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Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations

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  • Tanizaki, Hisashi
  • Mariano, Roberto S.

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  • Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
    • Handle: RePEc:eee:econom:v:83:y:1998:i:1-2:p:263-290
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    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    3. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    4. 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.
    5. Koop, Gary, 1994. "Recent Progress in Applied Bayesian Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 8(1), pages 1-34, March.
    6. Geweke, John, 1988. "Antithetic acceleration of Monte Carlo integration in Bayesian inference," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 73-89.
    7. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-417, October.
    8. Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-343, March.
    9. Barnett,William A. & Geweke,John & Shell,Karl (ed.), 1989. "Economic Complexity: Chaos, Sunspots, Bubbles, and Nonlinearity," Cambridge Books, Cambridge University Press, number 9780521355636.
    10. Brown, Bryan W & Mariano, Roberto S, 1989. "Measures of Deterministic Prediction Bias in Nonlinear Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 667-684, August.
    11. Mariano, Roberto S & Brown, Bryan W, 1983. "Asymptotic Behavior of Predictors in a Nonlinear Simultaneous System," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 523-536, October.
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    Cited by:

    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.
    2. Motta, Anderson C. O. & Hotta, Luiz K., 2003. "Exact Maximum Likelihood and Bayesian Estimation of the Stochastic Volatility Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(2), November.
    3. Pablo Marshall, 2000. "Difusion De Internet En Chile," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 3(2), pages 143-163.
    4. Yasuhiro Omori & Toshiaki Watanabe, 2003. "Block Sampler and Posterior Mode Estimation for a Nonlinear and Non-Gaussian State-Space Model with Correlated Errors," CIRJE F-Series CIRJE-F-221, CIRJE, Faculty of Economics, University of Tokyo.
    5. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Geweke, John & Tanizaki, Hisashi, 2001. "Bayesian estimation of state-space models using the Metropolis-Hastings algorithm within Gibbs sampling," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 151-170, August.
    7. Cadini, F. & Zio, E. & Avram, D., 2009. "Model-based Monte Carlo state estimation for condition-based component replacement," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 752-758.
    8. Miller, J. Isaac & Park, Joon Y., 2005. "How They Interact to Generate Persistency in Memory," Working Papers 2005-01, Rice University, Department of Economics.
    9. Timothy Cogley, 2005. "Changing Beliefs and the Term Structure of Interest Rates: Cross-Equation Restrictions with Drifting Parameters," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 420-451, April.
    10. Drew Creal, 2012. "A Survey of Sequential Monte Carlo Methods for Economics and Finance," Econometric Reviews, Taylor & Francis Journals, vol. 31(3), pages 245-296.
    11. Silvia Cagnone & Francesco Bartolucci, 2017. "Adaptive Quadrature for Maximum Likelihood Estimation of a Class of Dynamic Latent Variable Models," Computational Economics, Springer;Society for Computational Economics, vol. 49(4), pages 599-622, April.
    12. Cui, Qiurong & Xu, Yuqing & Zhang, Zhengjun & Chan, Vincent, 2021. "Max-linear regression models with regularization," Journal of Econometrics, Elsevier, vol. 222(1), pages 579-600.
    13. Levent Ozbek & Umit Ozlale & Fikri Ozturk, 2003. "Employing Extended Kalman Filter in a Simple Macroeconomic Model," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 3(1), pages 53-65.
    14. Tokovenko, Oleksiy & Gunter, Lewell F., 2008. "Quarterly Storage Model of U.S. Cotton Market: Estimation of the Basis under Rational Expectations," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6435, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    15. J. Huston McCulloch & Prasad V. Bidarkota, 2003. "Signal Extraction can Generate Volatility Clusters," Computing in Economics and Finance 2003 59, Society for Computational Economics.
    16. J. Huston McCulloch & Prasad V. Bidarkota, 2002. "Signal Extraction Can Generate Volatility Clusters From IID Shocks," Working Papers 02-04, Ohio State University, Department of Economics.
    17. Cagnone, Silvia & Bartolucci, Francesco, 2013. "Adaptive quadrature for likelihood inference on dynamic latent variable models for time-series and panel data," MPRA Paper 51037, University Library of Munich, Germany.
    18. Tomohiro Ando, 2008. "Measuring the baseline sales and the promotion effect for incense products: a Bayesian state-space modeling approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 763-780, December.
    19. F Cadini & D Avram & E Zio, 2010. "System state estimation by particle filtering for fault diagnosis and prognosis," Journal of Risk and Reliability, , vol. 224(3), pages 149-158, September.
    20. Chiachío, Juan & Chiachío, Manuel & Sankararaman, Shankar & Saxena, Abhinav & Goebel, Kai, 2015. "Condition-based prediction of time-dependent reliability in composites," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 134-147.
    21. Siem Jan Koopman & Kai Ming Lee, 2005. "Measuring Asymmetric Stochastic Cycle Components in U.S. Macroeconomic Time Series," Tinbergen Institute Discussion Papers 05-081/4, Tinbergen Institute.

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