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Financial conditions and density forecasts for US Output and inflation

  • Piergiorgio Alessandri
  • Haroon Mumtaz

The authors reassess the predictive power of financial indicators for output and inflation in the US by studying predictive densities generated by set of linear and nonlinear forecasting models. They argue that, if the linkage between financial and real economy is state-dependent as implied by standard models with financial frictions, predictive densities should reveal aspects of the co-movements between financial and macroeconomic variables that are ignored by construction in an ordinary (central) forecasting exercise. The authors study the performance of linear and nonlinear (Threshold and Markov-Switching) VARs estimated on a monthly US dataset including various commonly-used financial indicators. We obtain three important results. First, adding financial indicators to an otherwise standard VAR improves both central forecasts and predictive distributions for output, but the improvement is more substantial for the latter. Even in a linear model, financial indicators are more useful in predicting 'tails', or deviations of output and inflation from their expected paths, than 'means', namely the expected paths themselves. Second, nonlinear models with financial indicators tend to generate noisier central forecasts than their linear counterparts, but they clearly outperform them in predicting distributions. This is mainly because nonlinear models predict the likelihood of recessionary episodes more accurately. Third, the discrepancies between models are themselves predictable: a Bayesian forecaster can formulate a reasonable real-time guess on which model is likely to be more accurate in the near future.Â

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Paper provided by Centre for Central Banking Studies, Bank of England in its series Joint Research Papers with number 4.

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Date of creation: May 2013
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Handle: RePEc:ccb:jrpapr:4
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  1. Nobuhiro Kiyotaki & John Moore, 2012. "Liquidity, Business Cycles and Monetary Policy," ESE Discussion Papers 113, Edinburgh School of Economics, University of Edinburgh.
  2. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-54, December.
  3. Simon Gilchrist & Vladimir Yankov & Egon Zakrajsek, 2009. "Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets," NBER Working Papers 14863, National Bureau of Economic Research, Inc.
  4. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
  5. Deaton, A., 1989. "Saving And Liquidity Constraints," Papers 153, Princeton, Woodrow Wilson School - Public and International Affairs.
  6. Gertler, Mark & Karadi, Peter, 2011. "A model of unconventional monetary policy," Journal of Monetary Economics, Elsevier, vol. 58(1), pages 17-34, January.
  7. pengfei Wang & Tao Zha & Zheng Liu, 2012. "Land-Price Dynamics and Macroeconomic Fluctuations," 2012 Meeting Papers 85, Society for Economic Dynamics.
  8. 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.
  9. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
  10. Clements, M.P. & Smith J., 1998. "Evaluating The Forecast of Densities of Linear and Non-Linear Models: Applications to Output Growth and Unemployment," The Warwick Economics Research Paper Series (TWERPS) 509, University of Warwick, Department of Economics.
  11. Li, Shuyun May & Dressler, Scott, 2011. "Business cycle asymmetry via occasionally binding international borrowing constraints," Journal of Macroeconomics, Elsevier, vol. 33(1), pages 33-41, March.
  12. Sydney Ludvigson, 1996. "Consumption and credit: a model of time-varying liquidity constraints," Research Paper 9624, Federal Reserve Bank of New York.
  13. Kim, Sunghyun Henry & Kollmann, Robert & Kim, Jinill, 2010. "Solving the incomplete market model with aggregate uncertainty using a perturbation method," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 50-58, January.
  14. Gianni Amisano & Raffaella Giacomini, 2005. "Comparing Density Forecsts via Weighted Likelihood Ratio Tests," Working Papers ubs0504, University of Brescia, Department of Economics.
  15. Bianchi, Javier, 2009. "Overborrowing and Systemic Externalities in the Business Cycle," MPRA Paper 16270, University Library of Munich, Germany.
  16. Clark, Todd E., 2011. "Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 327-341.
  17. Cogley, Timothy W. & Morozov, Sergei & Sargent, Thomas J., 2003. "Bayesian fan charts for UK inflation: Forecasting and sources of uncertainty in an evolving monetary system," CFS Working Paper Series 2003/44, Center for Financial Studies (CFS).
  18. Den Haan, Wouter J. & De Wind, Joris, 2012. "Nonlinear and stable perturbation-based approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1477-1497.
  19. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-2009 Recession," NBER Working Papers 18094, National Bureau of Economic Research, Inc.
  20. James Mitchell & Kenneth F. Wallis, 2011. "Evaluating density forecasts: forecast combinations, model mixtures, calibration and sharpness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 1023-1040, 09.
  21. Nolan, Charles & Thoenissen, Christoph, 2008. "Financial shocks and the US business cycle," SIRE Discussion Papers 2008-58, Scottish Institute for Research in Economics (SIRE).
  22. Gordon, S.F. & Filardo, A.J., 1993. "Business Cycle Durations," Papers 9328, Laval - Recherche en Politique Economique.
  23. Nathan S. Balke, 2000. "Credit and Economic Activity: Credit Regimes and Nonlinear Propagation of Shocks," The Review of Economics and Statistics, MIT Press, vol. 82(2), pages 344-349, May.
  24. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
  25. Marcella Lucchetta & Gianni De Nicolo, 2012. "Systemic Real and Financial Risks; Measurement, Forecasting, and Stress Testing," IMF Working Papers 12/58, International Monetary Fund.
  26. Geweke, John & Amisano, Gianni, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 0969, European Central Bank.
  27. Simon Gilchrist & Egon Zakrajšek, 2011. "Credit Spreads and Business Cycle Fluctuations," NBER Working Papers 17021, National Bureau of Economic Research, Inc.
  28. Scott Brave & R. Andrew Butters, 2012. "Diagnosing the Financial System: Financial Conditions and Financial Stress," International Journal of Central Banking, International Journal of Central Banking, vol. 8(2), pages 191-239, June.
  29. Gertler, Mark & Kiyotaki, Nobuhiro, 2010. "Financial Intermediation and Credit Policy in Business Cycle Analysis," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 11, pages 547-599 Elsevier.
  30. McCallum, John, 1991. "Credit Rationing and the Monetary Transmission Mechanism," American Economic Review, American Economic Association, vol. 81(4), pages 946-51, September.
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