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Testing for two components in a switching regression model

By Jörn Dannemann and Hajo Holzmann


Switching regression models form a suitable model class for regression problems with unobserved heterogeneity. A basic issue encountered in applications of switching regression models is to choose the number of states of the switching regime. Based on the modified likelihood ratio test (LRT) statistic a test for two against more states of the regime is proposed, and its asymptotic distribution is derived in the case when there is a single switching parameter. Further, it is shown that the asymptotic distribution of the test remains unchanged if the regime is Markov dependent. A simulation study illustrates the finite-sample behavior of the test. Finally, the methodology is applied to the data of a dental health trial. In this case the model selection criteria AIC and BIC favor distinct binomial regression models with switching intercepts (AIC three states, BIC two states). The modified LRT allows us to reject the null hypothesis of two states in favor of three states.Decayed, missing and filled teeth index Hypothesis testing Logistic regression Switching regression Poisson regression Markov regime

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