Axiomatically Sound Poverty Measurement With Scarce Data And Price Dispersion
We derive a parametric formula of the Watts' poverty index for the bivariate lognormal distribution of price indices and nominal living standards. This enables us to analyze the contributions of price and nominal living standard distributions to poverty, to estimate poverty when only means and variances are known. We also derive a statistical inference framework. Using data from peasants in Rwanda in four quarters, we show that poverty estimates based on scarce information are generally not significantly different from nonparametric estimates based on full survey information.
|Date of creation:||Mar 2007|
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- Townsend, Robert M, 1994.
"Risk and Insurance in Village India,"
Econometric Society, vol. 62(3), pages 539-91, May.
- Townsend, R.M., 1991. "Risk and Insurance in Village India," University of Chicago - Economics Research Center 91-3, Chicago - Economics Research Center.
- Robert M. Townsend, . "Risk and Insurance in Village India," University of Chicago - Population Research Center 91-3a, Chicago - Population Research Center.
- van Praag, Bernard M S & Hagenaars, Aldi J M & van Eck, Wim, 1983. "The Influence of Classification and Observation Errors on the Measurement of Income Inequality," Econometrica, Econometric Society, vol. 51(4), pages 1093-108, July.
- Zheng, Buhong, 1997. " Aggregate Poverty Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 11(2), pages 123-62, June.
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