Nonlinear State-Space Models for Microeconometric Panel Data
In applied microeconometric panel data analyses, time-constant random effects and first-order Markov chains are the most prevalent structures to account for intertemporal correlations in limited dependent variable models. An example from health economics shows that the addition of a simple autoregressive error terms leads to a more plausible and parsimonious model which also captures the dynamic features better. The computational problems encountered in the estimation of such models -- and a broader class formulated in the framework of nonlinear state space models -- hampers their widespread use. This paper discusses the application of different nonlinear filtering approaches developed in the time-series literature to these models and suggests that a straightforward algorithm based on sequential Gaussian quadrature can be expected to perform well in this setting. This conjecture is impressively confirmed by an extensive analysis of the example application.
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- Florian Heiss & Axel Börsch-Supan & Michael Hurd & David A. Wise, 2009.
"Pathways to Disability: Predicting Health Trajectories,"
NBER Chapters,in: Health at Older Ages: The Causes and Consequences of Declining Disability among the Elderly, pages 105-150
National Bureau of Economic Research, Inc.
- Heiss, Florian & Börsch-Supan, Axel & Hurd, Michael D. & Wise, David A., 2006. "Pathways to disability : predicting health trajectories," Papers 07-30, Sonderforschungsbreich 504.
- Florian Heiss & Axel BÃ¶rsch-Supan & Michael Hurd & David Wise, 2007. "Pathways to Disability: Predicting Health Trajectories," MEA discussion paper series 07131, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
- Heiss, Florian & Börsch-Supan, Axel & Hurd, Michael & Wise, David, 2006. "Pathways to Disability: Predicting Health Trajectories," Sonderforschungsbereich 504 Publications 07-30, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
- Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics,in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441 Elsevier.
- Hajivassiliou, Vassilis A & Ruud, Paul A., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Department of Economics, Working Paper Series qt3cg196fr, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- V.A. Hajivassiliou & P. A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Econometrics 9311002, EconWPA.
- Vassilis A. Hajivassiliou and Paul A. Ruud., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Economics Working Papers 93-219, University of California at Berkeley.
- Vassilis A. Hajivassiliou & Paul A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Cowles Foundation Discussion Papers 1051, Cowles Foundation for Research in Economics, Yale University.
- Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
- Heiss, Florian & Winschel, Viktor, 2006. "Estimation with Numerical Integration on Sparse Grids," Discussion Papers in Economics 916, University of Munich, Department of Economics.
- Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35.
- Lee, L.F., 1994. "Simulated Maximum Likelihood Estimation of Dynamic Discrete Choice Statistical Models--Some Monte Carlo Results," Papers 94-06, Michigan - Center for Research on Economic & Social Theory.
- Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
- Jeffrey M. Wooldridge, 2002. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," CeMMAP working papers CWP18/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- Bo E. Honoré & Elie Tamer, 2006. "Bounds on Parameters in Panel Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 74(3), pages 611-629, 05.
- Danielsson, J & Richard, J-F, 1993. "Accelerated Gaussian Importance Sampler with Application to Dynamic Latent Variable Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 153-173, Suppl. De.
- Paul Contoyannis & Andrew M. Jones & Nigel Rice, 2004. "The dynamics of health in the British Household Panel Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(4), pages 473-503.
- Tanizaki, Hisashi & Mariano, Roberto S, 1994. "Prediction, Filtering and Smoothing in Non-linear and Non-normal Cases Using Monte Carlo Integration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 163-179, April-Jun.
- 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 761-764, May. Full references (including those not matched with items on IDEAS)