IDENTIFYING THE ROLE OF RISK SHOCKS IN THE BUSINESS CYCLE USING STOCK PRICE DATA

Authors

  • SAMI ALPANDA

    1. Alpanda: Canadian Economic Analysis Department, Bank of Canada, 234 Wellington Street, Ottawa, Ontario K1A 0G9, Canada. Phone 613-782-7619, Fax 613-782-7163, E-mail salpanda@bankofcanada.ca
    Search for more papers by this author
    • I thank Alejandro Badel, Dan Barbezat, Olivier Blanchard, John Cochrane, Silvio Contessi, Ricardo DiCeccio, Jose Dorich, William Gavin, Paul Johnson, Ergys Islamaj, Jens Iversen, Sharon Kozicki, Kenneth Kuttner, Enrique Martinez-Garcia, Ellen McGrattan, Rhys Mendes, Enrique Mendoza, Adrian Peralta-Alva, Andrea Pescatori, Robert Rebelein, Juan Rubio-Ramirez, Steven Schmeiser, Katherine Sims, Yi Wen, Geoffrey Woglom, seminar participants at Bank of Canada, Colby College, Federal Reserve Bank of St. Louis, IMF, JCT, University of South Carolina, Union College, Vassar College, Wesleyan University, EEA 2010, NBEA 2010 and WEAI 2010, and Coeditor Erwan Quintin and anonymous referees for suggestions and comments. All remaining errors are my own. The views expressed in this paper are solely those of the author. No responsibility for them should be attributed to the Bank of Canada.


Abstract

I analyze the sources of U.S. business cycle fluctuations in an estimated Dynamic Stochastic General Equilibrium model with a rich set of nominal and real rigidities and various exogenous disturbances. The model includes a shock to the expected risk-premium, which introduces a time-varying wedge between the policy rate set by the central bank and the cost-of-capital of firms. In the aggregate data, most U.S. corporations finance their investment using internal funds, and stock prices reveal the opportunity cost of this type of financing. I therefore use corporate market value and dividend data in the Bayesian estimation of the model to identify risk shocks. Variance decomposition exercises show that these shocks account for a substantial part of the variation in the stock market, as well as the variation in output and investment, especially at short forecast horizons. The variation of these variables at longer forecast horizons are mainly captured by shocks to investment-specific technological change. Historical decomposition points to the important role played by risk shocks in the run up of stock prices and output in the late 90s, and in the reversal of these variables in the early 2000s and during the recent recession. (JEL E32, E44)

Ancillary