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arXiv · 1503.00994

Empirical phi-divergence test statistics for testing simple null hypotheses based on exponentially tilted empirical likelihood estimators

Angel Felipe·Nirian Martín·Pedro Miranda·Leandro Pardo
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Abstract

In Econometrics, imposing restrictions without assuming underlying distributions to modelize complex realities is a valuable methodological tool. However, if a subset of restrictions were not correctly specified, the usual test-statistics for correctly specified models tend to reject erronously a simple null hypothesis. In this setting, we may say that the model suffers from misspecification. We study the behavior of empirical phi-divergence test-statistics, introduced in Balakrishnan et al. (2015), by using the exponential tilted empirical likelihood estimators of Schennach (2007), as a good compromise between efficiency of the significance level for small sample sizes and robustness under misspecification.

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Angel Felipe, Nirian Martín, Pedro Miranda, Leandro Pardo. 2015-03-03. Empirical phi-divergence test statistics for testing simple null hypotheses based on exponentially tilted empirical likelihood estimators. https://arxiv.org/abs/1503.00994

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