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Estimating Deterministric Trends with an Integrated or Stationary Noise Component

  • Pierre Perron

    ()

    (Department of Economics, Boston University)

  • Tomoyoshi Yabu

    ()

    (Department of Economics, Boston University)

We propose a test for the slope of a trend function when it is a priori unknown whether the series is trend-stationary or contains an autoregressive unit root. The procedure is based on a Feasible Quasi Generalized Least Squares method from an AR(1) specification with parameter [alpha], the sum of the autoregressive coefficients. The estimate of [alpha] is the OLS estimate obtained from an autoregression applied to detrended data and is truncated to take a value 1 whenever the estimate is in a T-[delta] neighborhood of 1. This makes the estimate "super-efficient" when [alpha]=1 and implies that inference on the slope parameter can be performed using the standard Normal distribution whether [alpha]=1 or [alpha]

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Paper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number WP2005-037.

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Length: 34 pages
Date of creation: Jul 2005
Date of revision:
Handle: RePEc:bos:wpaper:wp2005-037
Contact details of provider: Postal: 270 Bay State Road, Boston, MA 02215
Phone: 617-353-4389
Fax: 617-353-4449
Web page: http://www.bu.edu/econ/

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  46. repec:cup:etheor:v:6:y:1990:i:3:p:335-47 is not listed on IDEAS
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