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Technology shocks and aggregate fluctuations in an estimated hybrid RBC model

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  • Malley, Jim
  • Woitek, Ulrich

Abstract

This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of neutral and investment-specific technology shocks in explaining aggregate fluctuations. To achieve this, we estimate the model's posterior density using Bayesian methods. Within this framework we first extend (Ireland, 2001b) and (Ireland, 2004a) 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. Our main findings for the model with neutral technical change are: (i) the VARMA specification of the errors significantly improves the hybrid model's fit to the historical data relative to the VAR and AR alternatives; and (ii) despite setting the RBC model a more difficult task under the VARMA specification, neutral technology shocks are still capable of explaining a significant share of the observed variation in output and its components over shorter- and longer-forecast horizons as well as hours at shorter horizons. When the hybrid model is extended to incorporate investment shocks, we find that: (iii) the VAR specification is preferred to the alternatives; and (iv) the model's ability to explain fluctuations improves considerably.

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  • Malley, Jim & Woitek, Ulrich, 2010. "Technology shocks and aggregate fluctuations in an estimated hybrid RBC model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1214-1232, July.
  • Handle: RePEc:eee:dyncon:v:34:y:2010:i:7:p:1214-1232
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    as
    1. Ireland, Peter N., 2003. "Endogenous money or sticky prices?," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1623-1648, November.
    2. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    3. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    4. Jordi Galí & Pau Rabanal, 2005. "Technology Shocks and Aggregate Fluctuations: How Well Does the Real Business Cycle Model Fit Postwar U.S. Data?," NBER Chapters,in: NBER Macroeconomics Annual 2004, Volume 19, pages 225-318 National Bureau of Economic Research, Inc.
    5. Greenwood, Jeremy & Hercowitz, Zvi & Krusell, Per, 2000. "The role of investment-specific technological change in the business cycle," European Economic Review, Elsevier, vol. 44(1), pages 91-115, January.
    6. Watson, Mark W, 1993. "Measures of Fit for Calibrated Models," Journal of Political Economy, University of Chicago Press, vol. 101(6), pages 1011-1041, December.
    7. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
    8. Peter Ireland & Scott Schuh, 2008. "Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 473-492, July.
    9. Eichenbaum, Martin, 1991. "Real business-cycle theory : Wisdom or whimsy?," Journal of Economic Dynamics and Control, Elsevier, vol. 15(4), pages 607-626, October.
    10. 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.
    11. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    12. 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.
    13. Ireland, Peter N, 2004. "Money's Role in the Monetary Business Cycle," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(6), pages 969-983, December.
    14. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    15. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco J., 2005. "Habit formation and the persistence of monetary shocks," Journal of Monetary Economics, Elsevier, pages 1073-1088.
    16. 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.
    17. Juan F. Rubio-Ramirez & Jesus Fernández-Villaverde, 2005. "Estimating dynamic equilibrium economies: linear versus nonlinear likelihood," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 891-910.
    18. 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.
    19. McGrattan, Ellen R & Rogerson, Richard & Wright, Randall, 1997. "An Equilibrium Model of the Business Cycle with Household Production and Fiscal Policy," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(2), pages 267-290, May.
    20. 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.
    21. William Nordhaus, 2004. "Retrospective on the 1970s Productivity Slowdown," NBER Working Papers 10950, National Bureau of Economic Research, Inc.
    22. Christopher A. Sims, 1989. "Models and Their Uses," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 489-494.
    23. 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.
    24. 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 449-471, May.
    25. 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.
    26. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
    27. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Business Cycle Accounting," Econometrica, Econometric Society, pages 781-836.
    28. McGrattan, Ellen R., 1994. "The macroeconomic effects of distortionary taxation," Journal of Monetary Economics, Elsevier, pages 573-601.
    29. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, pages 1379-1399.
    30. Ruge-Murcia, Francisco J., 2007. "Methods to estimate dynamic stochastic general equilibrium models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2599-2636, August.
    31. Hans-Ulrich Derlien & B. Guy Peters, 2008. "Introduction," Chapters,in: The State at Work, Volume 2, chapter 1 Edward Elgar Publishing.
    32. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-287, April.
    33. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
    34. 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.
    35. 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 402-417, June.
    36. Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
    37. 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.
    38. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    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.
    45. 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.
    46. Christiano, Lawrence J., 1988. "Why does inventory investment fluctuate so much?," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 247-280.
    47. 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.
    48. 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.
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    Cited by:

    1. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    2. Jim Malley & Ulrich Woitek, 2009. "Productivity shocks and aggregate cycles in an estimated endogenous growth model," Working Papers 2009_23, Business School - Economics, University of Glasgow.
    3. Alessia Paccagnini, 2012. "Comparing Hybrid DSGE Models," Working Papers 228, University of Milano-Bicocca, Department of Economics, revised Dec 2012.
    4. Jim Malley & Ulrich Woitek, 2011. "Productivity Shocks and Aggregate Fluctuations in an Estimated Endogenous Growth Model with Human Capital," CESifo Working Paper Series 3567, CESifo Group Munich.
    5. Ben Zeev, Nadav & Pappa, Evi, 2015. "Multipliers of unexpected increases in defense spending: An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 205-226.

    More about this item

    Keywords

    Real business cycle Bayesian estimation Technology shocks Measurement errors;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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