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Understanding the Effect of Technology Shocks in SVARs with Long-Run Restrictions

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  • Chaudourne, Jeremy
  • Fève, Patrick
  • Guay, Alain

Abstract

This paper studies the statistical properties of impulse response functions in structural vector autoregressions (SVARs) with a highly persistent variable as hours worked and long-run identifying restrictions. The highly persistent variable is specified as a nearly stationary persistent process. Such process appears particularly well suited to characterized the dynamics of hours worked because it implies a unit root in finite sample but is asymptotically stationary and persistent. This is typically the case for per capita hours worked which are included in SVARs. Theoretical results derived from this specification allow to explain most of the empirical findings from SVARs which include U.S. hours worked. Simulation experiments from an estimated DSGE model confirm theoretical results.

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Bibliographic Info

Paper provided by Institut d'Économie Industrielle (IDEI), Toulouse in its series IDEI Working Papers with number 738.

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Date of creation: Aug 2012
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Handle: RePEc:ide:wpaper:26113

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Keywords: SVARs; long-run restrictions; locally nonstationary process; technology shocks; hours worked;

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  1. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  2. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," NBER Working Papers 10254, National Bureau of Economic Research, Inc.
  3. Ramey, Valerie A & Francis, Neville, 2002. "Is The Technology-Driven Real Business Cycle Hypothesis Dead? Shocks and Aggregate Fluctuations Revisted," University of California at San Diego, Economics Working Paper Series qt6x80k3nx, Department of Economics, UC San Diego.
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  21. John Fernald, 2012. "A quarterly, utilization-adjusted series on total factor productivity," Working Paper Series 2012-19, Federal Reserve Bank of San Francisco.
  22. Serena Ng & Pierre Perron, 1997. "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power," Boston College Working Papers in Economics 369, Boston College Department of Economics, revised 01 Sep 2000.
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