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Semiparametric estimation and inference for trending I(d) and related processes

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  • K Abadir
  • W Distaso
  • L Giraitis

Abstract

This paper deals with estimation and hypothesis testing in stationary and nonstationary models with a linear trend. Using semiparametric estimators, we obtain asymptotic confidence intervals for mean, trend, and memory parameters. The confidence intervals are applicable for a wide class of processes (including some nonlinear processes), exhibit high coverage accuracy and are easy to implement. We also develop joint hypothesis testing for these parameters, when the alternative for the memory parameter is one-sided, but the ones for the deterministic components are two-sided. We use our results to show that US GDP has less memory than is implied by a unit root, and that it evolves around a deterministic trend. This result has important implications for macroeconomic stabilization policies.

Suggested Citation

  • K Abadir & W Distaso & L Giraitis, "undated". "Semiparametric estimation and inference for trending I(d) and related processes," Discussion Papers 05/15, Department of Economics, University of York.
    • Handle: RePEc:yor:yorken:05/15
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    Cited by:

    1. Abadir, Karim M. & Caggiano, Giovanni & Talmain, Gabriel, 2013. "Nelson–Plosser revisited: The ACF approach," Journal of Econometrics, Elsevier, vol. 175(1), pages 22-34.
    2. Christian Macaro, 2007. "The Impact of Vintage on the Persistence of Gross Domestic Product Shocks," CEIS Research Paper 101, Tor Vergata University, CEIS.
    3. Macaro, Christian, 2008. "The impact of vintage on the persistence of gross domestic product shocks," Economics Letters, Elsevier, vol. 98(3), pages 301-308, March.

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