IDEAS home Printed from https://ideas.repec.org/p/ein/tuecis/0017.html
   My bibliography  Save this paper

A note on Michelacci and Zaffaroni, long memory, and time series of economic growth

Author

Listed:
  • B. Verspagen

    (ECIS, Eindhoven University of Technology)

  • G. Silverberg

    (MERIT - Maastricht Economic Research Institute on Innovation and Technology,)

Abstract

In a recent paper in The Journal of Monetary Economics, Michelacci and Zaffaroni (2000)estimate long memory parameters for GDP per capita of 16 OECD countries. In this note weargue that these estimations are questionable for the purposes of clarifying the time seriesproperties of these data (presence of unit roots, mean reversion, long memory) because theauthors a) filter out a deterministic linear-in-logs trend instead of first-differencing in logs,and manipulate the data in other highly questionable ways, b) rely on the semiparametricGeweke and Porter-Hudak (GPH) method as modified by Robinson, which is known to behighly biased in small samples. We re-examine these results using Berans nonparametricFGN estimator and Sowells exact maximum likelihood ARFIMA estimator. These methodsavoid the small-sample bias and arbitrariness of the cut-off parameters of Robinsons methodand allow us to control for short memory effects, although the parametric ARFIMA estimatorintroduces specification problems of its own. We also look at the influence of the choice ofsub-periods on the results. Finally, we apply Robinsons method to our treatment of the dataand show that MZs results no longer hold, nor are their cut-off parameter and filteringinsensitivity claims substantiated.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • B. Verspagen & G. Silverberg, 2000. "A note on Michelacci and Zaffaroni, long memory, and time series of economic growth," Working Papers 00.17, Eindhoven Center for Innovation Studies.
  • Handle: RePEc:ein:tuecis:0017
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    2. Michael A. Hauser, 1998. "Maximum Likelihood Estimators for ARMA and ARFIMA Models: A Monte Carlo Study," Econometrics 9809001, EconWPA.
    3. Joseph G. Haubrich & Andrew W. Lo, "undated". "The Sources and Nature of Long-Term Memory in the Business Cycle," Rodney L. White Center for Financial Research Working Papers 05-89, Wharton School Rodney L. White Center for Financial Research.
    4. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    5. Michelacci, Claudio & Zaffaroni, Paolo, 2000. "(Fractional) beta convergence," Journal of Monetary Economics, Elsevier, vol. 45(1), pages 129-153, February.
    6. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 189-209, September.
    7. Erhard Reschenhofer & Benedikt M. Pötscher & Michael A. Hauser, 1999. "Measuring persistence in aggregate output: ARMA models, fractionally integrated ARMA models and nonparametric procedures," Empirical Economics, Springer, vol. 24(2), pages 243-269.
    8. Sowell, Fallaw, 1992. "Modeling long-run behavior with the fractional ARIMA model," Journal of Monetary Economics, Elsevier, vol. 29(2), pages 277-302, April.
    9. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    10. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    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. Giovanni Caggiano & Leone Leonida, 2009. "International output convergence: evidence from an autocorrelation function approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 139-162.
    2. Guglielmo Caporale & Luis Gil-Alana, 2013. "Long memory in US real output per capita," Empirical Economics, Springer, vol. 44(2), pages 591-611, April.
    3. Luis Alberiko Gil-Alaña & Borja Balprad & Guglielmo Maria Caporale, 2015. "African Growth, Non-Linearities and Strong Dependence: An Empirical Study," NCID Working Papers 12/2015, Navarra Center for International Development, University of Navarra.

    More about this item

    Keywords

    long memory; economic growth;

    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:ein:tuecis:0017. 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: (). General contact details of provider: http://edirc.repec.org/data/ectuenl.html .

    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.