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Speed of adjustment and estimation of the partial adjustment model

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  • Marcus Chambers

Abstract

The effect which the speed of adjustment parameter has on the statistical properties of the partial adjustment model, and estimates of its parameters, is investigated. It is shown that in the case of very rapid adjustment, the model approaches a classical (static) regression model, but in the case of very slow adjustment, the dependent (or state) variable displays near random walk behaviour. The finite sample performance of the nonlinear least squares estimator is investigated in a simulation study, and it is found that substantial bias and mean squared error can be a feature of the estimates in the model with very slow adjustment. This suggests that extreme caution should be exercised in situations where the estimated speed of adjustment parameter is found to be small.

Suggested Citation

  • Marcus Chambers, 1996. "Speed of adjustment and estimation of the partial adjustment model," Applied Economics Letters, Taylor & Francis Journals, vol. 3(1), pages 21-23.
    • Handle: RePEc:taf:apeclt:v:3:y:1996:i:1:p:21-23
    DOI: 10.1080/758525509
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    References listed on IDEAS

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    1. McManus, Douglas A. & Nankervis, John C. & Savin, N. E., 1994. "Multiple optima and asymptotic approximations in the partial adjustment model," Journal of Econometrics, Elsevier, vol. 62(2), pages 91-128, June.
    2. Park, Joon Y. & Phillips, Peter C.B., 1989. "Statistical Inference in Regressions with Integrated Processes: Part 2," Econometric Theory, Cambridge University Press, vol. 5(1), pages 95-131, April.
    3. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, Decembrie.
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