Bayesian Inference for the Mixed-Frequency VAR Model
AbstractIn this paper a mixed-frequency VAR à la Mariano & Murasawa (2004) with Markov regime switching in the parameters is estimated by Bayesian inference. Unlike earlier studies, that used the pseuo-EM algorithm of Dempster, Laird & Rubin (1977) to estimate the model, this paper describes how to make use of recent advances in Bayesian inference on mixture models. This way, one is able to surmount some well-known issues connected to inference on mixture models, e.g. the label switching problem. The paper features a numerical simulation study to gauge the model performance in terms of convergence to true parameter values and a small empirical example involving US business cycles.
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Bibliographic InfoPaper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 1172.
Length: 22 : Anh. p.
Date of creation: 2011
Date of revision:
Markov mixture models; Label switching; Bayesian VAR; Mixed frequencies;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
- E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-14 (All new papers)
- NEP-ECM-2011-11-14 (Econometrics)
- NEP-ETS-2011-11-14 (Econometric Time Series)
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- Roberto S. Mariano & Yasutomo Murasawa, 2004.
"Constructing a Coincident Index of Business Cycles without Assuming a One-factor Model,"
22-2004, Singapore Management University, School of Economics, revised Oct 2004.
- Yasutomo Murasawa & Roberto S. Mariano, 2004. "Constructing a Coincident Index of Business Cycles Without Assuming a One-Factor Model," Econometric Society 2004 Far Eastern Meetings 710, Econometric Society.
- John Geweke, 1991. "Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments," Staff Report 148, Federal Reserve Bank of Minneapolis.
- Hamilton, James D., 2011.
"Calling recessions in real time,"
International Journal of Forecasting,
Elsevier, vol. 27(4), pages 1006-1026, October.
- Konstantin A. KHOLODILIN, 2001. "Markov-Switching Common Dynamic Factor Model with Mixed-Frequency Data," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2001020, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2009.
"MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area,"
CEPR Discussion Papers
7445, C.E.P.R. Discussion Papers.
- Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542.
- Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542, April.
- Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," Economics Working Papers ECO2009/32, European University Institute.
- Stephen Godfeld & Richard Quandt, 1973. "The Estimation Of Structural Shifts By Switching Regressions," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 2, number 4, pages 473-483 National Bureau of Economic Research, Inc.
- 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.
- Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
- Tommaso Proietti & Filippo Moauro, 2006.
"Dynamic factor analysis with non-linear temporal aggregation constraints,"
Journal of the Royal Statistical Society Series C,
Royal Statistical Society, vol. 55(2), pages 281-300.
- Tommaso Proietti & Filippo Moauro, 2004. "Dynamic Factor Analysis with Nonlinear Temporal Aggregation Constraints," Econometrics 0401003, EconWPA.
- Marin, Jean-Michel & Mengersen, Kerrie & Robert, Christian P., 2005. "Bayesian Modelling and Inference on Mixtures of Distributions," Economics Papers from University Paris Dauphine 123456789/6069, Paris Dauphine University.
- Zadrozny, Peter, 1988. "Gaussian Likelihood of Continuous-Time ARMAX Models When Data Are Stocks and Flows at Different Frequencies," Econometric Theory, Cambridge University Press, vol. 4(01), pages 108-124, April.
- Gary Koop & Dimitris Korobilis, 2009.
"Bayesian Multivariate Time Series Methods for Empirical Macroeconomics,"
Working Paper Series
47_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
- Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
- Koop, Gary & Korobilis, Dimitris, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," MPRA Paper 20125, University Library of Munich, Germany.
- Sims, Christopher A & Zha, Tao, 1998.
"Bayesian Methods for Dynamic Multivariate Models,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-68, November.
- Ivan Jeliazkov & Rui Liu, 2010. "A model-based ranking of U.S. recessions," Economics Bulletin, AccessEcon, vol. 30(3), pages 2289-2296.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
- Kadiyala, K Rao & Karlsson, Sune, 1997.
"Numerical Methods for Estimation and Inference in Bayesian VAR-Models,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
- John C. Robertson & Ellis W. Tallman, 1999.
"Improving forecasts of the federal funds rate in a policy model,"
99-3, Federal Reserve Bank of Atlanta.
- Robertson, John C & Tallman, Ellis W, 2001. "Improving Federal-Funds Rate Forecasts in VAR Models Used for Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 324-30, July.
- Christopher A. Sims, 1992.
"A Nine Variable Probabilistic Macroeconomic Forecasting Model,"
Cowles Foundation Discussion Papers
1034, Cowles Foundation for Research in Economics, Yale University.
- Christopher A. Sims, 1993. "A Nine-Variable Probabilistic Macroeconomic Forecasting Model," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 179-212 National Bureau of Economic Research, Inc.
- Christopher A. Sims, 1989. "A nine variable probabilistic macroeconomic forecasting model," Discussion Paper / Institute for Empirical Macroeconomics 14, Federal Reserve Bank of Minneapolis.
- Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
- Sylvia Fruhwirth-Schnatter, 2004. "Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 143-167, 06.
- Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
- Claudia Foroni & Massimiliano Marcellino, 2013.
"A survey of econometric methods for mixed-frequency data,"
Economics Working Papers
ECO2013/02, European University Institute.
- Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
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