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Refining Targeting against Poverty Evidence from Tunisia *
Author(s) -
Muller Christophe,
Bibi Sami
Publication year - 2010
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/j.1468-0084.2010.00583.x
Subject(s) - poverty , proxy (statistics) , econometrics , poverty reduction , transfer (computing) , estimation , computer science , economics , machine learning , economic growth , management , parallel computing
We introduce a new methodology to target direct transfers against poverty. Our method is based on estimation methods that focus on the poor . Using data from Tunisia, we estimate ‘focused’ transfer schemes that highly improve anti‐poverty targeting performances. Post‐transfer poverty can be substantially reduced with the new estimation method. For example, a one‐third reduction in poverty severity from proxy‐means test transfer schemes based on OLS method to focused transfer schemes requires only a few hours of computer work based on methods available on popular statistical packages. Finally, the obtained levels of undercoverage of the poor are particularly low.