Hostname: page-component-74656f9884-2dmjx Total loading time: 0 Render date: 2026-11-09T05:57:49.961Z Has data issue: false hasContentIssue false
  • English
  • Français

CONTRACTIONARY TECHNOLOGY SHOCKS

Published online by Cambridge University Press:  13 June 2017

Francesco Giuli  and
Massimiliano Tancioni
Francesco Giuli*
Affiliation:
Roma Tre University
Massimiliano Tancioni
Affiliation:
Sapienza University of Rome
*
Address correspondence to: Francesco Giuli, Department of Economics, Roma Tre University, Via Silvio D'Amico, 77, 00145 Rome, Italy; e-mail: francesco.giuli@uniroma3.it.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

This paper adds to the large body of literature on the effects of technology shocks empirically and theoretically. Using a structural vector error correction model, we first provide evidence that not only hours but also investment decline temporarily following a technology improvement. This result is robust to important data and identification issues addressed in the literature. We then show that the negative response of inputs is consistent with an estimated monetary model in which the presence of strategic complementarity in price setting, in addition to nominal rigidities, lowers the sensitivity of prices to marginal costs, and monetary policy does not fully accommodate the shock.

Keywords

Technology ShocksInputs DynamicsStructural Vector Error Correction ModelNew Keynesian DSGE ModelBayesian Inference

Information

Type
Articles
Information
Macroeconomic Dynamics , Volume 21 , Issue 7 , October 2017 , pp. 1752 - 1789
Copyright
Copyright © Cambridge University Press 2017 

Footnotes

We thank an associate editor and two anonymous referees for very useful feedback. We also thank Elton Beqiraj, Giuseppe Ciccarone, Enrico Marchetti, and Mario Tirelli for useful comments and discussions. The usual disclaimer holds. Financial support from the Roma Tre University, the Sapienza University of Rome, and the Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR) is gratefully acknowledged.

References

REFERENCES

Altig, David, Christiano, Lawrence J., Eichenbaum, Martin, and Lindé, Jasper (2011) Firm-specific capital, nominal rigidities and the business cycle. Review of Economic Dynamics 14 (2), 225–247.Google Scholar
Basu, Susanto (1998) Technology and Business Cycles: How Well Do Standard Models Explain the Facts? Conference Series: Proceedings, Federal Reserve Bank of Boston, June, 207–269.Google Scholar
Basu, Susanto, Fernald, John, and Kimball, Miles (2006) Are technology improvements contractionary? American Economic Review 96 (5), 1418–1448.Google Scholar
Beaudry, Paul and Portier, Franck (2007) When can changes in expectations cause business cycle fluctuations in neo-classical settings? Journal of Economic Theory 135 (1), 458–477.Google Scholar
Bils, Mark and Klenow, Pete (2004) Some evidence on the importance of sticky prices. Journal of Political Economy 112 (5), 947–985.Google Scholar
Blanchard, Olivier and Quah, Danny (1989) The dynamic effects of aggregate demand and supply disturbances. American Economic Review 79 (4), 655–673.Google Scholar
Bowman, David (2003) Market and Inflation. International Finance Discussion Paper 783.Google Scholar
Canova, Fabio, López-Salido, David, and Michelacci, Claudio (2010) The effects of technology shocks on hours and output: A robustness analysis. Journal of Applied Econometrics 25 (5), 755–773.Google Scholar
Christiano, Lawrence J., Eichenbaum, Martin, and Evans, Charles (2005) Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy 113 (1), 1–45.Google Scholar
Christiano, Lawrence J., Eichenbaum, Martin, and Vigfusson, Robert (2004) The response of hours to a technology shock: Evidence based on direct measures of technology. Journal of the European Economic Association 2 (3), 381–395.Google Scholar
Clarida, Richard, Galì, Jordi, and Gertler, Mark (1999) The science of monetary policy: A New Keynesian perspective. Journal of Economic Literature 37 (4), 1661–1707.Google Scholar
Del Negro, Marco, Schorfheide, Frank, Smets, Frank, and Wouters, Raf (2005) On the Fit and Forecasting Performance of New Keynesian Models. ECB working paper 491.Google Scholar
Eggertsson, Gauti, Ferrero, Andrea, and Raffo, Andrea (2014) Can structural reforms help Europe? Journal of Monetary Economics 61 (C), 2–22.CrossRefGoogle Scholar
Eichenbaum, Martin and Fisher, Jonas D.M. (2007) Estimating the frequency of price re-optimization in Calvo-style models. Journal of Monetary Economics 54 (7), 2032–2047.CrossRefGoogle Scholar
Fernald, John (2007) Trend breaks, long-run restrictions, and contractionary technology improvements. Journal of Monetary Economics 54 (8), 2467–2485.Google Scholar
Francis, Neville and Ramey, Valerie (2005) Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited. Journal of Monetary Economics 52, 1379–1399.CrossRefGoogle Scholar
Fry, Renee and Pagan, Adrian (2005) Some Issues in Using VARs for Macroeconometric Research. Australian National University, CAMA working paper 2005, No. 19.Google Scholar
Galì, Jordi (1999) Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? American Economic Review 89 (1), 249–271.Google Scholar
Galì, Jordi and Gertler, Mark (1999) Inflation dynamics: A structural econometric analysis. Journal of Monetary Economics 44 (2), 195–222.CrossRefGoogle Scholar
Galì, Jordi and Gertler, Mark (2007) Macroeconomic modeling for monetary policy evaluation. Journal of Economic Perspectives 21 (4), 25–46.Google Scholar
Galì, Jordi, Lopez-Salido, David, and Valles, Javier (2003) Technology shocks and monetary policy: Assessing the Fed's performance. Journal of Monetary Economics 50 (4), 723–743.Google Scholar
Garratt, Anthony, Lee, Kevin, Pesaran, Hashem, and Shin, Yongcheol (2003) A long run structural macroeconometric model of the UK. Economic Journal 113 (487), 412–455.Google Scholar
Gil-Alana, Luis and Moreno, Antonio (2009) Technology shocks and hours worked: A fractional integration perspective. Macroeconomic Dynamics 13, 580–604.CrossRefGoogle Scholar
Giuli, Francesco and Tancioni, Massimiliano (2012) Real rigidities, productivity improvements and investment dynamics. Journal of Economic Dynamics and Control 36 (1), 100–118.Google Scholar
Hamilton, B. Fout and Francis, Neville R. (2014) Imperfect transmission of technology shocks and the business cycle consequences. Macroeconomic Dynamics 18, 418–437.Google Scholar
Harvey, Andrew and Stock, James H. (1988) Continuous time autoregressive models with common stochastic trends. Journal of Economic Dynamics and Control 12 (2–3), 365–384.Google Scholar
Johansen, Soren (1995) Identifying restrictions of linear equations with applications to simultaneous equations and cointegration. Journal of Econometrics 69 (1), 111–132.Google Scholar
Juillard, Michael, Kamenik, Ondra, Kumhof, Michael, and Laxton, Douglas (2008) Optimal price setting and inflation inertia in a rational expectations model. Journal of Economic Dynamics and Control 32 (8), 2584–2621.Google Scholar
Kimball, Miles S. (1995) The quantitative analytics of the basic neomonetarist model. Journal of Money, Credit and Banking 27 (4), 1241–1277.Google Scholar
King, Robert, Plosser, Charles, Stock, James, and Watson, Mark (1991) Stochastic trends and economic fluctuations. American Economic Review 81 (4), 819–840.Google Scholar
Lindé, Jasper (2009) The effects of permanent technology shocks on hours: Can the RBC model fit the VAR evidence? Journal of Economic Dynamics and Control 33 (3), 597–613.Google Scholar
Lovcha, Yuliya and Perez-Laborda, Alejandro (2015) The hours worked productivity puzzle: Identification in a fractional integration setting. Macroeconomic Dynamics 19, 1593–1621.Google Scholar
MacKinnon, James, Haug, Alfred, and Michelis, Leo (1999) Numerical distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics 14, 563–577.Google Scholar
Orphanides, Athanasios (2003a) Monetary policy evaluation with noisy information. Journal of Monetary Economics 50 (3), 605–631.CrossRefGoogle Scholar
Orphanides, Athanasios (2003b) The quest for prosperity without inflation. Journal of Monetary Economics 50 (3), 633–663.CrossRefGoogle Scholar
Orphanides, Athanasios (2007) Taylor Rules. Finance and Economics Discussion Series 18, Board of Governors of the Federal Reserve SystemGoogle Scholar
Orphanides, Athanasios and Van Norden, Simon (2002) The unreliability of output-gap estimates in real time. Review of Economics and Statistics 84 (4), 569–583.Google Scholar
Pesaran, Hashem and Smith, Ron (1995) The role of theory in econometrics. Journal of Econometrics 67 (1), 61–79.Google Scholar
Pesavento, Elena and Rossi, Barbara (2005) Do technology shocks drive hours up or down? A little evidence from an agnostic procedure. Macroeconomic Dynamics 9, 478–488.Google Scholar
Riggi, Marianna and Tancioni, Massimiliano (2010) Nominal v. real wage rigidities in New Keynesian models with hiring costs: A Bayesian evaluation. Journal of Economic Dynamics and Control 34 (7), 1305–1324.Google Scholar
Rotemberg, Julio (2003) Stochastic technical progress, smooth trends, and nearly distinct business cycles. American Economic Review 93 (5), 1543–1559.Google Scholar
Shapiro, Matthew and Watson, Mark (1989) Sources of Business Cycle Fluctuations. NBER working paper 2589.Google Scholar
Schmitt-Grohé, Stephanie and Uribe, Martin (2011) Business cycles with a commond trend in neutral and investment-specific productivity. Review of Economic Dynamics, 14, 122–135.Google Scholar
Schorfheide, Frank (2008) DSGE model-based estimation of the New Keynesian Phillips curve. Economic Quarterly 94 (4), 397–433.Google Scholar
Smets, Frank and Wouters, Raf (2003) An estimated DSGE model of the Euro Area. Journal of the European Economic Association 1 (5), 1123–1175.Google Scholar
Smets, Frank and Wouters, Raf (2007) Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review 97 (3), 586–606.Google Scholar
Sveen, Tommy and Weinke, Lutz (2005) New perspectives on capital, sticky prices, and the Taylor principle. Journal of Economic Theory 123 (1), 21–39.Google Scholar
Vlaar, Peter (2004) Shocking the Eurozone. European Economic Review 48 (1), 109–131.Google Scholar
Woodford, Michael (2005) Firm-specific capital and the New Keynesian Phillips curve. International Journal of Central Banking 1 (2), 1–46.Google Scholar