Timothy Halliday () (Department of Economics, University of Hawaii at Manoa, John A. Burns School of Medicine, University of Hawaii at Manoa)
Abstract
We consider the identification of state dependence in a non-stationary process of binary outcomes within the context of the dynamic logit model with time-variant transition probabilities and an arbitrary distribution for the unobserved heterogeneity. We derive a simple identification result that allows us to calculate a test for state dependence in this model. We also consider alternative tests for state dependence that will have desirable properties only in stationary processes and derive their asymptotic properties when the true underlying process is non-stationary. Finally, we provide Monte Carlo evidence that shows a range of non-stationarity in which the effects of mis-specifying the binary process as stationary are not too large.
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Publisher Info
Paper provided by University of Hawaii at Manoa, Department of Economics in its series Working Papers with number
200601.
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