# **ANNEX  1. Measurement and Data Issues**

This annex will describe two aspects of the information used in this study. First, the obtaining of relevant survey data. Second, the establishment and application of meaningful indicators to present the data. Finally some observations on surveys and survey data will be offered, based on our recent experience.

# DATA SOURCES

The sources of primary data were sample surveys of households within transition economies of the ECA Region. Several possible sources for were considered for suitability. The survey types examined included: Living Standards Measurement Surveys (LSMS, assisted by the World Bank), Household Budget Surveys (HBS, also known as Income and Expenditure Surveys, assisted by the World Bank), Multiple Indicators Cluster Surveys (MICS, assisted by the UN), Demographic and Health Surveys (DHS, assisted by USAID), and national censuses of population.

The countries considered for data availability were all of those in the ECA region with transition economies, so all were considered except Turkey. In most cases the surveys are administered by the statistical agencies within each country with technical assistance from donor organizations. Other sources of data used in this study include: national official statistics, the World Development Indicators databank, the UN Habitat Global Urban Indicators databank, country Poverty Analysis reports, and other related literature.

The examination of household surveys lead to the compilation of a comprehensive and current listing of surveys undertaken in ECA Region, including survey details and technical and analytic contacts. In all around 200 surveys in 30 countries over the period from 1989 to 2003 were identified thorough desk research and discussion with other staff in Bank sectoral and research units.

The sophistication and usefulness of the household surveys undertaken in the Region have improved considerably during the 1989 - 2003 period. Most countries in the Region have a program of annual Household Budget Surveys (HBS). However the data available from this source, up until the late-1990's, was of poor quality largely because inadequate sampling techniques held over from the Soviet era. Until the sampling design was corrected these surveys were biased and misleading. The HBS approach does not always allow for the calculation of welfare aggregates based on consumption and expenditure or income must sometimes be used. The most recent LSMS surveys have benefited from a more rigorous sample frame being available from the national censuses conducted during 1999 - 2003.

LSMS and HBS surveys have been the most frequently used quantitative instrument for poverty monitoring and analysis in the region, as they are the only surveys that contain extensive information on household income and expenditures. The preference given to LSMS over HBS surveys lies into the fact that LSMS surveys usually cover a greater variety of topics, including infrastructure and energy poverty, and receive considerable care in terms of quality control.

After identifying the existence of these surveys, the list was screened according to relevance and availability of source datasets. A most likely survey was identified for each country, usually the most recent LSMS or "new design" HBS and examined for relevance. Relevance included both currency and coverage of urban and infrastructure issues. The primary consideration for urban data was the ability to separate out the capital city from other urban areas within the overall urban sample strata. The primary consideration for infrastructure data was the ability to derive level of service measures. This review is described in more detail below.

The next step was obtaining the selected source datasets and ensuring that the datasets included the necessary derived variables (especially the welfare aggregate used in Bank poverty work on the country) 63