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Key Uses of Household Survey Data

Kathleen BeegleWorkshop 17, Session 1bDesigning and Implementing Household SurveysMarch 31, 2009

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Wide range of uses Respond to the demand for data for

performance-based management. But it is also used for other purposes. Broad

categories of use:1. Basic Diagnostics of Living Standards:

MDGs, PRSPs, Poverty assessments, Poverty Maps

2. Evaluation/development of programs: PSIA, Proxy Means

3. Studies of development processes

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Millennium Development Goals (MDGs) Many, but not all, MDG indicators are

captured in an LSMS (IS). Some can be measures with adaptation (if

there is lack of other data sources for that indicator, such as IMR/immunization histories).

Other indicators require either larger samples than a typical LSMS (MMR), or administrative/other data.

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MDGs 1 -3 GOALS

INDICATORS

LSMS/IS (usually)

Proportion of population below $1 a day Yes Poverty gap ratio (incidence x depth of poverty) Yes Share of poorest quintile in national consumption Yes

1. Eradicate extreme poverty and hunger

Prevalence of underweight in children (under five years of age) Yes Proportion of population below minimum level of dietary energy

consumption No

Net enrollment ratio in primary education Yes

2. Achieve universal primary education

Proportion of pupils starting grade 1 who reach grade 5 Yes

Literacy rate of 15 to 24-year-olds Yes Ratio of girls to boys in primary, secondary, and tertiary

education Yes

Ratio of literate females to males among 15- to 24-year-olds Yes

3. Promote gender equality and empower women

Share of women in wage employment in the nonagricultural sector

Yes

Proportion of seats held by women in national parliament No

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MDGs 4 -8 GOALS

INDICATORS

LSMS/IS (usually)

4. Reduce child mortality

IMR and immunizations: usually not, but possible

Maternal mortality ratio No 5. Improve maternal health Proportion of births attended by skilled health personnel Yes (births in last

2 years) HIV prevalence among 15- to 24-year-old pregnant women n/a Contraceptive prevalence rate No Number of children orphaned by HIV/AIDS No Prevalence and death rates associated with malaria No

6.Combat HIV/AIDS, malaria, and other diseases

Proportion of population in malaria-risk areas using effective malaria prevention and treatment measures

prevention: Yes treatment: No

TB indicators No Land use, GDP per unit of energy use, Carbon dioxide emissions No 7. Ensure

environmental sustainability

Proportion of population with sustainable access to an improved water source, access to improved sanitation, access to secure tenure

Yes

8. Develop a global partnership for development

No for most (with exception of unemployment rate of 15- to 24-year-olds)

Secondary school enrollments,

12-18 year olds, Albania 2002

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• In almost all countries we have a single statistic: mean enrollment at the national level. In this case it is 61%.

•This is interesting for monitoring purposes, but it doesn’t say much about poverty or other factors.

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AveragePercent

• In many countries we have regional breakdowns, with marked contrasts

•The contrast between urban and rural rates emphasizes the disadvantages faced by rural communities.

• Other breakdowns would be useful

Urban

Rural

Secondary school enrollments,

12-18 year olds, Albania 2002

0%

10%

20%

30%

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50%

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100%

Q1 Q2 Q3 Q4 Q5

Percent

•…With the LSMS survey we can show enrollment rates broken down by consumption level--and thus understand an additional dimension

Consumption quintile

Female, urban

Male, urban

Male, rural

Female, rural

Average

Secondary school enrollments,

12-18 year olds, Albania 2002

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Poverty Maps Not necessarily “maps”, rather highly

disaggregated databases of poverty and inequality. This disaggregation is usually spatial.

Demand for poverty maps: geographic targeting of anti-poverty programs, decentralization and evidence-based policy,…

Linking LSMS/IS data to Census data to impute welfare levels in small areas

www.worldbank.org/povertymapping

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Example: Yunnan Province (China)

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Poverty and Social Impact Analysis: PSIA Analysis of consequences and distributional impacts

of policy interventions/reforms, such as: Utilities Pension reforms Civil service reform Ag reform Education/health (fees, decentralization) Fiscal (VAT, other taxes) Land reforms Etc…

http: //www.worldbank.org/psia

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Tools for PSIA

Volume of case studies (Coudouel, Dani and Paternostro 2006)

Types Examples Direct impact analysis Incidence tools

Poverty mapping

Behavioral models Supply and demand analysis Household models

Partial equilibrium tools Multi-market models

General equilibrium tools CGEs SAM-IO

Macro-micro models 1-2-3 PRSP PAMS

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Example: Malawi ADMARC reforms

Restructuring marketing functions of ADMARC (closing loss-making markets for inputs and outputs)

Objective: Investigate the importance of ADMARC services for various groups

Data: 1997/98 Malawi Integrated Household Survey, merged with location of ADMARC markets and roads network

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Malawi ADMARC reforms

Proximity has a larger positive effect in remote areas: Impact of markets on maize yields, demand for

fertilizer farm profits and consumption is significant only in remote areas.

Policy recommendations: In areas where the private sector operates and which

are close to a main road, loss-making markets could be closed without major distributional impacts.

In areas where the private sector does not operate and where households are isolated, subsidy to loss-making markets could be justified for their social role.

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Such analysis can also be used for ex-post evaluation/assessment of policy/events Evaluation of impact of Malawi fertilizer

voucher scheme by re-surveying subset of IHS 2004/05 households in 2006/07.

Rapid assessment of impact of Hurricane Mitch: Shortly after completing the 1998 LSMS Nicaragua, returned to households in sample in the areas affected.

Nicaragua Social Fund (FISE) evaluation by over-sampling FISE areas (booster sample in 1st stage) and linking with 1998 LSMS

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Proxy Means Testing for Programs Who should be beneficiaries? How to identify these people?

(Other uses of household survey data that influence program design: Geographic coverage; level benefits people receive)

Using household survey data to develop short list of simple indicator that can be collected in the field to “proxy” the household income/consumption.

Compile long list of possible indicators, then use econometrics to determine which indicators are useful and the weight to place on these indicators.

Analysis can be made more accurate by using more specific geographic regions (urban/rural, districts, etc) but this depends on the level at which results can be generalized from household data.

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Proxy Means Testing: Examples KIHBS 2007 data being used to create

targeting system for OVC CCT program that targets poorest 20%.

Panama Red de Oportunidades CCT program, developed with input from the 2003 Panama Living Standards Survey (Encuesta de Niveles de Vida, ENV)

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Understanding development & living standards Example from Vietnam: What are the long-

lasting effects of conflict events, in levels (poverty), and in changes (growth)? Detailed information on health and disability from

VHLSS 2006 Panel structure to look at changes Data on US military activities (bombing and

herbicide spray applications)

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Summary Household surveys like an LSMS can help monitor

welfare, as well as influence the design and implementation of social policy.

They are also a tool for studying development and living standards more generally.

The extent of these applications will depend on, among other factors: Comparability with existing data Developing questionnaire/sample to respond to needs Coordination with others (country teams, other groups) Public availability of well-documented data

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Summary Using existing data as a source for conducting

an evaluation: Need to understand the sample design and content of the questionnaire.

There is potential to embed an evaluation into a household survey, through piggy-backing (adding questions or a booster sample) or creating a panel (fielding a subsequent round). To be discussed later.