Brazil within Brazil : Testing the Poverty Map Methodology in Minas Gerais

The small-area estimation technique developed for producing poverty maps has been applied in a large number of developing countries. Opportunities to formally test the validity of this approach remain rare due to lack of appropriately detailed data. This paper compares a set of predicted welfare estimates based on this methodology against their true values, in a setting where these true values are known. A recent study draws on Monte Carlo evidence to warn that the small-area estimation methodology could significantly over-state the precision of local-level estimates of poverty, if underlying assumptions of spatial homogeneity do not hold. Despite these concerns, the findings in this paper for the state of Minas Gerais, Brazil, indicate that the small-area estimation approach is able to produce estimates of welfare that line up quite closely to their true values. Although the setting considered here would seem, a priori, unlikely to meet the homogeneity conditions that have been argued to be essential for the method, confidence intervals for the poverty estimates also appear to be appropriate. However, this latter conclusion holds only after carefully controlling for community-level factors that are correlated with household level welfare.

Bibliographic Details

Main Authors:	Elbers, Chris, Lanjouw, Peter, Leite, Phillippe George
Language:	English
Published:	World Bank, Washington, DC 2008-02
Subjects:	ADULT POPULATION, ANALYSIS OF POVERTY, AUTOCORRELATION, BOOTSTRAP, CALCULATION, CAPITA CONSUMPTION, CENSUS ENUMERATION AREA, CLUSTER CORRELATION, CLUSTER-LEVEL EFFECTS, COMMUNITY LEVEL, CONFIDENCE INTERVALS, CONSUMPTION DATA, CONSUMPTION EXPENDITURE, CORRELATIONS, COVARIANCE, DATA COLLECTION, DELTA METHOD, DESCRIPTIVE STATISTICS, DEVELOPING COUNTRIES, DEVELOPMENT ECONOMICS, DEVELOPMENT RESEARCH, DEVELOPMENT RESEARCH GROUP, DISTRICT LEVEL, DISTURBANCE TERM, ECONOMIC STATUS, EDUCATIONAL VARIABLES, ENUMERATION, ESTIMATES OF POVERTY, ESTIMATION OF POVERTY, EXPLANATORY VARIABLES, FINANCIAL SUPPORT, FIRST-STAGE PARAMETERS, HETEROSCEDASTICITY, HOUSEHOLD CONSUMPTION, HOUSEHOLD INCOME, HOUSEHOLD LEVEL, HOUSEHOLD SIZE, HOUSEHOLD SURVEY, HOUSEHOLD SURVEY DATA, HOUSEHOLD SURVEYS, HOUSEHOLD WEIGHTS, HOUSEHOLD-LEVEL, HUMAN CAPITAL, HUMAN DEVELOPMENT, IDIOSYNCRATIC ERROR, INCIDENCE OF POVERTY, INCOME DATA, INDIVIDUAL HOUSEHOLDS, INFANT, INFANT MORTALITY, INFANT MORTALITY RATE, INFANT MORTALITY RATES, LABOUR FORCE, LEVEL ESTIMATION OF WELFARE, LEVEL OF AGGREGATION, LIFE EXPECTANCY, LITERACY RATES, MATRIX, MAXIMUM LIKELIHOOD ESTIMATION, METHODOLOGICAL RESEARCH, METHODOLOGY, MIGRANTS, MORTALITY, NUMBER OF CHILDREN, NUMBER OF HOUSEHOLDS, PARAMETER ESTIMATES, PENSIONS, POLICY RESEARCH, POLICY RESEARCH WORKING PAPER, POPULATION CENSUS, POPULATION SIZE, POVERTY ALLEVIATION, POVERTY ESTIMATE, POVERTY LINE, POVERTY MAP, POVERTY MAPPING, POVERTY MAPS, POVERTY MEASURES, PRECISION, PREDICTION, PREDICTIONS, PROGRESS, PUBLIC SERVICE, QUESTIONNAIRES, RANDOM SAMPLING, REGRESSORS, RELIABILITY, RESEARCH WORKING PAPERS, RESEARCHERS, RESPECT, SAMPLE DESIGN, SAMPLE SURVEYS, SAMPLING DISTRIBUTIONS, SANITATION, SIGNIFICANCE LEVEL, SIMULATION, SIMULATION STAGE, SIMULATIONS, SMALL AREA ESTIMATION, SMALL NUMBER OF HOUSEHOLDS, SPATIAL CORRELATION, SPATIAL DISTRIBUTION, SPATIAL DISTRIBUTION OF POVERTY, STANDARD ERROR, STANDARD ERRORS, STATISTICAL PRECISION, STATISTICAL SENSE, STATISTICAL TERMS, STATISTICAL TESTS, SURVEY DATA, TECHNIQUES, TIME SERIES, TIME SERIES ANALYSIS, TV, URBAN AREAS, VALIDITY, VARIANCE-COVARIANCE MATRIX, WEIGHTING,
Online Access:	http://documents.worldbank.org/curated/en/2008/02/9035947/brazil-within-brazil-testing-poverty-map-methodology-minas-gerais https://hdl.handle.net/10986/6575
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