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Nonparametric identification of dynamic models with unobserved state variables

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  • Hu, Yingyao
  • Shum, Matthew

Abstract

We consider the identification of a Markov process {Wt,Xt∗} when only {Wt} is observed. In structural dynamic models, Wt includes the choice variables and observed state variables of an optimizing agent, while Xt∗ denotes time-varying serially correlated unobserved state variables (or agent-specific unobserved heterogeneity). In the non-stationary case, we show that the Markov law of motion fWt,Xt∗∣Wt−1,Xt−1∗ is identified from five periods of data Wt+1,Wt,Wt−1,Wt−2,Wt−3. In the stationary case, only four observations Wt+1,Wt,Wt−1,Wt−2 are required. Identification of fWt,Xt∗∣Wt−1,Xt−1∗ is a crucial input in methodologies for estimating Markovian dynamic models based on the “conditional-choice-probability (CCP)” approach pioneered by Hotz and Miller.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 171 (2012)
Issue (Month): 1 ()
Pages: 32-44

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Handle: RePEc:eee:econom:v:171:y:2012:i:1:p:32-44

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Web page: http://www.elsevier.com/locate/jeconom

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Citations

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Cited by:
  1. Yingyao Hu & Yutaka Kayaba & Matt Shum, 2010. "Nonparametric Learning Rules from Bandit Experiments: The Eyes have it!," Economics Working Paper Archive 560, The Johns Hopkins University,Department of Economics.
  2. Hu, Yingyao & Shum, Matthew, 2012. "Nonparametric identification of dynamic models with unobserved state variables," Journal of Econometrics, Elsevier, vol. 171(1), pages 32-44.
  3. Yingyao Hu & Matthew Shum & Wei Tan, 2010. "A Simple Estimator for Dynamic Models with Serially Correlated Unobservables," Economics Working Paper Archive 558, The Johns Hopkins University,Department of Economics.
  4. Hanming Fang & Edward Kung, 2012. "Why Do Life Insurance Policyholders Lapse? The Roles of Income, Health and Bequest Motive Shocks," PIER Working Paper Archive 12-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  5. Zhou, Yiyi, 2012. "Failure to Launch in Two-Sided Markets: A Study of the U.S. Video Game Market," MPRA Paper 42002, University Library of Munich, Germany.
  6. Yingyao Hu & Matthew Shum, 2008. "Identifying Dynamic Games with Serially-Correlated Unobservables," Economics Working Paper Archive 546, The Johns Hopkins University,Department of Economics.
  7. Jason R. Blevins, 2011. "Sequential Monte Carlo Methods for Estimating Dynamic Microeconomic Models," Working Papers 11-01, Ohio State University, Department of Economics.
  8. Shiu, Ji-Liang, 2014. "An alternative identification of nonlinear dynamic panel data models with unobserved covariates," Economics Letters, Elsevier, vol. 122(2), pages 338-342.
  9. Patrick Bajari & Chenghuan Sean Chu & Denis Nekipelov & Minjung Park, 2013. "A Dynamic Model of Subprime Mortgage Default: Estimation and Policy Implications," NBER Working Papers 18850, National Bureau of Economic Research, Inc.
  10. Susanne Schennach, 2012. "Measurement error in nonlinear models- a review," CeMMAP working papers CWP41/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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