Survey Nonresponse and the Distribution of Income

The authors examine the distributional implications of selective compliance in sample surveys, whereby households with different incomes are not equally likely to participate. They discuss poverty and inequality measurement implications for monotonically decreasing and inverted-U compliance-income relationships. The authors demonstrate that the latent income effect on the probability of compliance can be estimated from information on response rates across geographic areas. On implementing the method on the Current Population Survey for the United States, they find that the compliance probability falls monotonically as income rises. Correcting for non-response appreciably increases mean income and inequality, but has only a small impact on poverty incidence up to poverty lines common in the United States.

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Bibliographic Details
Main Authors: Korinek, Anton, Mistiaen, Johan A., Ravallion, Martin
Language:English
Published: World Bank, Washington, DC 2005-03
Subjects:CONSUMPTION FUNCTION, DATA COLLECTION, DATA REQUIREMENTS, DIMINISHING MARGINAL UTILITY, ECONOMETRICS, ECONOMIC REVIEW, ECONOMIC THEORY, EXPECTED VALUE, GINI COEFFICIENT, GINI INDEX, HOUSEHOLD INCOME, INCIDENCE OF POVERTY, INCOME, INCOME DISTRIBUTION, INCOME EFFECT, INCOME GROUPS, INCOME INEQUALITY, INCOME LEVELS, INEQUALITY, INEQUALITY MEASURES, LIVING STANDARDS, LORENZ CURVE, MARGINAL UTILITY, MATHEMATICAL ECONOMICS, MEAN INCOME, MEASURES OF POVERTY, OPPORTUNITY COST, POLICY RESEARCH, POLITICAL ECONOMY, POOR, POVERTY INCIDENCE, POVERTY LINES, POVERTY MEASUREMENT, POVERTY MEASURES, POVERTY RATES, SAMPLE SIZE, STATISTICAL ANALYSIS, SURVEY ­ DESIGN, URBAN AREAS, WAGE INCOME, WAGES, WEALTH,
Online Access:http://documents.worldbank.org/curated/en/2005/03/5681006/survey-nonresponse-distribution-income
https://hdl.handle.net/10986/8869
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Summary:The authors examine the distributional implications of selective compliance in sample surveys, whereby households with different incomes are not equally likely to participate. They discuss poverty and inequality measurement implications for monotonically decreasing and inverted-U compliance-income relationships. The authors demonstrate that the latent income effect on the probability of compliance can be estimated from information on response rates across geographic areas. On implementing the method on the Current Population Survey for the United States, they find that the compliance probability falls monotonically as income rises. Correcting for non-response appreciably increases mean income and inequality, but has only a small impact on poverty incidence up to poverty lines common in the United States.