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News Shocks

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Author Info
Robert B. Barsky
Eric R. Sims

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Abstract

We implement a new approach for the identification of "news shocks" about future technology. In a VAR featuring a measure of aggregate technology and several forward-looking variables, we identify the news shock as the shock orthogonal to technology innovations that best explains future variation in technology. In the data, news shocks account for the bulk of low frequency variation in technology. News shocks are positively correlated with consumption, stock price, and consumer confidence innovations, and negatively correlated with inflation innovations. The disinflationary nature of news shocks is consistent with the implications of sensibly modified versions of a New Keynesian model.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15312.

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Date of creation: Sep 2009
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Handle: RePEc:nbr:nberwo:15312

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Find related papers by JEL classification:
E0 - Macroeconomics and Monetary Economics - - General
E00 - Macroeconomics and Monetary Economics - - General - - - General
E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
E2 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment
E20 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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  1. Harald Uhlig, 2004. "Do Technology Shocks Lead to a Fall in Total Hours Worked?," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 361-371, 04/05. [Downloadable!] (restricted)
  2. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May. [Downloadable!] (restricted)
  3. Susanto Basu & John G. Fernald & Miles S. Kimball, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December. [Downloadable!]
    Other versions:
  4. 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. [Downloadable!] (restricted)
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  5. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2007. "How Structural Are Structural Parameters?," NBER Working Papers 13166, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. Julio J. Rotemberg, 2003. "Stochastic Technical Progress, Smooth Trends, and Nearly Distinct Business Cycles," American Economic Review, American Economic Association, vol. 93(5), pages 1543-1559, December. [Downloadable!]
  7. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December. [Downloadable!] (restricted)
  8. Athanasios Orphanides, 2003. "Historical monetary policy analysis and the Taylor rule," Finance and Economics Discussion Series 2003-36, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
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  9. 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. [Downloadable!] (restricted)
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  10. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2009. "News, Noise, and Fluctuations: An Empirical Exploration," NBER Working Papers 15015, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  11. Athanasios Orphanides, 2002. "Monetary-Policy Rules and the Great Inflation," American Economic Review, American Economic Association, vol. 92(2), pages 115-120, May. [Downloadable!]
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  12. Cochrane, John H, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, MIT Press, vol. 109(1), pages 241-65, February. [Downloadable!] (restricted)
  13. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," Cowles Foundation Discussion Papers 870, Cowles Foundation, Yale University. [Downloadable!]
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  14. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September. [Downloadable!] (restricted)
  15. Olivier Blanchard & Jordi Galí, 2007. "Real Wage Rigidities and the New Keynesian Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 35-65, 02. [Downloadable!] (restricted)
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  16. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  17. Neville Francis & Michael T. Owyang & Jennifer E. Roush, 2007. "A flexible finite-horizon identification of technology shocks," Working Papers 2005-024, Federal Reserve Bank of St. Louis. [Downloadable!]
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