Poverty analysis with missing data: alternative estimators compared
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DOI: 10.1007/s00181-008-0253-7
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Cited by:
- Pudney, Stephen & Diaz, Yadira, 2013. "Measuring poverty persistence with missing data with an application to Peruvian panel data," ISER Working Paper Series 2013-22, Institute for Social and Economic Research.
- Alessandra Mattei & Fabrizia Mealli & Barbara Pacini, 2014. "Identification of causal effects in the presence of nonignorable missing outcome values," Biometrics, The International Biometric Society, vol. 70(2), pages 278-288, June.
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More about this item
Keywords
Missing data; Partial identification; Propensity score; Imputation; Poverty; C25; I32;All these keywords.
JEL classification:
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
- I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
Statistics
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