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Measuring persistence in aggregate output: ARMA models, fractionally integrated ARMA models and nonparametric procedures

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Author Info

  • Erhard Reschenhofer

    ()
    (Institut für Statistik, Universität Wien, Universitätsstrasse 5, A-1010 Vienna, Austria)

  • Benedikt M. Pötscher

    ()
    (Institut für Statistik, Universität Wien, Universitätsstrasse 5, A-1010 Vienna, Austria)

  • Michael A. Hauser

    ()
    (Institut für Statistik, Wirtschaftsuniversität Wien, Augasse 2-6, A-1090 Vienna, Austria)

Abstract

Econometric issues in the estimation of persistence in macroeconomic time series are considered. In particular, the relative merits of estimates based on ARMA models, ARFIMA models and nonparametric procedures are investigated. It is shown that ARFIMA models are inappropriate for the purpose of estimating persistence. Furthermore, some of the criticism leveled in the literature against the use of ARMA models for estimating long run properties is put into perspective. Methodological issues arising in the estimation of ARMA models that are relevant to estimation of persistence are discussed. It is shown how overparameterization of an ARMA model may lead to severely downward biased estimates of persistence. The theoretical results are employed to explain some of the findings in Campbell & Mankiw (1987a) and Christiano & Eichenbaum (1990). The methodological aspects of the paper are also relevant for the problem of estimating the value of a spectral density at any given frequency. An empirical study confirms persistence estimates reported in Campbell & Mankiw (1987a), and shows that ARMA models as well as nonparametric procedures give very similar estimates of persistence if properly applied.

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 24 (1999)
Issue (Month): 2 ()
Pages: 243-269

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Handle: RePEc:spr:empeco:v:24:y:1999:i:2:p:243-269

Note: received: May 1996/final version received: March 1998
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Related research

Keywords: ARMA model · fractionally integrated ARMA model · persistence · spectral density estimation;

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Cited by:
  1. Hassler, Uwe, 2012. "Impulse responses of antipersistent processes," Economics Letters, Elsevier, vol. 116(3), pages 454-456.
  2. B. Verspagen & G. Silverberg, 2000. "A note on Michelacci and Zaffaroni, long memory, and time series of economic growth," Eindhoven Center for Innovation Studies (ECIS) working paper series 00.17, Eindhoven Center for Innovation Studies (ECIS).
  3. Silverberg,Gerald & Verspagen,Bart, 1999. "Long Memory in Time Series of Economic Growth and Convergence," Research Memorandum 015, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  4. Coleman, Simeon, 2010. "Inflation persistence in the Franc zone: Evidence from disaggregated prices," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 426-442, March.
  5. Ossama Mikhail & Curtis J. Eberwein & Jagdish Handa, 2003. "Testing and Estimating Persistence in Canadian Unemployment," Econometrics 0311004, EconWPA.
  6. Gary Koop, 1995. "Bayesian Analysis of Long Memory and Persistence using ARFIMA Models," Working Papers gkoop-95-01, University of Toronto, Department of Economics.
  7. Stefan C. Norrbin & Aaron D. Smallwood, 2006. "Generalized long memory processes, failure of cointegration tests and exchange rate dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 409-417.
  8. María Dolores Gadea & Laura Mayoral, 2006. "The Persistence of Inflation in OECD Countries: A Fractionally Integrated Approach," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
  9. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics.
  10. O. Mikhail & C. J. Eberwein & J. Handa, 2006. "Estimating persistence in Canadian unemployment: evidence from a Bayesian ARFIMA," Applied Economics, Taylor & Francis Journals, vol. 38(15), pages 1809-1819.

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