Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-23T10:10:06.341Z Has data issue: false hasContentIssue false
  • English
  • Français

TECHNOLOGY SHOCKS AND HOURS WORKED: A FRACTIONAL INTEGRATION PERSPECTIVE

Published online by Cambridge University Press:  13 October 2009

Luis Alberiko Gil-Alana  and
Antonio Moreno
Luis Alberiko Gil-Alana
Affiliation:
University of Navarra
Antonio Moreno*
Affiliation:
University of Navarra
*
Address correspondence to: Antonio Moreno, School of Economics, University of Navarra, 31080 Pamplona, Spain; e-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Previous research has found that the dynamic response of hours worked to a technology shock crucially depends on whether the hours variable is assumed to be an I(0) or an I(1) variable ex ante. In this paper we employ a multivariate fractionally integrated model that allows us to simultaneously estimate the order of integration of hours worked and its dynamic response to a technology shock. Our evidence lends support to the hypothesis that hours fall in response to a positive technology shock.

Keywords

Technology ShocksImpulse Response FunctionsHours WorkedFractional IntegrationMultivariate Analysis
Type
Articles
Information
Macroeconomic Dynamics , Volume 13 , Issue 5 , November 2009 , pp. 580 - 604
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Baillie, Robert T. (1996) Long memory processes and fractional integration in econometrics. Journal of Econometrics 73, 5–59.CrossRefGoogle Scholar
Baillie, Robert T. and Bollerslev, Tim (1994) The long memory of the forward premium. Journal of International Money and Finance 15, 565–571.CrossRefGoogle Scholar
Blanchard, Olivier J. and Quah, Danny (1989) The dynamic effects of aggregate demand and supply disturbances. American Economic Review 79, 655–673.Google Scholar
Bloomfield, Peter (1973) An exponential model in the spectrum of a scalar time series. Biometrika 60, 217–226.CrossRefGoogle Scholar
Christiano, Lawrence, Eichenbaum, Martin, and Evans, Charles L. (1999) Monetary policy shocks: What have we learned and to what end? In Taylor, John B. and Woodford, Michael (eds.), Handbook of Macroeconomics, Vol. 1A, pp. 65–148. Amsterdam: North Holland.CrossRefGoogle Scholar
Christiano, Lawrence, Eichenbaum, Martin, and Vigfusson, Robert (2003) What Happens After a Technology Shock? NBER Working Paper 9819.CrossRefGoogle Scholar
Dickey, David A. and Fuller, Wayne A. (1979) Distribution of the estimator for autoregressive time series with a unit root. Journal of the American Statistical Association 74, 427–431.Google Scholar
Diebold, Francis X. and Rudebusch, Glenn D. (1989) Long memory and persistence in aggregate output. Journal of Monetary Economics 24, 189–209.CrossRefGoogle Scholar
Diebold, Francis X. and Rudebusch, Glenn D. (1991) On the power of Dickey-Fuller tests against fractional alternatives. Economic Letters 35, 155–160.CrossRefGoogle Scholar
Ding, Zhuanxin and Granger, Clive W. J. (1996) Modelling volatility persistence of speculative returns. Journal of Econometrics 73, 185–215.CrossRefGoogle Scholar
Fernald, John (2007) Trend breaks, long-run restrictions, and the contractionary effects of technology shocks. Journal of Monetary Economics 54, 2467–2485.CrossRefGoogle Scholar
Fisher, Jonas (2006) The dynamic effects of neutral and investment-specific shocks. Journal of Political Economy 114, 413–451.CrossRefGoogle Scholar
Francis, Neville and Ramey, Valerie A. (2005a) Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations Revisited. Journal of Monetary Economics 52, 1379–1399.CrossRefGoogle Scholar
Francis, Neville and Ramey, Valerie A. (2005b) Measures of Per Capita Hours and Their Implications for the Technology-Hours Debate. NBER Working Paper 11694.CrossRefGoogle Scholar
Galí, Jordi (1999) Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? American Economic Review 89, 249–271.CrossRefGoogle Scholar
Galí, Jordi and Rabanal, Pau (2004) Technology shocks and aggregate fluctuations: How well does the RBC model fit postwar U.S. data? NBER Macroeconomics Annual, pp. 225–288.CrossRefGoogle Scholar
García-del-Barrio, Pedro and Gil-Alana, Luis A. (2007) New revelations about unemployment persistence in Spain: Time series and panel data approaches using regional data. Applied Economics 38 (21), 1–18.Google Scholar
Gil-Alana, Luis A. (2003a) A fractional multivariate long memory model for the US and the Canadian real output. Economic Letters 81, 355–359.CrossRefGoogle Scholar
Gil-Alana, Luis A. (2003b) Multivariate tests of fractionally integrated hypotheses. South African Statistical Journal 37, 1–28.Google Scholar
Gil-Alana, Luis A. and Hualde, Javier (2009) Fractional integration and cointegration: An overview and an empirical application. In Mills, Terence C. and Patterson, K. (eds.), Handbook of Applied Econometrics, Vol. 2, pp. 434–470. New York: Palgrave MacMillan, Ltd.Google Scholar
Gil-Alana, Luis A. and Robinson, Peter M. (1997) Testing of unit roots and other nonstationary hypotheses in macroeconomic time series. Journal of Econometrics 80, 241–268.CrossRefGoogle Scholar
Granger, Clive W. J. (1980) Long memory relationships and the aggregation of dynamic models. Journal of Econometrics 14, 227–238.CrossRefGoogle Scholar
Granger, Clive W. J. and Joyeaux, Roselyne (1980) An introduction to long memory time series and fractional differencing. Journal of Time Series Analysis 1, 15–29.CrossRefGoogle Scholar
Hamilton, James D. (1994) Time Series Analysis. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Hassler, Uwe and Wolters, Jurgen (1994) On the power of unit root tests against fractional alternatives. Economic Letters 45, 1–5.CrossRefGoogle Scholar
Kwiatkowski, Denis, Phillips, Peter C. B., Schmidt, Peter, and Shin, Yongcheol (1992) Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics 54, 159–178.CrossRefGoogle Scholar
Lee, Junsoo and Schmidt, Peter (1996) On the power of the KPSS test of stationarity against fractionally integrated alternatives. Journal of Econometrics 73, 285–302.CrossRefGoogle Scholar
Lobato, Ignacio N. and Savin, Nathan E. (1998) Real and spurious long-memory properties of stock market data. Journal of Business and Economic Statistics 16, 261–283.CrossRefGoogle Scholar
Marelli, Enrico (1994) Evolution of unemployment structures and regional specialisation in the EU. Economic Systems 28, 35–59.CrossRefGoogle Scholar
Nielsen, Morten Ørregaard (2004) Efficient inference in multivariate fractionally integrated time series models. Econometrics Journal 7, 63–97.CrossRefGoogle Scholar
Nielsen, Morten Ørregaard (2005) Multivariate Lagrange multiplier tests for fractional integration, Journal of Financial Econometrics 3, 372–398.CrossRefGoogle 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.CrossRefGoogle Scholar
Phillips, Peter C. B. and Perron, Pierre, (1988) Testing for a unit root in time series regression. Biometrika 75, 335–346.CrossRefGoogle Scholar
Robinson, Peter M. (1978) Statistical inference for a random coefficient autoregressive model. Scandinavian Journal of Statistics 5, 163–168.Google Scholar
Robinson, Peter M. (1994) Efficient tests of nonstationary hypotheses. Journal of the American Statistical Association 89, 1420–1437.CrossRefGoogle Scholar
Robinson, Peter M. (1995) Gaussian semi-parametric estimation of long range dependence. Annals of Statistics 23, 1630–1661.CrossRefGoogle Scholar
Sowell, Fallaw (1992) Maximum likelihood estimation of stationary univariate fractionally integrated time series models. Journal of Econometrics 53, 165–188.CrossRefGoogle Scholar