Identifying State Dependence in Non-Stationary Processes
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.
|Date of creation:||2006|
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- Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
- Thierry Magnac, 2003.
"Panel Binary Variables and Sufficiency: Generalizing Conditional Logit,"
Research Unit Working Papers
0308, Laboratoire d'Economie Appliquee, INRA.
- Thierry Magnac, 2004. "Panel Binary Variables and Sufficiency: Generalizing Conditional Logit," Econometrica, Econometric Society, vol. 72(6), pages 1859-1876, November.
- Hahn, Jinyong, 2001. "The Information Bound Of A Dynamic Panel Logit Model With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 17(05), pages 913-932, October.
- Bo E. Honoré & Elie Tamer, 2002. "Bounds on Parameters in Dynamic Discrete Choice Models," CAM Working Papers 2004-23, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics, revised Aug 2004.
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