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Testing parameter constancy in linear models against stochastic stationary parameters

  • Lin, Chien-Fu Jeff
  • Terasvirta, Timo

This paper considers testing parameter constancy in linear models when the alternative is that a subset of the parameters follow a stationary vector autoregressive process of known finite order. This kind of a linear model is only identified under the alternative, which usually precludes finding a test statistic with an analytic nuyll distribution. In the present situation, however, it is still possible to derive a test statistic with an asymptotic chi-squared distribution under the null hypothesis and this is done in the paper. The small-sample properties of the test statistic are investigated by simulation and found satisfactory. The test retains its power when the alternative to parameter constancy is a random walk parameter process.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 90 (1999)
Issue (Month): 2 (June)
Pages: 193-213

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Handle: RePEc:eee:econom:v:90:y:1999:i:2:p:193-213
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  1. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  2. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
  3. DAVIDSON, Russel & MACKINNON, James G., . "Heteroskedastcity-robust tests in regressions directions," CORE Discussion Papers RP 678, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  4. Watson, Mark W & Engle, Robert F, 1985. "Testing for Regression Coefficient Stability with a Stationary AR(1) Alternative," The Review of Economics and Statistics, MIT Press, vol. 67(2), pages 341-46, May.
  5. Bos, T & Newbold, P, 1984. "An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model," The Journal of Business, University of Chicago Press, vol. 57(1), pages 35-41, January.
  6. Brooks, Robert D., 1993. "Alternative point-optimal tests for regression coefficient stability," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 365-376.
  7. Min, Chung-ki & Zellner, Arnold, 1993. "Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 89-118, March.
  8. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
  9. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
  10. Dufour, Jean-Marie, 1982. "Recursive stability analysis of linear regression relationships: An exploratory methodology," Journal of Econometrics, Elsevier, vol. 19(1), pages 31-76, May.
  11. Shively, Thomas S., 1988. "An analysis of tests for regression coefficient stability," Journal of Econometrics, Elsevier, vol. 39(3), pages 367-386, November.
  12. Pagan, Adrian, 1980. "Some identification and estimation results for regression models with stochastically varying coefficients," Journal of Econometrics, Elsevier, vol. 13(3), pages 341-363, August.
  13. Farley, John U. & Hinich, Melvin & McGuire, Timothy W., 1975. "Some comparisons of tests for a shift in the slopes of a multivariate linear time series model," Journal of Econometrics, Elsevier, vol. 3(3), pages 297-318, August.
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