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Does Inflation Adjust Faster to Aggregate Technology Shocks than to Monetary Policy Shocks?

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Listed author(s):
  • LUIGI PACIELLO

Abstract

This paper studies U.S. inflation adjustment speed to aggregate technology shocks and to monetary policy shocks in a medium size Bayesian VAR model. According to the model estimated on the 1959-2007 sample, inflation adjusts much faster to aggregate technology shocks than to monetary policy shocks. These results are robust to different identification assumptions and measures of aggregate prices. However, by separately estimating the model over the pre- and post-1980 periods, this paper further shows that inflation adjusts much faster to technology shocks than to monetary policy shocks in the post-1980 period, but not in the pre-1980 period.

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File URL: http://hdl.handle.net/10.1111/j.1538-4616.2011.00462.x
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Article provided by Blackwell Publishing in its journal Journal of Money, Credit and Banking.

Volume (Year): 43 (2011)
Issue (Month): 8 (December)
Pages: 1663-1684

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Handle: RePEc:mcb:jmoncb:v:43:y:2011:i:8:p:1663-1684
DOI: j.1538-4616.2011.00462.x
Contact details of provider: Web page: http://www.blackwellpublishing.com/journal.asp?ref=0022-2879

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  1. Fabio Canova & Luca Gambetti & Evi Pappa, 2007. "The Structural Dynamics of Output Growth and Inflation: Some International Evidence," Economic Journal, Royal Economic Society, vol. 117(519), pages 167-191, 03.
  2. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
  3. Waggoner, Daniel F. & Zha, Tao, 2003. "Likelihood preserving normalization in multiple equation models," Journal of Econometrics, Elsevier, vol. 114(2), pages 329-347, June.
  4. Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2005. "Can Long-Run Restrictions Identify Technology Shocks?," Journal of the European Economic Association, MIT Press, vol. 3(6), pages 1237-1278, December.
  5. Luigi Paciello, 2012. "Monetary Policy and Price Responsiveness to Aggregate Shocks under Rational Inattention," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1375-1399, October.
  6. Bartosz Mackowiak & Mirko Wiederholt, 2008. "Business Cycle Dynamics under Rational Inattention," 2008 Meeting Papers 1059, Society for Economic Dynamics.
  7. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
  8. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
  9. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
  10. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
  11. Boivin, Jean & Kiley, Michael T. & Mishkin, Frederic S., 2010. "How Has the Monetary Transmission Mechanism Evolved Over Time?," Handbook of Monetary Economics,in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 8, pages 369-422 Elsevier.
  12. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2011. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(2), pages 225-247, April.
  13. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters,in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230 National Bureau of Economic Research, Inc.
  14. Dupor, Bill & Han, Jing & Tsai, Yi-Chan, 2009. "What do technology shocks tell us about the New Keynesian paradigm?," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 560-569, May.
  15. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?," Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
  16. Rochelle M. Edge & Thomas Laubach & John C. Williams, 2003. "The responses of wages and prices to technology shocks," Working Paper Series 2003-21, Federal Reserve Bank of San Francisco.
  17. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
  18. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
  19. 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.
  20. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2011. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(2), pages 225-247, April.
  21. Juan Francisco Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2005. "Markov-switching structural vector autoregressions: theory and application," FRB Atlanta Working Paper 2005-27, Federal Reserve Bank of Atlanta.
  22. Smets, Frank & Wouters, Raf, 2007. "Shocks and frictions in US business cycles: a Bayesian DSGE approach," Working Paper Series 722, European Central Bank.
  23. Dedola, Luca & Neri, Stefano, 2006. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Working Paper Series 705, European Central Bank.
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Cited by:

  1. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
  2. Lawrence J. Christiano & Martin S. Eichenbaum & Mathias Trabandt, 2016. "Unemployment and Business Cycles," Econometrica, Econometric Society, vol. 84, pages 1523-1569, 07.
  3. Slobodyan, Sergey & Wouters, Raf, 2012. "Learning in an estimated medium-scale DSGE model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 26-46.
  4. Lawrence J. Christiano & Martin S. Eichenbaum & Mathias Trabandt, 2015. "Understanding the Great Recession," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 110-167, January.
  5. Jouchi Nakajima & Nao Sudo & Takayuki Tsuruga, 2010. "How Well Do the Sticky Price Models Explain the Disaggregated Price Responses to Aggregate Technology and Monetary Policy Shocks?," Discussion papers e-10-007, Graduate School of Economics Project Center, Kyoto University.
  6. Christiano, Lawrence & Trabandt, Mathias & Walentin, Karl, 2010. "Involuntary unemployment and the business cycle," Working Paper Series 1202, European Central Bank.
  7. Paciello, Luigi, 2009. "Monetary Policy Activism and Price Responsiveness to Aggregate Shocks under Rational Inattention," MPRA Paper 16407, University Library of Munich, Germany.

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