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Testing for Restricted Stochastic Dominance under Survey Nonresponse with Panel Data: Theory and an Evaluation of Poverty in Australia

Rami V. Tabri, Mathew J. Elias

arXiv 22 Jun 2024 · Econometrics

arXiv:2406.15702 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper lays the groundwork for a unifying approach to stochastic dominance testing under survey nonresponse that integrates the partial identification approach to incomplete data and design-based inference for complex survey data. We propose a novel inference procedure for restricted $s$th-order stochastic dominance, tailored to accommodate a broad spectrum of nonresponse assumptions. The method uses pseudo-empirical likelihood to formulate the test statistic and compares it to a critical value from the chi-squared distribution with one degree of freedom. We detail the procedure's asymptotic properties under both null and alternative hypotheses, establishing its uniform validity under the null and consistency against various alternatives. Using the Household, Income and Labour Dynamics in Australia survey, we demonstrate the procedure's utility in a sensitivity analysis of temporal poverty comparisons among Australian households.

Citation extraction

64
references
102
in-text mentions
64
distinct cited
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18,132
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Davidson, R. and J.-Y. Duclos (2013) Testing for restricted stochastic dominance1.00063100%
2Fakih, A., P. Makdissi, W. Marrouch, R. V. Tabri, and M. Yazbeck (2022) A stochastic dominance test under survey nonresponse with an application to comparing trust levels in lebanese public institutions self0.96510590%
3Foster, J. E. and A. F. Shorrocks (1988) Poverty orderings0.92843100%
4Kline, P. and A. Santos (2013) Sensitivity to missing data assumptions: Theory and an evaluation of the u.s. wage structure0.8435460%
5Wu, C. and J. N. K. Rao (2006) Pseudo-empirical likelihood ratio confidence intervals for complex surveys0.7373367%
6Aitchison, J (1962) Large-sample restricted parametric tests0.73732100%
7Zhao, P., D. Haziza, and C. Wu (2020) Survey weighted estimating equation inference with nuisance functionals0.73732100%
8Watson, N. and T. R. Fry (2002) The household, income and labour dynamics in australia (hilda) survey: Wave 1 weighting0.64441100%
9Bhattacharya, D (2005) Asymptotic inference from multi-stage samples0.64422100%
10Bourguignon, F (2018) Simple adjustments of observed distributions for missing income and missing people0.64422100%

Showing the top 10 of 64 scored citations.