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Bounds on Parameters in Panel Dynamic Discrete Choice Models

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Author Info
Bo E. Honoré
Elie Tamer
Abstract

Identification of dynamic nonlinear panel data models is an important and delicate problem in econometrics. In this paper we provide insights that shed light on the identification of parameters of some commonly used models. Using these insights, we are able to show through simple calculations that point identification often fails in these models. On the other hand, these calculations also suggest that the model restricts the parameter to lie in a region that is very small in many cases, and the failure of point identification may, therefore, be of little practical importance in those cases. Although the emphasis is on identification, our techniques are constructive in that they can easily form the basis for consistent estimates of the identified sets. Copyright The Econometric Society 2006.

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File URL: http://hdl.handle.net/10.1111/j.1468-0262.2006.00676.x
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Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 74 (2006)
Issue (Month): 3 (05)
Pages: 611-629
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Handle: RePEc:ecm:emetrp:v:74:y:2006:i:3:p:611-629

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  1. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389. [Downloadable!]
  2. Heiss, Florian, 2006. "Nonlinear State-Space Models for Microeconometric Panel Data," Discussion Papers in Economics 1157, University of Munich, Department of Economics. [Downloadable!]
  3. Martin Browning & Jesus M. Carro, 2009. "Dynamic binary outcome models with maximal heterogeneity," Economics Series Working Papers 426, University of Oxford, Department of Economics. [Downloadable!]
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  4. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2009. "Identification and estimation of marginal effects in nonlinear panel models," CeMMAP working papers CWP05/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
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  5. Jörg Stoye, 2008. "More on confidence intervals for partially identified parameters," CeMMAP working papers CWP11/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
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  6. Hiroyuki Kasahara & Katsumi Shimotsu, 2006. "Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices," UWO Department of Economics Working Papers 20065, University of Western Ontario, Department of Economics. [Downloadable!]
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  7. Timothy J. Halliday, 2006. "Testing for State Dependence with Time-Variant Transition Probabilities," Working Papers 200614, University of Hawaii at Manoa, Department of Economics. [Downloadable!]
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  8. Francesco Bartolucci† & Valentina Nigro, 2007. "A dynamic model for binary panel data with unobserved heterogeneity admitting a Vn-consistent conditional estimator," CEIS Research Paper 97, Tor Vergata University, CEIS. [Downloadable!]
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