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What Happens After A Technology Shock? A Bayesian Perspective

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  • Ossama Mikhail

    (University of Central Florida)

Abstract

This paper investigates the effect of a positive technology shock on per capita hours worked within the class of Bayesian Vector Auto-Regressive [BVAR] models. Such a framework avoids the current debate regarding the specification issue of per capita hours [level versus first-difference stationary]. Six priors are considered and for each, we examine the impulse responses of per capita hours following a positive technology shock. The marginal posteriors of the VAR parameters are generated using the Markov Chain Monte Carlo (MCMC) Gibbs sampler. We find that the estimation of the VAR yields significantly different estimates under competing priors. Using the Francis and Ramey (2004, UCSD working paper) new measure for per capita hours, and after imposing the identifying restrictions (i.e., Blanchard-Quah and sign restrictions), the results show that per capita hours worked rise following a positive technology shock - if one [objectively] assumes a non-informative prior.

Suggested Citation

  • Ossama Mikhail, 2005. "What Happens After A Technology Shock? A Bayesian Perspective," Macroeconomics 0510016, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpma:0510016
    Note: Type of Document - pdf; pages: 34
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/mac/papers/0510/0510016.pdf
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    References listed on IDEAS

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    1. George W. Stadler, 1994. "Real Business Cycles," Journal of Economic Literature, American Economic Association, vol. 32(4), pages 1750-1783, December.
    2. Miles S. Kimball & John G. Fernald & Susanto Basu, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December.
    3. Christiano, Lawrence J & Eichenbaum, Martin & Evans, Charles, 1996. "The Effects of Monetary Policy Shocks: Evidence from the Flow of Funds," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 16-34, February.
    4. Martin S. Eichenbaum, 1996. "Some comments on the role of econometrics in economic theory," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 20(Jan), pages 22-31.
    5. 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.
    6. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 381-395, 04/05.
    7. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2004. "A Critique of Structural VARs Using Real Business Cycle Theory," Levine's Bibliography 122247000000000518, UCLA Department of Economics.
    8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    9. John Shea, 1999. "What Do Technology Shocks Do?," NBER Chapters, in: NBER Macroeconomics Annual 1998, volume 13, pages 275-322, National Bureau of Economic Research, Inc.
    10. Jordi Gali, 2005. "Trends in hours, balanced growth, and the role of technology in the business cycle," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 459-486.
    11. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    12. Koop, G, 1992. "Aggregate Shocks and Macroeconomic Fluctuations: A Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(4), pages 395-411, Oct.-Dec..
    13. Galí, Jordi & Rabanal, Pau, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Post-War US Data?," CEPR Discussion Papers 4522, C.E.P.R. Discussion Papers.
    14. Dorfman, Jeffrey H., 1995. "A numerical bayesian test for cointegration of AR processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 289-324.
    15. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139, Decembrie.
    16. Jordi Galí, 1992. "How Well Does The IS-LM Model Fit Postwar U. S. Data?," The Quarterly Journal of Economics, Oxford University Press, vol. 107(2), pages 709-738.
    17. BAUWENS, Luc & LUBRANO , Michel, 1994. "Identification Restrictions and Posterior Densities in Cointegrated Gaussian VAR Systems," LIDAM Discussion Papers CORE 1994018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Neville Francis & Michael T. Owyang & Athena T. Theodorou, 2003. "The use of long-run restrictions for the identification of technology shocks," Review, Federal Reserve Bank of St. Louis, vol. 85(Nov), pages 53-66.
    19. Shawn Ni & Dongchu Sun, 2005. "Bayesian Estimates for Vector Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 105-117, January.
    20. Neville Francis & Valerie A. Ramey, 2002. "Is the Technology-Driven Real Business Cycle Hypothesis Dead?," NBER Working Papers 8726, National Bureau of Economic Research, Inc.
    21. Mark P. Taylor, 2004. "Estimating structural macroeconomic shocks through long-run recursive restrictions on vector autoregressive models: the problem of identification," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(3), pages 229-244.
    22. Koop, Gary, 1991. "Cointegration tests in present value relationships : A Bayesian look at the bivariate properties of stock prices and dividends," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 105-139.
    23. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    24. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    25. Christopher A. Sims, 2005. "Commentary on \\"trends in hours, balanced growth, and the role of technology in the business cycle\\"," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 487-492.
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    More about this item

    Keywords

    Bayesian Vector Auto-Regression (BVAR); Blanchard-Quah Identification; Markov Chain Monte Carlo (MCMC) Gibbs Sampler; Technology Shock; Real Business Cycle (RBC);
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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