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Estimating wealth effects without expenditure data, or tears : an application to educational enrollments in states of India

October 1998 The relationship between household wealth and educational enrollment of children can be estimated without expenditure data. A method for doing so-which uses an index based on household asset ownership indicators-is proposed and defended in this paper. In India, children from the wealthiest households are over 30 percentage points more likely to be in school than those from the poorest households, although this gap varies considerably across states. To estimate the relationship between household wealth and the probability that a child (aged 6 to 14) is enrolled in school, Filmer and Pritchett use National Family Health Survey (NFHS) data collected in Indian states in 1992 and 1993. In developing their estimate Filmer and Pritchett had to overcome a methodological difficulty: The NFHS, modeled closely on the Demographic and Health Surveys, measures neither household income nor consumption expenditures. As a proxy for long-run household wealth, they constructed a linear asset index from a set of asset indicators, using principal components analysis to derive the weights. This asset index is robust, produces internally coherent results, and provides a close correspondence with data on state domestic product and on state level poverty rates. They validate the asset index using data on consumption spending and asset ownership from Indonesia, Nepal, and Pakistan. The asset index has reasonable coherence with current consumption expenditures and, more importantly, works as well as-or better than-traditional expenditure-based measures in predicting enrollment status. The authors find that on average a child from a wealthy household (in the top 20 percent on the asset index developed for this analysis) is 31 percent more likely to be enrolled in school than a child from a poor household (in the bottom 40 percent). This paper-a product of Poverty and Human Resources, Development Research Group-is part of a larger effort in the group to inform educational policy. The study was funded by the Bank's Research Support Budget under the research project Educational Enrollment and Dropout (RPO 682-11). Deon Filmer may be contacted at [email protected].

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  • "October 1998 The relationship between household wealth and educational enrollment of children can be estimated without expenditure data. A method for doing so-which uses an index based on household asset ownership indicators-is proposed and defended in this paper. In India, children from the wealthiest households are over 30 percentage points more likely to be in school than those from the poorest households, although this gap varies considerably across states. To estimate the relationship between household wealth and the probability that a child (aged 6 to 14) is enrolled in school, Filmer and Pritchett use National Family Health Survey (NFHS) data collected in Indian states in 1992 and 1993. In developing their estimate Filmer and Pritchett had to overcome a methodological difficulty: The NFHS, modeled closely on the Demographic and Health Surveys, measures neither household income nor consumption expenditures. As a proxy for long-run household wealth, they constructed a linear asset index from a set of asset indicators, using principal components analysis to derive the weights. This asset index is robust, produces internally coherent results, and provides a close correspondence with data on state domestic product and on state level poverty rates. They validate the asset index using data on consumption spending and asset ownership from Indonesia, Nepal, and Pakistan. The asset index has reasonable coherence with current consumption expenditures and, more importantly, works as well as-or better than-traditional expenditure-based measures in predicting enrollment status. The authors find that on average a child from a wealthy household (in the top 20 percent on the asset index developed for this analysis) is 31 percent more likely to be enrolled in school than a child from a poor household (in the bottom 40 percent). This paper-a product of Poverty and Human Resources, Development Research Group-is part of a larger effort in the group to inform educational policy. The study was funded by the Bank's Research Support Budget under the research project Educational Enrollment and Dropout (RPO 682-11). Deon Filmer may be contacted at [email protected]."@en

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  • "Estimating wealth effects without expenditure data or tears : an application to educational enrollments in states of India"
  • "Estimating wealth effects without expenditure data, or tears : an application to educational enrollments in states of India"@en
  • "Estimating wealth effects without expenditure data - or tears : with an application to educational enrollments in states of India"
  • "Estimating wealth effects without expenditure data-- or tears : an application to educational enrollments in states of India"
  • "Estimating wealth effects without expenditure data, or tears an application to educational enrollments in states of India"@en
  • "Estimating wealth effects without expenditure data -- or tears : with an application to educational enrollment in states of India"@en
  • "Estimating Wealth Effects without Expenditure Data or Tears: With an Application to Educational Enrollments in States of India"@en
  • "Estimating wealth effects without expenditure data - or tears : an application to educational enrollments in states of India"
  • "Estimating wealth effects without expenditure data -- or tears an application to educational enrollments in states of India"
  • "Estimating wealth effects without expenditure data -- or tears : an application to educational enrollments in States of India"