Kernel Density Estimation Based on Grouped Data : The Case of Poverty Assessment /

We analyze the performance of kernel density methods applied to grouped data to estimate poverty (as applied in Sala-i-Martin, 2006, QJE). Using Monte Carlo simulations and household surveys, we find that the technique gives rise to biases in poverty estimates, the sign and magnitude of which vary w...

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Bibliografiska uppgifter
Huvudupphovsman: Minoiu, Camelia
Övriga upphovsmän: Reddy, Sanjay
Materialtyp: Tidskrift
Språk:English
Publicerad: Washington, D.C. : International Monetary Fund, 2008.
Serie:IMF Working Papers; Working Paper ; No. 2008/183
Länkar:Full text available on IMF