Sources of inequality in the Philippines: Insights from stochastic dominance tests for richness and poorness

World Economy ◽  
2019 ◽  
Vol 43 (10) ◽  
pp. 2650-2673 ◽  
Author(s):  
Maria Rebecca Valenzuela ◽  
Wing‐Keung Wong ◽  
Zhen Zhen Zhu
Keyword(s):  
Stochastic Dominance ◽  
The Philippines ◽  
Dominance Tests

scholarly journals Testing for Stochastic Dominance up to a Common Relative Poverty Line

Econometrics ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 5
Author(s):  
Tahsin Mehdi
Keyword(s):  
Stochastic Dominance ◽  
Household Survey ◽  
Monte Carlo Study ◽  
Poverty Line ◽  
Poverty Measurement ◽  
Superior Performance ◽  
Relative Poverty ◽  
Income Distributions ◽  
Household Survey Data ◽  
Dominance Tests

Although a wide array of stochastic dominance tests exist for poverty measurement and identification, they assume the income distributions have independent poverty lines or a common absolute (fixed) poverty line. We propose a stochastic dominance test for comparing income distributions up to a common relative poverty line (i.e., some fraction of the pooled median). A Monte Carlo study demonstrates its superior performance over existing methods in terms of power. The test is then applied to some Canadian household survey data for illustration.

scholarly journals Assessing Deprivation with an Ordinal Variable: Theory and Application to Sanitation Deprivation in Bangladesh

2020 ◽  
Author(s):  
Suman Seth ◽  
Gaston Yalonetzky
Keyword(s):  
Stochastic Dominance ◽  
Poverty Alleviation ◽  
Poverty Measurement ◽  
Variable Theory ◽  
The Past ◽  
The Poor ◽  
Ordinal Variable ◽  
Poverty Measures ◽  
Dominance Tests ◽  
Empirical Illustration

Abstract The challenges associated with poverty measurement using a cardinal variable have received much attention over the past four decades, but there is a dearth of literature on how to meaningfully assess poverty with an ordinal variable. This article proposes a class of simple, intuitive, and policy-relevant poverty measures for ordinal variables. The measures are sensitive to the depth of deprivations, unlike the headcount ratio. Moreover, under appropriate restrictions, the measures ensure that priority is given to the poorest among the poor when targeting, monitoring, and evaluating poverty alleviation programs. To assess the robustness of poverty comparisons to alternative choices of parameters, the article develops various stochastic dominance tests (some of which are novel contributions to the stochastic dominance literature). The empirical illustration documenting changes in sanitation deprivation in Bangladesh showcases the measures’ ability to identify instances in which overall sanitation deprivation improved while leaving the poorest behind.

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