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BY 4.0 license Open Access Published by De Gruyter Open Access November 1, 2016

The Role of Economic Policy Uncertainty in Predicting U.S. Recessions: A Mixed-frequency Markov-switching Vector Autoregressive Approach

  • Mehmet Balcilar EMAIL logo , Rangan Gupta and Mawuli Segnon
From the journal Economics


This paper analyzes the performance of the monthly economic policy uncertainty (EPU) index in predicting recessionary regimes of the (quarterly) U.S. GDP. In this regard, the authors apply a mixed-frequency Markov-switching vector autoregressive (MF-MS-VAR) model, and compare its in-sample and out-of-sample forecasting performances to those of a Markov-switching vector autoregressive model (MS-VAR, where the EPU is averaged over the months to produce quarterly values) and a Markov-switching autoregressive (MS-AR) model. Their results show that the MF-MS-VAR fits the different recession regimes, and provides out-of-sample forecasts of recession probabilities which are more accurate than those derived from the MS-VAR and MS-AR models. The results highlight the importance of using high-frequency values of the EPU, and not averaging them to obtain quarterly values, when forecasting recessionary regimes for the U.S. economy.

JEL Classification: E32; E37; C32


Aastveit, K. A., Natvik, G. J., and Sola, S. (2013). Economic uncertainty and effectiveness of monetary policy. URL in Google Scholar

Alessandri, P., and Mumtaz, H. (2014). Financial regimes and uncertainty shocks. URL in Google Scholar

Bai, J., and Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1): 1–22. URL in Google Scholar

Baker, S., Bloom, N., and Davis, S. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, pages 1–37. URL http://qje.oxfordjournals. org/content/early/2016/07/05/qje.qjw024.abstract.Search in Google Scholar

Bekiros, S., and Paccagnini, A. (2013). On the predictibility of the time-varying VAR and DSGE models. Empirical Economics, 45(1): 635–664. URL in Google Scholar

Berge, T. J., and Jordà, O. (2011). Evaluating the classification of economic activity into recessions and expansions. American Economic Journal: Macroeconomics, 3(2): 246–277. URL in Google Scholar

Bernanke, B. (1983). Irreversibility, uncertainty and cyclical investment. Quarterly Journal of Economics, 98(1): 85–106. URL in Google Scholar

Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3): 623–685. URL in Google Scholar

Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Monthly Weather Review, 78(1): 1–3. URL in Google Scholar

Brock,W., Dechert, D., Scheinkman, J., and LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Reviews, 15(3): 197–235. URL in Google Scholar

Camacho, M. (2013). Mixed frequency VAR models with Markov switching dynamics. Economics Letters, 121(3): 369–373. URL in Google Scholar

Chauvet, M., and Hamilton, J. D. (2006). Nonlinear time series analysis of business cycles, chapter Dating business cycle turning points. Elsevier, North Holland.Search in Google Scholar

Colombo, V. (2013). Economic policy uncertainty in the US: Does it matter for the Euro area. Economics Letters, 121(1): 39–42. URL in Google Scholar

Davies, R. (1987). Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika, 74(1): 33–43. URL in Google Scholar

Diebold, F. X., and Mariano, R. (1995). Comparing predictive accuracy. Journal of Business and Economic Statistics, 13(1): 253–263. URL in Google Scholar

Dixit, A. K., and Pindyck, R. S. (1994). Investment under uncertainty. Princeton: Princeton University Press.10.1515/9781400830176Search in Google Scholar

Estrella, A., and Mishkin, F. S. (1998). Predicting U.S. recessions: Financial variables as leading indicators. The Review of Economics and Statistics, 80(1): 45–61. URL in Google Scholar

Hamilton, D. J., and Raj, B. (2002). New directions in business cycle research and financial analysis. Empirical Economics, 27(2): 149–162. URL in Google Scholar

Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2): 357–384. URL in Google Scholar

Hamilton, J. D. (2008). New palgrave dictionary of economics, chapter Regimeswitching models. Palgrave McMillan Ltd., 2nd edition.Search in Google Scholar

Jones, P. M., and Olson, E. (2013). The time-varying correlation between uncertainty, output and inflation: Evidence from a DCC-GARCH model. Economics Letters, 118(1): 33–37. URL in Google Scholar

Jurado, K., Ludvigson, S. C., and Ng, S. (2015). Measuring uncertainty. The American Economic Review, 105(3): 1177–1216. URL in Google Scholar

Karnizova, L., and Li, J. C. (2014). Economic policy uncertainty, financial markets and probability of US recessions. Economics Letters, 125(2): 261–265. URL in Google Scholar

Mariano, R., and Murasawa, Y. (2003). A new coincident index of business cycles based on monthly and quarterly series. Journal of Applied Econometrics, 18(4): 427–443. URL in Google Scholar

Mumtaz, H., and Theodoridis, K. (2016). The changing transmission of uncertainty shocks in the US: An empirical analysis. Journal of Business and Economic Statistics, pages 1–39. URL in Google Scholar

Mumtaz, H., and Zanetti, F. (2013). The impact of the volatility of monetary policy shocks. Journal of Money, Credit and Banking, 45(4): 535–558. URL in Google Scholar

Ng, S. (2014). Viewpoint: Boosting recessions. Canadian Journal of Economics, 47(1): 1–34. URL in Google Scholar

Ng, S., and Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica, 69(6): 1519–1554. URL in Google Scholar

Redl, C. (2015). Macroeconomic uncertainty in South Africa, Working Paper 509, Ersa Economic Research Southern Africa. URL in Google Scholar

Received: 2016-02-24
Revised: 2016-09-30
Accepted: 2016-10-18
Published Online: 2016-11-01
Published in Print: 2016-12-01

© 2016 Mehmet Balcilar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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