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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| Muut tekijät: | |
| Aineistotyyppi: | Aikakauslehti |
| Kieli: | English |
| Julkaistu: |
Washington, D.C. :
International Monetary Fund,
2008.
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| Sarja: | IMF Working Papers; Working Paper ;
No. 2008/183 |
| Linkit: | Full text available on IMF |