Identifying State Dependence in Non-Stationary Processes

Timothy Halliday

No 200601, Working Papers from University of Hawaii at Manoa, Department of Economics

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.

Keywords: Dynamic Panel Data Models; State Dependence; Non-Stationary Processes (search for similar items in EconPapers)
Pages: 29 pages
Date: 2006
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-ets
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http://www.economics.hawaii.edu/research/workingpapers/WP_06-1.pdf First version, 2006 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:hai:wpaper:200601

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