Surveys using lsms hbs lfs and silc for poverty analysis
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Surveys: Using LSMS, HBS, LFS and SILC for Poverty Analysis. Rachel Smith-Govoni April 4, 2008. Goals and Needs. Goals: Measure the poverty impact of economic policy Measure the distributional impact of economic policy Needs: Rely heavily on household survey data.

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Goals and Needs


  • Measure the poverty impact of economic policy

  • Measure the distributional impact of economic policy


  • Rely heavily on household survey data

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Household Surveys - types

  • Single Topic

  • Labour Force Surveys( LFS) (ILO)

    Census – national, 10 years – Serbia 2002

  • In-between

  • Multi-topic

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Household Surveys

  • Single Topic

  • In-between

  • Agricultural Surveys (FAO)

  • Demographic and Health (DHS)

  • Household Budget Surveys (HBS)

  • Multi-topic

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Household Surveys

  • Single Topic

  • In-between

  • Multi-topic

  • Multiple Indicator Cluster Survey UNICEF

  • Living Standards Measurement Study

  • Survey on Income and Living Conditions (SILC, EU)

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  • Accurate measure of the population of a country

  • Geographic distribution of the population

  • Basic demographic information

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  • Not a sample

  • Universal coverage

  • No sampling errors in estimates

  • Some corrections for non-response may be needed

  • Not many items

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  • Demographic information: age, sex, race/ethnicity, family and household composition

  • Housing information

  • Others: basic education, labour, disability

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Albania: 2001 (1989)

BiH 1991 (1981)

Montenegro 2003 (1991)

Serbia 2002

Kosovo 1981

Limited monitoring

Limited use if looking at impact of policies affecting taxes, tariffs or pricing

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  • Sample frame

  • Link with household surveys for small area estimation (data mapping)

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Two types of errors:

Sampling and non-sampling





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Sampling vs. non-sampling errors

Total error

Sampling error

Non-sampling error

Sample size

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Labour Force Survey (Anketa o radnoj snazi – ARS)


  • Direct measurement of unemployment

  • General characteristics of the labour force

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Labour Force Survey


  • Relatively large samples

  • Desire to disaggregate to different geographic areas

  • Individuals of working age

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Labour Force Survey


  • Characteristics of the labour force

    • Demographics

    • Education

  • Sectoral distribution of employment

  • Degree of formality

  • Seasonal

  • Income

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Labour Force Survey


  • LFS typically capture partial, not total, income, under-estimate welfare

  • Measurement Error - Labour income measurement error at both ends of the distribution

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LFS in Latin AmericaItem non-response

Source: Feres, 1998

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Household Budget Survey (Anketa o potrosnji domacinstava – APD,

  • Inputs to National Accounts on consumer expenditures

  • Track changes in expenditures over time

  • Weights for the Consumer Price Index

    (Indeks Potrosackih Cijena)

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Non response rates ( APD, Eurostat Household Budget Surveys, 2003)

  • Bulgaria: 39.7%

  • Estonia, 44%

  • Hungary, 58.8% before replacement

  • Romania, 21.6 %


  • Usually medium size sample

  • High non-response rates

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Household Budget Surveys APD,


  • Total Income

  • Total Consumption - diary

  • Short Demographics

  • Central Europe: agriculture

  • Limited health and education

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Household Budget Surveys APD,

Poverty Measurement

  • Consumption based welfare measure

  • Purpose of an HBS survey is NOT to measure welfare but to precisely measure mean expenditures on specific goods and services

  • These are conflicting goals

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Household Budget Surveys APD,

Poverty Measurement

  • Shortest possible reference periods

  • Minimize number of omitted expenditures

  • Good for precise measurement of regional or national means

  • Because of lumpy nature of purchases, not good for comparisons among households

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Multi-topic Household Surveys APD,

Those with a focus on measuring poverty

  • Survey on Income and Living Conditions (SILC)

  • Living Standards Measurement Study Surveys (LSMS)

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Multi-topic Household Surveys APD,


  • Analysis of welfare levels and distribution

  • Study links between welfare levels and individual and household characteristics, economic, human and social capital

  • Social exclusion

  • Levels of access to, and use of, social services, government programs and spending

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Multi-topic Household Surveys APD,


  • Small sample sizes

  • Trade-off issue: Quality and cost considerations

  • Limits ability to assess programs or policies that affect small groups or small areas (over-sample)

  • Infrequent in many countries

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LSMS 2002, 2003, 2007 APD,


1 household composition

2 housing

3 individual demographics

4 health

5 labour

6 work history

7 social programs

8 migration

9 values and opinions

10 consumption

11 agriculture

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Multi-topic Household Surveys APD,

Poverty Measurement

  • Total consumption

    • Longer reference periods

    • Able to calculate use value of durables and housing

  • Total income

    • Suffers from standard measurement errors

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Designs for surveys across time APD,

Repeated cross sectional surveys

(e.g. Household Budget Survey, Labour Force Survey)

  • Common design for large government surveys

  • New sample drawn for each survey

  • Carry similar questions each year

  • Used for trend analysis at aggregate level

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Designs for surveys across time APD,

Cohort Studies

  • Sample often based on an age group

  • Follow up same sample members at fairly long intervals

  • Developmental data as well as social and economic data

  • Data from parents, teachers associated with cohort member

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Designs for surveys across time APD,

e.g. Panel Study of Income Dynamics, USA – since 1968!

Living in BiH 2001-2004, LSMS Albania 2002-2004,

LSMS Serbia 2002-2003

  • Draw a sample at one point in time and follow those sample members indefinitely (or as long as the funding continues)

  • Collect individual level data in household context

  • Repeated measures at fixed intervals (annual data collection)

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Advantages of Panel Data APD,

  • Comparison of same individual over time - outcomes

  • Track of aspects of social change

  • Facilitates study of change and causal inference

  • Minimise the problem of inaccurate recall

  • Compare a person’s expectations with real change

  • Look at how changes in individuals’ behaviour affects their households

  • Identifies the co-variates of change and the relative risks of particular events for different types of people

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Net change - APD,

0.1% unemployed



Changes in Employment Status




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3.2% APD,




unemployed 2001 but employed 2007


employed 2001

but unemployed 2007




Changes in Employment Status


Still Unemployed



Still Employed



Net change - 0.1% unemployed

Actual change is 10.1

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Balkan Examples APD,

Albania - 15% of the unemployed in 2002 had made the transition to formal sector employment by 2004

BiH - About half who were poor in 2001 remained poor in 2004. Many individuals moved out of poverty.

(Cross section headcount 18% for both years)

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  • Employment and the labour market APD,

    • Unemployment duration and exit rates

    • Do the unemployed find stable employment?

    • The effect of non-standard employment on mental health

    • Temporary jobs: who gets them, what are they worth, and do they lead anywhere?

  • Family and Household

    • Patterns of household formation and dissolution

    • Breaking up - finances and well-being following divorce or split

    • The effect of parents’ employment on children's educational attainment

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    A Sample APD,

    • Concept of ‘longitudinal household’ problematic for a panel - households change in composition over time or disappear altogether

    • Individual level sample

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    Following rules APD,

    • All members of households interviewed at Wave One

    • Children born to these original sample members

    • Original members are followed as they move house, and any new individuals who join with them are eligible to be interviewed

    • New sample members are followed if they split from the original member

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    Questionnaire design APD,

    • Core content carried every wave

    • Rotating core questions

    • One-off variable components

      • lifetime job history

      • marital and fertility history

    • Variable questions to respond to new research and policy agendas

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    Attrition in panel surveys APD,

    • Inevitable to some extent but can be minimised

    • Multiple sources of attrition in a panel

      • refusal to take part

      • respondents move and cannot be traced

      • non-contacts

    • Worry is potential bias if people who drop out differ significantly from those who stay in

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    UK Panel Wave 1 Respondents APD, Wave-on wave re-interview rates

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    Fieldwork APD,

    • respondent incentives as a ‘thank-you’

    • extended fieldwork period for ‘tail-enders’

    • refusal conversion programme

    • tracking procedures during fieldwork

    • panel maintenance between waves

      • Change of Address cards to update addresses

      • mailing of Respondent Report

      • details of contacts with respondents between waves

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    The user database APD,

    • Longitudinal data is complex

    • Provide users with database structure which enhances usability

    • Consistent record structure over time

    • Key variables for matching and linking data cross wave

    • Consistent variable naming conventions

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    Conclusions APD,

    • Longitudinal panel data allows us to answer research questions that cannot be answered with with cross-sectional data

    • Provides a different view of the world - see process through the life-course not just a static picture

    • Is complex (but so is the real world) - so needs to be well designed and conducted with sufficient resources to be successful

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    Final APD, points

    • Welfare: household surveys- always missing the homeless, street children, institutionalized population

    • No one survey can meet all needs, review its purpose, coverage, content and quality before using

    • Need a system of surveys that meets the needs of data users