How Good a Map? Putting Small Area Estimation to the Test

The authors examine the performance of small area welfare estimation. The method combines census and survey data to produce spatially disaggregated poverty and inequality estimates. To test the method, they compare predicted welfare indicators for...

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Main Authors:	Demombynes, Gabriel, Elbers, Chris, Lanjouw, Jean O., Lanjouw, Peter
Format:	Policy Research Working Paper
Language:	English
Published:	World Bank, Washington, DC 2012
Subjects:	APPROACH CAPITA CONSUMPTION CAPITA EXPENDITURE CASE STUDY CENSUSES COMMUNITY LEVEL CONSUMPTION LEVEL CONSUMPTION MODEL CONSUMPTION SMOOTHING CORRELATIONS DEGREES OF FREEDOM DELTA METHOD DEVELOPING COUNTRIES DISTRICT-LEVEL DISTURBANCE TERM ECONOMIC GROWTH EDUCATION ESTIMATES OF POVERTY ESTIMATION OF POVERTY ESTIMATION PROCEDURE EXPERIMENTS EXPLANATORY VARIABLES FOLLOW UP SURVEYS GEOGRAPHIC PROFILE OF POVERTY HEADCOUNT RATE HEALTH HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEY DATA HOUSEHOLD WELFARE HOUSEHOLDS IDIOSYNCRATIC COMPONENT IDIOSYNCRATIC ERROR INCOME INCOME DATA INEQUALITY LEVEL ESTIMATION OF WELFARE LEVEL OF AGGREGATION NUMBER OF HOUSEHOLDS NUTRITION PARAMETER ESTIMATES PARAMETRIC PARAMETRIC APPROACH PARAMETRIC DISTRIBUTIONS POLICY RESEARCH POLICY RESEARCH WORKING PAPER POOR POOR COMMUNITIES POOR HOUSEHOLDS POPULATION CENSUS POPULATION SIZE POVERTY GAP POVERTY INDICES POVERTY LINE POVERTY MAPPING POVERTY MAPPING METHODOLOGY POVERTY MAPS POVERTY MEASURES POVERTY RATE PROGRESS REGRESSORS RELIABILITY RESEARCH WORKING PAPERS RESEARCHERS RURAL SIMULATION SIMULATION METHODS SIMULATION PROCEDURES SIMULATIONS SMALL AREA ESTIMATION SOCIAL SPENDING SPATIAL DIMENSIONS OF POVERTY STANDARD DEVIATION STANDARD ERROR STANDARD ERRORS TARGETING TECHNIQUES TIME SERIES ANALYSIS VARIANCE-COVARIANCE MATRIX WELFARE INDICATORS
Online Access:	http://documents.worldbank.org/curated/en/2007/03/7488024/good-map-putting-small-area-estimation-test http://hdl.handle.net/10986/7040

id	okr-10986-7040
recordtype	oai_dc
spelling	okr-10986-70402021-04-23T14:02:33Z How Good a Map? Putting Small Area Estimation to the Test Demombynes, Gabriel Elbers, Chris Lanjouw, Jean O. Lanjouw, Peter APPROACH CAPITA CONSUMPTION CAPITA EXPENDITURE CASE STUDY CENSUSES COMMUNITY LEVEL CONSUMPTION LEVEL CONSUMPTION MODEL CONSUMPTION SMOOTHING CORRELATIONS DEGREES OF FREEDOM DELTA METHOD DEVELOPING COUNTRIES DISTRICT-LEVEL DISTURBANCE TERM ECONOMIC GROWTH EDUCATION ESTIMATES OF POVERTY ESTIMATION OF POVERTY ESTIMATION PROCEDURE EXPERIMENTS EXPLANATORY VARIABLES FOLLOW UP SURVEYS GEOGRAPHIC PROFILE OF POVERTY HEADCOUNT RATE HEALTH HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEY DATA HOUSEHOLD WELFARE HOUSEHOLDS IDIOSYNCRATIC COMPONENT IDIOSYNCRATIC ERROR INCOME INCOME DATA INEQUALITY LEVEL ESTIMATION OF WELFARE LEVEL OF AGGREGATION NUMBER OF HOUSEHOLDS NUTRITION PARAMETER ESTIMATES PARAMETRIC PARAMETRIC APPROACH PARAMETRIC DISTRIBUTIONS POLICY RESEARCH POLICY RESEARCH WORKING PAPER POOR POOR COMMUNITIES POOR HOUSEHOLDS POPULATION CENSUS POPULATION SIZE POVERTY GAP POVERTY INDICES POVERTY LINE POVERTY MAPPING POVERTY MAPPING METHODOLOGY POVERTY MAPS POVERTY MEASURES POVERTY RATE PROGRESS REGRESSORS RELIABILITY RESEARCH WORKING PAPERS RESEARCHERS RURAL SIMULATION SIMULATION METHODS SIMULATION PROCEDURES SIMULATIONS SMALL AREA ESTIMATION SOCIAL SPENDING SPATIAL DIMENSIONS OF POVERTY STANDARD DEVIATION STANDARD ERROR STANDARD ERRORS TARGETING TECHNIQUES TIME SERIES ANALYSIS VARIANCE-COVARIANCE MATRIX WELFARE INDICATORS The authors examine the performance of small area welfare estimation. The method combines census and survey data to produce spatially disaggregated poverty and inequality estimates. To test the method, they compare predicted welfare indicators for a set of target populations with their true values. They construct target populations using actual data from a census of households in a set of rural Mexican communities. They examine estimates along three criteria: accuracy of confidence intervals, bias, and correlation with true values. The authors find that while point estimates are very stable, the precision of the estimates varies with alternative simulation methods. While the original approach of numerical gradient estimation yields standard errors that seem appropriate, some computationally less-intensive simulation procedures yield confidence intervals that are slightly too narrow. The precision of estimates is shown to diminish markedly if unobserved location effects at the village level are not well captured in underlying consumption models. With well specified models there is only slight evidence of bias, but the authors show that bias increases if underlying models fail to capture latent location effects. Correlations between estimated and true welfare at the local level are highest for mean expenditure and poverty measures and lower for inequality measures. 2012-06-04T19:29:50Z 2012-06-04T19:29:50Z 2007-03 http://documents.worldbank.org/curated/en/2007/03/7488024/good-map-putting-small-area-estimation-test http://hdl.handle.net/10986/7040 English Policy Research Working Paper; No. 4155 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank World Bank, Washington, DC Publications & Research :: Policy Research Working Paper Publications & Research Latin America & Caribbean Mexico
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	English
topic	APPROACH CAPITA CONSUMPTION CAPITA EXPENDITURE CASE STUDY CENSUSES COMMUNITY LEVEL CONSUMPTION LEVEL CONSUMPTION MODEL CONSUMPTION SMOOTHING CORRELATIONS DEGREES OF FREEDOM DELTA METHOD DEVELOPING COUNTRIES DISTRICT-LEVEL DISTURBANCE TERM ECONOMIC GROWTH EDUCATION ESTIMATES OF POVERTY ESTIMATION OF POVERTY ESTIMATION PROCEDURE EXPERIMENTS EXPLANATORY VARIABLES FOLLOW UP SURVEYS GEOGRAPHIC PROFILE OF POVERTY HEADCOUNT RATE HEALTH HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEY DATA HOUSEHOLD WELFARE HOUSEHOLDS IDIOSYNCRATIC COMPONENT IDIOSYNCRATIC ERROR INCOME INCOME DATA INEQUALITY LEVEL ESTIMATION OF WELFARE LEVEL OF AGGREGATION NUMBER OF HOUSEHOLDS NUTRITION PARAMETER ESTIMATES PARAMETRIC PARAMETRIC APPROACH PARAMETRIC DISTRIBUTIONS POLICY RESEARCH POLICY RESEARCH WORKING PAPER POOR POOR COMMUNITIES POOR HOUSEHOLDS POPULATION CENSUS POPULATION SIZE POVERTY GAP POVERTY INDICES POVERTY LINE POVERTY MAPPING POVERTY MAPPING METHODOLOGY POVERTY MAPS POVERTY MEASURES POVERTY RATE PROGRESS REGRESSORS RELIABILITY RESEARCH WORKING PAPERS RESEARCHERS RURAL SIMULATION SIMULATION METHODS SIMULATION PROCEDURES SIMULATIONS SMALL AREA ESTIMATION SOCIAL SPENDING SPATIAL DIMENSIONS OF POVERTY STANDARD DEVIATION STANDARD ERROR STANDARD ERRORS TARGETING TECHNIQUES TIME SERIES ANALYSIS VARIANCE-COVARIANCE MATRIX WELFARE INDICATORS
spellingShingle	APPROACH CAPITA CONSUMPTION CAPITA EXPENDITURE CASE STUDY CENSUSES COMMUNITY LEVEL CONSUMPTION LEVEL CONSUMPTION MODEL CONSUMPTION SMOOTHING CORRELATIONS DEGREES OF FREEDOM DELTA METHOD DEVELOPING COUNTRIES DISTRICT-LEVEL DISTURBANCE TERM ECONOMIC GROWTH EDUCATION ESTIMATES OF POVERTY ESTIMATION OF POVERTY ESTIMATION PROCEDURE EXPERIMENTS EXPLANATORY VARIABLES FOLLOW UP SURVEYS GEOGRAPHIC PROFILE OF POVERTY HEADCOUNT RATE HEALTH HOUSEHOLD INCOME HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEY DATA HOUSEHOLD WELFARE HOUSEHOLDS IDIOSYNCRATIC COMPONENT IDIOSYNCRATIC ERROR INCOME INCOME DATA INEQUALITY LEVEL ESTIMATION OF WELFARE LEVEL OF AGGREGATION NUMBER OF HOUSEHOLDS NUTRITION PARAMETER ESTIMATES PARAMETRIC PARAMETRIC APPROACH PARAMETRIC DISTRIBUTIONS POLICY RESEARCH POLICY RESEARCH WORKING PAPER POOR POOR COMMUNITIES POOR HOUSEHOLDS POPULATION CENSUS POPULATION SIZE POVERTY GAP POVERTY INDICES POVERTY LINE POVERTY MAPPING POVERTY MAPPING METHODOLOGY POVERTY MAPS POVERTY MEASURES POVERTY RATE PROGRESS REGRESSORS RELIABILITY RESEARCH WORKING PAPERS RESEARCHERS RURAL SIMULATION SIMULATION METHODS SIMULATION PROCEDURES SIMULATIONS SMALL AREA ESTIMATION SOCIAL SPENDING SPATIAL DIMENSIONS OF POVERTY STANDARD DEVIATION STANDARD ERROR STANDARD ERRORS TARGETING TECHNIQUES TIME SERIES ANALYSIS VARIANCE-COVARIANCE MATRIX WELFARE INDICATORS Demombynes, Gabriel Elbers, Chris Lanjouw, Jean O. Lanjouw, Peter How Good a Map? Putting Small Area Estimation to the Test
geographic_facet	Latin America & Caribbean Mexico
relation	Policy Research Working Paper; No. 4155
description	The authors examine the performance of small area welfare estimation. The method combines census and survey data to produce spatially disaggregated poverty and inequality estimates. To test the method, they compare predicted welfare indicators for a set of target populations with their true values. They construct target populations using actual data from a census of households in a set of rural Mexican communities. They examine estimates along three criteria: accuracy of confidence intervals, bias, and correlation with true values. The authors find that while point estimates are very stable, the precision of the estimates varies with alternative simulation methods. While the original approach of numerical gradient estimation yields standard errors that seem appropriate, some computationally less-intensive simulation procedures yield confidence intervals that are slightly too narrow. The precision of estimates is shown to diminish markedly if unobserved location effects at the village level are not well captured in underlying consumption models. With well specified models there is only slight evidence of bias, but the authors show that bias increases if underlying models fail to capture latent location effects. Correlations between estimated and true welfare at the local level are highest for mean expenditure and poverty measures and lower for inequality measures.
format	Publications & Research :: Policy Research Working Paper
author	Demombynes, Gabriel Elbers, Chris Lanjouw, Jean O. Lanjouw, Peter
author_facet	Demombynes, Gabriel Elbers, Chris Lanjouw, Jean O. Lanjouw, Peter
author_sort	Demombynes, Gabriel
title	How Good a Map? Putting Small Area Estimation to the Test
title_short	How Good a Map? Putting Small Area Estimation to the Test
title_full	How Good a Map? Putting Small Area Estimation to the Test
title_fullStr	How Good a Map? Putting Small Area Estimation to the Test
title_full_unstemmed	How Good a Map? Putting Small Area Estimation to the Test
title_sort	how good a map? putting small area estimation to the test
publisher	World Bank, Washington, DC
publishDate	2012
url	http://documents.worldbank.org/curated/en/2007/03/7488024/good-map-putting-small-area-estimation-test http://hdl.handle.net/10986/7040
_version_	1764401490244403200

How Good a Map? Putting Small Area Estimation to the Test

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