a familiarization opportunity for those who will have roles in training household interviewers once the methodology has been determined.
As well as firming up the final set of questions to be asked, testing will also help determine the best collection method, if not already known, and the time necessary to conduct interviews.

On this point, it should be noted that interviews conducted within the testing phase tend to take longer than real interviews as responses may be probed and discussed more than in a ‘live interview’.

Additionally, interviewers are not as familiar with the questionnaire as they will be for the actual survey.

251.
251.

Testing can be done in two stages96 – pretesting parts of the questionnaire on a small number of respondents (this may occur a number of times) and a comprehensive field test (or pilot test) involving more respondents who are selected to be reasonably representative of the population.

One reason for testing in stages is that the most mistakes are usually detected in the first few days.

Once those are identified and corrected, the second stage can take place within a larger geographic area.
Following UNSD, 97 it is recommended that questionnaire modules be tested on at least 50 respondents to that module (therefore, for individual ICT use, the questions should be pilot tested on 50 individuals who have used the Internet).

A large survey may also involve a final ‘dress rehearsal’ prior to launch.
This will test all aspects of the survey, including procedures and will also provide valuable information on costs, the adequacy of training and documentation, and the need for fine-tuning of timetables.

252.
Non-question elements of a questionnaire will differ for different form types (paper based personal interview, CAPI or CATI, self-enumerated questionnaire) and may include:98 • • • • an identifier for each variant of a questionnaire 99 and a unique identifier for each copy of the form (with a check digit100 if the identifier is to be entered by keying); boxes of appropriate size to record responses (for instance, the number of household members can be expected to require space for two digits, while household income might require space for 7 or more digits, depending on the currency); ‘office use only’ spaces might be used by interviewers, or data entry and processing staff to record information; if Optical Character Recognition (OCR), Intelligent Character Recognition (ICR) or Optical Mark Reading (OMR) software are used to convert responses on a paper questionnaire to a computer record, there may be need for additional information on the form (such as page identifiers) or a particular style of layout; and 96 97 98 99 100 UNSD (2005a, Chapter III).


Adapted from UNSD (2005b, Chapter 9).

Variants might include questionnaires in different languages.

A check digit is a number or letter in a keyed sequence, the value of which is derived from a function involving the other digits in the sequence.

If a data entry error is made, the derived check digit will differ from the actual check digit, thus signaling that a keying error has been made.
Check digits are typically used for record identifiers and codes rather than quantitative data.

Manual for Measuring ICT Access and Use by Households and Individuals 98 • Chapter 6.

Question and questionnaire design for ICT household surveys for self-enumerated forms, information about the survey (e.g.
its purpose, name and reference period, due date, how the questionnaire should be returned, how to obtain assistance with completing the form, contact details of the respondent and legal obligations) and general instructions to respondents (e.g.

how to mark boxes, how to correct errors).

ICT model questions 253.

Model questions for the ICT household indicators are shown in Table 5 in Chapter 4 and a model questionnaire is presented in Annex 2.
It is important to note that the model questions and questionnaire need to be adapted by each country to suit: • • • the survey vehicle and method of data collection (for instance, a questionnaire that is designed for a telephone survey will differ from a questionnaire that is used for face- to-face interviewing); cultural and linguistic conventions of the country; and ICT services available in the country, in particular in the case of Internet services (HH11) and multichannel TV services (HH13).

254.
254.

For comparability purposes, it is important that the meaning of the model questions is preserved and that the specified populations of households or individuals are asked each question.

255.

A number of the model questions have response categories (location of Internet use, Internet activities, frequency of Internet use, type of Internet access, multichannel TV services, barriers to household Internet access, ICT skills and household ICT expenditure).
Countries have some options about how they deal with these.

For instance, countries can add or split categories, with some examples shown below.

For international reporting, split categories need to be re-aggregated.

This process is explained in Chapter 8.

256.

Another variation is that countries can add an ‘other’ category to some of the category lists.

The model questions for the response category indicators, as presented in the model questionnaire in Annex 2, include ‘other’ categories.
It is important to note that one of the aims of questionnaire testing is to eliminate or at least reduce the use of the ‘other’ category.

Ideally, countries would ask respondents to specify details when they select an ‘other’ category.

This enables countries to recode ‘other’ category responses to an existing category.

Where there are significant responses in an ‘other’ category, countries should note the details for future questionnaire design.
Options might be to better describe existing categories or add additional categories.

257.

For HH8 (location of Internet use), some countries may wish to specify a particular location of importance for policy purposes, for example, Internet access provided through government supported public access centres (as a subcategory of ‘Community Internet access facility’).

The addition of such locations as a separate category would assist policy- makers to evaluate government support for such centres.

258.
258.

For HH9 (individual Internet activities), countries might like to split the broader categories to obtain more detailed information.

Countries could also ask the question in other ways, for example, rate each activity according to its frequency of use, or rank the activities by frequency.

259.

For HH11 (household Internet access by type of service), categories should be chosen such that responses can be aggregated and compared at the global level.
The suggested question in the model questionnaire (Annex 2) serves mostly as an example of the Manual for Measuring ICT Access and Use by Households and Individuals Chapter 6.

Question and questionnaire design for ICT household surveys 99 categories that could be used for comparison purposes, rather than the actual question that would be asked in a country survey.

Examples on how some countries have asked this question are presented in Box 19.

260.
260.

For HH12 (frequency of Internet use), countries can split a category; for example, ‘less than once a week’ could be split into ‘at least once a month but not every week’ and ‘less than once a month’.

261.

For HH15, more detailed ICT skills data could be collected where there is interest in knowing about additional or more specific skills.

262.

For HH16, more detailed expenditure data could be collected where national classifications support more detail.

Reference period 263.


Reference period (also know as recall period) refers to the period in respect of which respondents are asked to report.

For ICT use statistics, the length of the reference period has been much debated.

The general argument is that a question asked in respect of a long period is less likely to yield an accurate response because of problems the respondent has remembering the required information (see Chapter 4 for a discussion of recall issues).
On the other hand, a long reference period is more likely to capture a ‘rare event’.

264.

A variety of reference periods is used by countries (and also a mix).101 For the model questions associated with the core indicators, a 3-month reference period was agreed on during the latest revision of the household indicators by the EGH.102 Before this revision, the recommended reference period was 12 months.
The longer period is adopted by some countries, but most have already decided to use the period of three months, since they consider that the use of computer and Internet is now sufficiently frequent to capture the majority of users by employing such period.

ICT concepts that may be difficult to understand 265.

There are a number of concepts used in the core list of ICT indicators that may be difficult for respondents to understand and respond to consistently.
They include: • • • • • • definition of computer, Internet access services, multichannel television services, Internet activities related to government organizations, mobile cellular telephones, and computer-related activities (to measure ICT skills).

It is important when designing questions for ICT household surveys that these 266. concepts are explained clearly and placed in a country and cultural context.
101 The Eurostat 2013 model questionnaire (Eurostat, 2013b) effectively asks some questions in respect of both 12 months and three months (individual use of a computer and the Internet, purchases over the Internet), asks some questions in respect of the last 12 months (use of e- government services, types of Internet purchases) but ask others (e.g.

location and frequency of use and activities undertaken) in respect of the last three months.

102 1st EGH Meeting, São Paulo, Brazil (June 4–6 2013).
More information on the results of the meeting are available at: http://www.itu.int/en/ITU-D/Statistics/Pages/events/brazil2013/default.aspx.

Manual for Measuring ICT Access and Use by Households and Individuals 100 Chapter 6.

Question and questionnaire design for ICT household surveys Definition of computer 267.

Definition of a computer is used for indicators HH4 and HH5 and refers to “a desktop computer, a laptop computer or a tablet or similar handheld computer.
It does not include equipment with some embedded computing abilities, such as smart TV sets, and devices with telephony as a main function, such as mobile or smartphones.” 268.

With rapid changes and convergence of devices, it is difficult to cover potential new devices that will appear in the near future.

Already it is difficult to clearly differentiate between a smartphone and a tablet.
However, during the latest revision of the household indicators, only tablets are considered to be computers, as they usually have more computing and processing capacity and also because mobile phones are covered in separate indicators.

Internet access services 269.

Household core indicator HH11 deals with the types of Internet access services used by households with Internet access.
There are six response categories for the indicator, though in practice, countries may use a different number on national questionnaires, with wording adapted to the local situation.

Whichever approach is chosen, the categories are likely to be quite technical and the types of services may change as technology evolves.

Anecdotal evidence indicates that many respondents – and interviewers – will not understand the meaning of the Internet access service categories used.
It is therefore desirable that questions on this topic use categories that are relevant to services existing within the country at the time of the survey and are therefore likely to be understood in a local context.

Explanation of categories could use the product names or company brands of widely available broadband services, or alternatively, describe the technological aspects in an easy- to-understand way (see Box 19 for examples on how Mexico and the Czech Republic have asked the question).
There may also be a policy interest in particular Internet access services.

In this area, in particular, it is important that interviewers are familiar with technologies and their brand names.

Multichannel television services 270.

The new household core indicator HH13 deals with multichannel TV services, some of which may require some explanation (by interviewers or on questionnaires) as follows: • • • • IPTV should not be confused with watching TV over the Internet.
IPTV uses broadband networks to carry TV signals, while maintaining a guaranteed quality of service.

It is generally aimed at viewing over a television set, making the quality of experience comparable with that of other TV platforms.

IPTV should also not be confused with over-the-top (OTT) or online TV and video (e.g.

YouTube, Netflix), which are delivered via the Internet.

DTH satellite can be paid or not paid.

DTT is by default not paid (for countries that have made the digital transition).
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 6.

Question and questionnaire design for ICT household surveys 101 Box 19.

How to ask the question on Internet access by type of access Mexico The National Institute of Statistics and Geography of Mexico (INEGI) includes a module on access to, and use of, ICT in households in the national Labour Force Survey.
In 2010, for example, the question on the type of access is asked as follows: The main way of connection to Internet… (check the one that applies) 1.

Is through the telephone line, and while you are connected to the Internet it is not possible to talk over the phone?

(dial-up) 2.

Is through the telephone line, and you can talk over the phone when connected to the Internet?

(dedicated telephone line) 3.


Is through Cable TV (the connection is made via a cable TV network and you can watch TV while connected to the Internet) 4.

Is through wireless mode?

(connection by satellite, mobile broadband or 3G.

It excludes any wireless technology that allows for movement by using additional peripheral devices) Czech Republic Is your household connected to the Internet at home by: 1.

2.

3.

4.

5.

6.

ADSL technology A cable TV line (e.g.


Cable Internet from UPC) Optical fibre Fixed wireless access (e.g.

Wi-Fi) Dial-up over normal telephone line or ISDN (e.g.

Digital line ISDN2 from O2) Broadband 3G mobile phone network and computer (e.g.

Mobile Connection for your Notebook or Tablet) Broadband 3G mobile phone network and mobile phone (e.g.

Internet on your Mobile) 7.


Source: INEGI, http://www.inegi.org.mx/prod_serv/contenidos/espanol/bvinegi/productos/encuestas/especiales/endutih/201 0/endutih2010.pdf, Czech Statistical Office.

Internet activities related to government organizations 271.

The measurement of e-government has been dealt with by the Partnership on Measuring ICT for Development, which has established a statistical framework, including a core list of indicators on e-government (Partnership and UNECA, 2012).
The indicators considered are classified into four areas: use of ICT by employees of government, availability of ICT to government organizations, use of ICT by government organizations and supply of e-government services to citizens.

272.

Household core indicator HH9 deals with the Internet activities undertaken by individuals.

The response categories include ‘getting information from general government organizations’ and ‘interacting with general government organizations’.
It is important to differentiate between these categories.

Whereas the former refers to obtaining information (often from websites), the latter is more interactive and covers activities such as completing forms online and making online payments.

273.

In both cases, the definition of what constitutes a general government organization may prove difficult for respondents to understand, especially in a consistent way.
Statistically, it is recommended that the SNA93 (2008 revision) concept of government be used, as follows: According to the SNA “… the principal functions of government are to assume responsibility for the provision of goods and services to the community or to individual households and to finance their provision out of taxation or other incomes; to redistribute income and wealth by Manual for Measuring ICT Access and Use by Households and Individuals 102 Chapter 6.
Question and questionnaire design for ICT household surveys means of transfers; and to engage in non-market production.” (UNSD, 2008b) 274.

General government organizations include central, state and local government units, as well as all non-market non-profit institutions that are controlled by government units, and social security funds.
It should be noted that general government organizations do not include public corporations (legal entities, predominantly owned and controlled by the government that are created for the purpose of producing goods and services for the market and may be a source of profit or other financial gain to their owner/s) (UNSD, 2008b).

275.

Clearly, the concept of government is complex and needs to be interpreted within a country context.
It could be useful to provide examples of websites of government organizations that are thought to be widely used (for instance, websites of government-run media organizations, transport services or national statistical office websites).

276.

The response categories for HH9 (getting information from, and interacting with, general government organizations) may be accompanied by a list of e-government services.
A more comprehensive list of Internet-based services is provided by the Partnership and UNECA (2012) in relation to indicator EG7: Selected Internet-based services available to citizens, by level of sophistication of service.

This list may be used during the interview as a list of examples, although it is not comprehensive.

Box 20 reproduces the question asked by the Census and Statistics Department of Hong Kong, China in 2008.
The question assists the respondent by providing examples of each class of e-government services.

Box 20.

Hong Kong, China: question on use of e-Government services, 2008 In the past 12 months, had you used any of the e-Government services for your personal matters?

(e.g.

search for Government information, submit application, book appointment for identity card application, book leisure facilities, registration, pay tax or pay other governmental charges, etc.)
If “yes”: Show card In the past 12 months, which e-Government services had you used for personal matters?

(Allow multiple answers) • Browse and enquire information disseminated by the Government (e.g.

enquiring about weather condition, traffic condition, statistical data, air pollution index, Government news etc.)

• Online financial management (e.g.


paying various Government bills, such as rates, Government rent, water charges, tax, purchasing tax reserve certificates, paying fixed penalty tickets for traffic offences or littering etc.)

• Online appointment booking or licenses/certificates application (e.g.
appointment booking for road test and vehicle examination, renewing driving and vehicle licenses, appointment booking for registration of identity card/ giving of marriage notice, applying for copy of birth/ death/ marriage certificates) • Online registration services (e.g.

voter registration and volunteer scheme registration) • Online change of personal particulars (e.g.

changing address) • Online job search and recruitment (e.g.
searching for job vacancies, registering job vacancies and searching for suitable candidates) • Online purchase of Government publications and Government statistical publications • Online booking of Government venues or facilities (e.g.

sports venues, training courses or leisure facilities) • Online submission of information to Government (e.g.

filing of tax return) • Online library services (e.g.
book reservation, book renewal) • Download Government forms • General browsing of government websites • Others (Please specify): _______________ • Have used, but forget the types of service Source: Questionnaire for the Thematic Household Survey on Information Technology Usage and Penetration in 2008 (Census and Statistics Department, Hong Kong, China, 2008).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 6.
Question and questionnaire design for ICT household surveys 103 Mobile cellular telephones 277.

More information on the conceptual challenges of e-government measurement can be found in the publication Framework for a set of e-government core indicators (Partnership and UNECA 2012).

278.

There are both household and individual mobile telephone indicators in the core list (HH3 and HH10 respectively) and corresponding model questions (see Table 5).

The meaning in each context is different.


In the household context, the interest is in whether the household has access to a mobile telephone that is an ‘asset’ of the household, as it has been traditionally understood for fixed telephones.

In the individual context, the interest is in the use of a mobile cellular telephone by an individual, irrespective of who owns or pays for it.

279.

The concept for individual mobile telephone use is different from a mobile telephone subscription.
The model question corresponding to HH10 specifies that “Use of a mobile telephone does not necessarily mean that the telephone is owned or paid for by the individual but should be reasonably available through work, a friend or family member, etc.

It excludes occasional use, for instance, borrowing a mobile telephone to make a call.” Subscribers, on the other hand, subscribe to a mobile telephone service by a postpaid subscription or a prepaid account.
They are therefore likely to be owners of a mobile telephone in a legal sense.

They may also be organizations, such as businesses, rather than individuals.

Computer-related activities (to measure ICT skills) 280.

The new household core indicator HH15 deals with computer activities that reflect an individual’s level of ICT skills.

The items are ordered broadly by degree of difficulty (from simplest to most complex).
It is considered probable that if an individual does not understand the meaning of a particular task (e.g.

copying or moving a file or folder, creating electronic presentations with presentation software) then they are unlikely to have undertaken that task.

Questionnaire logic 281.

The structure and logic for a set of core ICT questions were presented in Figure 4.
It is assumed that the ICT access and use questions are included as a module in a larger household survey (which will usually be the case for developing economies).

The structure, question wording and definitions suggested in this manual would not necessarily be used unchanged (or literally translated).

However, it is important to retain the suggested meanings and logic.

282.
282.

The structure should be used in conjunction with the model questions and associated definitions of terms and categories (Table 5).

283.

Note that the term population refers to the units that are in scope for each indicator.

For example, a question collecting ‘Types of Internet access services used at home’ (used for deriving HH11) is asked only of the (population of) households that have Internet access.

284.

The data collection method used will influence the way questions are asked.
A questionnaire delivered by personal interview will include instructions to the interviewer in the form of prompts and skips.89 Prompts should reflect the definitions of terms (e.g.

computer, the Internet) shown in Table 5.

285.

Box 21 illustrates interviewer instructions through excerpts from the ICT household questionnaires of Canada and Hong Kong, China.

Manual for Measuring ICT Access and Use by Households and Individuals 104 Chapter 6.
Question and questionnaire design for ICT household surveys 286.

A model questionnaire covering the core list of ICT household indicators is presented at Annex 2.

Box 21.
Box 21.

Interviewer instructions for ICT household surveys of Canada and Hong Kong, China Canadian Internet Use Survey, 2005 (personal interview face-to-face or telephone) Section: Ever Users (EV) EV_BEG Begin Module Coverage: All respondents EV_Q01 Have you ever used the Internet (E-mail or World Wide Web) from home, work, school, or any other location for personal non-business use?
1 Yes 2 No..........................................(Go to EV_END) DK, RF........................................(Go to EV_END)103 Coverage: All respondents EV_Q02 How many years have you used the Internet?

INTERVIEWER: Read categories to respondent.
1 Less than 1 year 2 1 to 2 years (1 year or more but less than 2 years) 3 2 to 5 years (2 years or more but less than 5 years) 4 5 or more years DK, RF Coverage: Respondents who have ever used the Internet EV_END End Module Hong Kong, China, Thematic Household Survey on Information Technology Usage and Penetration in 2008 (personal interview face-to-face) D14 Show card Including all places, for what purposes did you usually use (desktop computer or laptop / notebook / tablet PC or desktop game console (e.g.
Playstation II/III or Sony (PS2/PS3), Xbox/Xbox360 of Microsoft, Game Cube/Wii of Nintendo etc.))

via wired Internet connection?

Any other purposes?

Any others?

(Allow multiple answers) F4 Show card In the past 12 months, which e-Government services had you used for personal matters?

(Allow multiple answers) Source: Statistics Canada, 2005; Census and Statistics Department, Hong Kong, China, 2008.

103 DK=don’t know; RF=refusal.


Manual for Measuring ICT Access and Use by Households and Individuals Chapter 7.

Sampling for ICT household surveys 105 Chapter 7.

Sampling for ICT household surveys 287.

This chapter focuses on the design of ICT household surveys, including survey scope and target populations, statistical units, and sample design and selection.

288.

Many aspects of survey design are not specific to ICT household surveys.
Indeed, as we saw in Chapter 5, many countries use existing household surveys to collect ICT access and use data.

These may be multipurpose surveys, labour force surveys, household budget surveys or population censuses.

Therefore, this chapter considers design of household surveys generally, with additional emphasis on the application to ICT measurement.

Scope and coverage for households and individuals 289.
The scope of a survey refers to the statistical units (members of the target population) required to be represented by the survey and for which data are to be collected and tabulated.

For household surveys, the scope may be all households, a subset of household types or geographic locations, or a set of certain individuals within households.

290.
290.

In respect of ICT household statistics, the Partnership has proposed several statistical standards associated with the core list of ICT indicators, including recommendations on survey scope for households and individuals.

291.

For individuals, the suggested age scope is 5 years old and above.

Some countries, such as Korea or the United States have used a minimum scope of 3 years old.

There is no maximum age scope recommended.

292.


Most countries will have individual scope limitations not related to age, for instance, the scope exclusion of individuals in institutions such as prisons and nursing homes, members of the armed forces, diplomats, short-term foreign visitors and those with no fixed address, such as nomads.
In countries with a large proportion of temporary workers living in collective accommodation, it may be useful to include this subpopulation with a specific sampling scheme.

Ideally, the scope of surveys that collect household ICT access/use data should 293. include both urban and rural areas.

294.

Coverage is the degree to which the in-scope units are actually on the sample frame (and therefore represented in the sample).
Once the required scope is determined, alternative sample frames can be investigated to identify sources that provide the best (most up-to-date and/or complete) coverage of households and individuals that are within the scope of the survey.

295.

There may be geographic coverage issues for some countries, for example, certain rural or remote populations may be in scope but poorly covered.

296.

Other omissions will reflect coverage issues such as errors in the sample frame (discussed below).
It is important that the omission of a significant proportion of the population, whether by a specific scope limitation or because of undercoverage, be mentioned in output metadata.

One example of failure to do so is that comparisons are made between the whole population of one country and the urban population of another.

Manual for Measuring ICT Access and Use by Households and Individuals 106 Chapter 7.

Sampling for ICT household surveys Target populations and sample frames 297.
The target population is the population about which survey estimates will be produced, that is, the scope of the survey.

The sample frame (alternatively known as or ‘survey frame’ or ‘population frame’) is the list from which the units in the sample are selected.

Household survey samples are generally selected in two stages: first by area, then by household within area.

298.
298.

The frame most commonly used in the first sampling stage is a list of enumeration areas, frequently based on the most recent population census.

In certain countries, alternative first-stage sample frames can be developed on the basis of the territorial division of the country into polling stations, or from property valuation files.

Where a population census is used, enumeration areas are likely to consist of only a few hundred households.
Areas sampled from the list of enumeration areas are often referred to as ‘primary sampling units’ (PSUs) and are selected either with equal probability or (much more often) with probability proportional to size (pps), using as a measure of size the number of households, the number of dwellings, or the population in the area, as reported by the census.104 Using a proportional criterion for choosing the PSUs implies that a large PSU is more likely to be selected than a small one.105 299.
The second-stage sample frame is the complete list of all households in each selected PSU.

Within each PSU, a fixed number of households is generally selected from that list, with equal probability.

300.

This two-stage strategy results in a sample composed of ‘clusters’ of households that are relatively closely located geographically.

301.

The first sampling stage may occasionally need to be adapted to local conditions.
One common alternative is the use of a ‘master sample frame’ – a common set of PSUs used by many different household surveys over several years.

302.

Other forms of sample frames for ICT household surveys include registers of individuals (often known as central population registers).

Such frames are used in some European countries, where registers are maintained for administrative purposes.
Some developing economies have registers of households or dwellings that may be based on population census records or maintained for administrative purposes, such as for land taxes, or some other listing, such as electricity connections.

303.

A frame may be quite suitable for one set of data requirements but hold unacceptable biases for other data.106 This is clearly an issue to be considered when ICT questions are included in a multipurpose household survey.

304.
304.

Generally speaking, the desirable characteristics of sample frames are: • • completeness with respect to coverage of the in-scope population; timeliness: it should be as up to date as possible and have the potential to be updated in the future to permit further iterations of the household survey; 104 105 Advice on the selection of Primary Sampling Units (PSUs) with pps can be found in Chapter XV of UNSD (2005a).
PSUs that are exceptionally large may need to be divided into portions, one of which is selected per PSU in order to economize on household listings.

This process, known as segmentation, only needs to be conducted in the large PSUs that happen to be selected in the sample.

Segmentation is not a very desirable operation, because it is often conducted by unsupervised fieldworkers as a part of the household listing operation.
This is almost impossible to supervise, thus entailing the serious risk of selection bias.

106 An example is a frame consisting of households who live in homes that they own.

While this may be a good frame for measuring characteristics of home ownership, it is likely to be a poor frame for measuring household ICT access because home owners could be more likely to have access to, and use, ICT.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 7.
Sampling for ICT household surveys 107 • • • accuracy of information on the records; availability of descriptive data that will assist in sample design and possibly classification of data, for example, location of units; and availability of household access numbers.107 information: usually address or telephone 305.

Major frame problems for household surveys include undercoverage, clusters of elements, blanks and duplicate listings.
Undercoverage is a particular concern for household surveys in developing economies and may occur at the levels of geographic area, household and/or individual.

A typical problem is the identification of households within an area.

Clusters of elements refers to the situation where a single unit on the frame consists of multiple units in the target population, for example, a dwelling with several households.
Blanks refer to units that do not contain a member of the target population, for example, an empty dwelling.

Duplicate listings occur when a member of the target population appears more than once on the frame, for example, a nomad person moving from place to place may have a higher probability of selection.108 306.

Field-testing of questionnaires and procedures may present an opportunity to test problems with the sample frame and to make adjustments if feasible.

307.
307.

UNSD 109 recommends that NSOs with significant household survey programmes invest resources in creating and maintaining a master frame of PSUs, based on the geographic areas defined and used in the preceding census.

Ideally, the frame would be created as soon as possible after the completion of a population census, thereby reducing the amount of labour involved.

308.
308.

It is often the case that only the NSO in a country has access, for confidentiality reasons, to an adequate household or individual survey frame.

Other organizations that carry out ICT surveys (such as ministries for ICT, telecommunication regulatory authorities or private institutions) may not have a reliable frame.

It is therefore important for them to collaborate with NSOs to avoid using poor frames that could produce biased estimates.

Statistical units 309.


For ICT household measurement, there are typically two statistical units: households and individuals.

The household unit is used to elicit information about the facilities in place in the household (e.g.

whether there is a computer or Internet connection).

Box 22 presents an example of modifications to the statistical unit at the household level.
The individual unit is used to provide information on use of ICT (both at, and away from, home) and, most importantly, the nature of that use (for instance, frequency and range of activities undertaken).

The core indicators require that both the household and the individual are statistical units.

It is necessary to select both households and individuals, and to design questionnaires and other survey materials for both types of units.
107 Though in some circumstances, survey questions may be posed, or subsequent household visits arranged, at a central location where householders or heads of households attend, for example, for voting.

108 109 See UNSD (2005a, Chapter II) for more detail.

See UNSD (2005a, Chapter V; 2005b, Chapter 4).

Manual for Measuring ICT Access and Use by Households and Individuals 108 Chapter 7.

Sampling for ICT household surveys Box 22.


Honduras: change in statistical units in household surveys The National Statistical Institute of Honduras modified the statistical unit for several questions on access to ICT in the Living Conditions Surveys of 2005, 2006 and 2007.
In particular, questions about access to radio, TV set, fixed telephone and computer were recorded at dwelling level until 2006 but at household level in 2007, while access to a mobile telephone was asked at dwelling level until 2005 and at the individual level from 2006.

Source: Presentation by INIDE Honduras at the 4th workshop on the Measurement of Information Society in Latin America and the Caribbean (San Salvador, February 2008).

310.
310.

In respect of definition of ‘household’, UNSD (2005a) states that “Most surveys consider households to be the collection of persons who usually reside in a housing unit.

Two components are thus important: the definition of a usual resident and the definition of a housing unit.”110 Of these, the definition of housing unit may be more problematic and it may not always be clear what constitutes a ‘housing unit’.
UNSD considers that a housing unit definition takes into account whether the persons living there live and eat separately from others in the same structure.

311.

The following definition is based on the ‘housekeeping concept’ described in the UNSD’s Principles and Recommendations for Population and Housing Censuses Revision 2 (UNSD, 2008a): “The concept of household is based on the arrangements made by persons, individually or in groups, for providing themselves with food and other essentials for living.
A household may be either (a) a one- person household, that is to say, a person who makes provision for his or her own food and other essentials for living without combining with any other person to form a multi-person household or (b) a multi- person household, that is to say, a group of two or more persons living together who make common provision for food and other essentials for living.
The persons in the group may pool their resources and may have a common budget; they may be related or unrelated persons or constitute a combination of persons both related and unrelated.”111 312.

This concept does not assume that the number of households and housing units are – or should be – equal.

Further elaboration by UNSD makes it clear that the institutional population are not members of households, although they are in scope of population censuses.
The institutional population consists of “… persons living in military installations, correctional and penal institutions, dormitories of schools and universities, religious institutions, hospitals and so forth.” However, households do include “…persons living in hotels or boarding houses …” who “… should be distinguished as members of one- or multi- person households, on the basis of the arrangements that they make for providing themselves with the essentials for living.” 313.
For the purposes of the Manual, it is recommended that the definition of household be based on the UNSD housekeeping concept and be defined as follows.

A household consists of one or more people, who: • • • may or may not be related to each other, share accommodation, and make common provision for food.

110 111 UNSD (2005a, Chapter VIII).

UNSD (2008a) also discusses the ‘household-dwelling’ concept of a household, whereby a household is associated with a single housing unit.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 7.

Sampling for ICT household surveys 109 314.

With respect to the institutional population, it is suggested that it will generally be impractical to include them in scope of individuals.

315.

Examples of household definitions are presented in Box 23.

Box 23.
Box 23.

Definition of household used in Australia and Hong Kong, China The Australian Bureau of Statistics (ABS), in its 2006–07 multipurpose survey, that included ICT topics, defined a household as “…a person living alone, or two or more related or unrelated persons who live and eat together in private residential accommodation.” Hong Kong, China defined a domestic household as “a group of persons who live together and make common provision for essentials for living.

These persons need not be related.


If a person makes provision for essentials for living without sharing with other persons, he is also regarded as a household.” Source: ABS (2007); Census and Statistics Department, Hong Kong, China (2008).

Sample design and selection 316.

The main sample design and selection issue for ICT household statistics is the need to produce a representative sample of households and individuals (in order to measure household access to ICT and individual use of ICT).
Otherwise, the issues applying more generally to household surveys also apply to those measuring ICT access and use.

317.

Some general points related to sampling techniques, and calculation of sample sizes and sampling errors are presented below.

112 • • • • For household surveys using face-to-face interviews, where fine geographic tabulation is not required, the clustering of sampled units, that is, concentrating the sample is very cost effective (with smaller transportation and listing costs).
Potential losses of precision can usually be compensated by increases in sample size.

few geographic areas, into a Stratification refers to a grouping of population units into mutually exclusive groups of units referred to as ‘strata’, within each of which an independent sample is chosen.
Stratification is usually done with one of two objectives: either to potentially improve the overall precision of the estimates by gaining control over the composition of the sample; or to produce estimates for subgroups of the population that could otherwise be poorly represented in the sample.

These two objectives are not complementary and it is the second that is generally pursued in household surveys to ensure adequate statistics for the relevant geographical units.
An example of stratification for Greece is shown in Box 24.

Actual sample size, rather than the sampling fraction within strata, is the major determinant of the size of sampling error.

Therefore, minimum sample sizes need to be maintained, even in strata where the population is low.

Conversely, where total sample size is necessarily low because of costs, fine stratification should be avoided.
Sample sizes will need to be higher where a higher degree of reliability or confidence is required.113 In general, a greater level of detail in output requires a higher sample size for a constant degree of reliability (reflected by the magnitude of sampling error).

This is relevant to ICT household statistics where data are disaggregated by some or all the classificatory variables described in Chapter 4.
A particular case is sampling for topics where samples may be designed to provide good estimates, requiring some 112 113 Readers should refer to specific chapters of UNSD manuals (UNSD, 2005a, b) for more detailed information.

Confidence in an estimate is often expressed as the 95% confidence interval around the estimate, that is the value of the estimate +/– two standard errors (this assumes a normal distribution of the variable being measured).
It may also be expressed as the ratio of the estimate’s standard error to the estimate (referred to as the coefficient of variation or the relative standard error).

Manual for Measuring ICT Access and Use by Households and Individuals 110 Chapter 7.

Sampling for ICT household surveys loss of efficiency (that is, the sample size is larger than needed for achieving the desired accuracy for estimates at the national level).114 • in interviewed Individual selection.
The number of household residents ICT household surveys varies across countries, with some countries interviewing all members and others interviewing one selected person.

Where all household members are selected for interview, in order to avoid selection bias, it is important to make contact with all members, rather than only those who are available at the time of interview.

If only one member of the household is selected for interview, that member should be selected at random and in an unbiased manner.
In the event that the selected person is not present when the interviewer visits or phones the dwelling, he/she should be contacted later by a follow up visit (or perhaps by a telephone call).
Methods of random selection of a household member include: Kish grids,115 selecting the person with the next or last (most recent) birthday, and selecting individuals according to random selection of pre-assigned identification codes.116 Answers given on behalf of the absent individual (proxy answers) are undesirable in all kinds of surveys (but particularly in many of the questions related to ICT indicators measurement).117 Box 24.
Greece: stratification of the sample of the ICT household survey In Greece, the 2012 household survey on ICT was carried out as a stand-alone survey using a subsample of the Survey on Living Conditions (EU-SILC), which is harmonized in all European Union Member States.

The sample design was three-stage stratified sampling, with primary sampling units defined as areas (one or more geographic areas) and the final unit the household.

Collective households were excluded from the in- scope population.
For the individual questionnaire, one member of the household was selected at random.

There were two levels of stratification: (i) The first level was geographical stratification based on the partition of the country area into thirteen standard regions corresponding to the European NUTS II level.

The two major city agglomerations of Greater Athens and Greater Thessalonica constituted separate major geographical strata.
(ii) The second level of stratification involved grouping of municipalities and communes within each NUTS II region by degree of urbanization (that is, according to their population size) into four categories.

These categories were defined by the population size intervals 1–999, 1000–4999, 5000–29999 and 30000 and over.

The number of final strata in the thirteen regions was 50.
The two major city agglomerations, which account for 40 per cent of the population, were further partitioned into 31 and 9 substrata (administrative subsections), respectively, on the basis of the city blocks of the municipalities that constitute them.

Thus, the total number of strata for this survey was 90.

Source: National Statistical Service of Greece, http://www.statistics.gr/portal/page/portal/ESYE/BUCKET/A1901/Other/A1901_SFA20_MT_AN_00_2012_0 0_2012_06_F_EN.pdf.

318.
318.

As introduced above, most countries have samples selected in a series of stages as follows: • Area sampling.

The first stage is a stratified sample of areas, known as ‘enumeration areas’ (or ‘primary sampling units’ (PSUs)) as a first step.

The areas have known characteristics (commonly derived from the previous population census).

The benefits of stratification are particularly evident at this stage, therefore a significant 114 115 UNSD (2005a, Chapter II).
Kish, Leslie (September 1949), "A Procedure for Objective Respondent Selection within the Household", Journal of the American Statistical Association 44 (p247).

The procedure involves creation of a list individuals based on age and sex.

Choices can be made based on rotation of combinations of age and sex.

116 Ainsworth, Martha and Juan Muñoz (1986) “The Côte d'Ivoire Living Standards Survey: Design and Implementation”, LSMS Working Paper No.

26, The World Bank (pp15-16).


The procedure involves assigning a code (1-20 in the original study) to household members and then making a random selection of the assigned codes.

117 Collection of information about children’s use of ICT can be complicated by national laws preventing interviewing of minors.
The alternative of asking another household member to provide information in respect of children’s activities can introduce bias (especially for older children whose activities may not be known to the respondent).

However, a number of countries collect information about children in this way.

Those that do should take measures to minimize response bias.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 7.
Sampling for ICT household surveys 111 effort should be made to properly stratify geographic areas.118 For most household surveys in developing and transition economies, PSUs are selected with probability proportional to population size (that is, a large area is more likely to be selected than a small one).

This first stage of PSUs results in geographic ‘clusters’.
As the name implies, these are sets of units (usually dwellings or households) that are closely located geographically (‘clustered’) in order to minimize the cost of collection.

Clustering, while reducing costs, is also likely to increase sampling error because of higher homogeneity of units within clusters (the ‘clustering effect’).119 There may be a second sampling stage at the subcluster level (for example, ‘segments’ or ‘blocks’).

Household sampling.
Household sampling.

Households (or dwellings) within clusters (or subclusters) are typically listed in some fashion in order to create a sample frame.

It is common to have a fixed size sample of households within each cluster, and to select it by systematic, equal probability sampling.120 If there is more than one household in a dwelling, there is a need to sample households within the dwelling.
Typically, information about the household will be provided by an individual within that household (randomly chosen or a responsible person as defined by the statistical agency; some countries select the household head to provide the information).

Sampling of individual/s within the household.

As discussed above, some countries sample all individuals in a household and others sample a single individual (at random).

The Manual recommends that all members be sampled where this is feasible.

• • • • • 319.
• • • • • 319.

Error associated with a sample is known as sampling error (or sample error).

This is an element of data quality and is examined in Chapter 9.

320.

Because the sample of households and individuals selected is unlikely to be representative of the population, it is important to weight responses according to independent estimated distributions of the population.

This is further discussed in the next chapter.

118 119 120 UNSD (2005a, Chapter IV).


See UNSD (2005b, Chapter 3) for more details.

UNSD (2005b, Chapter 3).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 8.

Data processing for ICT household statistics 113 Chapter 8.

Data processing for ICT household statistics 321.

This chapter discusses data processing for ICT household statistics, from the data entry phase of a survey cycle to calculation of output data.
Emphasis is placed on the importance of integrating computer-based quality controls to field operations for achieving the high data quality standards discussed in the following chapter.

Tabulation of results, while an aspect of data processing, is discussed in Chapter 10, Dissemination.

322.

Experience from the past three decades shows that data management can and should play a critical role beginning with the very earliest stages of the survey effort.
Starting in the mid 1980s, the integration of computer-based quality controls to field operations has been identified as one of the keys to improving the quality and timeliness of household surveys.

Under this strategy, data entry and consistency controls are applied on a household-by- household basis as a part of field operations, so that errors and inconsistencies are solved during the interview or by means of re-visits to the households.121 323.
The most important and direct benefit of integration of these quality controls is that it significantly improves the quality of the information, because it permits correction of errors and inconsistencies while the interviewers are still in the field rather than by office ‘cleansing’ later.

Besides being lengthy and time-consuming, office cleansing processes tend to produce databases that are internally consistent but do not necessarily reflect the realities observed in the field.
The uncertainty stems from the myriad of decisions – generally undocumented – that need to be made far from where the data are collected, and possibly long after the data collection.

324.

The integration of computer-based quality controls can also generate databases that are ready for tabulation and analysis in a timely fashion.

Furthermore, databases may even be prepared as the survey is conducted, thus giving survey managers the ability to effectively monitor field operations.
Integration also fosters the application of uniform criteria by all the interviewers and throughout the whole period of data collection.

325.

Planning for the integration of computer-based quality controls should run in parallel with other survey planning and be well advanced prior to finalization of questionnaire design.

Sequencing of questions and the inclusion of questions that facilitate edit checks need to be planned in conjunction with data processing preparations.

326.
326.

Many data processing tasks are not specific to ICT measurement.

This chapter therefore pays particular attention to ICT-specific data processing issues, including editing and calculation of ICT indicators.

327.

Even though the integration of computer-based quality controls should improve data quality, non-sampling errors may still occur in data processing.

This will be discussed in the next chapter.

Data entry 328.

As stated above, data should ideally be entered during fieldwork.
When using CAPI or CATI programs this will result by default.

When more traditional pen and paper interviews are in place, this can be done by organizing fieldworkers into teams that include a data entry operator, two to four interviewers and a supervisor.

Where the data entry operator cannot 121 Ideally while the interviewing team is still working in the area.

Manual for Measuring ICT Access and Use by Households and Individuals 114 Chapter 8.
Data processing for ICT household statistics join the team during its visits to each survey location (generally a primary sampling unit), the latter are visited at least twice, to give the operator time to enter and verify the consistency of the data in between visits so that interviewers can re-ask questions where errors, omissions or inconsistencies are detected by the data entry program.
If notebook computers are available, the data entry operator can join the rest of the team in its visits to the survey locations or the interviewers can be asked to enter the data themselves.

The whole team stays in the location until all the data are entered and certified as complete and correct by the data entry program.

329.

Data entry may also occur as a separate process in a specialized data entry unit of the statistical agency (though, as discussed above, this is not the preferred approach).
As with other aspects of survey implementation, it is important to have good training and procedures for data entry.

These will help to minimize data entry errors as will techniques such as use of check digits122 and other checks of keying accuracy.

Data editing 330.

Data editing refers to the operations that are carried out to produce a final file ready for analysis.

It includes checking the validity of individual records (i.e.

at the individual and household levels) as well as that of aggregates.
These forms of editing are commonly referred to as ‘microediting’ and ‘macroediting respectively.

Microedits 331.

Microediting may also be called input editing and is applied to individual records.

There are five different types of microedits: range edits, checks against reference data, skip checks, consistency checks and typographical checks.
They can be described as follows: 123 • • • • • Range edits check that data values are valid, for instance, categorical variables can only have a predefined value (e.g.

sex can be coded only as 1 or 2).

Checks against reference data are an example of a range check and involve a comparison of the reported value with external data (such as a reasonable household size range).
Skip checks verify that the logic of the questionnaire has been followed, for instance, that the correct populations are asked each question; in a CAPI or CATI environment, the program will usually determine the skips, so errors should not occur if the programming has been done correctly.124 Consistency checks determine whether the information in the questionnaire is internally consistent, for instance, reported age matches reported date of birth (see Box 25 for an example of a consistency check related to ICT data).
Typographical checks (to find keying errors by the interviewer or data entry operator); these may be difficult to find and may be discovered as a result of other edits or through check-add (or ‘control’) totals or check digits.

122 A number or letter in a keyed sequence, the value of which is derived from a function involving the other digits in the sequence.

If a data entry error is made, the derived check digit will differ from the actual check digit, thus signaling that a keying error has been made.
Check digits are typically used for recording identifiers and codes rather than quantitative data.

123 Adapted from UNSD (2005a, Chapter XV).

124 However, this apparent advantage of CAPI/CATI systems can also make some errors undetectable: if the interviewer enters 2 instead of 22 as a person’s age, the program will obediently – and wrongly – omit the questions on ICT use, which should be asked of adults but not of very young children.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 8.

Data processing for ICT household statistics 115 Box 25.

Example of a consistency check An individual respondent belongs to a household that responded “No” to the question “Does any member of this household have Internet access at home regardless of whether it is used?”.
If that individual responds “Yes” to the option “Home” as a response category to the question “Where did you use the Internet in the last 12 months?”, the response is not internally consistent and should be queried by the interviewer.

In addition to the five microedits types mentioned above, it can be useful to distinguish 332.

‘fatal’ from ‘non-fatal’ edit failures.


There is typically more tolerance of the latter, which are designed to identify values or conditions that are not impossible but are uncommon and worthy of investigation.

Fatal errors indicate a situation that is logically impossible and will include things like data components not adding to a total or inconsistent information on age and date of birth.

Where there are a large number of fatal errors, investigations into the reasons should be undertaken.
They may indicate a problem with the editing program or systematic errors made by an individual interviewer.

Fatal errors need to be resolved before compromised data records are incorporated into any final tabulation of results.

Resolution could be to amend the values causing the failures or to omit the records in error, where they cannot be fixed.

125 It is important to note that both actions have implications for the final calculation of estimates.

333.
333.

Where data are collected by personal interview, data editing is often performed during the interview.

As mentioned before, this can be facilitated by use of CAPI or CATI programs, which should automatically advise the interviewer of edit failures.

However, on-the-spot editing during interview can also happen even when these computer assisted programs are not used.

For instance, the interviewer may have prompts indicating a range of realistic responses.
In the case of ICT statistics, an example of such a prompt is that where a household has access to the Internet at home, an individual who uses the Internet but does not select home as one of the locations of use should be probed by the interviewer.

This is a ‘non-fatal’ error – a ‘no’ response to home use may be correct.

334.

In cases where data are not edited at time of interview, good questionnaire design can be very helpful in minimizing respondent errors.
Some checks may be used during data entry to uncover keying errors.

335.

Table 11 suggests a number of microlevel edits for ICT data.

They would ideally be applied during an interview – as prompts to the interviewer using a paper form, as part of data entry programs operated in integration with fieldwork.

or as part of CATI/CAPI programs.

During an interview, microedits may result in probes (or prompts), for example, to confirm a ‘no’ response or to clarify an ‘other’ response.
Examples of probes are also included in Table 11.

Macroedits 336.
Macroediting might also be called output editing and consists of checks of aggregated data for coherence, including: • • consistency of estimates over time, for instance, use of the Internet by individuals is expected to grow over time; relationship with data external to the survey, for instance a survey estimate of the proportion of households with a fixed telephone line should be related to ITU’s infrastructure indicator, fixed telephone lines per 100 inhabitants; and 125 Such records would be ‘flagged’ with an edit status indicating the existence of fatal errors.
It is a simple matter to omit records with such a flag.

Manual for Measuring ICT Access and Use by Households and Individuals 116 Chapter 8.

Data processing for ICT household statistics • logical rules are obeyed, for instance, components of a percentage distribution should add to 100.

In cases where multiple responses are allowed (for instance HH9 – Internet activities) percentages are expected to add to more than 100.
If major errors are found during macroediting, they might be simply fixed by, for 337. instance, correcting estimation programs if that is where the errors originated.

However, if their source lies with original unit record data, it can be difficult to fix the problem once a survey is completed.

It is therefore suggested that, where possible, interim tabulations and macroedits are performed during the course of the survey so that errors that cause failures may be addressed.
An understanding of the macroedits to be applied might also be useful at the inception of the survey, for instance, in designing questionnaires or input edits so that failures are less likely to occur at the output stage.

338.

Table 11 presents a range of possible macroedits applying to the core ICT indicators.

Macroedits would be undertaken on tabulated data as explained above.
Countries collecting ICT household statistics for the first time might use results from the surveys of similar countries to apply macroediting.

Table 11.

Micro and macroedits for ICT household statistics Possible macroedits (edits applied to aggregated data) Historical trends, would expect a flat trend or slow growth when the definition is updated to include radios included in other devices.

Historical trends, would expect a flat trend or slow growth.
Indicator HH1 Proportion of households with a radio HH2 Proportion of households with a television Possible microedits and probes (edits applied to individual records, preferably at time of interview) If the interview takes place at the household’s residence, the interviewer could check for the presence of a radio (or a radio integrated in another device).
The interviewer will need to ascertain whether at least one radio in working condition is generally available for use by all members of the household at any time, that is, that the radio is considered a household asset (if not, the correct response is that the household does not have a radio).

If the interview takes place at the household’s residence, the interviewer could check for the presence of a TV aerial or a TV set (or a TV integrated in another device).
The interviewer will need to ascertain whether at least one TV in working condition is generally available for use by all members of the household at any time, that is, that the TV is considered a household asset (if not, the correct response is that the household does not have a TV).
Manual for Measuring ICT Access and Use by Households and Individuals HH3 Proportion of households with fixed telephone line HH3 Proportion of households with mobile cellular telephone HH4 Proportion of households with a computer HH5 Proportion of individuals using a computer HH6 Proportion of households with Internet HH7 Proportion of individuals using the Internet Chapter 8.
Data processing for ICT household statistics 117 If the interview takes place at the household’s residence, the interviewer could check for the presence of a fixed telephone line if the respondent is not sure.
As a mobile phone is a personal device, the interviewer will need to ascertain whether at least one mobile telephone in working condition is generally available for use by all members of the household at any time, that is, that the mobile phone is considered a household asset (if not, the correct response is that the household does not have a mobile telephone).
If the interview takes place at the household’s residence, the interviewer could check for the presence of a computer (noting the devices that are now defined as a computer).

The interviewer will need to ascertain whether at least one computer in working condition is generally available for use by all members of the household at any time (if not, the correct response is that the household does not have a computer).
Where a household has access to a computer (HH4), it is quite likely that the interviewed individual/s (especially if young and educated) use a computer.

Therefore probe a ‘no’ response.

If the interview takes place at the household’s residence, the interviewer could check for the presence of an Internet connection (e.g.

modem connection, mobile network).


The interviewer will need to ascertain whether the Internet is generally available for use by all members of the household at any time (if not, the correct response is that the household does not have Internet).

Where a household has access to the Internet (HH6), it is quite likely that the selected individual/s use the Internet.

Therefore probe a ‘no’ response.

1.

Historical trends, would expect a fairly flat trend or show slow decline.

2.
2.

Broad consistency with core indicator A1 (fixed telephone subscriptions per 100 inhabitants), absolute values and growth.

1.

Historical trends, would expect medium to high growth (though once the revised concept of household access is adopted, countries may see a decline in the level of mobile telephone access).

2.

Broad consistency with (but lower than) growth rate and values for core indicator A2 (mobile cellular telephone subscriptions per 100 inhabitants).
Historical trends, would expect medium to high growth (though once the revised concept of household access is adopted, countries may see a decline in the level of computer access).

Historical trends, would expect medium to high growth.

Historical trends, would expect medium to high growth (though once the revised concept of household access is adopted, countries may see a decline in the level of Internet access).

Historical trends, would expect medium to high growth.
Manual for Measuring ICT Access and Use by Households and Individuals 1.

Historical trends may not change much unless there is a large change in locations of access, for instance, home Internet access increases or government run community access facilities are opened.

2.

The values of these categories, as a percentage of individuals using the Internet, would add to more than 100 (per cent), because at least some individuals use the Internet at more than one location.
Where household access to the Internet is high, this will generally be the largest output category.

118 Chapter 8.

Data processing for ICT household statistics HH8 Proportion of individuals using the Internet, by location If HH7 is ‘yes’ at least one of the response categories must be selected.

See suggestions for response items, below.

Home Work Place of education Where a household has access to the Internet, Internet users who record a ‘no’ against this category should be probed.
Where a household does not have access to the Internet, a ‘yes’ against this category is possible (according to the revised concept of household access), but could be probed.

Those in the workforce who are Internet users and who record a ‘no’ against this category could be probed.

Students who are Internet users and who record ‘no’ against this category could be probed.
Individuals who are not students should not report ‘yes’ against this category; teachers and others who work at a place of education, would report ‘work’ as place of Internet use.

Where a place of education is used as a location for general community Internet access, such use should be reported under Community Internet access facility.

Another person’s home Community Internet access facility (typically free of charge) Interviewers may need to use examples relevant to the country to explain this category.
The values in this category may increase with policy intervention.

Commercial Internet access facility (typically paid) Interviewers may need to use examples relevant to the country to explain this category.

In mobility Interviewers may need to explain the concept of ‘in mobility’ (that is, while mobile) and the devices that can be used.

Where household access to the Internet is low, this category will often be high, where such facilities are available.

This is a new category (introduced in 2013).


It is likely that values will continue to increase as mobile and portable devices receiving mobile network signal spread.

Other locations (where used)126 A ‘yes’ response should be probed as it may need to be recoded.

The value of this category should be very low.

126 Other locations is not a category in core indicator HH8.

However, it can be useful to include ‘Other’ categories in questionnaires.
Where the set of response categories (excluding ‘Other’) is considered to be comprehensive, then ‘Other’ responses should be queried and the response recoded if appropriate.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 8.

Data processing for ICT household statistics 119 HH9 Proportion of individuals using the Internet, by type of activity If HH7 is ‘yes’ at least one of the response categories must be selected.
Getting information about goods or services Seeking health information Interviewers may need to use examples.

The values of these categories, as a percentage of individuals using the Internet, should add to significantly more than 100 (per cent), as most individuals undertake more than one activity.

Note that categories are not mutually exclusive (that is, there is overlap between some categories).

This is often the second highest output category, after Sending or receiving e-mail.
This is a rewording of the previous (2009) category, Getting information related to health or health services.

This is a new category (introduced in 2013).

Making an appointment with a health practitioner via a website Getting information from government organizations Interacting with general government organizations Interviewers may need to use examples to show which organizations conform to the definition of general government organizations.
There may be data from government organizations indicating the extent of usage of their websites.

There may be data from government organizations indicating the extent of interactive usage of their websites.

Sending or receiving e- mail Interviewers may need to explain what e-mail is.

This is likely to be the largest output category.

Telephoning over the Internet/VoIP Interviewers may need to explain the technicalities involved in this category and provide examples, such as Skype.
Participating in social networks Interviewers may need to explain the technicalities involved in this category and provide examples, such as Facebook, Twitter.

It is likely that values will continue to increase over time for countries at earlier stages of Internet use.

For other countries, flat trends are expected.

This is a split of the previous (2009) category Posting information or instant messaging.
Accessing chat sites, blogs, newsgroups or online discussions Interviewers may need to explain the technicalities involved in this category.

This is a split of the previous (2009) category Posting information or instant messaging.

Purchasing or ordering goods or services Interviewers may need to provide definitions so that payments are excluded.

Selling goods or services Interviewers may need to provide examples of major selling websites such as eBay (there may be national examples as well).
The size of this category may be related to several factors, including the online security environment and the availability of Internet commerce sites.

This is a new category (introduced in 2013).

Using services related to travel or travel- related accommodation Interviewers may need to provide examples of major websites in their country.

This is a new category (introduced in 2013).

Internet banking Interviewers may need to explain the activities per the definition.
The size of this category should be related to the availability of Internet banking.

Manual for Measuring ICT Access and Use by Households and Individuals 120 Chapter 8.

Data processing for ICT household statistics HH9 cont.

Doing a formal online course (in any subject) Consulting wikis, online encyclopaedias or other websites for formal learning purposes Interviewers may need to provide examples of major websites such as Wikipedia (there may be national examples as well).
Listening to web radio (either paid or free of charge) Interviewers may need to provide examples of major websites in their country.

Watching web television (either paid or free of charge) Interviewers may need to provide examples of major websites in their country.

Interviewers may need to provide examples of major websites in their country.
Streaming or downloading images, movies, videos or music; playing or downloading games (either paid or free of charge) This is a split of the previous (2009) category, Education or learning activities.

This is a split of the previous (2009) category, Education or learning activities.
The two previous (2009) categories, Playing or downloading video games or computer games and Downloading movies, images, music, watching TV or video, or listening to radio or music have been rearranged into three new categories, including this one.

The two previous (2009) categories, Playing or downloading video games or computer games and Downloading movies, images, music, watching TV or video, or listening to radio or music have been rearranged into three new categories, including this one.


Downloading software or applications Interviewers may need to provide examples per the definition.
This is a rewording of the previous (2009) category, Downloading Reading or downloading online newspapers or magazines, electronic books Looking for a job or sending/submitting a job application Participating in professional networks Managing personal/own homepage Uploading self/user- created content to a website to be shared Interviewers may need to provide examples.

Interviewers may need to provide examples.

This is a new category (introduced in 2013).


Interviewers may need to provide examples of major websites in their country.

This is a new category (introduced in 2013).

This is a new category (introduced in 2013).

This is a new category (introduced in 2013).

Interviewers may need to provide examples of major social networking websites such as Facebook (there may be national examples as well).
Blogging: maintaining or adding contents to a blog Interviewers may need to explain the technicalities involved in this category.

This is a new category (introduced in 2013).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 8.

Data processing for ICT household statistics 121 HH9 cont.

Posting opinions on civic or political issues via websites Interviewers may need to provide examples of major websites in their country.

This is a new category (introduced in 2013).


Interviewers may need to provide examples of major websites in their country.

This is a new category (introduced in 2013).

Interviewers may need to provide examples of major applications.

This is a new category (introduced in 2013).

Interviewers may need to provide examples of major applications.

This is a new category (introduced in 2013).


Taking part in online consultations or voting to define civic or political issues Using storage space on the Internet to save documents, pictures, music, video or other files Using software run over the Internet for editing text documents, spreadsheets or presentations Other activities (where used)127 HH10 Proportion of individuals using a mobile cellular telephone A ’yes’ response should be probed as it may need to be recoded.
However, some activities are valid for this category, for example, online gambling and use of ‘adult content’.

The definition of use should be included in question wording and/or probes.

It does not equate to a subscriber or owner.

HH11 Proportion of households with Internet, by type of service: If HH6 is ‘yes’ at least one of the response categories must be selected.

The value of this category is unlikely to be zero given that the list of activities is not comprehensive.

1.
1.

Historical trends, would expect medium to high growth.

2.

Broad consistency with core indicator A2 (mobile subscriptions/100 inhabitants), absolute values and growth.128 3.

Check growth with published information from service providers.

1.

Historical trends, depending on services available, may see an increase in broadband and mobile broadband via a card or USB modem, as a proportion of households with Internet.

2.
2.

The values of these categories, expressed as a percentage of households with Internet access, should add to more than 100 (per cent), allowing for some households having more than one access method.

127 128 Other activities is not a category in core indicator HH9.

However, it can be useful to include ‘Other’ categories in questionnaires.

The relationship between the indicators HH10 and A2 may be complex.

Manual for Measuring ICT Access and Use by Households and Individuals 122 Chapter 8.
Data processing for ICT household statistics HH11 cont.

Fixed (wired) narrowband Fixed (wired) broadband Terrestrial fixed (wireless) broadband Satellite broadband Mobile broadband via a handset Mobile broadband via a card or USB modem Interviewers may need to assist by providing specific examples of Internet service providers and products available in the country, in each category used in the questionnaire.
If an interview takes place at household residence, interviewers could ask to see an invoice and check the name of the operator and service, or physically check the type of connection.

Additionally, interviewers could check the type of devices and/or cable plug used for the Internet connection.
It should be possible to differentiate: • fixed (wired) Internet connections from mobile Internet connections • dial-up connections from other fixed (wired) connections by the type of modem or by asking/checking whether the telephone line is available for calling while there is an open Internet connection • mobile Internet connections via a mobile telephone or over USB modem/dongle.
HH12 Proportion of individuals using the Internet, by frequency If HH7 is ‘yes’ at least one of the response categories must be selected.

At least once a day At least once a week but not every day Less than once a week HH13 Proportion of households with multichannel television, by type These categories refer to a typical period; therefore, respondents should ignore weekends (if they only use the Internet at work or school etc) and breaks from their usual routine, such as holidays.
There should be no response to this question if HH2 is ‘no’ (that is, no TV).

Manual for Measuring ICT Access and Use by Households and Individuals 1.

Historical trends, may expect slight growth in frequent use and a decrease in infrequent use.

2.

The values of the three categories, expressed as a percentage of Internet users, should add to 100 (per cent) with allowances for rounding (up to 2 percentage points).

HH13 (households with any form of multichannel TV) should be less than or equal to HH2.
This is a new indicator.

For some or all categories, there may not be historical series on which to compare.

Absolute values for Cable TV and Internet-protocol TV can be compared with the corresponding ITU subscription indicator data for these services because they are paid (therefore, require a subscription).

Chapter 8.

Data processing for ICT household statistics 123 HH13 cont.
Cable TV Direct-to-home satellite services Internet-protocol TV Digital terrestrial TV Interviewers may need to assist by providing specific examples of popular TV programmes that are offered in each TV platform.

A mapping of programmes onto TV platforms should allow interviewers to determine what type of TV connection(s) the household has.

An interviewer could directly check for availability of given TV channels if respondent is not sure (if interview takes place at household residence).
An interviewer could check for the presence of a satellite dish or a cable connection if respondent is not sure (if interview takes place at household residence).

If the household subscribes to a pay-TV service, interviewers could ask to see an invoice and check the name of the operator and service, thereby identifying the type of TV platform.
If the household does not pay for the TV service, it will most likely receive: analogue terrestrial free-to- air TV (not counted as multichannel TV), digital terrestrial free-to-air TV or free-to-air satellite services.

It should be possible to differentiate between each of these TV platforms based on the programmes received.
Since piracy may distort the difference between free and pay TV, in some cases a more practical approach would be just asking about the TV programmes received and then deriving from them the TV platform(s) available.

HH14 Barriers to household Internet access Note that the population for this question is households without Internet access therefore if HH6 is ‘no’, at least one of the response categories of HH14 should be selected.
The values of these categories, expressed as a percentage of households without Internet access, should add to more than 100 (per cent), allowing for some households having more than one barrier to Internet access.

Manual for Measuring ICT Access and Use by Households and Individuals 124 Chapter 8.

Data processing for ICT household statistics The reasons may need to be explained per the definitions in the indicator (Table 5).
The values of these categories, expressed as a percentage of individuals having used computers, should add to much more than 100 (per cent), allowing for most individuals having done more than one activity.

For each individual having answered ‘yes’ to use of computer (HH5), at least one of the response categories should be selected.
The activities may need to be explained per the definitions in the indicator (Table 5).However, it is considered probable that if an individual does not understand the meaning of a particular task, then they are unlikely to have undertaken that task.

The tasks are broadly ordered from less complex to more complex, although there is no requirement for a respondent to select simpler tasks before selecting a more complex task.

HH14 cont.
Do not need the Internet Have access to the Internet elsewhere Lack of confidence, knowledge or skills to use the Internet Cost of the equipment is too high Cost of the service is too high Privacy or security concerns Internet service is not available in the area Internet service is available but it does not correspond to household needs Cultural reasons HH15 Individuals with ICT skills, by type of skills Copying or moving a file or folder Using copy and paste tools to duplicate or move information within a document Sending e-mails with attached files Using basic arithmetic formulae in a spreadsheet Connecting and installing new devices Finding, downloading, installing and configuring software Creating electronic presentations with presentation software Transferring files between a computer and other devices Writing a computer program using a specialized programming language Manual for Measuring ICT Access and Use by Households and Individuals HH16 Household expenditure on ICT Chapter 8.
Data processing for ICT household statistics 125 This indicator will usually be derived from a household budget survey.

Where household access data are also obtained from the budget survey, comparisons may be possible.

For example, if a household does not have a particular ICT, there should be low (or no) expenditure in the corresponding expenditure category.

1.

Historical trends, may expect growth in proportion of ICT expenditure over time.

2.
2.

ICT expenditure as a proportion of total household expenditure could be compared across overall income or expenditure intervals (e.g.

quartile or quintile).


Telephone and telefax equipment (COICOP 08.2.0) Telephone and telefax services (COICOP 08.3.0) Equipment for the reception, recording and reproduction of sound and picture (COICOP 09.1.1) Information processing equipment (COICOP 09.1.3) Repair of audio-visual, photographic and information processing equipment (COICOP 09.1.5) Imputation for missing data (non-response) 339.
Non-response can occur for the whole response – unit non-response, where the respondent refuses, or is unable, to take part in the survey.

It can also occur at the primary sampling unit (e.g.

district, village) if weather conditions, natural disasters, conflicts or other reasons prevent collection of information from households in that selected sampling area.

Non-response can also apply to parts of a questionnaire and this is referred to as item non- response.
An example is where a respondent refuses to answer a sensitive question.

340.

In many cases, the agency conducting the survey will make estimates for non- response; this is usually referred to as imputation.

Both non-response per se and non- response estimates can be a significant source of bias and therefore need to be handled carefully, especially if there is a high rate of non-response.

341.
341.

According to the experience in European countries, there are systematic patterns of non-response in older respondents or lower educated respondents as they are more at risk of not understanding the questions (Eurostat, 2013a).

342.

Non-response rates can be distributed by type.

The most commonly used categories for non-response include: no contact (for example, due to wrong address, temporary or permanent absence, language barrier or health impairment) and refusals.
In general, survey organizations will record rates of response for each reason, to understand possible biases and improve operations of future surveys (for example, by launching communication campaigns to request cooperation, improving the address directory or preparing different language versions of the questionnaire).

Manual for Measuring ICT Access and Use by Households and Individuals 126 Chapter 8.
Data processing for ICT household statistics Imputation for unit non-response may occur in household surveys though, commonly, 343. it will be dealt with by substituting other respondents.

Imputation, if performed, may take the form of adjusting weights so that responding units have higher weights and non-responding units have a zero weight.129 344.
Item non-response (that is non-response to parts of a questionnaire) can be treated like unit non-response if a large proportion of the questionnaire is unanswered.

Where this is not the case, the missing data may be imputed, that is, they are replaced with information derived from survey data (from the same or other respondents).

In ICT household surveys, there are usually not sensitive questions that might provoke item non-response.
However, some of the questions are technical and it is useful for interviewers to have access to technical information, such as definitions of particular ICTs, and information on ICT services and websites available in the country.

345.

Imputation techniques for item non-response include use of regression models, hot deck imputation or nearest neighbour imputation.130 Annex 3 includes examples of imputation for missing items.

346.
346.

It should be noted that imputation is not guaranteed to remove a significant potential problem with non-response, which is non-response bias – non-respondents cannot be assumed to be similar to respondents in their questionnaire responses.

Even though it is not possible to completely eliminate non-response, there are many actions that can help to reduce it.
For instance, interviewer selection, good interviewer training and survey material (including initial contact letters or telephone calls, questionnaires and publicity material, if used), workload assigned to each interviewer and supervision.

Furthermore, when respondents are not available during an initial interview, they should be re-contacted, possibly by telephone in the case of a face-to-face interview methodology.131 347.
The analysis of non-response, its treatment and impact should be reported as part of the quality assessment of the survey implementation and results.

The quality assessment in relation to non-response may include: • • • The presentation of unit non-response rates by types of non-response, and for different population segments (urban/rural, language groups, etc.).

The presentation of item non-response rates for a selected number of questionnaire items.
This may be accompanied by a statistical analysis of the distribution of item non-response for different population segments.

For more detailed analysis, the organization may analyse the relationship between non-response and the conditions under which the survey was carried out, such as time and day of the interview, interviewer, place of the interview or number of attempts to contact the interviewee.

These parameters are usually recorded and referred to as survey paradata.
• The calculation of different measures of bias and impact.132 Weighting of data 348.

Data from a sample are weighted to represent the population.

The initial design weight of a unit in a particular stratum is the inverse of its probability of selection.

For example, if a stratum has a population of 100 and 20 units are sampled randomly with equal probability, 129 130 131 132 Information on this and other imputation techniques for unit non-response can be found in UNSD (2005a, Chapter VIII).
These are described in some detail in UNSD (2005a, Chapters VIII and XVI).

UNSD (2005a, Chapter VIII) recommends use of more skilled interviewers to undertake such callback work.

The description of advanced methods of treatment of non-response and analysis of its effect is outside the scope of this manual.

For a useful reference, consider de Leeuw et al.

(2003), Journal of Official Statistics, Vol.

19 No.

2, 2003, pp 153-176.


Manual for Measuring ICT Access and Use by Households and Individuals Chapter 8.

Data processing for ICT household statistics 127 then the probability of selection is 20/100 and the design weight is 100/20 (that is, 5).

We saw in the last chapter that most household surveys have more than one stage of sampling.

The design weights will incorporate the probability of selection at each stage, that is, weights are given to primary sampling units and to each household in them.
If individuals are sampled within the household, they should also be given a weight.

A simple example of data weighting is presented in Annex 3.

349.

Design weights will often need to be adjusted to reflect non-response, unknown eligibility, out-of-scope units and/or frame problems, such as duplicate records and undercoverage.

133 It is also important to weight responses according to independent estimated distributions of the population.
This form of weighting compensates for non- representativeness of the effective sample (that is, the population of respondents to the survey).

It may be referred to as ‘post-stratification’ or ‘benchmarking’.

Box 26 provides an example of post-stratification.

Box 26.

Australia: example of post-stratification The Australian multipurpose household survey (MPHS) for 2006–07 included a number of ICT household questions.
The first step in calculating weights for each unit of the MPHS was to assign an initial weight, which was the inverse of the probability of the unit being selected in the survey.

The initial weights were then calibrated to align with independent estimates of the population of interest, referred to as ‘benchmarks’.

This ensured that survey estimates conformed to an independently estimated distribution of the population rather than the distribution within the sample.
Benchmarks were produced to match the survey’s scope.

Estimates for individuals were benchmarked to the estimated civilian population aged 15 years and over living in private dwellings in each Australian state and territory, excluding persons out of scope.

Household benchmarks were actually estimates themselves and not strictly known population totals.

Source: ABS, 2007.

350.


An additional tier of weighting, ‘trimming of weights’, consists of reducing the size of very large weights to reduce their contribution to the magnitude of estimates and their variance.

However, its impact on bias should also be taken into account.

134 351.

For more information on weighting, readers are referred to UNSD (2005b, Chapter 6), which presents a comprehensive technical discussion of the subject.

Calculating and reporting ICT household indicators 352.
Calculation of the ICT household indicators, while not complex, needs to be clear so will be described in some detail.

Indicators arising from ICT use surveys will generally be presented as proportions.135 353.

They the whole population of households/individuals or of include proportions of subpopulations, such as particular household types or age groups.

Additionally, countries may present data as a proportion of households/individuals that have access to, or use, computers or the Internet.
Having two methods of calculation for some indicators can be potentially confusing to users, so it is important to be clear which denominator is used to construct a particular indicator and to have a common approach for reporting purposes.

Formulae for the calculation of the core indicators are provided in Chapter 4.

354.
354.

When reporting data to ITU, countries should provide estimates of the total numbers of units (rather than proportions or percentages) with a particular ‘ICT characteristic’, for 133 134 135 See UNSD (2005b, Chapter 6) for adjustment of design weights.

UNSD (2005b, Chapter 6).

In particular, all the core ICT household indicators are proportions data.

Manual for Measuring ICT Access and Use by Households and Individuals 128 Chapter 8.
Data processing for ICT household statistics example, the estimated number of adult Internet users or the estimated number of adult male computer users.

In addition, the estimated total number of units in the subpopulations (in this example, all in-scope adults and all in-scope adult males) also need to be provided so that proportions can be calculated.

All data should be weighted estimates of the population rather than the number of units in the sample.
An example of data reporting is provided in Table 12.

It can be seen that the presentation in Table 12 provides the data user with maximum 355. flexibility.
Examples of calculations that can be made include: • • • • • • the proportion of individuals using a computer, the proportion of males and females using the Internet, the proportion of individuals using the Internet at home, the proportion of female Internet users using the Internet at work, the proportion of Internet users aged 15 years or over using the Internet at another person’s home, and the proportion of young people aged 5–24 using computers.136 Table 12.
Example of data reporting: partial table Variable Total estimated population (total in-scope population, not sample number), in thousands HH5 Estimated number of individuals who used a computer (from any location) in the last three months, in thousands Sex Age Male Female 5–14 15–24 25+ 1,214 1,121 370 507 1,458 595 605 183 403 614 HH7 Estimated number of individuals who used the 402 439 122 297 422 Internet (from any location) in the last three months, in thousands HH8 Estimated number of individuals who used the 206 217 81 150 192 Internet at home in the last three months, in thousands HH8 Estimated number of individuals who used the 189 152 5 147 189 Internet at work in the last three months, in thousands HH8 Estimated number of individuals who used the 130 134 107 119 38 Internet at their place of education in the last three months, in thousands HH8 Estimated number of individuals who used the 53 68 46 38 37 Internet at another person's home in the last three months, in thousands 356.
Care should be taken when aggregating response categories into those required for international comparability.

Some countries may construct indicators for the core indicators HH8, HH9, HH11, HH12 and HH13 based on more detailed response categories.

For example, in the ‘location of use’ question in a country survey, the response category ‘community Internet access facility’ could be comprised of the subcategories, public libraries, digital community centres and other government agencies.
136 The last two calculations involve aggregation of categories.

This would not be possible if only percentages (expressed as the proportion within each age group) were provided.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 8.

Data processing for ICT household statistics 129 In this example, the proportion of Internet users using the Internet at community 357.
Internet access facilities is calculated by deriving the number of users who used the Internet at one or more of the locations, public libraries, digital community centres or other government agencies.
Clearly, this aggregation has to be done at the unit record level rather than from aggregated data and gives a different answer than if the percentages or numbers accessing the Internet at each of the component locations are summed (this is because those individuals who use the Internet at more than one of these locations will be counted more than once).

358.
358.

More information on ITU’s data collection and dissemination for ICT household statistics can be found in Chapter 10 and Annex 4 (which shows an extract from the questionnaire ITU uses to collect ICT household statistics).

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 9.

Data quality and evaluation for ICT household statistics 131 Chapter 9.

Data quality and evaluation for ICT household statistics 359.
An underlying principle, applicable to all aspects of survey design and implementation, is that it is important to understand sources of error so that it can be minimized.

This chapter outlines survey data quality issues, in particular, those specific to household ICT access and use statistics.

360.

The chapter examines both sampling and non-sampling error, and provides information on quality assurance techniques and frameworks.

It concludes with some general advice on data evaluation.

361.
In general, countries should aim to reduce survey error as much as possible by: • • • • • • using well-designed samples that are of sufficient size to produce reliable data (that is having low standard errors for the required aggregates); careful design and testing of questions and question sequences; intensive training and supervision of interviewers and other staff; reducing non-response rates as far as possible; integrating computer-based quality controls to fieldwork; and minimizing data entry, editing and other processing errors.
362.

In practice, there will often be trade-offs between sampling and non-sampling error.

UNSD 137 cites the example of having smaller sample sizes and using more skilled interviewers.

The latter allows for better management, which would be expected to reduce non-sampling error, including non-response bias.

However, for a given sample design, this strategy will result in higher sampling error, as sampling error is related to sample size.

Sampling error 363.
Sampling error 363.

Sampling error is the component of survey error that occurs because only a fraction of the total population is sampled.

It is said to measure the precision of an estimate.

The sampling error of an estimate can be expressed in three ways, all of them a function of the standard error around the estimate, 138 noting that the quoted standard error of a survey estimate is itself an estimate based on observations from the sample.

364.
364.

Sampling error may be expressed in terms of the standard error of the estimate of interest, but more commonly it is expressed as a ratio of the standard error of the estimate to the value of the estimate and converted to a percentage (for instance, as 2 per cent of the value of the estimate).

This provides scale in relation to the estimate and enables simple comparison of the sampling error around different estimates (see Box 27 for an illustration).
The ratio is referred to as the ‘relative standard error’ (RSE) or ‘coefficient of variation’ (CV).

365.

Sampling error can also be expressed as a confidence interval around an estimate, commonly, a 95 per cent confidence interval.

This refers to the probability (0.95 or 95 per cent) that the parameter to be estimated will lie within an interval around the estimate of +/– 2 137 138 UNSD (2005a, Chapter II).

The standard error of an estimate is the square root of the estimate’s variance.
Manual for Measuring ICT Access and Use by Households and Individuals 132 Chapter 9.

Data quality and evaluation for ICT household statistics standard errors.139 It assumes that the estimate conforms with a normal statistical distribution, an assumption that is rarely questioned as it usually applies well to large samples.

Box 27.
Box 27.

Sampling error of the value of an ICT household indicator If the estimated proportion of individuals who used the Internet in country A in the last year is 0.83 and the standard error of the estimate is 0.01, then the value for core indicator HH7 is 83 per cent and the relative standard error is 100*0.01/0.83 = 1.2 per cent of the estimate.
If the estimated proportion of people aged 55–64 who used the Internet in country A in the last year is 0.49 and the SE of the estimate is 0.03, then the value for core indicator HH7 (individuals aged 55–64) is 49 per cent and the RSE is 100*0.03/0.49 = 6.1 per cent of the estimate.

It can be seen that the reliability of the two estimates can be directly compared by using the value of the respective RSEs.
With a probability of 95 per cent, the value of the parameter to be estimated will lie within the 95 per cent confidence interval.

The interval can be expressed as: the sample estimate +/– twice139 its standard error.

In the first example, the 95 per cent confidence interval around the estimate is 0.83 +/– 0.02 (twice the SE).
Therefore, with a confidence level of 95 per cent, the value of the parameter to be estimated (in percentage terms) will lie in the interval 83–2 to 83+2, that is, between 81 and 85 per cent.

The 95 per cent confidence interval in the second example is 0.49 +/– 0.06, that is 43 to 55 per cent.

366.

The core indicators for household ICT access and use are all proportions, for instance, the proportion of individuals who used the Internet in the last three months.
Proportions may be of the total population (for instance, the proportion of households with Internet access) or a subpopulation, such as the proportion of households with Internet access that use broadband to access the Internet at home.

In the first case, the estimate is of a proportion.

In the second, it is a ratio calculated as an estimate of the number of households with broadband access to the estimate of the number with Internet access.
In the case of a simple random sample without replacement (which is rarely the case 367. for household surveys), the standard error (SE) of a sample proportion, pˆ , of the population (the first example above) is estimated by: (1) SE )ˆ( p = − nN − )1 n N ( 1(ˆ p − )ˆ p , where pˆ is the sample estimate of the true proportion, p. Under the same sampling design, the relative standard error (or ‘coefficient of / pˆ .
Examples of the use of standard errors to show RSEs and 368. variation’) of pˆ is 100* confidence intervals of simple proportions are provided in Box 27.

)ˆ( p SE 369.

For a complex proportion, both the numerator x and denominator y are estimated separately from the survey, forming a ratio estimate x y .

370.

There is no unbiased estimate with a closed form for the RSE of a ratio, and generally approximations are used.
As an example, the Australian Bureau of Statistics (ABS, 2007), used the following approximation to calculate the RSE of a ratio estimate x y as a function of the RSE of x and the RSE of y: (2) RSE    x y  =  ([RSE(x)] 2 − 2 [RSE(y)] ) .

139 This is an approximation, the multiplier is actually 1.96.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 9.

Data quality and evaluation for ICT household statistics 133 371.
ABS applied the formula to the estimate of the proportion of households with broadband access, where x was the estimate of the number of households with broadband access and y was the estimate of the number of households with Internet access.

372.

Of particular interest for many statistics, including ICT statistics, is the calculation of the SE of an estimate of change over time (for instance, the number of computer users in 2000 compared with the number in 2007).
If the samples on which the two estimates are based are independent, then the SE of the difference over time, xt+1 – xt, is as follows: (3) SE ( x − x t t + 1 ) = [ SE ( x 2 ] ) + [ SE ]2 ) .

( x t t + 1 373.

There is a relationship between the SE and the sample size (n), with the SE decreasing as n increases (SE is inversely proportional to √n).

Commonly, survey designers will determine in advance (and preferably in accordance with users’ needs) the required reliability for major aggregates (e.g.
the estimated percentage of households with Internet access should have a RSE of no more than 2 per cent) and then use estimates of the SEs around those aggregates to determine sample size.

140 Other determinants of the size of the SE are the population size, the sampling method and the inherent variability in the population of the variable being estimated.

374.
374.

Determination of the SE of an estimate becomes much more complicated with a complex survey design, for example, a design involving stratification and two sampling stages.

Consideration must be given to the degree of homogeneity of units within a cluster and other design effects.141 In this case, SEs are usually calculated as approximations, using specialized software.142 375.

It is beyond the scope of this manual to do more than introduce the subject of sample design and sampling error.
Readers are referred to UNSD (2005b), which deals primarily with the design of household surveys and UNSD (2005a), which covers all aspects of household sample survey design and implementation in respect of developing and transition economies.

UNSD143 also provides an overview of analysis software packages that may be used to estimate sampling error.

A more complete review may be found on the Harvard’s Summary of Survey Analysis Software webpage.144 Non-sampling error 376.
Non-sampling error (also referred to as ‘bias’) refers to errors in output that are not due to sampling.

Non-sampling error (NSE) has diverse origins.

The sources and prevention of NSE have been discussed throughout this manual.
NSEs include those related to: • • • • • frame inadequacies, including undercoverage, duplicates and incorrect data; inappropriate or misunderstood question wording; poor quality or inconsistent interview performance; non-response; respondent effects (for instance, proxy reporting); and 140 Such estimates might come from previous data.

Where the survey is run for the first time, other information could be used, for instance, data on sampling error from similar countries.
141 Described by UNSD (2005a) as follows: “The design effect represents the factor by which the variance of an estimate based on a simple random sample of the same size must be multiplied to take account of the complexities of the actual sample design due to stratification, clustering and weighting.” The square root of the design effect (which UNSD calls the ‘design factor’) is the multiplier applied to a standard error.
The design effect is specific to each estimate in a given survey and is generally greater than one.

142 143 144 See UNSD (2005a, Chapter XXI) for details.

UNSD (2005b, Chapter XXI).

See http://www.hcp.med.harvard.edu/statistics/survey-soft/.

Manual for Measuring ICT Access and Use by Households and Individuals 134 Chapter 9.

Data quality and evaluation for ICT household statistics • problems in data processing and tabulation.

377.
377.

While non-sampling error is controllable in theory, in practice some NSE will often persist and it is important to try to describe its extent and nature to data users, even though the size (and sometimes even the direction) of the error is usually difficult to measure.

378.

As we saw in Chapter 3, careful planning and testing should reduce NSE.

In particular, attention to interviewer training and questionnaire design, will be well rewarded.
Furthermore, human supervision, as mentioned in Chapter 3, is crucial for reducing NSE.

379.

More information on NSE can be found in UNSD,145 which discusses ‘non-observation’ errors.

These are errors arising from non-response or non-coverage (which is a frame problem, referred to as undercoverage in this manual).

UNSD146 also discusses NSE arising from the questionnaire, method of data collection, the interviewer and the respondent.
It provides some techniques that will assist in understanding bias from these sources and broadly quantifying it.

Assessment of data quality 380.

Within the constraints of survey resources, a high level of data quality should be the goal of every survey statistician.

147 Good statistical agencies have a strong data quality culture that not only enables them to produce high quality data, but also lends credibility to those data.
Data quality considerations must be paramount at each stage of the survey process.

381.

Data quality can be considered in terms of several dimensions or criteria (e.g.

relevance, accuracy, 148 timeliness and punctuality, accessibility and clarity, comparability, and coherence).

It is recommended that countries use at least these dimensions to ensure the quality of ICT household statistics.
More specific guidance may be found from the experiences of those statistical organizations that have quality assurance (QA) frameworks based on these dimensions.

They include the Australian Bureau of Statistics’ 2011 Data Quality Framework, 149 Eurostat’s 2009 Standard for Quality Reports 150 and the IMF’s Data Quality Assessment Framework.
151 The World Bank, in the context of the International Household Survey Network (IHSN), is developing a survey quality assurance framework (SQAF) which will be adapted to the specific conditions of developing economies.152 382.

Detailed data quality reports are typically produced for internal approval processes and should address the quality dimensions referred to above.
They will also include detailed information about the survey’s results including the results of macro (or output) editing (see Chapter 8) and an explanation of divergences from expected findings.

153 Table 18 in Chapter 10 presents metadata associated with the core ICT indicators.

The metadata include topics relating to data quality.

145 147 146 UNSD (2005a, Chapter VIII).

UNSD (2005a, Chapter IX).

Data quality, like everything else in a system of limited resources, is not boundless.
For instance, sample sizes may be smaller than ideal or interviewers may be relatively inexperienced.

A good survey manager will maximize the quality of the output and may need to suppress data which he/she considers to be unreliable.

148 The word “accuracy” is used by UNSD (2005b) to refer only to non-sampling error.

The Manual uses the term to refer to both sampling and non-sampling error.

This is consistent with usage of Eurostat and the ABS.
See Glossary of terms and abbreviations for more information.

149 See http://www.abs.gov.au/websitedbs/D3310114.nsf/home/Quality:+The+ABS+Data+Quality+Framework.. See http://epp.eurostat.ec.europa.eu/portal/page/portal/ver-1/quality/documents/ESQR_FINAL.pdf.

Even though the IMF primarily deals with economic statistics, a DQAF module on household income in a poverty context has been developed 150 151 in collaboration with the World Bank.

See http://dsbb.imf.org/Applications/web/dqrs/dqrsdqaf/.
152 See http://www.ihsn.org/home/projects/survey-quality-assessment-framework-SQAF.

153 UNSD (2005a, Chapter X) discusses quality assurance in some detail.

It suggests the need for quality standards, QA procedures and evaluation of QA.

It describes the World Health Survey quality standards and assurance procedures devised by the World Health Organization.

The standards are presented in stages, representing the stages of a survey cycle and include useful checklists of QA procedures and issues.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 9.

Data quality and evaluation for ICT household statistics 135 Evaluation 383.

An element of both data quality and evaluation is careful documentation of survey processes and procedures.

These may include a priori descriptions of survey plans, including costs, methodologies and procedures.

They should also include documentation of costs and procedures as they occur during survey implementation.
An example of the latter is the importance of documenting any changes in sample design during the field phase, reflecting changes or adaptations.154 This is necessary for later adjustments and is particularly useful for designing future surveys.

384.

After the survey is completed, further documentation should describe the collection and present survey data and metadata.

A subset of such information should be disseminated as part of the survey’s output.

This is addressed in the next chapter.

385.


Staff contributions can also be important to survey evaluation.

The experiences of all staff, including interviewers, supervisors and data entry operators, can be very useful input to evaluation of a survey and should be obtained shortly after completion of the survey.

155 386.

The references on quality assessment mentioned above, as well as those on planning mentioned in Chapter 3 can be used to prepare evaluation reports.

154 155 UNSD (2005b, Chapter 5).


See UNSD (2005a, Chapter IV).

Their input should be encouraged at other stages as well, given their specialized knowledge of the operations of the survey.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 10.

Dissemination of ICT household data and metadata 137 Chapter 10.

Dissemination of ICT household data and metadata 387.

This chapter deals with dissemination of ICT household statistical data and metadata.
It includes example tabulations of core indicator data for household ICT access and individual ICT use.

388.

The chapter also considers the international data collection and dissemination work carried out by ITU.

An extract from the questionnaire used by ITU to collect the core ICT household data from countries is presented in Annex 4.

Data dissemination 389.


Data may be released in different formats,156 including: • • • • hardcopy publications; electronic publications (for instance pdf files of hardcopy publications, web publications in html form); tables on websites, spreadsheets, motion graphics; and microdata files, containing individual confidentialized records from surveys.

390.

Data may be free or charged, or a combination.


For instance, pdf files might be free to download but printed versions may be charged, reflecting their cost of production.

Hardcopy releases may be provided free to some users, for instance, government departments, but provided at cost to other users.

Some agencies provide some free data on their website, but may charge for more detailed data.

391.

Some countries may provide microdata from household surveys.
These are data at unit record level that have been confidentialized.

Such information can be very useful for detailed analysis.

For a comprehensive set of tools for disseminating and documenting microdata, see the Accelerated Data Program,157 an initiative in the frame of the International Household Survey Network.

392.

All released data should be based on a single approved version of the dataset, unless revisions are later made (in which case, all released data are subject to revision).

393.
393.

Where data are deemed unreliable (usually because of high standard errors), they should be suppressed and that should be indicated by a symbol in the cell, for instance, n.a.

(for ‘not available’).

394.


Where categories are combined for purposes of national reporting, the advice on aggregating response categories should be followed (see Chapter 8).158 156 It is recommended that electronic formats for dissemination are open, such as text files (.TXT, .CSV) or software that does not require costly investment by the users.

157 158 See http://adp.ihsn.org/.


Even though this advice applies to international reporting in the current context, it is true for any situation where response categories are combined.

Manual for Measuring ICT Access and Use by Households and Individuals 138 Chapter 10.

Dissemination of ICT household data and metadata Tabulation plans for ICT indicators 395.
We saw in Chapter 8 how the ICT household indicators should be calculated and how they should be provided to collection agencies for international compilation purposes.

396.

The situation is different for national presentation purposes.

In a national context, ICT household data are most likely to be presented as percentages, rather than numbers of individuals or households.
For indicators with multiple response categories, it may be more relevant to present data using the population that was asked the question as the denominator, for example, in an indicator referring to location of Internet use, the proportion could be calculated using as denominator the number of individuals using the Internet rather than the whole population of individuals.
In addition, national presentation may be more (or less) detailed and could include additional classificatory variables of national interest (such as an urban/rural split or by administrative divisions of the country).

397.

Tables 13 and 14 below are examples of how ICT household core indicator access data might be tabulated for dissemination purposes.

Table 15 presents an example of tabulation for individual ‘whole population’ ICT use indicators.
Table 16 presents a tabulation for the location of Internet use.

Table 17 presents an example tabulation for ICT skills of individuals.

The examples include all the classificatory variables recommended for use with the core indicators.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 10.

Dissemination of ICT household data and metadata 139 Table 13.
Example tabulation for household ICT access core indicators Households with: Telephone Internet access at home Radio TV 159 any fixed only mobile only both fixed and mobile Computer any fixed narrow- band satellite broad- band fixed broad- band mobile broad- band Percentage of households Household characteristics Household composition has children under 15 does not have children under 15 Household size (number of members) 1 2 3–5 6–10 more than 10 Household income160 Province or state161 Zone161 urban rural All households 159 Countries able to collect data for HH13 (Households with multichannel TV) could split this into the following categories: any TV (HH2), cable TV, direct-to-home (DTH) satellite services, Internet-protocol TV (IPTV) and digital terrestrial TV (DTT).
160 Household income.

While this is not a recommended core indicator classificatory variable, it can be a very useful household characteristic.

No categories or presentation are suggested, although a quartile presentation might be the simplest.

161 Province or state, and Zone.


These are not recommended core indicator classificatory variables but can also be very useful household characteristics for policy purposes, especially where information is required in respect of different areas of a country, including information about any rural/urban divide.

Manual for Measuring ICT Access and Use by Households and Individuals 140 Chapter 10.

Dissemination of ICT household data and metadata Table 14.
Example tabulation for barriers to household Internet access Households with barriers to Internet access: do not need Internet have access else- where lack confid- ence, skills high equip- ment cost high service cost privacy or security concerns Internet service not available service available but not suitable cultural reasons Percentage of households Household characteristics Household composition has children under 15 does not have children under 15 Household size (number of members) 1 2 3–5 6–10 more than 10 Household income Province or state Zone urban rural All households Manual for Measuring ICT Access and Use by Households and Individuals Chapter 10.
Dissemination of ICT household data and metadata 141 Table 15.
Example tabulation for ‘whole population’ individual ICT use indicators162 Individuals who used (from any location, last three months): a computer the Internet a mobile telephone Percentage of individuals Individual characteristics163 Age under 5 5–9 10–14 15–24 25–34 35–44 45–54 55–64 65–74 75 and over Sex male female Highest education level164 primary education or lower lower secondary education upper secondary or post-secondary non-tertiary tertiary or post-tertiary education Labour force status165 employees self-employed workers not classifiable by status unemployed outside the labour force Occupation166 legislators, senior officials and managers professionals technicians and associate professionals clerks service workers and shop and market sales workers skilled agricultural and fishery workers craft and related trades workers plant and machine operators and assemblers elementary occupations armed forces167 not applicable (outside the labour force) Languages read/spoken168 Disability status 169 All individuals 162 163 164 165 166 167 168 That is, those indicators, where the whole population (in each population category, e.g.
males) is the only possible denominator.

For notes on the classifications, see Chapter 4.

Based on ISCED2011.

Self-employed includes: employers, own account workers members of producers' cooperatives and contributing family workers.

Based on ISCO-88; categories would change slightly with the implementation of ISCO-08 in 2008.

Armed forces personnel may be out of scope, in which case the category would not be included.
This is not a recommended core indicator classificatory variable but can be very useful in a country where a number of languages are read/spoken (especially where this might be limiting in terms of employment, education, ICT use or other activities).

169 This is not a recommended core indicator classificatory variable but will be of policy interest in some countries.

It is important to establish the existence of disability carefully and this might require several questions.
Manual for Measuring ICT Access and Use by Households and Individuals 142 Chapter 10.

Dissemination of ICT household data and metadata Table 16.
Example tabulation for the location of Internet use Location of Internet use (in the last three months): home work place of education another person's home community Internet access facility commercial Internet access facility in mobility Percentage of Internet users Individual characteristics170 Age under 5 5–9 10–14 15–24 25–34 35–44 45–54 55–64 65–74 75 and over Sex male female Highest education level primary education or lower lower secondary education upper secondary or post- secondary non-tertiary tertiary or post-tertiary education Labour force status employees self-employed workers not classifiable by status unemployed outside the labour force Occupation legislators, senior officials and managers professionals technicians and associate professionals clerks service workers and shop and market sales workers skilled agricultural and fishery workers craft and related trades workers plant and machine operators and assemblers elementary occupations armed forces not applicable (outside the labour force) All individuals 170 For notes on the classifications, including other possible classifications, see Chapter 4.
Manual for Measuring ICT Access and Use by Households and Individuals Chapter 10.

Dissemination of ICT household data and metadata 143 Table 17.
Example tabulation for ICT skills of individuals Computer users who have undertaken the following computer-related activities (last three months) copying, moving file or folder using copy and paste tools sending e- mails with attached files using basic arithmetic formulae in spread- sheet connect- ing, installing new devices finding, download- ing, installing, configuring software creating electronic presentations with presentation software transferring files between a computer and other devices writing a computer program using a specialized programming language Individual characteristics Percentage of computer users Age under 5 5–9 10–14 15–24 25–34 35–44 45–54 55–64 65–74 75 and over Sex male female Highest education level primary education or lower secondary upper secondary or post-secondary non- tertiary or post-tertiary education Labour force status employees self-employed workers not classifiable by status unemployed outside the labour force Occupation legislators, senior officials and managers professionals technicians and associate professionals clerks service workers and shop and market sales skilled agricultural and fishery workers craft and related trades workers plant and machine operators and elementary occupations armed forces not applicable (outside the labour force) All individuals Manual for Measuring ICT Access and Use by Households and Individuals 144 Chapter 10.
Dissemination of ICT household data and metadata Metadata reporting and dissemination 398.

It is important that countries include metadata about the survey as a whole and individual observations in published statistical output.

This includes information on data quality, which may be considered in terms of several dimensions or criteria (e.g.

relevance, accuracy,148 timeliness and punctuality, accessibility and clarity, comparability, and coherence).
A number of statistical organizations have quality assurance (QA) frameworks based on these dimensions; these were discussed in the previous chapter.

Eurostat provides guidance to member country statisticians on how to report data quality according to Eurostat’s quality criteria.171 The reports for Eurostat’s information society statistics consist of web pages containing metadata on the community business and household surveys of ICT access and use.172 399.
Limitations of survey data should be emphasized and would cover the likely existence of non-sampling error (with steps taken to reduce it) and, where relevant, the fact that output data were based on a sample of units.

Any time series incompatibility should also be described, for instance, that results should not be compared with those of earlier surveys because of differences in scope or methodology.

400.
400.

Standard errors for at least the major aggregates from a survey should be disseminated to data users as they provide a vital indication of the reliability of the estimates.

Where relative standard errors are high, users should be alerted to this fact.

UNSD suggests that a RSE of 7.5 per cent of the estimate is the maximum that should be allowable for major aggregates.
173 Where RSEs are higher than this level, consideration should be given to suppressing the affected data because of its poor reliability and potential to mislead rather than inform.

Some countries flag data with high standard error in statistical tables to inform users of the accuracy of figures.

401.

Metadata can relate to a whole survey or to particular survey results (e.g.

a particular indicator).


174 Table 18 recommends the broad classes of metadata that should be disseminated with ICT survey data and provides examples.

171 Information to be reported for each quality criterion and indicators can be found here in the ESS Handbook for Quality Reports, http://epp.eurostat.ec.europa.eu/portal/page/portal/quality/quality_reporting.
172 The base page http://epp.eurostat.ec.europa.eu/portal/page/portal/information_society/methodology is a very useful reference for information society statisticians and includes links to questionnaires and other methodological information (including the methodological manuals for information society statistics).
See also the ‘Rolling review of the Information Society (IS) statistics’ carried out by Eurostat in 2011: http://epp.eurostat.ec.europa.eu/portal/page/portal/quality/documents/Executive%20Summary_IS%20Rolling%20Review_0.pdf.

173 Based on the recommendation in UNSD (2005b, Chapter 3).
Note that this is higher than the levels stated by Eurostat, which recommends for ICT household surveys that “The estimated standard error (standard deviation), expressed by the square root of the estimate of the sampling variance, shall not exceed 2 percentage points of the overall proportions and shall not exceed 5 percentage points for the proportions relating to the different subgroups of the population, where these subgroups constitute at least 10% of the total population in the scope of the survey.” (Eurostat, 2013a).
174 An example of survey result (or survey estimate) metadata is information that the estimated proportion of households with a computer is understated because computers were restricted to desktop computers.

Manual for Measuring ICT Access and Use by Households and Individuals Chapter 10.

Dissemination of ICT household data and metadata 145 Table 18.
Metadata associated with ICT household surveys Metadata class Examples of metadata Reference period Survey name and organization conducting the survey (if relevant) General information about the survey Main statistical standards used Scope (target population), survey frame and coverage, statistical units Survey methodology Response rate Survey history.

Main changes over time to survey scope, methodology, definitions, etc.

Frequency of survey (quarterly, annual etc.).


Whether a stand-alone survey or not; a stand-alone survey only collects ICT use data and any other information required to tabulate results (e.g.

age, sex).

If not a stand-alone survey, indicate the survey vehicle used to include ICT questions.

Whether a mandatory or voluntary survey (legal basis for the survey).

Major underlying statistical frameworks used (e.g.

Partnership core ICT indicators concepts and definitions).
Divergence from international or national standards (for instance, scope differences or differences in concepts or definitions used for individual ICT indicators).

Changes in standards over time and their likely impact (for instance, a change in the definition of ‘computer’ between one survey and the next).

Might include a glossary of terms used (e.g.

the Internet).

Main classifications used (e.g.

ISCED).

Description of household and individual scope where relevant.
Any significant limitations on the scope or coverage of the survey (e.g.

the exclusion of non-urban populations).

Survey frame/s used including any inaccuracies such as undercoverage and duplication.

Statistical units (household and individual).

Collection technique (e.g.

face-to-face interview using CAPI).

Sample size.

Sample design (stratification, sampling stages).

Changes in survey methodology and impact on estimates.
Weighting methods, including final benchmarking against independent estimates.

For each unit type, households and individuals, and possibly for major disaggregations (e.g.

for males and females, areas, linguistic groups).

Non-response treatment Imputation rules for missing units.

Imputation rules for missing items.


Relative standard errors (coefficients of variation) or confidence intervals Known non-sampling error The best presentation for RSEs is probably as a table corresponding to data tables; alternatively, RSEs may be presented in a range for each type of aggregate (e.g.

total level, province level).

Bias (e.g.

non-response, frame errors, questionnaire bias) and attempts made to minimize it.
Reference to further information about the survey (usually a website link) Might include links to more detailed methodological information, questionnaires, how to obtain more detailed data, future plans etc.

Contact information for further information about the survey or survey data An e-mail address is very useful.

For privacy purposes, this could be generic.

Manual for Measuring ICT Access and Use by Households and Individuals 146 Chapter 10.
Dissemination of ICT household data and metadata Data collection and dissemination of ICT statistics by ITU 402.

ITU collects telecommunication data annually for over 200 economies worldwide, with some data series going back as far as 1960.

These series traditionally refer to telecommunication and ICT infrastructure data, such us fixed-telephone subscriptions, mobile-cellular subscriptions and Internet subscriptions.
Some of them are included in the Partnership’s core list of indicators (namely, the ICT infrastructure and access indicators, see Annex 1 for details).

The main sources for these data are national regulatory authorities and sector ministries in charge of telecommunication/ICT that collect administrative data directly from operators and service providers.

Data are collected using an online questionnaire available at the ITU ICT Eye175 website.

403.
403.

ITU has expanded its statistical work since 2003 by collecting official household and individual ICT data from national statistical offices.

From 2005, ITU has sent an annual questionnaire to all NSOs, requesting data on the core indicators on access to, and use of, ICT by households and individuals.

404.

Calculation and reporting of data to ITU for international comparability purposes was described in Chapter 8.
As discussed, the preferred approach is for countries to provide data on numbers of units (households, individuals) with a particular characteristic rather than proportions or percentages.

Numbers for total populations and subpopulations also need to be provided to enable calculation of proportions for various population groups.

The point was also made that data on the number of units with a particular ‘ICT characteristic’ (e.g.
the number of adult Internet users) and number of units in the population of reference (e.g.

the number of in-scope adults) should represent weighted estimates rather than the number of units in the sample.

405.

ITU statistics are disseminated in various ways, including printed publications, CD- ROM, and electronic download.

In particular, data are disseminated through the World Telecommunication/ICT Indicators (WTI) Database, which is available on CD-ROM as well as by electronic download.
The WTI Database includes annual time series for over 140 indicators.

ITU also produces a number of global and regional reports to analyse regional market trends and developments.

Some key telecommunication/ICT data are provided for free, through the ITU statistics website (www.itu.int).

406.

Household and individual ICT data collected by ITU are disseminated via regional and global reports and the ITU Yearbook of Statistics.
Relevant results from the questionnaire have also been used to prepare other ITU statistical publications such as the Use of Information and Communication Technology by the World’s Children and Youth (ITU, 2008) as well as the publications, ICT Facts and Figures and Measuring the Information Society Report (for example, ITU, 2013a).

The latter is of particular relevance and has been published annually since 2009.
It features the ICT Development Index (IDI), in which three of the household core indicators are featured: households with a computer, households with Internet and Individuals using the Internet.

In addition, editions from 2011 and 2013 featured, respectively, a chapter on the role of some socio-demographic conditions in increasing Internet use and a chapter on digital natives, which were based on household survey results reported to ITU through its data collection questionnaire.
Publications of interest are available from the ITU statistics website.

ICT household data collected by ITU will figure prominently in future ITU publications that analyse trends in ICT access and use.

175 See http://www.itu.int/net4/ITU-D/icteye/Login.aspx.

Manual for Measuring ICT Access and Use by Households and Individuals Annex 1.

Core list of ICT Indicators (revised 2013) 147 Annex 1.
Core list of ICT Indicators (revised 2013) Core indicators on ICT infrastructure and access This list was discussed by the Expert Group on Telecommunication/ICT Indicators (EGTI) and a revised version was agreed upon during the EGTI meeting held in Mexico City, on 2–3 December 2013.
A1 A2 A3 A4 A5 A6 A7 A8 A9 Fixed telephone subscriptions per 100 inhabitants Mobile cellular telephone subscriptions per 100 inhabitants Fixed (wired)-broadband Internet subscriptions per 100 inhabitants, broken down by speed Wireless-broadband subscriptions per 100 inhabitants International Internet bandwidth per inhabitant (bits/second/inhabitant) Percentage of the population covered by at least a 3G mobile network Fixed broadband Internet prices per month Mobile cellular telephone prepaid prices per month Mobile broadband Internet prices per month A10 TV broadcasting subscriptions Core indicators on access to, and use of, ICT by households and individuals HH1 HH2 HH3 Proportion of households with a radio Proportion of households with a television Proportion of households with telephone: A fixed telephone A mobile telephone Any telephone Fixed telephone only Mobile telephone only HH4 HH5 HH6 HH7 HH8 Both fixed and mobile telephone Proportion of households with a computer Proportion of individuals using a computer Proportion of households with Internet Proportion of individuals using the Internet Proportion of individuals using the Internet, by location: Home Work Manual for Measuring ICT Access and Use by Households and Individuals 148 Annex 1.
Core list of ICT Indicators (revised 2013) Place of education Another person’s home Community Internet access facility Commercial Internet access facility In mobility HH9 Proportion of individuals using the Internet, by type of activity: Getting information about goods or services Seeking health information Making an appointment with a health practitioner via a website Getting information from general government organizations Interacting with general government organizations Sending or receiving e-mail Telephoning over the Internet/VoIP Participating in social networks Accessing chat sites, blogs, newsgroups or online discussions Purchasing or ordering goods or services Selling goods or services Using services related to travel or travel-related accommodation Internet banking Doing a formal online course Consulting wikis, online encyclopaedias or other websites for formal learning purposes Listening to web radio Watching web television Streaming or downloading images, movies, videos or music; playing or downloading games Downloading software or applications Reading or downloading online newspapers or magazines, electronic books Looking for a job or sending/submitting a job application Participating in professional networks Managing personal/own homepage Uploading self/user-created content to a website to be shared Blogging: maintaining or adding contents to a blog Posting opinions on civic or political issues via websites that may be created by any individual or organization Taking part in online consultations or voting to define civic or political issues Using storage space on the Internet to save documents, pictures, music, video or other files Using software run over the Internet for editing text documents, spreadsheets or presentations HH10 HH11 Proportion of individuals using a mobile cellular telephone Proportion of households with Internet, by type of service: Fixed (wired) narrowband network Fixed (wired) broadband network Terrestrial fixed (wireless) broadband network Manual for Measuring ICT Access and Use by Households and Individuals Annex 1.
Core list of ICT Indicators (revised 2013) 149 Satellite broadband network Mobile broadband network (at least 3G, e.g.

UMTS) via a handset Mobile broadband network (at least 3G, e.g.
UMTS) via a card or USB modem HH12 Proportion of individuals using the Internet, by frequency: At least once a day At least once a week but not every day Less than once a week HH13 Proportion of households with multichannel television, by type: Cable TV (CATV) Direct-to-home (DTH) satellite services Internet-protocol TV (IPTV) Digital terrestrial TV (DTT) HH14 Barriers to household Internet access: Do not need the Internet Have access to the Internet elsewhere Lack of confidence, knowledge or skills to use the Internet Cost of the equipment is too high Cost of the service is too high Privacy or security concerns Internet service is not available in the area Internet service is available but it does not correspond to household needs Cultural reasons HH15 Individuals with ICT skills, by type of skills: Copying or moving a file or folder Using copy and paste tools to duplicate or move information within a document Sending e-mails with attached files Using basic arithmetic formulae in a spreadsheet Connecting and installing new devices Finding, downloading, installing and configuring software Creating electronic presentations with presentation software Transferring files between a computer and other devices Writing a computer program using a specialized programming language HH16 Household expenditure on ICT: Telephone and telefax equipment (COICOP 08.2.0) Telephone and telefax services (COICOP 08.3.0) Equipment for the reception, recording and reproduction of sound and picture (COICOP 09.1.1) Information processing equipment (COICOP 09.1.3) Repair of audio-visual, photographic and information processing equipment (COICOP 09.1.5) Manual for Measuring ICT Access and Use by Households and Individuals 150 Annex 1.
Core list of ICT Indicators (revised 2013) Core indicators on use of ICT by businesses B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 Proportion of businesses using computers Proportion of persons employed routinely using computers Proportion of businesses using the Internet Proportion of persons employed routinely using the Internet Proportion of businesses with a web presence Proportion of businesses with an intranet Proportion of businesses receiving orders over the Internet Proportion of businesses placing orders over the Internet Proportion of businesses using the Internet by type of access: Narrowband Fixed broadband Mobile broadband Proportion of businesses with a local area network (LAN) Proportion of businesses with an extranet Proportion of businesses using the Internet by type of activity: Sending or receiving e-mail Telephoning over the Internet/VoIP Posting information or instant messaging Getting information about goods or services Getting information from general government organizations Interacting with general government organizations Internet banking Accessing other financial services Providing customer services Delivering products online Internal or external recruitment Staff training Core indicators on the ICT (producing) sector ICT1 ICT2 Proportion of total business sector workforce involved in the ICT sector ICT sector share of gross value added Core indicators on international trade in ICT goods ICT3 ICT4 ICT goods imports as a percentage of total imports ICT goods exports as a percentage of total exports Manual for Measuring ICT Access and Use by Households and Individuals Annex 1.
Core list of ICT Indicators (revised 2013) 151 Core indicators on ICT in education ED1 ED2 ED3 ED4 Proportion of schools with a radio used for educational purposes (for ISCED 1-3) Proportion of schools with a television used for educational purposes (for ISCED 1-3) Proportion of schools with a telephone communication facility (for ISCED 1-3) Learners-to-computer ratio in schools with computer-assisted instruction (for ISCED 1-3) ED4bis Learners-to-computer ratio (for ISCED 1-3) ED5 Proportion of schools with Internet access (for ISCED 1-3): Any Internet access Access by fixed narrowband only Access by fixed broadband only Both fixed narrowband and broadband access ED6 ED7 ED8 EDR1 Proportion of learners who have access to the Internet at school (for ISCED 1-3) Proportion of learners enrolled at the post-secondary level in ICT-related fields (for ISCED levels 4-6) Proportion of ICT-qualified teachers in schools (for ISCED 1-3) Proportion of schools with electricity 176 (for ISCED 1-3) Core indicators on e-government EG1 EG2 EG3 EG4 EG5 EG6 EG7 Proportion of persons employed in central government organizations routinely using computers Proportion of persons employed in central government organizations routinely using the Internet Proportion of central government organizations with a local area network (LAN) Proportion of central government organizations with an intranet Proportion of central government organizations with Internet access, by type of access Narrowband Fixed (wired) broadband Wireless broadband Proportion of central government organizations with a web presence Selected Internet-based services available to citizens, by level of sophistication of service 176 Electricity is not an ICT commodity, but is an important prerequisite for using many ICTs, so is included as a reference indicator.
Studies reviewed by UIS reveal that lack of electricity is a significant barrier in many developing economies and monitoring trends of its provision is as relevant as monitoring the supply and use of ICT.

Manual for Measuring ICT Access and Use by Households and Individuals Annex 2.

Model questionnaire for measuring ICT access and use by households and individuals 153 Annex 2.
Model questionnaire for measuring ICT access and use by households and individuals The model questionnaire can be used in a stand-alone ICT household survey or as a module in an existing survey vehicle, for example, a multipurpose household survey.
If used as a module in an existing survey, it is likely that sections 1 and 3 (Household characteristics and Individual characteristics, respectively) would not be needed (or could be reduced) as such information is likely to be included elsewhere in the survey vehicle.

The model questionnaire is not an operational questionnaire that can be used directly in countries’ household surveys.
This is because countries conduct household ICT access and use surveys in different ways, each requiring their own types of survey instruments.

For instance, a questionnaire that is self-enumerated will look quite different from one designed for a telephone survey, which in turn will differ from a questionnaire used in face-to-face interviewing.
It is not expected that the structure, question wording or definitions that comprise the model questionnaire would be used unchanged (or literally translated) in national surveys.

However, it is important for comparability purposes that: • • Where questions are used, their meanings are preserved, and The logic is preserved to the extent that the same populations of households or individuals are asked each question.
Notes and instructions to questionnaire designers • • • • Where there is no ‘Go to’ direction in the model questionnaire, the respondent is asked the next question.

For questions 10, 11, 19, 21 and 23, country variations are: remove categories where items are not feasible; and add or split categories corresponding to country data requirements.

Care should be taken when adding or splitting categories that statistical bias is not introduced.
This could occur if the provision of alternative categories affects response.

Care should be taken when aggregating detailed subcategories of these questions to avoid double counting individuals who respond to more than one of the subcategories.

For multiple response questions (except for Q22), countries may ask about response categories as a series of yes/no questions, rather than a single 'list' question.

The method chosen will reflect the method of data collection e.g.
a telephone interview is more likely to use a series of yes/no questions, especially for the questions with a large number of response items.

For question 22, countries are able to add additional frequency categories if they wish to obtain finer level information.

Manual for Measuring ICT Access and Use by Households and Individuals 154 Annex 2.
Model questionnaire for measuring ICT access and use by households and individuals Model questionnaire for measuring ICT access and use by households and individuals Section 1: Household characteristics 1 Number of household members -This question is asked of all in-scope households.

-It includes members who are older or younger than any individual age scope used for the survey.

2 Are there any children aged under 15 years living in this household?
Yes No -This question is asked of all in-scope households.

Section 2: Household access to information and communication technology 3 Does this household have a radio?

Yes No -This question is asked of all in-scope households.
-A radio is defined as a device capable of receiving broadcast radio signals, using common frequencies, such as FM, AM, LW and SW. A radio may be a stand-alone device, or it may be integrated with another device, such as an alarm clock, an audio player, a mobile telephone or a computer.

-The equipment should be in working condition at the time of the survey.

4 Does this household have a television?

Yes No Go to Q6 -This question is asked of all in-scope households.
-A television (TV) is a device capable of receiving broadcast television signals, using popular access means such as over-the-air, cable and satellite.

A television set is typically a stand-alone device, but it may also be integrated with another device, such as a computer or a mobile telephone.

-The equipment should be in working condition at the time of the survey.

5 Does this household have any of the following television services?

Please tick all that apply.


Cable TV (CATV) -Multichannel programming delivered over a coaxial cable for viewing on television sets.

Internet-protocol TV (IPTV) -Multimedia services such as television/video/audio/text/graphics/data delivered over an IP-based network managed to support the required level of quality of service, quality of experience, security, interactivity and reliability; it does not include video accessed over the public Internet, for example, by streaming.
IPTV services are also generally aimed at viewing over a television set rather than a personal computer.

Direct-to-home (DTH) satellite services -TV services received via a satellite dish capable of receiving satellite television broadcasts.

Digital terrestrial TV (DTT) -The technological evolution from analogue terrestrial television, providing capability for significantly more channels.

Additional question notes -This question is asked of all in-scope households with a television.
-Record all multichannel services used by the household (that is, allow multiple responses).

-The TV service(s) selected should be working at the time of the survey.

Manual for Measuring ICT Access and Use by Households and Individuals Annex 2.

Model questionnaire for measuring ICT access and use by households and individuals 155 6 Does this household have a fixed telephone line?

Yes No -This question is asked of all in-scope households.
-A fixed telephone line refers to a telephone line connecting a customer's terminal equipment (e.g.

telephone set, facsimile machine) to the public switched telephone network (PSTN) and which has a dedicated port on a telephone exchange.

This term is synonymous with the terms main station or Direct Exchange Line (DEL) that are commonly used in telecommunication documents.

It may not be the same as an access line or a subscription.

-The equipment should be in working condition at the time of the survey.
7 Does this household have a mobile telephone?

Yes No -This question is asked of all in-scope households.

-A mobile (cellular) telephone refers to a portable telephone subscribing to a public mobile telephone service using cellular technology, which provides access to the PSTN.

This includes analogue and digital cellular systems and technologies such as IMT-2000 (3G) and IMT-Advanced.

Users of both post-paid subscriptions and pre-paid accounts are included.
-The equipment should be in working condition at the time of the survey.

8 Does this household have a computer (desktop, laptop, tablet or similar)?

Yes No -This question is asked of all in-scope households.

-The equipment should be in working condition at the time of the survey.

-A computer refers to a desktop computer, a laptop (portable) computer or a tablet (or similar handheld computer).
It does not include equipment with some embedded computing abilities, such as smart TV sets, and devices with telephony as their primary function, such as smartphones.

-Desktop: a computer that usually remains fixed in one place; normally the user is placed in front of it, behind the keyboard.
-Laptop (portable) computer: a computer that is small enough to carry and usually enables the same tasks as a desktop computer; it includes notebooks and netbooks but does not include tablets and similar handheld computers.

-Tablet (or similar handheld computer): a tablet is a computer that is integrated into a flat touch screen, operated by touching the screen rather than (or as well as) using a physical keyboard.

9 Does this household have Internet?


Yes No Go to Q11 -The Internet is a world-wide public computer network.

It provides access to a number of communication services including the World Wide Web and carries e-mail, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer - it may also be by mobile telephone, tablet, PDA, games machine, digital TV etc.).

-Access can be via a fixed or mobile network.


-An Internet connection in the household should be working at the time of the survey.

Manual for Measuring ICT Access and Use by Households and Individuals 156 Annex 2.

Model questionnaire for measuring ICT access and use by households and individuals 10 What type/s of Internet services are used for Internet access at home?

Please tick all that apply.
Fixed (wired) narrowband network, at advertised download speeds below 256 kbit/s: -Analogue modem (dial-up via standard telephone line) -ISDN (Integrated Services Digital Network) -DSL (Digital Subscriber Line) at advertised download speeds below 256 kbit/s -Other fixed (wired) narrowband with an advertised download speed of less than 256 kbit/s Fixed (wired) broadband network, at advertised download speeds of at least 256 kbit/s: -DSL (Digital Subscriber Line) at advertised download speeds of at least 256 kbit/s -Cable modem -High speed leased lines -Fibre-to-the-home/building -Powerline -Other fixed (wired) broadband Terrestrial fixed (wireless) broadband network, at advertised download speeds of at least 256 kbit/s: -WiMAX -Fixed CDMA Satellite broadband network (via a satellite connection), at advertised download speeds of at least 256 kbit/s Mobile broadband network (at least 3G, e.g.
UMTS) via a handset Mobile broadband network (at least 3G, e.g.

UMTS) via a card: -Integrated SIM card in a computer -USB modem Additional question notes -This question is asked of all in-scope households with the Internet at home.

-Record all Internet services used by the household (that is, allow multiple responses).

-The response categories need to be adapted by countries according to plans and services offered by operators, and terminologies that are more familiar to users.
-According to local context, additional information could be collected to better identify the correct type of access.

Go to Q12 11 Why does this household not have Internet access?

Please tick all that apply.

Do not need the Internet -Not useful, not interesting, lack of local content.
Have access to the Internet elsewhere Lack of confidence, knowledge or skills to use the Internet Cost of the equipment is too high Cost of the service is too high Privacy or security concerns Internet service is not available in the area Internet service is available but it does not correspond to household needs -For example, quality, speed.

Cultural reasons -For example, exposure to harmful content.
Additional question notes -This question is asked of all in-scope households which did not have the Internet at home.

-Record all reasons (that is, allow multiple responses).

Manual for Measuring ICT Access and Use by Households and Individuals Annex 2.

Model questionnaire for measuring ICT access and use by households and individuals 157 Section 3: Individual characteristics 12 Age (years) -This question is asked of all in-scope individuals.
13 Sex Male Female -This question is asked of all in-scope individuals.

14 Highest educational level.

Please tick one.

Primary education or lower Lower secondary education Upper secondary education or post-secondary non-tertiary education Tertiary Post-tertiary Additional question notes -This question is asked of all in-scope individuals.

-Only one educational level can be selected.


-Categories are based on UNESCO's International Standard Classification of Education (ISCED-A 2011), or the equivalent national classification.

15 Labour force status.

Please tick one.

Employee Self-employed -Includes employers, own-account workers, members of producers' cooperatives and contributing family workers.
Workers not classifiable by status -For whom insufficient relevant information is available, and/or who cannot be included in either of the preceding categories.

Unemployed Outside the labour force -Individuals who are not economically active: usually students (not in the workforce), people undertaking home duties only, and those who are retired or infirm.

Additional question notes -This question is asked of all in-scope individuals.

-Only one labour force status category can be selected.
Respondents should select the option that best describes their labour force status.

-If respondents tick either of the last two categories, they should go to Q17.

-Categories are based on the International Labour Organization's (ILO) International Classification of Status in Employment (ICSE-93), or the equivalent national classification, with additional categories for unemployed and outside the labour force .
16 Main occupation (please describe) ..………….................................................................................. -This question is asked of all in-scope individuals who are employed (employees, self-employed and workers not classifiable by status).

-Responses should be coded according to the 1-digit categories of the International Labour Organization's International Standard Classification of Occupations (ISCO 1988 or 2008), or the equivalent national classification.
Manual for Measuring ICT Access and Use by Households and Individuals 158 Annex 2.

Model questionnaire for measuring ICT access and use by households and individuals Section 4: Individual use of information and communication technology 17 Have you used a mobile telephone in the last three months?

Yes No -This question is asked of all in-scope individuals.

-Mobile telephone is defined in Q7.


-Use of a mobile telephone does not necessarily mean that the telephone is owned or paid for by the individual but should be reasonably available through work, a friend or family member, etc.

It excludes occasional use, for instance, borrowing a mobile telephone to make a call.

18 Have you used a computer (desktop, laptop, tablet or similar) from any location in the last three months?

Yes No Go to Q20 -This question is asked of all in-scope individuals.
-Computer is defined in Q8.

19 Which of the following computer-related activities have you carried out in the last three months?

Please tick all that apply.

Copying or moving a file or folder Using copy and paste tools to duplicate or move information within a document Sending e-mails with attached files -For example, a document, picture, video Using basic arithmetic formulas in a spreadsheet Connecting and installing new devices -For example, a modem, camera, printer.
Finding, downloading, installing and configuring software Creating electronic presentations with presentation software -Including text, images, sound, video or charts Transferring files between a computer and other devices Writing a computer program using a specialized programming language Additional question notes -This question is only asked of individuals who used a computer in the last three months.

-Record all activities (that is, allow multiple responses).
20 Have you used the Internet from any location in the last three months?

Yes No Go to end -This question is asked of all in-scope individuals (not only those who have used a computer).

-Internet is defined in Q9.

-Access can be via a fixed or mobile network.

-"Go to end" instruction.

If the respondent selects 'No', there are no more questions for the core ICT indicators.

The word "end" should be replaced with the appropriate location in national questionnaires.
Manual for Measuring ICT Access and Use by Households and Individuals Annex 2.

Model questionnaire for measuring ICT access and use by households and individuals 159 21 Where did you use the Internet in the last 12 months?

Please tick all that apply.

Home Work -Where a person’s workplace is located at his/her home, then he/she would answer yes to the home category only.
Place of education -applies only to students – teachers and others who work at a place of education would report ‘work’ as the place of Internet use; where a place of education is also made available as a location for general community Internet use, such use should be reported in the Community Internet access facility category.

Another person’s home -The home of a friend, relative or neighbour.
Community Internet access facility -Typically free of charge; includes Internet use at community facilities such as public libraries, publicly provided Internet kiosks, non-commercial telecentres, digital community centres, post offices, other government agencies; access is typically free and available to the general public.
Commercial Internet access facility -Typically not free of charge; includes Internet use at publicly available commercial facilities such as Internet or cybercafés, hotels, airports etc, where access is typically paid.

In mobility – use of the Internet while mobile -Via a mobile cellular telephone, including devices with mobile telephone functionality.

-Via other mobile access devices, e.g.

a laptop computer, tablet or other handheld device connected to a mobile phone network.
Other locations (please specify)………………...…………………………...……………............................. Additional question notes -This question is only asked of individuals who used the Internet in the last three months.

-Access via a mobile device should be classified to the appropriate location or to ‘in mobility’, that is, while mobile.

-Record all locations where individuals used the Internet (that is, allow multiple responses).
-Countries can replace the Community and/or Commercial Internet access facility categories with those that reflect the types of facilities available in their country.

22 How often did you typically use the Internet during the last three months (from any location)?

Please tick one.

At least once a day -Once a working day for respondents who only (or most frequently) use the Internet from work or school etc.
At least once a week but not every day Less than once a week Additional question notes -This question is only asked of individuals who used the Internet in the last three months.

-Only one frequency can be selected.

-The question refers to a typical period; therefore, respondents should ignore weekends (if they only use the Internet from work or school) and breaks from their usual routine, such as holidays.

Manual for Measuring ICT Access and Use by Households and Individuals 160 Annex 2.
Model questionnaire for measuring ICT access and use by households and individuals 23 For which of the following activities did you use the Internet for private purposes in the last 12 months (from any location)?

Please tick all that apply.

Getting information about goods or services Seeking health information -On injury, disease, nutrition etc.
Making an appointment with a health practitioner via a website Getting information from general government organizations Interacting with general government organizations -Downloading/requesting forms, completing/lodging forms online, making online payments and purchasing from government organizations etc.

General government organizations should be consistent with the SNA93 (2008 revision) concept of general government.
According to the SNA “… the principal functions of government are to assume responsibility for the provision of goods and services to the community or to individual households and to finance their provision out of taxation or other incomes; to redistribute income and wealth by means of transfers; and to engage in non-market production.” (General) government organizations include central, state and local government units.
Sending or receiving e-mail Telephoning over the Internet/VoIP -Using Skype, iTalk, etc.

; includes video calls via webcam.

Participating in social networks -Creating user profile, posting messages or other contributions to Facebook, Twitter etc.
Accessing chat sites, blogs, newsgroups or online discussions Purchasing or ordering goods or services -Purchase orders placed via the Internet whether or not payment was made online; excludes orders that were cancelled or not completed; includes purchasing of products such as music, travel and accommodation via the Internet.

Selling goods or services -Via eBay, Mercado libre, Facebook etc.
Using services related to travel or travel-related accommodation Internet banking Includes electronic transactions with a bank for payment, transfers, etc.

or for looking up account information; excludes electronic transactions via the Internet for other types of financial services such as share purchases, financial services and insurance.

Doing a formal online course (in any subject) Consulting wikis (Wikipedia etc.
), online encyclopaedias or other websites for formal learning purposes Listening to web radio -Either paid or free of charge.

Watching web television -Either paid or free of charge.

Manual for Measuring ICT Access and Use by Households and Individuals Annex 2.

Model questionnaire for measuring ICT access and use by households and individuals 161 23 (Cont.)

For which of the following activities did you use the Internet for private purposes in the last 12 months (from any location)?
Please tick all that apply.

Streaming or downloading images, movies, videos or music; playing or downloading games -Either paid or free of charge.

Downloading software or applications -Includes patches and upgrades, either paid or free of charge.

Reading or downloading online newspapers or magazines, electronic books -Includes accessing news websites, either paid or free of charge; includes subscriptions to online news services.
Looking for a job or sending/submitting a job application -Includes searching specific web sites for a job; sending/submitting an application online.

Participating in professional networks -These are also seen in the broader context of social networking and have the same requirement of profile creation, contributing through messaging or chat, or uploading text or audio-visual content files.

-Examples of professional or business networks are LinkedIn and Xing.
Managing personal/own homepage Uploading self/user-created content to a website to be shared -Text, images, photos, videos, music, software, etc.

Blogging: maintaining or adding contents to a blog Posting opinions on civic or political issues via websites -Blogs, social networks, etc.

that may be created by any individual or organization.

Taking part in online consultations or voting to define civic or political issues -Urban planning, signing a petition etc.
Using storage space on the Internet to save documents, pictures, music, video or other files -For example, Google Drive, Dropbox, Windows Skydrive, iCloud, Amazon Cloud Drive.

Using software run over the Internet for editing text documents, spreadsheets or presentations Other activities (please specify)…………………………..................................……………...…………….

Additional question notes -This question is only asked of individuals who used the Internet in the last three months.
-Record all Internet activities undertaken (that is, allow multiple responses).

Activities are not mutually exclusive, that is, there is overlap between some categories.

-"Private purposes" means not as part of one's current job or business.

Manual for Measuring ICT Access and Use by Households and Individuals Annex 3.

Examples of imputation and weighting 163 Annex 3.


Examples of imputation and weighting Imputation for missing data The following table shows raw data from a survey on ICT use by households.

Each row represents data from one survey record.

‘Missing’ refers to item non-response.

The statistician is interested in imputing a value for the missing data ‘use of Internet’ for records #1, #4 and #6.
Record ID Access to Internet (household) Education level (individual) Use of Internet (individual) #1 #2 #3 #4 #5 #6 #7 #8 No No Yes Yes Yes Yes No No Primary Primary Tertiary Secondary Tertiary Tertiary Secondary Primary Missing No Yes Missing Yes Missing Yes No The statistician can select different rules for imputation as follow: Rule 1: A deterministic rule that imputes ‘Yes’ to all missing values for the item ‘Use of Internet’ if the household has access to Internet and ‘No’ otherwise.
Rule 2: A deterministic rule that imputes ‘Yes’ to all missing values for the item ‘Use of Internet’ if the household has access to Internet and the level of education of the individual is ‘Tertiary’, and ‘No’ otherwise.

Rule 3: A rule that imputes the most frequent value of the item ‘Use of Internet’ in the set of records with the same value for ‘Access to Internet’.
Rule 4: A rule that imputes the most frequent value of the item ‘Use of Internet’ in the set of records with the same value for ‘Level of education’.

The application of the above rules is shown below.

Manual for Measuring ICT Access and Use by Households and Individuals 164 Annex 3.
Examples of imputation and weighting Rule Record #1 Record #4 Record #6 Imputed value for ‘use of Internet’ 1 2 3 4 No No Yes No Yes Yes No (there are 2 ‘No’ and 1 ‘Yes’ responses in the set of records with no access to Internet) Yes (there are 2 ‘Yes’ and 0 ‘No’ responses in the set of records with access to Internet) Yes (there are 2 ‘Yes’ and 0 ‘No’ responses in the set of records with access to Internet) No (there are 2 ‘No’ and 0 ‘Yes’ responses in the set of records with Primary education) Yes (there is 1 ‘Yes’ and 0 ‘No’ responses in the set of records with Secondary education) Yes (there are 2 ‘Yes’ and 0 ‘No’ responses in the set of records with Tertiary education) It should be noted that the selection of one or other rule will produce biases in the final estimates.
In general, methods based on the replacement of a missing value by a modal, median or average value of the same variable in a set of ‘similar’ records reduces the bias, but also artificially reduces the variance of the population.

Weighting records Suppose that a population of households has been sampled, producing a stratified random sample of 9 units from strata A and B as follows: Stratum Population size Sample size A B 3,000 1,000 5 4 407.
The results of the survey provide the following records: Household ID Stratum Access to computer (household) Access to Internet (household) #1 #2 #3 #4 #5 #6 #7 #8 #9 A A B A B A B A B No No Yes Yes Yes Yes No Yes Yes No No No Yes Yes Yes No No No Manual for Measuring ICT Access and Use by Households and Individuals Annex 3.

Examples of imputation and weighting 165 The sampling weight of each household in A is equal to 3,000 /5 = 600, while for one in B, it is 1,000/4 = 250.
Population estimates for the proportion of households with access to a computer are calculated by weighting each household in A by 600 and each one in B by 250.
This gives the following statistics: Stratum Number of households with access to computer (unweighted) Number of households with access to Internet (unweighted) Number of households with access to computer (weighted) Number of households with access to Internet (weighted) A B 3 3 2 1 1,800 750 1,200 250 The weighted proportions of households with a computer and access to the Internet are: Total number of households Stratum Number of households with access to computer (weighted) Number of households with access to Internet (weighted) Proportion of households with access to computer (weighted) Proportion of households with access to Internet (weighted) A B 3,000 1,800 1,200 1,800/3,000 = 60% 1,200/3,000 = 40% 1,000 750 250 750/1,000 = 75% 250/1,000 = 25% While, in each stratum, the weighted estimate is equivalent to the estimate based on the sample proportion, for the total population, the estimates are: Population Total number of households Number of households with access to computer (weighted) Number of households with access to Internet (weighted) Proportion of households with access to computer Proportion of households with access to Internet (weighted) A+B 4,000 1,800+750 = 2,550 1,200+250 = 1,450 2,550/4,000 = 63.75% 1,450/4,000 = 36.25% Manual for Measuring ICT Access and Use by Households and Individuals Annex 4.
ITU Questionnaire on ICT Access and Use by Households and Individuals 167 Annex 4.

ITU Questionnaire on Information and Communication Technology (ICT) Access and Use by Households and Individuals Annex 4 shows the data items that ITU will collect from countries from 2014.

They are based on the core indicators presented in this manual.
Manual for Measuring ICT Access and Use by Households and Individuals 168 ICT Access by urban/rural and household composition Urban/Rural Household composition All households Urban Rural has children under 15 does not have children under 15 Total Urban Rural Total Urban Rural No.
Indicator HH1 HH2 HH3 Number of households with a radio Number of households with a television Number of households with any telephone (fixed and/or mobile) Number of households with fixed telephone only Number of households with mobile cellular telephone only Number of households with both fixed and mobile telephone HH4 Number of households with a computer (all types of computer) Desktop Laptop (portable) computer Tablet (or similar handheld computer) HH6 Number of households with Internet HH11 Number of households with Internet, by type of service Fixed (wired) narrowband network Fixed (wired) broadband network Terrestrial fixed (wireless) broadband network Satellite broadband network Mobile broadband network via a handset Mobile broadband network via a card or USB modem HH13 Number of households with multichannel television by type Cable TV (CATV) Direct-to-home (DTH) satellite services Internet-protocol TV (IPTV) 1 6 8 A n n e x 4 .
No.

Indicator Digital terrestrial TV (DTT) HH14 Reasons for not having Internet access (i.e.
Barriers) (number of households without Internet access) Do not need the Internet (not useful, not interesting, lack of local content) Have access to the Internet elsewhere Lack of confidence, knowledge or skills to use the Internet Cost of the equipment too high Cost of the service too high Privacy or security concerns Internet service is not available in the area Internet service is available but it does not correspond to household needs (e.g.

quality, speed) Cultural reasons (e.g.
exposure to harmful content) HH16 Total household expenditure on ICT Telephone and telefax equipment (COICOP 08.2.0) Telephone and telefax services, includes Internet (COICOP 08.3.0) Equipment for the reception, recording and reproduction of sound and picture (COICOP 09.1.1) Information processing equipment (COICOP 09.1.3) Repair of audio-visual, photographic and information processing equipment (COICOP 09.1.5) HHR1 Number of households with electricity Urban/Rural Household composition All households Urban Rural has children under 15 does not have children under 15 Total Urban Rural Total Urban Rural 169 A n n e x 4 .
170 ICT Usage by sex and urban/rural No.
HH5 HH7 HH8 Indicators Number of individuals using a computer (from any location) in the last three months (all types of computer) Desktop Laptop (portable) computer Tablet (or similar handheld computer) Number of individuals using the Internet (from any location) in the last three months Number of individuals using the Internet in the last three months, by location At home At work At place of education At another person's home At community Internet access facility At commercial Internet access facility In mobility (while mobile) Via a mobile cellular telephone Via other mobile access devices HH9 Number of individuals using the Internet in the last three months, by type of activity Getting information about goods or services Seeking health information (on injury, disease, nutrition, etc.)
Making an appointment with a health practitioner via a website Getting information from general government organizations Interacting with general government organizations Sending or receiving e-mail Telephoning over the Internet/VoIP Participating in social networks Accessing chat sites, blogs, newsgroups or online discussions Purchasing or ordering goods or services Selling goods or services All individuals Sex Urban Rural Male Female Total Male Female Total Male Female 1 7 0 A n n e x 4 .
No.
Indicators All individuals Sex Urban Rural Male Female Total Male Female Total Male Female 171 Using services related to travel or travel-related accommodation Internet banking Consulting wikis, online encyclopaedias or other websites for formal learning purposes Watching web television Streaming or downloading images, movies, videos or music, playing or downloading games Downloading software or applications Reading or downloading online newspapers or magazines, electronic books Looking for a job or sending/submitting a job application For a complete list of activities included in the ITU questionnaire see p.57.
Number of individuals using a mobile cellular telephone in the last three months Number of individuals using the Internet (from any location) in the last three months, by frequency HH10 HH12 At least once a day At least once a week but not every day Less than once a week HH15 Number of individuals with ICT skills, by type of skills Copying or moving a file or folder Using copy and paste tools to duplicate or move information within a document Sending e-mails with attached files (e.g.
document, picture, video) Using basic arithmetic formulas in a spreadsheet Connecting and installing new devices (e.g.

a modem, camera, printer) Finding, downloading, installing and configuring software Creating electronic presentations with presentation software (including images, sound, video or charts) Transferring files between a computer and other devices Writing a computer program using a specialized programming language A n n e x 4 .
172 ICT Usage by age and sex No.
HH5 Indicators Number of individuals using a computer (from any location) in the last three months Desktop Laptop (portable) computer Tablet (or similar handheld computer) HH7 HH8 Number of individuals using the Internet (from any location) in the last three months Number of individuals using the Internet in the last three months, by location At home At work At place of education At another person's home At community Internet access facility At commercial Internet access facility In mobility (while mobile) Via a mobile cellular telephone Via other mobile access devices Number of individuals using the Internet in the last three months, by type of activity HH9 Getting information about goods or services Seeking health information (on injury, disease, nutrition, etc.)
Making an appointment with a health practitioner via a website Getting information from general government organizations Interacting with general government organizations Sending or receiving e-mail Telephoning over the Internet/VoIP Participating in social networks Accessing chat sites, blogs, newsgroups or online discussions Purchasing or ordering goods or services Selling goods or services Age less than 15 Age 15-24 Age 25-74 Age 75 and over Total Male Female Total Male Female Total Male Female Total Male Female 1 7 2 A n n e x 4 .
No.
Indicators Total Male Female Total Male Female Total Male Female Total Male Female Age less than 15 Age 15-24 Age 25-74 Age 75 and over 173 Using services related to travel or travel- related accommodation Internet banking Watching web television Streaming or downloading images, movies, videos or music, playing or downloading games Downloading software or applications Reading or downloading online newspapers or magazines, electronic books Looking for a job or sending/submitting a job application For a complete list of activities included in the ITU questionnaire see p.57.
Number of individuals using a mobile cellular telephone in the last three months Number of individuals using the Internet (from any location) in the last three months, by frequency At least once a day At least once a week but not every day Less than once a week HH10 HH12 HH15 Number of individuals with ICT skills by type Copying or moving a file or folder Using copy and paste tools to duplicate or move information within a document Sending e-mails with attached files (e.g.
document, picture, video) Using basic arithmetic formulas in a spreadsheet Connecting and installing new devices (e.g.

a modem, camera, printer) Finding, downloading, installing and configuring software Creating electronic presentations with presentation software (including images, sound, video or charts) Transferring files between a computer and other devices Writing a computer program using a specialized programming language A n n e x 4 .
174 ICT Usage by highest education level attained* and sex No.
Indicators Total Male Female Total Male Female Total Male Female Total Male Female Primary education or lower (ISCED 0,1) Lower secondary education (ISCED 2) Upper secondary or post- secondary non-tertiary (ISCED 3,4) Tertiary and post-tertiary education (ISCED 5,6,7,8) HH5 Number of individuals using a computer (from any location) in the last three months Desktop Laptop (portable) computer Tablet (or similar handheld computer) HH7 HH8 Number of individuals using the Internet (from any location) in the last three months Number of individuals using the Internet in the last three months, by location At home At work At place of education At another person's home At community Internet access facility At commercial Internet access facility In mobility (while mobile) Via a mobile cellular telephone Via other mobile access devices HH9 Number of individuals using the Internet in the last three months, by type of activity Getting information about goods or services Seeking health information (on injury, disease, nutrition, etc.)
Making an appointment with a health practitioner via a website Getting information from general government organizations Interacting with general government organizations Sending or receiving e-mail Telephoning over the Internet/VoIP Participating in social networks Accessing chat sites, blogs, newsgroups or online discussions 1 7 4 A n n e x 4 .

 No.
Indicators Total Male Female Total Male Female Total Male Female Total Male Female Primary education or lower (ISCED 0,1) Lower secondary education (ISCED 2) Upper secondary or post- secondary non-tertiary (ISCED 3,4) Tertiary and post-tertiary education (ISCED 5,6,7,8) 175 Purchasing or ordering goods or services Selling goods or services Internet banking Consulting wikis, online encyclopaedias or other websites for formal learning purposes Streaming or downloading images, movies, videos or music, playing or downloading games Downloading software or applications Reading or downloading online newspapers or magazines, electronic books Looking for a job or sending/submitting a job application For a complete list of activities included in the ITU questionnaire see p.57.
HH10 Number of individuals using a mobile cellular telephone in the last three months HH12 Number of individuals using the Internet (from any location) in the last three months, by frequency At least once a day At least once a week but not every day Less than once a week HH15 Number of individuals with ICT skills by type Copying or moving a file or folder Sending e-mails with attached files (e.g.
document, picture, video) Finding, downloading, installing and configuring software Writing a computer program using a specialized programming language For a complete list of skills included in the ITU questionnaire see p.69.

* Highest educational level that the person has completed.

That is, the person has received a degree or certificate.

A n n e x 4 .
176 ICT Usage by labour force status and sex Employee Self-employed Workers not classifiable by status Outside the labour force Unemployed Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female No.
HH5 Indicators Number of individuals using a computer (from any location) in the last three months HH7 HH8 Desktop Laptop (portable) computer Tablet (or similar handheld computer) Number of individuals using the Internet (from any location) in the last three months Number of individuals using the Internet in the last three months, by location At home At work At place of education At another person's home At community Internet access facility At commercial Internet access facility In mobility (while mobile) Via a mobile cellular telephone Via other mobile access devices HH9 Number of individuals using the Internet in the last three months, by type of activity Getting information about goods or services Seeking health information (on injury, disease, nutrition, etc.)
Making an appointment with a health practitioner via a website Getting information from general government organizations 1 7 6 A n n e x 4 .

 No.
Indicators Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Employee Self-employed Workers not classifiable by status Outside the labour force Unemployed 177 Interacting with general government organizations Sending or receiving e-mail Telephoning over the Internet/VoIP Participating in social networks Accessing chat sites, blogs, newsgroups or online discussions Purchasing or ordering goods or services Selling goods or services Using services related to travel or travel-related accommodation Internet banking Doing a formal online course Consulting wikis, online encyclopaedias or other websites for formal learning purposes Listening to web radio Watching web television Streaming or downloading images, movies, videos or music, playing or downloading games Downloading software or applications Reading or downloading online newspapers or magazines, electronic books Looking for a job or sending/submitting a job application Participating in professional networks Managing personal/own homepage A n n e x 4 .
178 No.
Indicators Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Employee Self-employed Workers not classifiable by status Outside the labour force Unemployed Uploading self/user-created content to a website to be shared For a complete list of activities included in the ITU questionnaire see p.57.
HH10 Number of individuals using a mobile cellular telephone in the last three months HH12 Number of individuals using the Internet (from any location) in the last three months, by frequency At least once a day At least once a week but not every day Less than once a week HH15 Number page of individuals with ICT skills by type Copying or moving a file or folder Using copy and paste tools to duplicate or move information within a document Sending e-mails with attached files (e.g.
document, picture, video) Using basic arithmetic formulas in a spreadsheet Connecting and installing new devices (e.g.

a modem, camera, printer) Finding, downloading, installing and configuring software Creating electronic presentations with presentation software (including images, sound, video or charts) Transferring files between a computer and other devices Writing a computer program using a specialized programming language 1 7 8 A n n e x 4 .
ICT Usage by occupation No.
Indicator All individuals HH5 Number of individuals using a computer (from any location) in the last three months Desktop Laptop (portable) computer Tablet (or similar handheld computer) HH7 HH8 Number of individuals using the Internet (from any location) in the last three months Number of individuals using the Internet in the last three months, by location At home At work At place of education At another person's home At community Internet access facility At commercial Internet access facility In mobility (while mobile) Via a mobile cellular telephone Via other mobile access devices HH9 Number of individuals using the Internet in the last three months, by type of activity Getting information about goods or services Seeking health information (on injury, disease, nutrition, etc.)
Making an appointment with a health practitioner via a website Getting information from general government organizations Interacting with general government organizations Sending or receiving e-mail 179 legislators, senior officials and managers professionals technicians and associate professionals clerks service workers and shop and market sales workers skilled agricultural and fishery workers craft and related trades workers armed forces A n n e x 4 .
180 No.
Indicator All individuals legislators, senior officials and managers professionals technicians and associate professionals clerks service workers and shop and market sales workers skilled agricultural and fishery workers craft and related trades workers armed forces Telephoning over the Internet/VoIP Participating in social networks Accessing chat sites, blogs, newsgroups or online discussions Purchasing or ordering goods or services Selling goods or services Using services related to travel or travel- related accommodation Internet banking Doing a formal online course Consulting wikis, online encyclopaedias or other websites for formal learning purposes Listening to web radio Watching web television Streaming or downloading images, movies, videos or music, playing or downloading games Downloading software or applications Reading or downloading online newspapers or magazines, electronic books Looking for a job or sending/submitting a job application Participating in professional networks Managing personal/own homepage Uploading self/user-created content to a website to be shared Blogging: maintaining or adding contents to a blog Posting opinions on civic or political issues via websites that may be created by any individual or organization Taking part in online consultations or voting to define civic or political issues 1 8 0 A n n e x 4 .
No.
Indicator All individuals legislators, senior officials and managers professionals technicians and associate professionals clerks service workers and shop and market sales workers skilled agricultural and fishery workers craft and related trades workers armed forces 181 Using storage space on the Internet to save documents, pictures, music, video or other files Using software run over the Internet for editing text documents, spreadsheets or presentations HH10 Number of individuals using a mobile cellular telephone in the last three months HH12 Number of individuals using the Internet (from any location) in the last three months, by frequency At least once a day At least once a week but not every day Less than once a week HH15 Number of individuals with ICT skills by type Copying or moving a file or folder Using copy and paste tools to duplicate or move information within a document Sending e-mails with attached files (e.g.
document, picture, video) Using basic arithmetic formulas in a spreadsheet Connecting and installing new devices (e.g.

a modem, camera, printer) Finding, downloading, installing and configuring software Creating electronic presentations with presentation software (including images, sound, video or charts) Transferring files between a computer and other devices Writing a computer program using a specialized programming language A n n e x 4 .
Annex 5.

Glossary of terms and abbreviations 183 Annex 5.


Glossary of terms and abbreviations Term or abbreviation 3G mobile cellular network Accuracy ADSL Area sampling Blog (short for Web log) Broadband Notes Third generation of mobile communications technology, a group of mobile technologies that have been approved by ITU as IMT-2000.

These technologies allow voice, data and video communications.
Currently, five standards have been specified as IMT-2000 based on various combinations of mobile technologies: CDMA Direct Spread (WCDMA), CDMA Multi-Carrier (CDMA2000), CDMA Time division (TD-CDMA), TDMA Single-Carrier and FDMA/TDMA and OFDMA TDD WMAN (IEEE 802.16).

Denotes the closeness of computations or estimates to the exact or true values.
Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).

Asymmetric digital subscriber line, a modem technology that converts twisted-pair telephone lines into access paths for multimedia and high- speed data communications.
The bit rates transmitted in both directions are different.

Source ITU (2011) Eurostat Standard Quality Report (2003) ITU (2011) Selection of geographical area units that comprise sampling frame (may include selection of area segments, defined as mapped subdivisions of administrative area).
UNSD (2005b) A blog (a truncation of the expression web log) is a discussion or informational site published on the World Wide Web and consisting of discrete entries ("posts") typically displayed in reverse chronological order (the most recent post appears first).

Wikipedia A general term meaning a telecommunications signal or device of greater bandwidth, in some sense, than another standard or usual signal or device; the broader the band, the greater the capacity for traffic).
In data communications, the term refers to a data transmission rate of at least 256 kbit/s.

ITU (2011) Cable modem A cable modem is a layer two termination device that terminates the customer end of the J.112 (or J.122) connection.
ITU (2011) Cable TV (CATV) Multichannel programming delivered over a coaxial cable for viewing on television sets CAPI CATI Computer assisted personal interviewing Computer assisted telephoning interviewing Cluster sampling Sampling in which next-to-last stage is geographically-defined unit such as census enumeration area (EA).

Clustering; clustered Refers to tendency of sample units – persons or households – to have similar characteristics.
This manual, HH13 UNSD (2005b) UNSD (2005b) Commercial Internet access facility Enables Internet use at publicly available commercial facilities such as Internet or cyber cafés, hotels, airports etc., where access is typically paid (i.e.

not free of charge).


This manual, HH8 Community Internet access facility Enables Internet use at community facilities such as public libraries, publicly provided Internet kiosks, non-commercial telecentres, digital community centres, post offices, other government agencies; access is typically free and is available to the general public.

This manual, HH8 Complex sample design Refers to use of multiple stages, clustering and stratification in household survey samples, as opposed to simple random sampling.
UNSD (2005b) Manual for Measuring ICT Access and Use by Households and Individuals 184 Annex 5.

Glossary of terms and abbreviations Confidence level Design effect – deff Describes degree of statistical confidence with which precision or margin of error around the survey estimate is obtained, 95 per cent generally being regarded as the standard.
Ratio of variance from complex sample design to simple random sample of same sample size; deft is ratio of standard errors; sometimes referred to as clustering effect though deff includes effects of stratification as well as clustering.

Desktop computer A computer that usually remains fixed in one place.

Normally the user is placed in front of it, behind the keyboard.
Dial-up Internet access Uses an (analogue) modem and fixed telephone line to connect to the Internet; it requires that the modem dial a telephone number when Internet access is needed.
Digital terrestrial TV (DTT) The technological evolution from analogue terrestrial television, providing capability for significantly more channels Direct-to-home (DTH) satellite services Television services received via a satellite dish capable of receiving satellite television broadcasts DQAF DSL Data Quality Assessment Framework (IMF) Digital subscriber line/s, a technology for bringing high-bandwidth information to homes and small businesses over ordinary copper telephone lines EU European Union Fixed (wired) broadband network Refers to technologies at advertised download speeds of at least 256 kbit/s, such as DSL, cable modem, high speed leased lines, fibre-to-the- home/building, powerline and other fixed (wired) broadband.
Fixed (wired) narrowband network Fixed telephone line General government organizations Includes analogue modem (dial-up via standard telephone line), ISDN (Integrated Services Digital Network), DSL (Digital Subscriber Line) at advertised download speeds below 256 kbit/s, and other forms of access with an advertised download speed of less than 256 kbit/s.

A telephone line connecting a customer's terminal equipment (e.g.
telephone set, facsimile machine) to the public switched telephone network (PSTN) and which has a dedicated port on a telephone exchange.

This term is synonymous with the terms main station or Direct Exchange Line (DEL) that are commonly used in telecommunication documents.

It may not be the same as an access line or a subscription.

Are defined per the SNA93 (2008 revision) concept of general government.
According to the SNA "… the principal functions of government are to assume responsibility for the provision of goods and services to the community or to individual households and to finance their provision out of taxation or other incomes; to redistribute income and wealth by means of transfers; and to engage in non-market production."

(General) government organizations include central, state and local government units.)
Handheld computer A small computer including a personal digital assistants (PDA), also known as a palmtop computer.

Homepage Household HTML ICT ILO A home page, index page, or main page is a page on a website.

For the purposes of the Manual, a household consists of one or more people, who may or may not be related to each other; share accommodation; and make common provision for food.
Hypertext markup language Information and communication technology International Labour Organization UNSD (2005b) UNSD (2005b) This manual, HH4 ITU (2011) This manual, HH13 This manual, HH13 ITU (2011) This manual, HH11 This manual, HH11 This manual, HH3 This manual, HH9 This manual, HH4 Wikipedia This manual, Chapter 7 Manual for Measuring ICT Access and Use by Households and Individuals Annex 5.
Glossary of terms and abbreviations 185 This manual, HH8 This manual, HH6 This manual, HH13 In mobility (Internet use) Use of the Internet while mobile, via a mobile cellular telephone (including devices with mobile telephone functionality) or other mobile access devices, for example, a laptop computer, tablet or other handheld device connected to a mobile phone network.
Internet Internet-protocol TV (IPTV) IP ISDN ISP IT ITU kbit/s (or Kbit/s or kbps) Laptop (portable) computer Master sample Mobile (cellular) telephone A worldwide public computer network.

It provides access to a number of communication services including the World Wide Web and carries e- mail, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer – it may also be by mobile phone, PDA, games machine, digital TV etc.).
Access can be via a fixed or mobile network.

Multimedia services such as television/video/audio/text/graphics/data delivered over an IP-based network managed to support the required level of quality of service, quality of experience, security, interactivity and reliability; it does not include video accessed over the public Internet, for example, by streaming.

IPTV services are also generally aimed at viewing over a television set rather than a personal computer.
Internet protocol Integrated services digital network, a network that provides digital connections between user-network interfaces.

ITU (2011) Internet service provider Information technology International Telecommunication Union Kilobits per second (1 kilobit per second=one thousand bits per second).

A kilobit is 1,024 bits.

A bit expresses a 1 or a 0 in a binary numeral, or a true or false logical condition.
ITU (2011) and ABS (2007) A computer that is small enough to carry and usually enables the same tasks as a desktop computer.

It includes notebooks and netbooks but does not include tablets and similar handheld computers.

A supersample intended to be used for multiple surveys and/or multiple rounds of the same survey, usually over 10-year time frame.

A portable telephone subscribing to a public mobile telephone service using cellular technology, which provides access to the PSTN.
This includes analogue and digital cellular systems and technologies such as IMT-2000 (3G) and IMT-Advanced.

Users of both post-paid subscriptions and pre-paid accounts are included.

This manual, HH4 UNSD (2005b) This manual, HH3, HH10 Mobile broadband network via a card or USB modem Mobile broadband network via a handset Mobile broadband network (at least 3G, e.g.

UMTS) via a card (e.g.

integrated SIM card in a computer) or USB modem.

Mobile broadband network (at least 3G, e.g.


UMTS) via a handset Modem Modulator-demodulator, a device or program that enables a computer to transmit data over, for example, telephone or cable lines.

Non-sampling error Bias in survey estimate arising from errors in design and implementation; refers to accuracy or validity of an estimate as opposed to its reliability or precision.
NSDS NSO OCR OECD OSILAC National strategy for the development of statistics (PARIS21) National statistical office Optical character recognition Organisation for Economic Co-operation and Development Observatory for the Information Society in Latin America and the Caribbean This manual, HH11 This manual, HH11 This manual, HH11 UNSD (2005b) Manual for Measuring ICT Access and Use by Households and Individuals 186 Annex 5.
Glossary of terms and abbreviations Partnership Partnership on Measuring ICT for Development PDA Personal digital assistant Primary sampling unit, PSU Geographically-defined administrative unit selected at first stage of sampling UNSD (2005b) Probability sampling Selection methodology whereby each population unit (person, household, etc.)

has known, non-zero chance of inclusion in the sample.
UNSD (2005b) Radio A device capable of receiving broadcast radio signals, using common frequencies, such as FM, AM, LW and SW. A radio may be a stand-alone device, or it may be integrated with another device, such as an alarm clock, an audio player, a mobile telephone or a computer.

Reliability (precision, margin of error) Refers to degree of sampling error associated with a given survey estimate.

RSE Relative standard error (coefficient of variation), standard error as percentage of survey estimate, i.e.
standard error divided by estimate.

Sample frame(s) Set of materials from which sample is actually selected, such as a list or set of areas Sample size Number of units (households or persons) selected This manual, HH1 UNSD (2005b) UNSD (2005b) UNSD (2005b) UNSD (2005b) Sampling error (standard error) Random error in survey estimate due to the fact that a sample rather than entire population is surveyed; square root of sampling variance.
UNSD (2005b) Selecting sample in (generally) two time periods, with second phase typically a subsample of first-phase sample; not to be confused with trend sampling (see below).

UNSD (2005b) Sampling in phases; also known as double sampling or post- stratified sampling Sampling in stages Means by which sample of administrative areas and households/persons is chosen in successive stages to pinpoint geographic locations where survey is conducted.
Sampling variance Square of standard error or sampling error Satellite broadband network Satellite broadband network (via a satellite connection), at advertised download speeds of at least 256 kbit/s Segment A delineated, mapped subdivision of a larger cluster UNSD (2005b) UNSD (2005b) This manual, HH11 UNSD (2005b) SNA System of National Accounts Social network/networking Social networking can be distinguished from other communication and content activities by the aspect of creating a profile on certain websites.
Eurostat (2013) Stratified sampling Technique of organizing sample frame into subgroupings that are internally homogeneous and externally heterogeneous to ensure sample selection is spread properly across important population subgroups.

Systematic sampling Selection from a list, using a random start and predetermined selection interval, successively applied.

Tablet A computer that is integrated into a flat touch screen, operated by touching the screen rather than (or as well as) using a physical keyboard.
UNSD (2005b) UNSD (2005b) This manual, HH4 Target population Definition of population intended to be covered by survey; also known as coverage universe.

UNSD (2005b) Television A stand-alone device capable of receiving broadcast television signals, using popular access means such as over-the-air, cable and satellite.

A television set is typically a stand-alone device, but it may also be integrated with another device, such as a computer or a mobile telephone.
This manual, HH2 Manual for Measuring ICT Access and Use by Households and Individuals Annex 5.
Glossary of terms and abbreviations 187 Terrestrial fixed (wireless) broadband network UIS UMTS UNCTAD UNECA UNECLAC UNESCAP UNESCO UNESCWA UNSC UNSD URL USB modem This manual, HH11 ITU (2011) Refers to technologies at advertised download speeds of at least 256 kbit/s, such as WiMAX, fixed CDMA UNESCO Institute for Statistics Universal mobile telecommunications system, the telecommunications system, incorporating mobile cellular and other functionality that is the subject of standards produced by 3GPP (Third Generation Partnership Project).
United Nations Conference on Trade and Development United Nations Economic Commission for Africa United Nations Economic Commission for Latin America and the Caribbean United Nations Economic and Social Commission for Asia and the Pacific United Nations Educational, Scientific and Cultural Organization United Nations Economic and Social Commission for Western Asia United Nations Statistical Commission United Nations Statistics Division Uniform resource locator Universal serial bus, an external bus standard that supports data transfer rates of 12 Mbit/s ITU (2011) User-created content Can be uploaded by anyone, includes texts, photos, music files and video clips, which often act as the centre for interaction within a network (e.g.
YouTube, MySpace).

Eurostat (2013) VoIP Web presence Website WiFi Wiki WiMAX WPIIS WSIS WWW xDSL Voice over Internet protocol, refers to managed VoIP and is the same as IP telephony.

ITU (2011) Includes a website, homepage or presence on another entity's website.

It excludes inclusion in an online directory and any other web pages where the entity does not have control over the content of the page.
A web presence includes social media pages and accounts (for example, Facebook, YouTube and Twitter) if the entity has control over content.

Location on the World Wide Web identified by a web address.

Collection of web files on a particular subject that includes a beginning file called a home page.

Information is encoded with specific languages (Hypertext mark-up language (HTML), XML, Java) readable with a web browser, like Netscape's Navigator or Microsoft's Internet Explorer.
Partnership and ECA (2012) ITU (2009) Wireless fidelity, a wireless local area network based on the Institute of IEEE 802.11 standard ITU (2011) Usually refers to a web application which allows people to add, modify, or delete content in a collaboration with others.

Text is usually written using a simplified markup language or a rich-text editor.
Wikipedia Wireless interoperability for microwave access/Worldwide Interoperability for Microwave Access, a family of telecommunications protocols that provide fixed and mobile Internet access, based on the IEEE 802.16 standard.

ITU (2011) Working Party on Indicators for the Information Society (OECD) World Summit on the Information Society World Wide Web Any of the various types of digital subscriber lines technologies, e.g.
ADSL ITU (2011) Manual for Measuring ICT Access and Use by Households and Individuals Bibliography 189 Bibliography ABS (Australian Bureau of Statistics) (2007), Household Use of Information Technology, Australia, 2006-07, cat.

no.

8146.0, www.abs.gov.au/ausstats/abs@.nsf/mf/8146.0.

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ITU (2010b), Child Online Protection: Statistical Framework and Indicators, http://www.itu.int/pub/D-IND-COP.01-11-2010.
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PARIS21 (2013), Home page, http://www.paris21.org.

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Manual for Measuring ICT Access and Use by Households and Individuals MANUAL for Measuring ICT Access and Use by Households and Individuals 2014 EDITION Printed in Switzerland Geneva, 2014 E-Couv_Measuring_Access_2014.indd 1 22.11.2013 11:10:45