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What Explains the Varying Monetary Response to Technology SHocks in G7-Countries

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  • Athena T. Theodorou
  • Neville R. Francis
  • Michael T. Owyang

Abstract

Structural vector autoregressions (SVARs) have become a standard tool used to determine the roles of monetary policy shocks in generating cyclical fluctuations in the United States. Using both long- and short-run identifying restrictions, various authors have explored the empirical response of the economy to exogenous monetary innovations. While the majority of the studies of monetary policy have focused on the effect of exogenous money growth or interest rate shocks, recent research has begun to investigate the effect of endogenous monetary policy -- that is, the central bank's reaction to non-monetary shocks. One exogenous shock that many economists believe contributes to the business cycle fluctuations that feed into the Taylor rule is the technology shock. In an effort to identify the empirical effects of technology shocks, Gali (1999) estimated two models: a bivariate model of productivity and hours and a five-variable model adding money, inflation, and interest rates. His identification estimates a decomposition of productivity and hours into innovations to technology and non-technology components by assuming that only the former can have long-run effects on labor productivity. Empirical identification of the technology shock was a key first step in developing a unified reduced-form framework with which to examine the role that monetary policy has played in smoothing economic fluctuations. Along these lines, Gali, Lopez-Salido, and Valles (2003 -- henceforth GLV) examined the endogenous response of monetary policy to identified technology shocks in the United States. GLV examine a four-variable structural VAR for the United States with labor productivity, labor hours, the real interest rate, and inflation. Using the Gali (1999) identification, they find that during the Volcker-Greenspan (VG) era the Fed's response to the technology shock is to raise the nominal interest rate, while during the Martin-Burns-Miller (MBM) era the Fed lowers the nominal rate. Moreover, they find that the inflation and hours responses in the two periods differ in sign. Our goal is to expand the scope of GLV to an international context to determine whether the effect of technology shocks is consistent across the major industrialized countries. In particular, we are interested in how the different central banks respond to technology shocks. We investigate the possibility that technology shocks in different countries produce fundamentally different inflation and employment responses and to what extent those effects alter the monetary response. Using a theoretical model adapted from King and Wolman (1996), we find that the empirical responses can be matched with theoretical responses. Differences in these theoretical responses can be attributed to alternative policy rules and changes in the cost of capital adjustment. Further tests verify that these country characteristics could, indeed, have some explanatory power. Our results are by no means conclusive; however, they do suggest a number of theoretically consistent similarities across countries in each subgroup. While we believe more investigation into these cross-country comparisons is warranted, the initial indication is that the manner in which monetary policy is conducted and the degree of rigidity in capital markets may be determining factors in a country's response to technology shocks. Gali, Jordi (1999). "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?" American Economic Review, March 1999, 89(1), pp. 249-271. Gali, Jordi; Lopez-Salido, J. David; and Valles, Javier (2003). "Technology Shocks and Monetary Policy: Assessing the Fed's Performance." Journal of Monetary Economics, May 2003, 50(4), pp. 723-743. King, Robert G., and Wolman, Alexander L. (1996). "Inflation Targetting in a St. Louis Model of the 21st Century." Federal Reserve Bank of St. Louis Review, May/June 1996, 78(3), pp. 83-107.

Suggested Citation

  • Athena T. Theodorou & Neville R. Francis & Michael T. Owyang, 2004. "What Explains the Varying Monetary Response to Technology SHocks in G7-Countries," Econometric Society 2004 North American Summer Meetings 444, Econometric Society.
  • Handle: RePEc:ecm:nasm04:444
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    Cited by:

    1. Lorenza Rossi & Fabrizio Mattesini, 2008. "We analyze, in this paper, a DSGE New Keynesian model with indi- visible labor where firms may belong to two different final goods producing sectors one where wages and employment are determined in co," DISCE - Quaderni dell'Istituto di Economia e Finanza ief0077, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    2. Hofmann, Boris & Peersman, Gert & Straub, Roland, 2012. "Time variation in U.S. wage dynamics," Journal of Monetary Economics, Elsevier, vol. 59(8), pages 769-783.
    3. Hashmat Khan & John Tsoukalas, 2005. "Technology Shocks and UK Business Cycles," Macroeconomics 0512006, EconWPA.
    4. Fabrizio Mattesini & Lorenza Rossi, 2008. "Productivity Shocks And Optimal Monetary Policy In A Unionized Labor Market Economy," Manchester School, University of Manchester, vol. 76(5), pages 578-611, September.
    5. Mattesini, Fabrizio & Rossi, Lorenza, 2009. "Optimal monetary policy in economies with dual labor markets," Journal of Economic Dynamics and Control, Elsevier, vol. 33(7), pages 1469-1489, July.
    6. 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.
    7. Jordi Galí, 2004. "Trends in Hours, Balanced Growth, and the Role of Technology in the Business Cycle," Working Papers 187, Barcelona Graduate School of Economics.
    8. Jordi Galí, 2005. "Trends in hours, balanced growth, and the role of technology in the business cycle," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 459-486.
    9. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 638-647, October.
    10. Rossi, Lorenza & Mattesini, Fabrizio, 2007. "Productivity Shock and Optimal Monetary Policy in a Unionized Labor Market. Forthcoming: The Manchester School," MPRA Paper 8414, University Library of Munich, Germany, revised 2008.
    11. Edward Nelson, 2012. "The correlation between money and output in the United Kingdom: resolution of a puzzle," Finance and Economics Discussion Series 2012-29, Board of Governors of the Federal Reserve System (U.S.).
    12. Rossi, Lorenza & Mattesini, Fabrizio, 2007. "Optimal Monetary Policy in a Dual Labor Market Economy," MPRA Paper 2468, University Library of Munich, Germany, revised 15 Mar 2007.

    More about this item

    Keywords

    Technology; Productivity; Monetary Policy; Taylor Rule; Capital Adjustment Costs;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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