Testing for State Dependence with Time-Variant Transition Probabilities

We derive a simple result that allows us to test for the presence of state dependence in a dynamic Logit model with time-variant transition probabilities and an arbitrary distribution of the unobserved heterogeneity. 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 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.