Testing for State Dependence with Time-Variant Transition Probabilities

Timothy Halliday

No 200614, Working Papers from University of Hawaii at Manoa, Department of Economics

Abstract: We consider the identification of state dependence in a dynamic Logit model with timevariant transition probabilities and an arbitrary distribution of the unobserved heterogeneity. We derive a simple result that allows us to test for the presence of state dependence in this model. Monte Carlo evidence suggests that this test has desirable properties even when there are some violations of the model’s assumptions. We also consider alternative tests for state dependence that will have desirable properties only when the transition probabilities do not depend on time and provide evidence that there is an "acceptable" range in which ignoring time-dependence does not matter too much. We conclude with an application to the Barker Hypothesis.

Keywords: Dynamic Panel Data Models; State Dependence; Health (search for similar items in EconPapers)
Pages: 24 pages
Date: 2006-12-31
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (1)

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http://www.economics.hawaii.edu/research/workingpapers/WP_06-14.pdf First version, 2006 (application/pdf)

Related works:
Journal Article: Testing for State Dependence with Time-Variant Transition Probabilities (2007)
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