IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-07c30068.html
   My bibliography  Save this article

Long run and short run dynamics in italian manufacturing labour productivity

Author

Listed:
  • Tatiana Cesaroni

    (ISAE (Institute for Studies and Economic Analysis))

  • Carmine Pappalardo

    (ISAE)

Abstract

This paper examines structural changes in the Italian manufacturing sector, focusing on labour productivity in recent decades. To this end it distinguishes between trend and cyclical movements in the data using a multivariate unobserved components model. Changes in the relative importance of cyclical and trend components in labour productivity allow discrimination among the impacts of the factors affecting the performance of the Italian manufacturing sector during the 1980s, 1990s and in the more recent period.

Suggested Citation

  • Tatiana Cesaroni & Carmine Pappalardo, 2008. "Long run and short run dynamics in italian manufacturing labour productivity," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-11.
  • Handle: RePEc:ebl:ecbull:eb-07c30068
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/pubs/EB/2008/Volume3/EB-07C30068A.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Martin Neil Baily & Eric J. Bartelsman & John Haltiwanger, 2001. "Labor Productivity: Structural Change And Cyclical Dynamics," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 420-433, August.
    2. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
    3. Francesco Daveri & Cecilia Jona-Lasinio, 2005. "Italy's Decline: Getting the Facts Right," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 64(4), pages 365-410, December.
    4. Gerhard Runstler, 2004. "Modelling phase shifts among stochastic cycles," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 232-248, June.
    5. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    6. Tommaso Proietti & Alberto Musso & Thomas Westermann, 2007. "Estimating potential output and the output gap for the euro area: a model-based production function approach," Empirical Economics, Springer, vol. 33(1), pages 85-113, July.
    7. Clark, Peter K., 1989. "Trend reversion in real output and unemployment," Journal of Econometrics, Elsevier, vol. 40(1), pages 15-32, January.
    8. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    9. Ms. Silvia Sgherri, 2005. "Long-Run Productivity Shifts and Cyclical Fluctuations: Evidence for Italy," IMF Working Papers 2005/228, International Monetary Fund.
    10. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    11. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
    Full references (including those not matched with items on IDEAS)

    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. repec:ebl:ecbull:v:3:y:2008:i:15:p:1-11 is not listed on IDEAS
    2. Philippe Moës, 2006. "The production function approach to the Belgian output gap, estimation of a multivariate structural time series model," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 49(1), pages 59-91.
    3. Michael ARTIS & Massimiliano MARCELLINO & Tommaso PROIETTI, 2002. "Dating the Euro Area Business Cycle," Economics Working Papers ECO2002/24, European University Institute.
    4. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2019. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 541-569, September.
    5. Joao Valle e Azevedo & Siem Jan Koopman & Antonio Rua, 2003. "Tracking Growth and the Business Cycle: a Stochastic Common Cycle Model for the Euro Area," Tinbergen Institute Discussion Papers 03-069/4, Tinbergen Institute.
    6. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    7. Kum Hwa Oh & Eric Zivot & Drew Creal, 2006. "The Relationship between the Beveridge-Nelson Decomposition andUnobserved Component Models with Correlated Shocks," Working Papers UWEC-2006-16-FC, University of Washington, Department of Economics.
    8. Tommaso Proietti, 2009. "Structural Time Series Models for Business Cycle Analysis," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 9, pages 385-433, Palgrave Macmillan.
    9. Philippe Moës, 2008. "Multivariate structural time series models with dual cycles : implications for measurement of output gap and potential growth," Working Paper Research 136, National Bank of Belgium.
    10. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    11. Tommaso Proietti, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Econometrics 0209002, University Library of Munich, Germany.
    12. Siem Jan Koopman & Joao Valle e Azevedo, 2003. "Measuring Synchronisation and Convergence of Business Cycles," Tinbergen Institute Discussion Papers 03-052/4, Tinbergen Institute.
    13. Omar H. M. N. Bashar, 2015. "The Trickle‐down Effect of the Mining Boom in Australia: Fact or Myth?," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 94-108, June.
    14. Siem Jan Koopman & André Lucas & Pieter Klaassen, 2002. "Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation," Tinbergen Institute Discussion Papers 02-107/2, Tinbergen Institute.
    15. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.
    16. Siem Jan Koopman & Soon Yip Wong, 2006. "Extracting Business Cycles using Semi-parametric Time-varying Spectra with Applications to US Macroeconomic Time Series," Tinbergen Institute Discussion Papers 06-105/4, Tinbergen Institute.
    17. Andrew C. Harvey, 2002. "Trends, Cycles, and Convergence," Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Raimundo Soto & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series Editor) (ed.),Economic Growth: Sources, Trends, and Cycles, edition 1, volume 6, chapter 8, pages 221-250, Central Bank of Chile.
    18. repec:spo:wpmain:info:hdl:2441/1461 is not listed on IDEAS
    19. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    20. Tucker McElroy & Thomas Trimbur, 2015. "Signal Extraction for Non-Stationary Multivariate Time Series with Illustrations for Trend Inflation," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 209-227, March.
    21. Marian Vavra, 2016. "Testing the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle Decompositions," Working and Discussion Papers WP 4/2016, Research Department, National Bank of Slovakia.
    22. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    More about this item

    Keywords

    unobserved component models;

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    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:ebl:ecbull:eb-07c30068. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: John P. Conley (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.