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Marginal homogeneity tests with panel data

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  • Federico Bugni
  • Jackson Bunting
  • Muyang Ren

Abstract

A panel dataset satisfies marginal homogeneity if the time-specific marginal distributions are homogeneous or time-invariant. Marginal homogeneity is relevant in economic settings such as dynamic discrete games. In this paper, we propose several tests for the hypothesis of marginal homogeneity and investigate their properties. We consider an asymptotic framework in which the number of individuals n in the panel diverges, and the number of periods T is fixed. We implement our tests by comparing a studentized or non-studentized T-sample version of the Cramer-von Mises statistic with a suitable critical value. We propose three methods to construct the critical value: asymptotic approximations, the bootstrap, and time permutations. We show that the first two methods result in asymptotically exact hypothesis tests. The permutation test based on a non-studentized statistic is asymptotically exact when T=2, but is asymptotically invalid when T>2. In contrast, the permutation test based on a studentized statistic is always asymptotically exact. Finally, under a time-exchangeability assumption, the permutation test is exact in finite samples, both with and without studentization.

Suggested Citation

  • Federico Bugni & Jackson Bunting & Muyang Ren, 2024. "Marginal homogeneity tests with panel data," Papers 2408.15862, arXiv.org.
  • Handle: RePEc:arx:papers:2408.15862
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    References listed on IDEAS

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    1. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    2. Markus Pauly & Edgar Brunner & Frank Konietschke, 2015. "Asymptotic permutation tests in general factorial designs," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 77(2), pages 461-473, March.
    3. Mitsuru Igami & Nathan Yang, 2016. "Unobserved heterogeneity in dynamic games: Cannibalization and preemptive entry of hamburger chains in Canada," Quantitative Economics, Econometric Society, vol. 7(2), pages 483-521, July.
    4. Marc Ditzhaus & Daniel Gaigall, 2022. "Testing marginal homogeneity in Hilbert spaces with applications to stock market returns," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 749-770, September.
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