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Loading... Kernel density estimation based on grouped data : the case of poverty assessmentby Camelia Minoiu
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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 with the bandwidth, the kernel, the number of datapoints, and across poverty lines. Depending on the chosen bandwidth, the 1/day poverty rate in 2000 varies by a factor of 1.8, while the 2/day headcount in 2000 varies by 287 million people. Our findings challenge the validity and robustness of pove No library descriptions found. |
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Google Books — Loading... GenresMelvil Decimal System (DDC)339.46Social sciences Economics Macroeconomics and related topics Factors Impacting GDP PovertyLC ClassificationRatingAverage: No ratings.Is this you?Become a LibraryThing Author. |