Regional Course on SDG Indicators:
Measuring decent work using microdata
from labour force surveys
03 October 2019
UN SIAP, Chiba, Japan

Sharing ADB’s Experience inArturo Martinez Jr.
Statistician
Joseph Bulan
Associate Statistics Analyst
Statistics and Data Innovation Unit
Office of the Chief Economist and Director General
Asian Development Bank

Order of Presentation• Introduction• Existing Data Collection Practices• Scope of ADB’s Previous Project on
Measurement of Informal Economy• Key Findings from ADB Project• Lessons Learned from ADB Project• Institutionalizing Expanded LFS• Policy UsesIntroduction
Some countries have not institutionalized thecompilation of statistics on informal economy.
Why?
• Data collection may be ‘expensive’
Construction of sampling frame may be costly
Informal production units are difficult to locate because of their characteristics• Not much demand for the statistics?
• Standard definitions of informal employment andinformal sector need to be operationalized carefully

Data Collection Practices• Special surveys
Most appropriate but difficult and very costly
A separate listing operation is needed to form the sampling frame of the survey• Household surveys
LFS -- may not correctly capture the characteristics of the enterprise that are not known by therespondents who are just workers
HIES -- can help identify informal sector activity through the sources of income data items but thestandard HIES questionnaire gathers very little information on the type of enterprise and othercharacteristics of the informal sector unit

• Establishment / enterprise surveys
Traditional approach
Usual sampling frame does not include the informal production units because of employment size
thresholds• Mixed surveys – household and enterprise survey
Sampling frame for informal sector production units survey (phase 2) is constructed from ahousehold survey (phase 1)
Makes it possible to link informal sector activities/business owner characteristics with householdcharacteristics

ADB’s Previous Project on
Measuring the Informal Economy
Contribute to the increase in evidence-based
policy making for poverty reduction• By helping NSOs acquire a sound strategy forcollecting data on the informal economy• By exploring the processes to integrate data on
informal economy into national accounts datacompilation framework• By studying the links between poverty and theinformal sector

Scope of the Project
Methodological and Economic Research• Estimating the prevalence of informal employment• Estimating the contribution of informal enterprises toGDPProject Team
Lead: Dalisay Maligalig
Members: Sining Cuevas Estrella Domingo Pamela Lapitan

Arturo Martinez Jr.

Similar Study -- ICMISIE• UN Development Account Project – Interregional
Cooperation on Measurement of the Informal Sector
and Informal Employment• Six countries from 3 regions (ECLAC, ESCWA,ESCAP)• For Asia – Mongolia, the Philippines, and Sri Lanka
were assisted by ESCAP• Data collection and estimation in 2007- 2009• Regional Conference: December 2009

Implementation Arrangements• The three pilot countries were identified and ADB implemented themixed survey approach for collecting data on the informal sector andinformal employment
Countries covered: Armenia, Bangladesh, Indonesia
Criteria: (i) Regular LFS with sufficiently large sample;(ii) informal sector that is perceived to begrowing; and(iii) not covered by UN ESCAP’s project• For each participating country, country team was formed: units
handling national accounts, labor and industry, and household
surveys were represented• Project Team collaborated with country teams; undertook research;wrote handbook• Period: December 2007 – March 2011

Cost-Effective Data Collection Strategy

Poverty status

Employment

Policy‐related issues

Capital formation
Policy‐related issues

Methodology• The methodology entails identification ofvariables and conditions to apply in
distinguishing formal and informal jobs andin classifying the production units these jobs
are engaged at  generation of decision
matricesThings we may need to capture to(i) distinguish between formal and informaljobs & (ii) examine whether a person works forformal / informal enterprise…
• Bookkeeping practices• Pay slips• Market Production• Type of enterprise• Legal Status• Place of work

• Business registration• Benefits / socialprotection• Contracts

Distinguishing between
formal and informal jobs…

Notes:The process of developing decision matrices entail
iterative procedures, in combination with theknowledge of labor concepts and consideration of
local or country specific practices.
One could also look at social protection coverage
too when distinguishing formal vs. informal jobs.
Source: ADB. 2011. A Handbook on Using the Mixed Survey Approach for Measuring Informal Employment and theInformal Sector. Manila. https://www.adb.org/sites/default/files/publication/28294/measuring-informal-sector.pdf

Examining whether a person works forformal / informal enterprise…

Source: ADB. 2011. A Handbook on Using the Mixed Survey Approach for Measuring Informal Employment and theInformal Sector. Manila. https://www.adb.org/sites/default/files/publication/28294/measuring-informal-sector.pdf

Things we may need to capture toestimate gross value added of informal
enterprises…
• Expenditures on rawmaterials and stock• Operational expenses• Capital expenditures• Inventory• Value of production
for own consumption• Value of products /services sold / offeredImplication ofAdding Survey Questions
Phase 2Phase 1

LFS + Addt’l Modules + Informal Sector Survey
Formal vs. Informal Jobs
GVA of informal enterprises
Formal vs. Informal Enterprise(approx.) 10 mins extension of interview / respondent
to identify formal vs. informal jobs and enterprise(approx.) 30 mins for conducting ISS to measure
economic contribution of informal enterprises

Nature of Employment
Bangladesh

ArmeniaIndonesia• In Armenia, informalemployment (in primaryand/or in secondary job) wasestimated at 52% of the total
employment and comprised
621,700 of the total jobs.
• In Bangladesh, majority ofworkers with one job (88%)
depended on an informal job,
while only 12% held one
formal job.
• In Indonesia, informal
enterprises engaged 87% of
the total employment in
Yogyakarta; while the jobs
supplied by informal
enterprises were relatively
less at 71% of the total inBanten.

Contribution of Informal Enterprises to GDP
Armenia

BangladeshIndonesiaLabor Productivity of Informal Enterprises
Armenia• According to the survey results, thehighest labor productivity among
informal enterprises was recorded inreal estate, renting, and businessactivities (AMD20,229,000); healthand social work (AMD1,9718,000);
and education (AMD11,039,000).
• The lowest labor productivity among
informal enterprises was recorded inagriculture, hunting, and forestry(AMD304,000); other community,social, and personal service
activities (AMD991,000); andmanufacturing (AMD2,169,000).

18

Labor Productivity of Informal Enterprises
Bangladesh• Among informal enterprises, the highestlabor productivity was recorded in realestate sector; the lowest laborproductivity was estimated in the mining
and quarrying sector.
• In the industry sector, labor productivity
in the formal** sector was 33 times
higher than the labor productivity among
informal enterprises. Similarly, in theservices sector, labor productivity in theformal** sector was seven times higher
than the labor productivity among
informal enterprises.
• On the other hand, in agriculture, thelabor productivity among informal
enterprises was 25% higher than that in
the formal** sector.

19Labor Productivity of Informal EnterprisesIndonesia• Labor productivity among informal enterprises in real estate, renting, andbusiness activities in Yogyakarta showed the highest figure of Rp68.46 million;
the lowest labor productivity is in finance, which recorded a figure of Rp0.07
million.
• The informal sector industry, such as real estate and other business activities,
had
20 the highest labor productivity in Banten at Rp23.7 million. The lowest laborproductivity, at Rp1.7 million, occurred in finance.

Lessons Learned• Mixed survey, or the '1-2' survey, is cost effective andreliable for measuring informal employment andeconomic contribution of informal enterprises.
• To cut survey operations costs & minimize
discrepancies between phases 1 and 2 surveys, thequestionnaires for the two phases can beadministered simultaneously.
• If not all identified HUEMs will be interviewed for phase2, sub-sampling must be carefully planned so that
all industry sectors can be adequately represented in
the phase 2 survey.

Lessons Learned• Phase 1 or the expanded LFS should beadministered regularly (annually, if possible). It willprovidecomparativeanalysis
ofemployment
characteristics (informal vs. formal) such as extent ofsocial protection, industry sector, wage differentials,gender, etc.
• To cut the costs, phase 2 may be administered every
two to three years. Annual estimates of informal
sector contribution to GDP can be derived on thebasis of indicators from phase 1.
• There is a need to carefully examine sampling
designs for phase 2 (use of master sample, spread
survey over 12 months); for improving questionnaires
for both phases; for moving forward the estimates of
the contribution of the informal sector to GDP using
phase 1 indicators.

Lessons Learned• While the HUEM survey was able to attain its objectives
and generate useful datasets, data quality can still
benefit significantly from improvements in thequestionnaire design, field operations, interview process,and data processing.
• Questionnaire Designo Issues on the questionnaire design do not only involve
the ISS (or HUEM) form itself but also include theframework of the expanded Labor Force Survey(eLFS).
o Because of the 1-2 approach of the survey, the eLFS
plays a critical role in screening the respondents for theHUEM survey.
o It also determines the number of respondents to beinterviewed for ISS, as well as classifying enterprises tothe industries to which they belong.

Lessons Learned• Questionnaire Designo All three countries experienced difficulty in using thedata collected in the module on capital expenditures inestimating the GVA either using production or income
estimation approach.
o It should be noted that while the survey enumerators
may be knowledgeable in carrying out household
and/or establishment surveys, their understanding of
the national accounts estimation process may belimited. Hence, conducting training on nationalaccounts estimation process is essential forenumerators / interviewers to better understand how
the concepts of national accounts are operationalized
in the survey data collection instrument.

Institutionalizing Expanded LFS
 A good way to move forward is to conduct an
expanded LFS regularly.
 However, the ISS (or HUEM survey) may not
be feasible (and practical) to conduct as
frequently as an eLFS.
 ISS may be conducted in longer year
intervals than the eLFS.

Institutionalizing Expanded LFS
For years when we conduct, eLFS and ISS, we can provide
benchmark estimates on the following:
INFORMAL EMPLOYMENT

Expanded LFS

EMPLOYMENT IN
INFORMAL ENTERPRISESINCOME / WAGES
etc.

ISS / HUEM Survey

GVA of INFORMAL
ENTERPRISESPRODUCTIVITY OF INFORMAL
ENTERPRISESetc.

Institutionalizing Expanded LFS
For years when we conduct eLFS but not ISS, we canimpute economic contribution of informal enterprises:
INFORMAL EMPLOYMENT

Expanded LFS

EMPLOYMENT IN
INFORMAL ENTERPRISESINCOME / WAGESetc.

GVA of INFORMAL
ENTERPRISES?

PRODUCTIVITY OF INFORMAL
ENTERPRISESetc.

Policy Uses
To induce an environment that is conducive for formalization,
we need to understand what drives informality.
• Should we reduce registration costs?
• Multidimensional -> investments ineducation, etc.

infrastructure,

health,As an economy develops, informal sector outputs andprevalence of informal employment tend to decrease as
economy develops. However, it can be stalled during episodes of
economic uncertainty and stagnation -> need to develop soundbusiness environment to facilitate uninterrupted transition frominformal to formal sector activities• Training on firm management• Increased access to market (find a niche) so they can competewith larger firms• Increased access to financing

Moving Forward:
Using Innovative Data Sources

Global Distribution ofIntensity of Nighttime Lights

Moving Forward:
Using Innovative Data Sources
Correlation between Provincial Poverty Rates andNighttime Lights Index Values

Moving Forward:
Using Innovative Data Sources
Can we use nighttime lights data to capture informal
economy and better estimate economic output andeconomic growth?
What other types of innovative data sources can beused?

Thank you.
Arturo Martinez Jr.
amartinezjr@adb.org+63 2 632 6527
Joseph Bulan
jbulan@adb.org+63 2 632 4375

For additional details, please see:https://www.adb.org/projects/41144‐012/main