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
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Browning, Martin & Carro, Jesus M., 2014. "Dynamic binary outcome models with maximal heterogeneity," Journal of Econometrics, Elsevier, vol. 178(2), pages 805-823.
- Martin Browning & Jesus M. Carro, 2009. "Dynamic binary outcome models with maximal heterogeneity," Economics Series Working Papers 426, University of Oxford, Department of Economics.
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:cte:werepe:we1117. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ana Poveda)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.