Ghent, Andra (2006): Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?
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I generate priors for a VAR from four competing models of economic fluctuations: a standard RBC model, Fisher’s (2006) investment-specific technology shocks model, an RBC model with capital adjustment costs and habit formation, and a sticky price model with an unaccommodating monetary authority. I compare the accuracy of the forecasts made with each of the resulting VARs. The economic models generate similar forecast errors to one another. However, at horizons of one to two years and greater, the models generally yield superior forecasts to those made using both an unrestricted VAR and a VAR that uses shrinkage from a Minnesota prior.
|Item Type:||MPRA Paper|
|Original Title:||Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?|
|Keywords:||Model Evaluation; Priors from DSGE models; Economic Fluctuations; Hours Debate; Business Cycles;|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations; Cycles
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods; Simulation Methods
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General
|Depositing User:||Andra Ghent|
|Date Deposited:||07. Oct 2006|
|Last Modified:||13. Feb 2013 03:21|
Altig, D., L.J. Christiano, M. Eichenbaum, and J. Linde, 2004. Firm-Specific Capital, Nominal Rigidities and the Business Cycle. Manuscript, Northwestern University.
Basu, S., J. Fernald, and M. Kimball, 2006. Are Technology Improvements Contractionary? American Economic Review, forthcoming.
Baxter, M. and R.G. King, 1999. Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series. The Review of Economics and Statistics 81, 575-593.
Beaudry, P. and A. Guay, 1996. What Do Interest Rates Reveal About the Functioning of Real Business Cycle Models? Journal of Economic Dynamics and Control 20, 1661-1682.
Bils, M. and P.J. Klenow, 2004. Some Evidence on the Importance of Sticky Prices. Journal of Political Economy 112, 947-985.
Blanchard, O.J. and C.M. Kahn, 1980. The Solution of Linear Difference Models under Rational Expectations. Econometrica 48, 1305-1312.
Boldrin, M., L. Christiano, and J. Fisher, 2001. Habit Persistence, Asset Returns, and the Business Cycle. American Economic Review 79, 655-673.
Calvo, G.A., 1983. Staggered Prices in a Utility-Maximizing Framework. Journal of Monetary Economics 12, 383-398.
Chari, V.V., P.J. Kehoe, and E.R. McGrattan, 2000. Sticky Price Models of the Business Cycle: Can the Contract Multiplier Solve the Persistence Problem? Econometrica 68, 1151-1179.
Chari, V.V., P.J. Kehoe, and E.R. McGrattan, 2005. A Critique of Structural VARs Using Real Business Cycle Theory. Federal Reserve Bank of Minneapolis Staff Report 364.
Christiano, L.J., M. Eichenbaum, and C. Evans, 2005. Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy. Journal of Political Economy 113, 1-45.
Christiano, L.J., M. Eichenbaum, and R. Vigfusson, 2003. What Happens After a Technology Shock? NBER Working Paper 9819.
Clarida, R., J. Gali, and M. Gertler, 1999. The Science of Monetary Policy: A New Keynesian Perspective. Journal of Economic Literature 37, 1661-1707.
Comin, D. and M. Gertler, 2006. Medium Term Business Cycles. American Economic Review 96, 523-551.
Del Negro, J. and F. Schorfheide, 2004. Priors from General Equilibrium Models for VARS. International Economic Review 45, 643-673.
Del Negro, J., F. Schorfheide, F. Smets, and R. Wouters, 2005. On the Fit and Forecasting Performance of New-Keynesian Models. European Central Bank Working Paper No. 491.
Diebold, F.X. and R.S. Mariano, 1995. Comparing Predictive Accuracy. Journal of Business & Economic Statistics 13, 253-263.
Doan, T., R. Litterman, and C. Sims, 1984. Forecasting and Conditional Projection Using Realistic Prior Distributions. Econometric Reviews 3, 1-100.
Eichenbaum, M. and J.D.M. Fisher, 2004. Evaluating the Calvo Model of Sticky Prices. NBER Working Paper 10617.
Erceg, C.J., L. Guerrieri, and C. Gust, 2006. Can Long-Run Restrictions Identify Technology Shocks? Journal of the European Economic Association, forthcoming.
Erceg, C.J., D.W. Henderson, and A.T. Levin, 2000. Optimal Monetary Policy with Staggered Wage and Price Contracts. Journal of Monetary Economics 46, 281-313.
Fernald, J., 2004. Trend Breaks, Long Run Restrictions, and the Contractionary Effects of Technology Shocks. Manuscript, Federal Reserve Bank of San Francisco.
Fernandez-Villaverde, J. and J.F. Rubio-Ramirez, 2004. Comparing Dynamic Equilibrium Models to Data: A Bayesian Approach. Journal of Econometrics 123, 153-187.
Fernandez-Villaverde, J., J.F. Rubio-Ramirez, and T.J. Sargent, 2005. A, B, C’s (and D)’s for Understanding VARs. NBER Technical Working Paper 308.
Fisher, J.D.M., 2006. The Dynamic Effects of Neutral and Investment-Specific Technology Shocks. Journal of Political Economy 114, 413-451.
Francis, N. and V.A. Ramey, 2005a. Is the Technology-Driven Real Business Cycle Hypothesis Dead? Shocks and Aggregate Fluctuations Revisited. Journal of Monetary Economics 52, 1379-1399.
Francis, N. and V.A. Ramey, 2005b. Measures of Per Capita Hours and their Implications for the Technology-Hours Debate. Manuscript, University of California, San Diego.
Gali, J., 1999. Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations? American Economic Review 89, 249-271.
Gali, J., J.D. Lopez-Salido, and J. Valles, 2003. Technology Shocks and Monetary Policy: Assessing the Fed’s Performance. Journal of Monetary Economics 50, 723-743.
Giacomini, R. and H. White, 2005. Tests of Conditional Predictive Ability. Manuscript, University of California, Los Angeles.
Greenwood, J., Z. Hercowitz, and P. Krusell, 1997. Long-Run Implications of Investment-Specific Technological Change. American Economic Review 87, 342-362.
Hansen, G.D., 1985. Indivisible Labor and the Business Cycle. Journal of Monetary Economics 16, 309-327.
Hulten, C.R., 1992. Growth Accounting When Technological Change is Embodied in Capital. American Economic Review 82, 964-980.
Ingram, B.F. and C.H. Whiteman, 1994. Supplanting the ‘Minnesota’ Prior: Forecasting Macroeconomic Time Series Using Real Business Cycle Model Priors. Journal of Monetary Economics 34, 497-510.
Ireland, P.N., 2001. Sticky Price Models of the Business Cycle: Specification and Stability. Journal of Monetary Economics 47, 3-18.
Ireland, P. N., 2003. Notes on Ireland (2004). Manuscript, Boston College.
Ireland, P. N., 2004. A Method for Taking Models to the Data. Journal of Economic Dynamics & Control 28, 1205-1226.
Jermann, U.J., 1998. Asset Pricing in Production Economies. Journal of Monetary Economics 41, 257-275.
Jones, C.I., 2002. Using Chain-Weighted NIPA Data. FRBSF Economic Letter 2002-22, 1-3.
Judge, G.G., W.E. Griffiths, R.C. Hill, H. Lutkepohl, and T-C. Lee, 1985. The Theory and Practice of Econometrics, 2nd ed. (John Wiley and Sons, New York).
Kadiyala, K.R. and S. Karlsson, 1997. Numerical Methods for Estimation and Inference in Bayesian VAR Models. Journal of Applied Econometrics 12, 99-132.
Kim, C-J. and C.R. Nelson, 1999. Has the US Economy Become More Stable? A Bayesian Approach Based on a Markov-Switching Model of the Business Cycle. The Review of Economics and Statistics 81, 608-616.
King, R.G., C.I. Plosser, and S.T. Rebelo, 1988. Production, Growth and Business Cycles: I. The Basic Neoclassical Model. Journal of Monetary Economics 21, 195-232.
King, R.G., C.I. Plosser, J.H. Stock, and M.W. Watson, 1991. Stochastic Trends and Economic Fluctuations. The American Economic Review 81, 819-840.
King, R.G. and A.L. Wolman, 1996. Inflation Targeting in a St. Louis Model of the 21st Century. NBER Working Paper 5507.
Korenok, O. and N.R. Swanson, 2005. The Incremental Predictive Information Associated with Using New Keynesian DSGE Models vs. Simple Linear Econometric Models. Oxford Bulletin of Economics and Statistics 67, 905-930.
Linde, J., 2005. The Effects of Permanent Technology Shocks on Labor Productivity and Hours in the RBC Model. Manuscript, Sveriges Riksbank.
Litterman, R.B., 1986. Forecasting with Bayesian Vector Autoregressions: Five Years of Experience. Journal of Business & Economic Statistics 4, 25-38.
Malley, J.R., V.A. Muscatelli, and U. Woitek, 2005. Real Business Cycles, Sticky Wages, or Sticky Prices? The Impact of Technology Shocks on US Manufacturing. European Economic Review 49, 745-760.
Manuelli, R.E., 2003. Technological Change, the Labor Market and the Stock Market. Manuscript, University of Wisconsin, Madison.
McConnell, M.M. and G. Perez-Quiros, 2000. Output Fluctuations in the United States: What Has Changed since the Early 1980’s? American Economic Review 90, 1464-1476.
Ni, S. and D. Sun, 2003. Noninformative Priors and Frequentist Risks of Bayesian Estimators of Vector-Autoregressive Models. Journal of Econometrics 115, 159-197.
Perron, P. and T. Wada, 2005. Trends and Cycles: A New Approach and Explanations of Some Old Puzzles. Manuscript, Boston University.
Pesavento, E. and B. Rossi, 2005. Do Technology Shocks Drive Hours Up or Down? A Little Evidence from an Agnostic Procedure. Macroeconomic Dynamics 9, 469-477.
Rabanal, P. and J.F. Rubio-Ramirez, 2005. Comparing New Keynesian Models of the Business Cycle: A Bayesian Approach. Journal of Monetary Economics 52, 1151-1166.
Robertson, J.C. and E.W. Tallman, 1999. Vector Autoregressions: Forecasting and Reality. Federal Reserve Bank of Atlanta Economic Review 1st quarter, 4-18.
Rotemberg, J.J., 2003. Stochastic Technical Progress, Smooth Trends, and Nearly Distinct Business Cycles. American Economic Review 93, 1543-1559.
Sims, C.A. and T. Zha, 1998. Bayesian Methods for Dynamic Multivariate Models. International Economic Review 39, Symposium on Forecasting and Empirical Methods in Macroeconomics and Finance, 949-968.
Todd, R.M., 1984. Improving Economic Forecasting with Bayesian Vector Autoregression. Federal Reserve Bank of Minneapolis Quarterly Review 8, 18-29.
Walsh, C.E., 2003. Monetary Theory and Policy, 2nd ed. (MIT Press, Cambridge, Massachusetts).
West, K.D., 2005. Forecast Evaluation, in G. Elliott, C.W.J. Granger, and A. Timmermann, eds., Handbook of Economic Forecasting, forthcoming (Elsevier).
Whelan, K., 2000. A Guide to the Use of Chain Aggregated NIPA Data. Manuscript, Federal Reserve Board of Governors.
Woodford, M., 2003. Interest and Prices: Foundations of a Theory of Monetary Policy. (Princeton University Press, Princeton).
Yun, T., 1996. Nominal Price Rigidity, Money Supply Endogeneity, and Business Cycles. Journal of Monetary Economics 37, 345-370.