IDEAS home Printed from https://ideas.repec.org/a/cup/macdyn/v9y2005i04p478-488_04.html
   My bibliography  Save this article

Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure

Author

Listed:
  • PESAVENTO, ELENA
  • ROSSI, BARBARA

Abstract

This paper analyzes the robustness of the estimate of a positive productivity shock on hours to the presence of a possible unit root in hours. Estimations in levels or in first differences provide opposite conclusions. We rely on an agnostic procedure in which the researcher does not have to choose between a specification in levels or in first differences. We find that a positive productivity shock has a negative impact effect on hours, but the effect is much shorter lived, and disappears after two quarters. The effect becomes positive at business-cycle frequencies, although it is not significant.

Suggested Citation

  • Pesavento, Elena & Rossi, Barbara, 2005. "Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 9(4), pages 478-488, September.
  • Handle: RePEc:cup:macdyn:v:9:y:2005:i:04:p:478-488_04
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1365100505040356/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Elliott, Graham & Jansson, Michael, 2003. "Testing for unit roots with stationary covariates," Journal of Econometrics, Elsevier, vol. 115(1), pages 75-89, July.
    2. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    3. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    4. Elliott, Graham & Stock, James H., 2001. "Confidence intervals for autoregressive coefficients near one," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 155-181, July.
    5. Graham Elliott & Michael Jansson & Elena Pesavento, 2005. "Optimal Power for Testing Potential Cointegrating Vectors With Known Parameters for Nonstationarity," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 34-48, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jordi Gali & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBS Model Fit Postwar U.S. Data?," NBER Working Papers 10636, National Bureau of Economic Research, Inc.
    2. Patrick Fève & Alain Guay, 2010. "Identification of Technology Shocks in Structural Vars," Economic Journal, Royal Economic Society, vol. 120(549), pages 1284-1318, December.
    3. Ulrich K. Müller & Mark W. Watson, 2008. "Testing Models of Low-Frequency Variability," Econometrica, Econometric Society, vol. 76(5), pages 979-1016, September.
    4. Chevillon, Guillaume & Mavroeidis, Sophocles & Zhan, Zhaoguo, 2016. "Robust inference in structural VARs with long-run restrictions," ESSEC Working Papers WP1702, ESSEC Research Center, ESSEC Business School.
    5. Ghent, Andra C., 2009. "Comparing DSGE-VAR forecasting models: How big are the differences?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 864-882, April.
    6. Ali YOUSEFI & Sadegh KHALILIAN & Mohammad Hadi HAJIAN, 2010. "The Role of Water Sector in Iranian Economy: A CGE Modeling Approach," EcoMod2010 259600173, EcoMod.
    7. Morten O. Ravn & Saverio Simonelli, 2007. "Labor Market Dynamics and the Business Cycle: Structural Evidence for the United States," Scandinavian Journal of Economics, Wiley Blackwell, vol. 109(4), pages 743-777, December.
    8. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2014. "Persistence and cycles in US hours worked," Economic Modelling, Elsevier, vol. 38(C), pages 504-511.
    9. Nikolay Gospodinov & Alex Maynard & Elena Pesavento, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 455-467, October.
    10. Rujin, Svetlana, 2019. "What are the effects of technology shocks on international labor markets?," Ruhr Economic Papers 806, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    11. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2012. "Persistence and Cycles in US Hours Worked," CESifo Working Paper Series 3767, CESifo.
    12. Di Pace, Federico & Villa, Stefania, 2016. "Factor complementarity and labour market dynamics," European Economic Review, Elsevier, vol. 82(C), pages 70-112.
    13. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "The Variance-Frequency Decomposition as an Instrument for VAR Identification: an Application to Technology Shocks," Working Papers 2072/261537, Universitat Rovira i Virgili, Department of Economics.
    14. Riccardo DiCecio & Michael T. Owyang, 2010. "Identifying technology shocks in the frequency domain," Working Papers 2010-025, Federal Reserve Bank of St. Louis.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.
    2. Elena Pesavento, 2006. "Near-Optimal Unit Root Tests with Stationary Covariates with Better Finite Sample Size," Economics Working Papers ECO2006/18, European University Institute.
    3. Fossati, Sebastian, 2012. "Covariate unit root tests with good size and power," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3070-3079.
    4. Elliott, Graham & Pesavento, Elena, 2006. "On the Failure of Purchasing Power Parity for Bilateral Exchange Rates after 1973," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1405-1430, September.
    5. Kaddour Hadri & Eiji Kurozumi & Daisuke Yamazaki, 2015. "Synergy between an Improved Covariate Unit Root Test and Cross-sectionally Dependent Panel Data Unit Root Tests," Manchester School, University of Manchester, vol. 83(6), pages 676-700, December.
    6. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.
    7. Rossi, Barbara, 2005. "Confidence Intervals for Half-Life Deviations From Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 432-442, October.
    8. Claude Lopez & Christian J. Murray & David H. Papell, 2013. "Median-unbiased estimation in DF-GLS regressions and the PPP puzzle," Applied Economics, Taylor & Francis Journals, vol. 45(4), pages 455-464, February.
    9. Pierre Perron & Gabriel Rodríguez, "undated". "Residuals-based Tests for Cointegration with GLS Detrended Data," Boston University - Department of Economics - Working Papers Series wp2015-017, Boston University - Department of Economics, revised 19 Oct 2015.
    10. Giancarlo Corsetti & Luca Dedola & Sylvain Leduc, 2008. "Productivity, External Balance, and Exchange Rates: Evidence on the Transmission Mechanism among G7 Countries," NBER Chapters, in: NBER International Seminar on Macroeconomics 2006, pages 117-194, National Bureau of Economic Research, Inc.
    11. Elliott, Graham & Jansson, Michael, 2003. "Testing for unit roots with stationary covariates," Journal of Econometrics, Elsevier, vol. 115(1), pages 75-89, July.
    12. Shahbaz, Muhammad & Farhani, Sahbi & Ozturk, Ilhan, 2013. "Coal Consumption, Industrial Production and CO2 Emissions in China and India," MPRA Paper 50618, University Library of Munich, Germany, revised 12 Oct 2013.
    13. Ching-Chuan Tsong & Cheng-Feng Lee, 2013. "Further Evidence On Real Interest Rate Equalization: Panel Information, Non-Linearities And Structural Changes," Bulletin of Economic Research, Wiley Blackwell, vol. 65, pages 85-105, May.
    14. Mehdi Hosseinkouchack & Uwe Hassler, 2016. "Powerful Unit Root Tests Free of Nuisance Parameters," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 533-554, July.
    15. Barbara Rossi & Elena Pesavento, 2006. "Small-sample confidence intervals for multivariate impulse response functions at long horizons," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1135-1155.
    16. Tsong, Ching-Chuan & Wu, Chien-Wei & Chiu, Hsien-Hung & Lee, Cheng-Feng, 2013. "Covariate unit root tests under structural change and asymmetric STAR dynamics," Economic Modelling, Elsevier, vol. 33(C), pages 101-112.
    17. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    18. Maurizio Bovi, 2004. "The Dark, And Independent, Side Of Italy," ISAE Working Papers 46, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    19. Joakim Westerlund, 2013. "A computationally convenient unit root test with covariates, conditional heteroskedasticity and efficient detrending," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 477-495, July.
    20. Chukiat Chaiboonsri & Prasert Chaitip & N. Rangaswamy, 2009. "Modelling International Tourism Demand in Thailand," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 9(3), pages 125-146.

    More about this item

    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
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cup:macdyn:v:9:y:2005:i:04:p:478-488_04. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Keith Waters). General contact details of provider: https://www.cambridge.org/mdy .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.