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Technology shocks and aggregate fluctuations in an estimated hybrid RBC model

  • Jim Malley
  • Ulrich Woitek

This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of technology shocks in explaining aggregate fluctuations. To this end we estimate the model’s posterior density using Markov-Chain Monte-Carlo (MCMC) methods. Within this framework we extend Ireland’s (2001, 2004) hybrid estimation approach to allow for a vector autoregressive moving average (VARMA) process to describe the movements and co-movements of the model’s errors not explained by the basic RBC model. The results of marginal likelihood ratio tests reveal that the more general model of the errors significantly improves the model’s fit relative to the VAR and AR alternatives. Moreover, despite setting the RBC model a more difficult task under the VARMA specification, our analysis, based on forecast error and spectral decompositions, suggests that the RBC model is still capable of explaining a significant fraction of the observed variation in macroeconomic aggregates in the post-war U.S. economy.

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Paper provided by Business School - Economics, University of Glasgow in its series Working Papers with number 2009_15.

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Date of creation: Apr 2009
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Handle: RePEc:gla:glaewp:2009_15
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  1. Ellen R. McGrattan & Richard Rogerson & Randall Wright, 1995. "An equilibrium model of the business cycle with household production and fiscal policy," Staff Report 191, Federal Reserve Bank of Minneapolis.
  2. William Nordhaus, 2004. "Retrospective on the 1970s Productivity Slowdown," NBER Working Papers 10950, National Bureau of Economic Research, Inc.
  3. hafedh bouakez & emanuela cardia, 2003. "Habit Formation and the Persistence of Monetary Shocks," Computing in Economics and Finance 2003 72, Society for Computational Economics.
  4. Hall, George J., 1996. "Overtime, effort, and the propagation of business cycle shocks," Journal of Monetary Economics, Elsevier, vol. 38(1), pages 139-160, August.
  5. Greenwood, J. & Hercowitz, Z. & Krusell, P., 1998. "The Role of Investment-Specific Technological Change in the Business Cycle," RCER Working Papers 449, University of Rochester - Center for Economic Research (RCER).
  6. V. V. Chari & Patrick Kehoe & Ellen McGrattan, 2004. "Business Cycle Accounting," Levine's Bibliography 122247000000000560, UCLA Department of Economics.
  7. Robert J. Gordon, 2000. "Interpreting the "One Big Wave" in U.S. Long-Term Productivity Growth," NBER Working Papers 7752, National Bureau of Economic Research, Inc.
  8. Eichenbaum, Martin, 1991. "Real business-cycle theory : Wisdom or whimsy?," Journal of Economic Dynamics and Control, Elsevier, vol. 15(4), pages 607-626, October.
  9. Galí, Jordi, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," CEPR Discussion Papers 1499, C.E.P.R. Discussion Papers.
  10. Fernandez-Villaverde, Jesus & Francisco Rubio-Ramirez, Juan, 2004. "Comparing dynamic equilibrium models to data: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 123(1), pages 153-187, November.
  11. Ireland, Peter N., 2001. "Technology shocks and the business cycle: On empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 25(5), pages 703-719, May.
  12. Peter N. Ireland, 2000. "Money's Role in the Monetary Business Cycle," Boston College Working Papers in Economics 458, Boston College Department of Economics.
  13. Ireland, Peter N., 2001. "Sticky-price models of the business cycle: Specification and stability," Journal of Monetary Economics, Elsevier, vol. 47(1), pages 3-18, February.
  14. Christiano, Lawrence J., 1988. "Why does inventory investment fluctuate so much?," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 247-280.
  15. RUGE-MURCIA, Francisco J., 2003. "Methods to Estimate Dynamic Stochastic General Equilibrium Models," Cahiers de recherche 2003-23, Universite de Montreal, Departement de sciences economiques.
  16. Lawrence J. Christiano & Martin Eichenbaum & Robert J. Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
  17. Greenwood, Jeremy & Hercowitz, Zvi & Huffman, Gregory W, 1988. "Investment, Capacity Utilization, and the Real Business Cycle," American Economic Review, American Economic Association, vol. 78(3), pages 402-17, June.
  18. Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez, 2004. "Estimating dynamic equilibrium economies: linear versus nonlinear likelihood," FRB Atlanta Working Paper 2004-3, Federal Reserve Bank of Atlanta.
  19. DeJong, David N. & Ingram, Beth F. & Whiteman, Charles H., 2000. "A Bayesian approach to dynamic macroeconomics," Journal of Econometrics, Elsevier, vol. 98(2), pages 203-223, October.
  20. Kim, Jinill, 2000. "Constructing and estimating a realistic optimizing model of monetary policy," Journal of Monetary Economics, Elsevier, vol. 45(2), pages 329-359, April.
  21. Peter Ireland, 1999. "A Method for Taking Models to the Data," Computing in Economics and Finance 1999 1233, Society for Computational Economics.
  22. Jordi Gali Garreta & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations; How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 04/234, International Monetary Fund.
  23. Watson, Mark W, 1993. "Measures of Fit for Calibrated Models," Journal of Political Economy, University of Chicago Press, vol. 101(6), pages 1011-41, December.
  24. Ellen R. McGrattan, 1991. "The macroeconomic effects of distortionary taxation," Discussion Paper / Institute for Empirical Macroeconomics 37, Federal Reserve Bank of Minneapolis.
  25. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Staff Report 364, Federal Reserve Bank of Minneapolis.
  26. Ireland, Peter N., 2003. "Endogenous money or sticky prices?," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1623-1648, November.
  27. Altug, Sumru, 1989. "Time-to-Build and Aggregate Fluctuations: Some New Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(4), pages 889-920, November.
  28. Peter N. Ireland & Scott Schuh, 2006. "Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model," Boston College Working Papers in Economics 642, Boston College Department of Economics.
  29. Ramey, Valerie A & Francis, Neville, 2002. "Is The Technology-Driven Real Business Cycle Hypothesis Dead? Shocks and Aggregate Fluctuations Revisted," University of California at San Diego, Economics Working Paper Series qt6x80k3nx, Department of Economics, UC San Diego.
  30. Timothy Cogley & James M. Nason, 1993. "Output dynamics in real business cycle models," Working Papers in Applied Economic Theory 93-10, Federal Reserve Bank of San Francisco.
  31. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
  32. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
  33. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
  34. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
  35. Christopher A. Sims, 1989. "Models and Their Uses," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 489-494.
  36. Ireland, Peter N., 1997. "A small, structural, quarterly model for monetary policy evaluation," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 83-108, December.
  37. Hans-Ulrich Derlien & B. Guy Peters, 2008. "Introduction," Chapters, in: The State at Work, Volume 2, chapter 1 Edward Elgar Publishing.
  38. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
  39. Bencivenga, Valerie R, 1992. "An Econometric Study of Hours and Output Variation with Preference Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(2), pages 449-71, May.
  40. A'Hearn, Brian & Woitek, Ulrich, 2001. "More international evidence on the historical properties of business cycles," Journal of Monetary Economics, Elsevier, vol. 47(2), pages 321-346, April.
  41. David N. DeJong & Beth F. Ingram & Charles H. Whiteman, 2000. "Keynesian impulses versus Solow residuals: identifying sources of business cycle fluctuations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(3), pages 311-329.
  42. Zanetti, Francesco, 2008. "Labor and investment frictions in a real business cycle model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3294-3314, October.
  43. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-87, April.
  44. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
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