Browsing by Subject "poverty"
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Item Restricted Calculating Comparable Statistics from Incomparable Surveys, with an Application to Poverty in India(2006) Tarozzi, AlessandroApplied economists are often interested in studying trends in important economic indicators, such as inequality or poverty, but comparisons over time can be made impossible by changes in data collection methodology. We describe an easily implemented procedure, based on inverse probability weighting, that allows to recover comparability of estimated parameters identified implicitly by a moment condition. The validity of the procedure requires the existence of a set of auxiliary variables whose reports are not affected by the different survey design, and whose relation with the main variable of interest is stable over time. We analyze the asymptotic properties of the estimator taking into account the presence of clustering, stratification and sampling weights which characterize most household surveys. The main empirical motivation of the paper is provided by a recent controversy on the extent of poverty reduction in India in the 1990s. Due to important changes in the expenditure questionnaire adopted for data collection in the 1999-2000 round of the Indian National Sample Survey, the resulting poverty numbers are likely to understate poverty relative to the previous rounds. We use previous waves of the same survey to provide evidence supporting the plausibility of the identifying assumptions and conclude that most, but not all, of the very large reduction in poverty implied by the official figures appears to be real, and not a statistical artifact.Item Open Access Getting into Poverty Without a Husband, and Getting Out, With or Without(1988) Kniesner, MB McElroy with Thomas; Wilcox, Stephen PInterest in the poverty of U.S. women with children but without husbands stems from numerous sources including (i) the secular growth of this demographic group-up 110 percent since 1970 to a total of 6 million (almost 20 percent of all families) in 1985; (ii) the high poverty rates of these women -34 percent in 1985; (iii) the overrepresentation of blacks in this group-about 42 percent in 1985; (iv) the increasing fraction of children raised in these families-over 16 percent in 1984 vs. 6 percent in 1959; and (v) the size of government transfers to this particular group-almost $17 billion for income support under the AFDC program alone in 1985.1 Our research uncovers some important racial similarities as well as stark differences in how women enter and exit single-mother poverty status.Item Open Access Inequality and Support for Government Responses to Covid-19(IZA Discussion Paper) Dang, Hai-Anh H; Malesky, Edmund; Nguyen, Cuong VietItem Open Access Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas(2008) Deaton, A; Tarozzi, AlessandroHousehold expenditure survey data cannot yield precise estimates of poverty or inequality for small areas for which no or few observations are available. Census data are more plentiful, but typically exclude income and expenditure data. Recent years have seen a widespread use of small-area “poverty maps” based on census data enriched by relationships estimated from household surveys that predict variables not covered by the census. These methods are used to estimate putatively precise estimates of poverty and inequality for areas as small as 20,000 households. In this paper we argue that to usefully match survey and census data in this way requires a degree of spatial homogeneity for which the method provides no basis, and which is unlikely to be satisfied in practice. The relationships that are used to bridge the surveys and censuses are not structural but are projections of missing variables on a subset of those variables that happen to be common to the survey and the census supplemented by local census means appended to the survey. As such, the coefficients of the projections will generally vary from area to area in response to variables that are not included in the analysis. Estimates of poverty and inequality that assume homogeneity will generally be inconsistent in the presence of spatial heterogeneity, and error variances calculated on the assumption of homogeneity will underestimate mean squared errors and overestimate the coverage of calculated confidence intervals. We use data from the 2000 census of Mexico to construct synthetic “household surveys” and to simulate the poverty mapping process. In this context, our simulations show that while the poverty maps contain useful information, their nominal confidence intervals give a misleading idea of precision.