The identification of a mixture of first order binary Markov Chains
Let S be the number of components in a finite discrete mixing distribution. We prove that the number of waves of panel being greater than or equal to 2S is a sufficient condition for global identification of a dynamic binary choice model in which all the parameters are heterogeneous. This model results in a mixture of S binary first order Markov Chains
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- Hiroyuki Kasahara & Katsumi Shimotsu, 2009. "Nonparametric Identification of Finite Mixture Models of Dynamic Discrete Choices," Econometrica, Econometric Society, vol. 77(1), pages 135-175, 01.
- Martin Browning & Jesus Carro, 2006. "Heterogeneity and Microeconometrics Modelling," CAM Working Papers 2006-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
- Martin Browning & Jesus M. Carro, 2009.
"Dynamic binary outcome models with maximal heterogeneity,"
Economics Series Working Papers
426, University of Oxford, Department of Economics.
- Browning, Martin & Carro, Jesus M., 2014. "Dynamic binary outcome models with maximal heterogeneity," Journal of Econometrics, Elsevier, vol. 178(2), pages 805-823.
- Carro, Jesús M. & Browning, Martin, 2009. "Dynamic binary outcome models with maximal heterogeneity," UC3M Working papers. Economics we091710, Universidad Carlos III de Madrid. Departamento de Economía.
- Martin Browning & Jesus M. Carro, 2007. "Dynamic Binary Outcome Models with Maximal Heterogeneity," CAM Working Papers 2009-08, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics, revised Feb 2009.
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