Optimising Anti-Poverty Transfers With Quantile Regressions
AbstractAnti-poverty transfer schemes are one of the main way of fightingpoverty. Under perfect observation of incomes, designing such scheme boilsdown to solving an optimisation program under constraints, which can beachieved with well-defined methods. In contrast, when incomes cannot beperfectly observed, the schemes are usually based on predictions of livingstandards using ancillary regressions and household survey data to predict theunobserved living standards of households. In this paper, we study the povertyminimisation program under imperfect information. We show why usingpredictions of living standards helps to deal approximately with an otherwiseintractable problem. Then, we propose a new approach to the practicaloptimisation procedure based on improved predictions of living standards interms of the targeting problem to be solved. Our new empirical methodology totarget direct transfers against poverty is based on observable correlates and onestimation methods that can focus on the poor: the quantile regressions. Weillustrate our results using data from Tunisia.
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Bibliographic InfoPaper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2006-07.
Length: 29 pages
Date of creation: Jun 2006
Date of revision:
Publication status: Published by Ivie
Poverty minimization; Quantile regressions; Policy targeting.;
Other versions of this item:
- Christophe Muller, 2006. "Optimising Anti-Poverty Transfers With Quantile Regressions," IDEP Working Papers 0601, Institut d'economie publique (IDEP), Marseille, France, revised Feb 2006.
- NEP-ALL-2006-06-17 (All new papers)
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