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Maximum likelihood estimation of an extended latent markov model for clustered binary panel data

  • Francesco Bartolucci


    (Dipartimento diEconomia, Finanza e Statistica, Universit`a di Perugia,)

  • Valentina Nigro


    (Dipartimento di Studi Economico-Finanziari e Metodi Quantitativi Universit`a di Roma “Tor Vergata”,)

Computational aspects concerning a model for clustered binary panel data are analysed. The model is based on the representation of the behavior of a subject (individual panel member) in a given cluster by means of a latent process that is decomposed into a cluster-specific component, which follows a first-order Markov chain, and an individual-specific component, which is timeinvariant and is represented by a discrete random variable. In particular, an algorithm for computing the joint distribution of the response variables is introduced. The algorithm may be used even in the presence of a large number of subjects in the same cluster. Also an Expectation-Maximization (EM) scheme for the maximum likelihood estimation of the model is described showing how the Fisher information matrix can be estimated on the basis of the numerical derivative of the score vector. The estimate of this matrix is used to compute standard errors for the parameter estimates and to check the identifiability of the model and the convergence of the EM algorithm. The approach is illustrated by means of an application to a dataset concerning Italian employees illness benefits.

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Paper provided by Tor Vergata University, CEIS in its series CEIS Research Paper with number 96.

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Length: 22
Date of creation: 20 Feb 2007
Date of revision:
Handle: RePEc:rtv:ceisrp:96
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  1. Arellano, Manuel & Honore, Bo, 2001. "Panel data models: some recent developments," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 53, pages 3229-3296 Elsevier.
  2. James J. Heckman, 1981. "Heterogeneity and State Dependence," NBER Chapters, in: Studies in Labor Markets, pages 91-140 National Bureau of Economic Research, Inc.
  3. M. Yang & H. Goldstein & A. Heath, 2000. "Multilevel models for repeated binary outcomes: attitudes and voting over the electoral cycle," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(1), pages 49-62.
  4. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
  5. Chintagunta, Pradeep & Kyriazidou, Ekaterini & Perktold, Josef, 2001. "Panel data analysis of household brand choices," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 111-153, July.
  6. V A Hajivassiliou & DL McFadden, 1997. "The Method of Simulated Scores for the Estimation of LDV Models," STICERD - Econometrics Paper Series 328, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  7. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
  8. James J. Heckman & Robert J. Willis, 1975. "A Beta-Logistic Model for the Analysis of Sequential Labor Force Participation by Married Women," NBER Working Papers 0112, National Bureau of Economic Research, Inc.
  9. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-64, May.
  10. Fuertes, Ana-Maria & Kalotychou, Elena, 2006. "Early warning systems for sovereign debt crises: The role of heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1420-1441, November.
  11. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
  12. Francesco Bartolucci, 2006. "Likelihood inference for a class of latent Markov models under linear hypotheses on the transition probabilities," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 155-178.
  13. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-91, May.
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