Poverty analysis with missing data: alternative estimators compared |
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Authors: | Cheti Nicoletti |
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Institution: | 1. Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK
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Abstract: | Poverty models are generally estimated by using sample surveys affected by missing data problems. Most methods proposed to
take account of missing data problems consider point estimators which typically impose restrictive assumptions. However, it
is possible to identify a range of logically possible values for the poverty probability, an identification interval, without
imposing any assumption. It is then of interest to check whether the point estimates lie within the identification interval.
This is a way to check the validity of the assumptions imposed by point estimators. Using the ECHP we perform this check to
assess different estimation methods. |
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