Non-Markovian Regime Switching with Endogenous States and Time-Varying State Strengths
AbstractThis article presents a non-Markovian regime switching model in which the regime states depend on the sign of an autoregressive latent variable. The magnitude of the latent variable indexes the `strength' of the state or how deeply the system is embedded in the current regime. The autoregressive nature of this non-Markovian regime switching implies time-varying state transition probabilities, even in the absence of an exogenous covariate. Furthermore, with time-varying regime strengths, the expected duration of a regime is time-varying. In this framework, it is natural to allow the autoregressive latent variable to be endogenous so that regimes are determined jointly with the observed data. We apply the model to GDP growth, as in Hamilton (1989), Albert and Chib (1993) and Filardo and Gordon (1998) to illustrate the relation of the regimes to NBER-dated recessions and the time-varying expected durations of regimes
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 600.
Date of creation: 11 Aug 2004
Date of revision:
Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
Regime switching; Markov Chain Monte Carlo;
Other versions of this item:
- Michael Dueker, 2004. "Non-Markovian Regime Switching with Endogenous States and Time-Varying State Strengths," Econometric Society 2004 Latin American Meetings 34, Econometric Society.
- Siddhartha Chib & Michael J. Dueker, 2004. "Non-Markovian regime switching with endogenous states and time-varying state strengths," Working Papers 2004-030, Federal Reserve Bank of St. Louis.
- F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Eichengreen, Barry & Watson, Mark W & Grossman, Richard S, 1985. "Bank Rate Policy under the Interwar Gold Standard: A Dynamic Probit Model," Economic Journal, Royal Economic Society, vol. 95(379), pages 725-45, September.
- Christopher A. Sims & Tao Zha, 2004.
"Were there regime switches in U.S. monetary policy?,"
2004-14, Federal Reserve Bank of Atlanta.
- Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
- Christopher A. Sims & Tao Zha, 2005. "Were There Regime Switches in U.S. Monetary Policy?," Working Papers 92, Princeton University, Department of Economics, Center for Economic Policy Studies..
- Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-31, May.
- Filardo, Andrew J, 1994.
"Business-Cycle Phases and Their Transitional Dynamics,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 12(3), pages 299-308, July.
- Tom Doan, . "RATS programs to replicate Filardo JBES 1994 paper with time-varying Markov switching," Statistical Software Components RTZ00059, Boston College Department of Economics.
- Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
- Kim, Chang-Jin & Piger, Jeremy & Startz, Richard, 2008.
"Estimation of Markov regime-switching regression models with endogenous switching,"
Journal of Econometrics,
Elsevier, vol. 143(2), pages 263-273, April.
- Chang-Jin Kim & Jeremy M. Piger & Richard Startz, 2004. "Estimation of Markov regime-switching regression models with endogenous switching," Working Papers 2003-015, Federal Reserve Bank of St. Louis.
- de Jong, Robert M. & Woutersen, Tiemen, 2011.
"Dynamic Time Series Binary Choice,"
Cambridge University Press, vol. 27(04), pages 673-702, August.
- Tiemen Woutersen & Robert M. de Jong, 2004. "Dynamic time series binary choice," Econometric Society 2004 North American Summer Meetings 365, Econometric Society.
- Robert M. de Jong & Tiemen Woutersen, 2007. "Dynamic time series binary choice," Economics Working Paper Archive 538, The Johns Hopkins University,Department of Economics.
- Pok-sang Lam, 2004. "A Markov-Switching Model Of Gnp Growth With Duration Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 175-204, 02.
- repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
- Filardo, Andrew J. & Gordon, Stephen F., 1998.
"Business cycle durations,"
Journal of Econometrics,
Elsevier, vol. 85(1), pages 99-123, July.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
- Chib, Siddhartha & Greenberg, Edward, 1996.
"Markov Chain Monte Carlo Simulation Methods in Econometrics,"
Cambridge University Press, vol. 12(03), pages 409-431, August.
- Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, EconWPA, revised 24 Oct 1994.
- Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2012.
"Combination schemes for turning point predictions,"
The Quarterly Review of Economics and Finance,
Elsevier, vol. 52(4), pages 402-412.
- Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combination Schemes for Turning Point Predictions," Tinbergen Institute Discussion Papers 11-123/4, Tinbergen Institute.
- Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Combination schemes for turning point predictions," Working Paper 2012/04, Norges Bank.
- Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Combination schemes for turning point predictions," Working Papers 2012_15, Department of Economics, University of Venice "Ca' Foscari".
- Mark W. French, 2005. "A nonlinear look at trend MFP growth and the business cycle: result from a hybrid Kalman/Markov switching model," Finance and Economics Discussion Series 2005-12, Board of Governors of the Federal Reserve System (U.S.).
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.