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Technology-Hours Redux: Tax Changes and the Measurement of Technology Shocks

  • Mertens, Karel
  • Ravn, Morten O

A number of empirical studies find that permanent technological improvements give rise to a temporary drop in hours worked. This finding seriously questions the technology-driven business cycle hypothesis. In this paper we argue that it is important to control for permanent changes in taxes, which invalidate the standard long run identifying assumptions for technology shocks and induce low frequency fluctuations in hours worked. Using the narrative data of Romer and Romer (2010), we find that tax shocks have significant long run effects on aggregate hours, output and labor productivity. We also find that, after controlling for tax shocks, permanent shocks to labor productivity generate short run increases in hours worked and are an important source of fluctuations in US output.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7962.

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Date of creation: Aug 2010
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Handle: RePEc:cpr:ceprdp:7962
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  1. Chen, Kaiji & Imrohoroglu, Ayse & Imrohoroglu, Selahattin, 2009. "A quantitative assessment of the decline in the U.S. current account," Journal of Monetary Economics, Elsevier, vol. 56(8), pages 1135-1147, November.
  2. Susanto Basu & John Fernald & Miles Kimball, 2002. "Are Technology Improvements Contractionary?," Harvard Institute of Economic Research Working Papers 1986, Harvard - Institute of Economic Research.
  3. Karel Mertens & Morten O. Ravn, 2009. "Empirical evidence on the aggregate effects of anticipated and unanticipated US tax policy shocks," Working Paper Research 181, National Bank of Belgium.
  4. Favero, Carlo A. & Giavazzi, Francesco, 2010. "Reconciling VAR-based and Narrative Measures of the Tax-Multiplier," CEPR Discussion Papers 7769, C.E.P.R. Discussion Papers.
  5. 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.
  6. Saikkonen, Pentti & Lütkepohl, Helmut, 1998. "Testing for the cointegrating rank of a VAR process with an intercept," SFB 373 Discussion Papers 1998,51, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  7. Eric M. Leeper & Todd B. Walker & Shu-Chun Susan Yang, 2008. "Fiscal Foresight: Analytics and Econometrics," Caepr Working Papers 2008-013, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  8. Yongsung Chang & Joao Gomes & Frank Schorfheide, 2002. "Learning by Doing as a Propagation Mechanism," Macroeconomics 0204002, EconWPA.
  9. Karel Mertens & MortenO. Ravn, 2010. "Measuring the Impact of Fiscal Policy in the Face of Anticipation: A Structural VAR Approach," Economic Journal, Royal Economic Society, vol. 120(544), pages 393-413, 05.
  10. Neville Francis & Valerie A. Ramey, 2004. "The Source of Historical Economic Fluctuations: An Analysis using Long-Run Restrictions," NBER Working Papers 10631, National Bureau of Economic Research, Inc.
  11. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
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