Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples

For capturing dynamic demographic relationships, longitudinal household data can have considerable advantages over more widely used cross-sectional data. But because the collection of longitudinal data may be difficult and expensive, analysts must assess the magnitudes of the problems, specific to l...

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Main Authors:	Alderman, Harold, Behrman, Jere R., Kohler, Hans-Peter, Maluccio, John A., Cotts Watkins, Susan
Format:	Publications & Research
Language:	en_US
Published:	World Bank, Washington, DC 2015
Subjects:	aged biases Child Development data set data sets dependent variable developed countries developing countries Development Research employment equations family planning fathers Food Policy Research household characteristics household data household income household level household survey household surveys individual level informal networks intervention interviewer interviews labor force labor force participation labor market Living Standards Living Standards Measurement migration Mortality multivariate analyses multivariate analysis multivariate regression Nutrition nutritional status outcome variables parents policy research population size Population Studies precision preschool children probabilities probability radio random sample Research Institute Research Working Papers researchers rural areas siblings significance level social networks social scientists Specification tests survey data urban areas urban communities weighting Household surveys Longitudinal method Demographic indicators Longitudinal data Sample surveys Household size Reduction in force Migrations Case studies Family background Variables (mathematics) Multivariate analysis Behavioral responses
Online Access:	http://hdl.handle.net/10986/21336

id	okr-10986-21336
recordtype	oai_dc
spelling	okr-10986-213362021-04-23T14:04:01Z Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples Alderman, Harold Behrman, Jere R. Kohler, Hans-Peter Maluccio, John A. Cotts Watkins, Susan aged biases Child Development data set data sets dependent variable developed countries developing countries Development Research employment equations family planning fathers Food Policy Research household characteristics household data household income household level household survey household surveys individual level informal networks intervention interviewer interviews labor force labor force participation labor market Living Standards Living Standards Measurement migration Mortality multivariate analyses multivariate analysis multivariate regression Nutrition nutritional status outcome variables parents policy research population size Population Studies precision preschool children probabilities probability radio random sample Research Institute Research Working Papers researchers rural areas siblings significance level social networks social scientists Specification tests survey data urban areas urban communities weighting Household surveys Longitudinal method Demographic indicators Longitudinal data Sample surveys Household size Reduction in force Migrations Case studies Family background Variables (mathematics) Multivariate analysis Behavioral responses For capturing dynamic demographic relationships, longitudinal household data can have considerable advantages over more widely used cross-sectional data. But because the collection of longitudinal data may be difficult and expensive, analysts must assess the magnitudes of the problems, specific to longitudinal, but not to cross-sectional data. One problem that concerns many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be especially severe where there is considerable migration between rural, and urban areas. And attrition is likely to be selective on such characteristics as schooling, so high attrition is likely to bias estimates. The authors consider the extent, and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high annual attrition rates between survey rounds. Their estimates indicate that: 1) the means for a number of critical outcome, and family background variables differ significantly between those who are lost to follow-up, and those who are re-interviewed. 2) A number of family background variables are significant predictors of attrition. 3) Nevertheless, the coefficient estimates for standard family background variables in regressions, and probit equations for the majority of outcome variables in all three data sets, are not significantly affected by attrition. So attrition is apparently not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to those for industrial countries, suggest that multivariate estimates of behavioral relations may not be biased because of attrition. This would support the collection of longitudinal data. 2015-01-22T21:13:39Z 2015-01-22T21:13:39Z 2000-09 http://hdl.handle.net/10986/21336 en_US Policy Research Working Paper;No. 2447 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper Africa Latin America & Caribbean Bolivia Kenya South Africa
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	en_US
topic	aged biases Child Development data set data sets dependent variable developed countries developing countries Development Research employment equations family planning fathers Food Policy Research household characteristics household data household income household level household survey household surveys individual level informal networks intervention interviewer interviews labor force labor force participation labor market Living Standards Living Standards Measurement migration Mortality multivariate analyses multivariate analysis multivariate regression Nutrition nutritional status outcome variables parents policy research population size Population Studies precision preschool children probabilities probability radio random sample Research Institute Research Working Papers researchers rural areas siblings significance level social networks social scientists Specification tests survey data urban areas urban communities weighting Household surveys Longitudinal method Demographic indicators Longitudinal data Sample surveys Household size Reduction in force Migrations Case studies Family background Variables (mathematics) Multivariate analysis Behavioral responses
spellingShingle	aged biases Child Development data set data sets dependent variable developed countries developing countries Development Research employment equations family planning fathers Food Policy Research household characteristics household data household income household level household survey household surveys individual level informal networks intervention interviewer interviews labor force labor force participation labor market Living Standards Living Standards Measurement migration Mortality multivariate analyses multivariate analysis multivariate regression Nutrition nutritional status outcome variables parents policy research population size Population Studies precision preschool children probabilities probability radio random sample Research Institute Research Working Papers researchers rural areas siblings significance level social networks social scientists Specification tests survey data urban areas urban communities weighting Household surveys Longitudinal method Demographic indicators Longitudinal data Sample surveys Household size Reduction in force Migrations Case studies Family background Variables (mathematics) Multivariate analysis Behavioral responses Alderman, Harold Behrman, Jere R. Kohler, Hans-Peter Maluccio, John A. Cotts Watkins, Susan Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples
geographic_facet	Africa Latin America & Caribbean Bolivia Kenya South Africa
relation	Policy Research Working Paper;No. 2447
description	For capturing dynamic demographic relationships, longitudinal household data can have considerable advantages over more widely used cross-sectional data. But because the collection of longitudinal data may be difficult and expensive, analysts must assess the magnitudes of the problems, specific to longitudinal, but not to cross-sectional data. One problem that concerns many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be especially severe where there is considerable migration between rural, and urban areas. And attrition is likely to be selective on such characteristics as schooling, so high attrition is likely to bias estimates. The authors consider the extent, and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high annual attrition rates between survey rounds. Their estimates indicate that: 1) the means for a number of critical outcome, and family background variables differ significantly between those who are lost to follow-up, and those who are re-interviewed. 2) A number of family background variables are significant predictors of attrition. 3) Nevertheless, the coefficient estimates for standard family background variables in regressions, and probit equations for the majority of outcome variables in all three data sets, are not significantly affected by attrition. So attrition is apparently not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to those for industrial countries, suggest that multivariate estimates of behavioral relations may not be biased because of attrition. This would support the collection of longitudinal data.
format	Publications & Research
author	Alderman, Harold Behrman, Jere R. Kohler, Hans-Peter Maluccio, John A. Cotts Watkins, Susan
author_facet	Alderman, Harold Behrman, Jere R. Kohler, Hans-Peter Maluccio, John A. Cotts Watkins, Susan
author_sort	Alderman, Harold
title	Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples
title_short	Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples
title_full	Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples
title_fullStr	Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples
title_full_unstemmed	Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples
title_sort	attrition in longitudinal household survey data : some tests for three developing-country samples
publisher	World Bank, Washington, DC
publishDate	2015
url	http://hdl.handle.net/10986/21336
_version_	1764447973507334144

Attrition in Longitudinal Household Survey Data : Some Tests for Three Developing-Country Samples

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