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Original Articles

Markov-Switching Three-Pass Regression Filter

, &
Pages 285-302 | Received 01 Dec 2016, Published online: 16 Oct 2018

References

  • Aastveit, K., Carreiro, A., Clark, T., and Marcellino, M. (2017), “Have Standard VARs Remained Stable since the Crisis?” Journal of Applied Econometrics, 32, 931–951.
  • Abbate, A., and Marcellino, M. (2016), “Point, Interval and Density Forecasts of Exchange Rates with Time-Varying Parameter Models,” Journal of the Royal Statistical Society, Series A, 181, Part 1, 155–179.
  • Amengual, D., and Watson, M. W. (2007), “Consistent Estimation of the Number of Dynamic Factors in a Large N and T Panel,” Journal of Business & Economic Statistics, 25, 91–96.
  • Ang, A., and Timmermann, A. (2012), “Regime Changes and Financial Markets,” Annual Review of Financial Economics, 4, 313–337.
  • Bai, J., and Ng, S. (2008), “Forecasting Economic Time Series using Targeted Predictors,” Journal of Econometrics, 146, 304–317.
  • Barnett, W. A., Chauvet, M., and Leiva-Leon, D. (2016), “Real-Time Nowcasting of Nominal GDP with Structural Breaks,” Journal of Econometrics, 191, 312–324.
  • Bates, B. J., Plagborg-Moller, M., Stock, J. H., and Watson, M. W. (2013), “Consistent Factor Estimation in Dynamic Factor Models with Structural Instability,” Journal of Econometrics, 177, 289–304.
  • Billio, M., Getmansky, M., Lo, A. W., and Pelizzon, L. (2012), “Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors,” Journal of Financial Economics, 104, 535–559.
  • Bry, G., and Boschan, C. (1971), “Cyclical Analysis of Time Series: Procedures and Computer Programs,” National Bureau of Economic Research, Inc., New York, NY.
  • Camacho, M., Pérez-Quirós, G., and Poncela, P. (2012), “Markov-Switching Dynamic Factor Models in Real Time,” CEPR Discussion Papers 8866, C.E.P.R.
  • Canova, F. (1993), “Modelling and Forecasting Exchange Rates with a Bayesian Time-Varying Coefficient Model,” Journal of Economic Dynamics and Control, 17, 233–261.
  • Carter, A., and Steigewald, D. (2012), “Testing for Regime Switching: A Comment,” Econometrica, 80, 1809–1812.
  • Chauvet, M. (1998), “An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching,” International Economic Review, 39, 969–996.
  • Cheng, X., Liao, Z., and Schorfheide, F. (2016), “Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities,” Review of Economic Studies, 83, 1511–1543.
  • Ching, W.-K., Fung, E., and Ng, M. (2002), “A Multivariate Markov Chain Model for Categorical Data Sequences and its Applications in Demand Predictions,” IMA Journal of Management Mathematics, 13, 187–199.
  • Chinn, M. D. (1991), “Some Linear and Nonlinear Thoughts on Exchange Rates,” Journal of International Money and Finance, 10, 214–230.
  • Cho, J. S., and White, H. (2007), “Testing for Regime Switching,” Econometrica, 75, 1671–1720.
  • D’Agostino, A., Gambetti, L., and Giannone, D. (2013), “Macroeconomic Forecasting and Structural Change,” Journal of Applied Econometrics, 28, 82–101.
  • Del Negro, M., and Otrok, C. (2008), “Dynamic Factor Models with Time-Varying Parameters: Measuring Changes in International Business Cycles,” Staff Reports 326, Federal Reserve Bank of New York.
  • De Mol, C., Giannone, D., and Reichlin, L. (2008), “Forecasting using a Large Number of Predictors: Is Bayesian Shrinkage a Valid Alternative to Principal Components?,” Journal of Econometrics, 146, 318–328.
  • Diebold, F. X., and Mariano, R. S. (1995), “Comparing Predictive Accuracy,” Journal of Business & Economic Statistics, 13, 253–263.
  • Diebold, F. X., and Yilmaz, K. (2014), “On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms,” Journal of Econometrics, 182, 119–134.
  • Douc, R., Moulines, E., and Rydén, T. (2004), “Asymptotic Properties of the Maximum Likelihood Estimator in Autoregressive Models with Markov Regime,” Annals of Statistics, 32, 2254–2304.
  • Efron, B., Hastie, T., Johnstone, I., and Tibshirani, R. (2004), “Least Angle Regression,” Annals of Statistics, 32, 407–499.
  • Eickmeier, S., Lemke, W., and Marcellino, M. (2015), “Classical Time Varying Factor-Augmented Vector Auto-Regressive Models Estimation, Forecasting and Structural Analysis,” Journal of the Royal Statistical Society, Series A, 178, 493–533.
  • Engel, C., Mark, N. C., and West, K. D. (2015), “Factor Model Forecasts of Exchange Rates,” Econometric Reviews, 34, 32–55.
  • Forni, M., Hallin, M., Lippi, M., and Reichlin, L. (2005), “The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting,” Journal of the American Statistical Association, 100, 830–840.
  • Foroni, C., Guérin, P., and Marcellino, M. (2018), “Using Low Frequency Information for Predicting High Frequency Variables,” International Journal of Forecasting, forthcoming.
  • Giacomini, R., and Rossi, B. (2010), “Forecast Comparisons in Unstable Environments,” Journal of Applied Econometrics, 25, 595–620.
  • Greenaway-McGrevy, R., Mark, N., Sul, D., and Wu, J.-L. (2016), “Identifying Exchange Rate Common Factors,” Mimeo, Notre Dame.
  • Groen, J., and Kapetanios, G. (2016), “Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting,” Computational Statistics & Data Analysis, 100, 221–239.
  • Guérin, P., and Leiva-Leon, D. (2017), “Monetary Policy, Stock Market and Sectoral Comovement,” Banco de España Working Paper, 1731.
  • Guérin, P., and Marcellino, M. (2013), “Markov-Switching MIDAS Models,” Journal of Business & Economic Statistics, 31, 45–56.
  • Hamilton, J. D., and Owyang, M. T. (2012), “The Propagation of Regional Recessions,” The Review of Economics and Statistics, 94, 935–947.
  • Harding, D., and Pagan, A. (2002), “Dissecting the Cycle: A Methodological Investigation,” Journal of Monetary Economics, 49, 365–381.
  • Hepenstrick, C., and Marcellino, M. (2016), “Forecasting Gross Domestic Product Growth with Large Unbalanced Datasets: The Mixed-Frequency Three-Pass Regression Filter,” Journal of the Royal Statistical Society, Series A, forthcoming.
  • Hubrich, K., and Tetlow, R. J. (2015), “Financial Stress and Economic Dynamics: The Transmission of Crises,” Journal of Monetary Economics, 70, 100–115.
  • Kelly, B., and Pruitt, S. (2015), “The Three-Pass Regression Filter: A New Approach to Forecasting using Many Predictors,” Journal of Econometrics, 186, 294–316.
  • Leroux, B. (1992), “Maximum-Likelihood Estimation for Hidden Markov Models,” Stochastic Processes and their Applications, 40, 127–143.
  • Marcellino, M., Stock, J., and Watson, M. (2006), “A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series,” Journal of Econometrics, 135, 499–526.
  • McCracken, M. W., and Ng, S. (2016), “FRED-MD: A Monthly Database for Macroeconomic Research,” Journal of Business & Economic Statistics, 34, 574–589.
  • Mikkelsen, J. G., Hillebrand, E., and Urga, G. (2015), “Maximum Likelihood Estimation of Time-Varying Loadings in High-Dimensional Factor Models,” CREATES Research Papers 2015-61, School of Economics and Management, University of Aarhus.
  • Nakajima, J., and West, M. (2013), “Bayesian Analysis of Latent Threshold Dynamics Models,” Journal of Business Economics and Statistics, 31, 151–164.
  • Pesaran, M. H., and Timmermann, A. (2009), “Testing Dependence Among Serially Correlated Multicategory Variables,” Journal of the American Statistical Association, 104, 325–337.
  • Rossi, B. (2013), “Exchange Rate Predictability,” Journal of Economic Literature, 51, 1063–1119.
  • Sims, C. (1993), “A 9 Variable Probabilistic Macroeconomic Forecasting Model,” Business Cycles, Indicators and Forecasting, NBER Studies in Business Cycles, 28, 179–214.
  • Sims, C. A., and Zha, T. (2006), “Were There Regime Switches in U.S. Monetary Policy?” American Economic Review, 96, 54–81.
  • Smith, A., Prasad, N., and Tsai, C.-L. (2006), “Markov-Switching Model Selection using Kullback-Leibler Divergence,” Journal of Econometrics, 134, 553–577.
  • Stock, J. H., and Watson, M. W. (1999), “A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series,” in Cointegration, Causality, and Forecasting: A Festschrift in Honor of Clive W.J. Granger, eds. R. Engle and H. White, Oxford: Oxford University Press, pp. 1–44.
  • ——— (2002a), “Forecasting using Principal Components from a Large Number of Predictors,” Journal of the American Statistical Association, 97, 1167–1179.
  • ——— (2002b), “Macroeconomic Forecasting Using Diffusion Indexes,” Journal of Business & Economic Statistics, 20, 147–162.
  • ——— (2016), “Dynamic Factor Models, Factor-augmented Vector Autoregressions, and Structural Vector Autoregressions,” in Handbook of Macroeconomics (Vol. 2), eds. J. B. Taylor, and H. Uhlig, Elsevier, pp. 415–525.
  • Verdelhan, A. (2015), “The Share of Systematic Variation in Bilateral Exchange Rates,” Journal of Finance, 73, 375–418.
  • Von Ganske, J. (2016), “A Regime Switching Partial Least Squares Approach to Forecasting Industry Stock Returns,” Mimeo, Edhec-Risk Institute.

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