Financial Indicators and Density Forecasts for US Output and Inflation

66 Pages Posted: 17 Jan 2015

Date Written: October 23, 2014

Abstract

When do financial markets help in predicting economic activity? With incomplete markets, the link between financial and real economy is state-dependent and financial indicators may turn out to be useful particularly in forecasting "tail" macroeconomic events. We examine this conjecture by studying Bayesian predictive distributions for output growth and inflation in the US between 1983 and 2012, comparing linear and nonlinear VAR models. We find that financial indicators significantly improve the accuracy of the distributions. Regime-switching models perform better than linear models thanks to their ability to capture changes in the transmission mechanism of financial shocks between good and bad times. Such models could have sent a credible advance warning ahead of the Great Recession. Furthermore, the discrepancies between models are themselves predictable, which allows the forecaster to formulate reasonable real-time guesses on which model is likely to be more accurate in the next future.

Keywords: financial frictions, predictive densities, Great Recession, threshold VAR

JEL Classification: C53, E32, E44, G01

Suggested Citation

Alessandri, Piergiorgio and Mumtaz, Haroon, Financial Indicators and Density Forecasts for US Output and Inflation (October 23, 2014). Bank of Italy Temi di Discussione (Working Paper) No. 977, Available at SSRN: https://ssrn.com/abstract=2550781 or http://dx.doi.org/10.2139/ssrn.2550781

Piergiorgio Alessandri (Contact Author)

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Haroon Mumtaz

Queen Mary, University of London ( email )

Lincoln's Inn Fields
Mile End Rd.
London, E1 4NS
United Kingdom

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