Markov-Switching Dynamic Factor Models in Real Time

We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as ragged edges and mixed frequencies. We examine the theoretical benefits of this extension and corroborate the results through several MonteCarlo simulations. Finally, we assess its empirical reliability to compute real-time inferences of the US business cycle.

[1]  Máximo Camacho,et al.  Jump-and-Rest Effect of U.S. Business Cycles , 2005 .

[2]  Athanasios Orphanides,et al.  The Unreliability of Output-Gap Estimates in Real Time , 2002, Review of Economics and Statistics.

[3]  Dean Croushore,et al.  A real-time data set for macroeconomists , 2001 .

[4]  Michael P. Clements,et al.  Macroeconomic Forecasting With Mixed-Frequency Data , 2008 .

[5]  Marcelle Chauvet,et al.  An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching , 1998 .

[6]  M. Rothschild,et al.  Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets , 1982 .

[7]  J. Geweke,et al.  Bayesian Forecasting , 2004 .

[8]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

[9]  Calyampudi R. Rao,et al.  Linear Statistical Inference and Its Applications. , 1975 .

[10]  J. Stock,et al.  Forecasting Using Principal Components From a Large Number of Predictors , 2002 .

[11]  John R. Hershey,et al.  Approximating the Kullback Leibler Divergence Between Gaussian Mixture Models , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[12]  Maximo Camacho,et al.  Introducing the Euro-Sting: Short-Term Indicator of Euro Area Growth , 2009 .

[13]  James D. Hamilton.  Calling Recessions in Real Time , 2010 .

[14]  Gabriel Pérez-Quirós,et al.  Extracting Nonlinear Signals from Several Economic Indicators , 2012 .

[15]  Clifford Lam,et al.  Estimation of latent factors for high-dimensional time series , 2011 .

[16]  Matteo Ciccarelli,et al.  Information Combination and Forecast (St)Ability Evidence from Vintages of Time-Series Data , 2007 .

[17]  Serena Ng,et al.  Are more data always better for factor analysis , 2006 .

[18]  Marco Lippi,et al.  The Generalized Factor Model: Identification and Estimation , 2000 .

[19]  Measuring business cycles , 1947 .

[20]  Irwin Guttman,et al.  Optimal collapsing of mixture distributions in robust recursive estimation , 1989 .

[21]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[22]  Marco Lippi,et al.  New Eurocoin: Tracking Economic Growth in Real Time , 2007 .

[23]  Jonathan M. Nichols,et al.  Calculation of Differential Entropy for a Mixed Gaussian Distribution , 2008, Entropy.

[24]  Jonathan D. Cryer,et al.  Time Series Analysis , 1986, Encyclopedia of Big Data.

[25]  Olivier Darné,et al.  Dynamic Factor Models: A Review of the Literature , 2013 .

[26]  S. Cui.  Comparison of approximation methods to Kullback–Leibler divergence between Gaussian mixture models for satellite image retrieval , 2016 .

[27]  Pilar Poncela,et al.  More is not always better : back to the Kalman lter in Dynamic Factor Models , 2012 .

[28]  J. Bai,et al.  Forecasting economic time series using targeted predictors , 2008 .

[29]  Volker Wieland,et al.  Data Uncertainty and the Role of Money as an Information Variable for Monetary Policy , 2003, SSRN Electronic Journal.

[30]  J. Stock,et al.  A Probability Model of the Coincident Economic Indicators , 1988 .

[31]  Glenn D. Rudebusch,et al.  Forecasting Output with the Composite Leading Index: A Real-Time Analysis , 1991 .

[32]  N. L. Johnson,et al.  Linear Statistical Inference and Its Applications , 1966 .

[33]  Tom Stark and Dean Croushore.  Forecasting with a Real-Time Data Set for Macroeconomists , 2001 .

[34]  Chang-Jin Kim,et al.  Business Cycle Turning Points, A New Coincident Index, and Tests of Duration Dependence Based on a Dynamic Factor Model With Regime Switching , 1998, Review of Economics and Statistics.

[35]  Marc Hallin,et al.  The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting , 2003 .

[36]  Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions , 2010 .

[37]  Real-Time Measurement of Business Conditions , 2009 .

[38]  Tommaso Proietti,et al.  Dynamic factor analysis with non‐linear temporal aggregation constraints , 2006 .

[39]  Chang‐Jin Kim,et al.  Dynamic linear models with Markov-switching , 1994 .

[40]  R. Mariano,et al.  A New Coincident Index of Business Cycles Based on Monthly and Quarterly Series , 2002 .

[41]  Myung-Jig Kim,et al.  New index of coincident indicators: A multivariate Markov switching factor model approach , 1995 .

[42]  Travis J. Berge,et al.  The Classification of Economic Activity into Expansions and Recessions , 2009 .

[43]  James D. Hamilton.  A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .

[44]  A Comparison of the Real-Time Performance of Business Cycle Dating Methods , 2008 .

[45]  David H. Small,et al.  Nowcasting: the real time informational content of macroeconomic data releases , 2008 .