Journal Article

Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality

Duclos, Jean-Yves, Davidson, Russell

2000

Overview

We derive the asymptotic sampling distribution of various estimators frequently used to order distributions in terms of poverty, welfare, and inequality. This includes estimators of most of the poverty indices currently in use, as well as estimators of the curves used to infer stochastic dominance of any order. These curves can be used to determine whether poverty, inequality, or social welfare is greater in one distribution than in another for general classes of indices and for ranges of possible poverty lines. We also derive the sampling distribution of the maximal poverty lines up to which we may confidently assert that poverty is greater in one distribution than in another. The sampling distribution of convenient dual estimators for the measurement of poverty is also established. The statistical results are established for deterministic or stochastic poverty lines as well as for paired or independent samples of incomes. Our results are briefly illustrated using data for four countries drawn from the Luxembourg Income Study data bases.

• Publisher: Blackwell Publishers Ltd,Econometrica Society,Blackwell,George Banta Pub. Co. for the Econometric Society,Blackwell Publishing Ltd
• Subject: Covariance / Distribution / Distribution theory / distribution-free statistical inference / Dominance / Economic theory / Estimators / Exact sciences and technology / Income inequality / Indexes / Inequality / Inference / Mathematics / Measurement / Nonparametric inference / order-restricted inference / Parametric inference / Population distributions / Poverty / Poverty gap / Poverty line / Probability and statistics / Public assistance programs / Sampling / Sampling distributions / Sampling theory, sample surveys / Sciences and techniques of general use / Social inequality / Social welfare / Statistical analysis / Statistical inference / Statistical inferences / Statistics / Stochastic dominance / Stochastic models / Stochastic processes / Studies / Welfare measurement