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Spurious Break

Published online by Cambridge University Press:  11 February 2009

Abstract

A quasi-maximum likelihood estimator of the break date is analyzed. Consistency of the estimator is demonstrated under very general conditions, provided that the data-generating process is not integrated. However, the asymptotic distribution of the estimator is quite different for time series that are integrated of order one. In that case, when there is no break, the analyst can be spuriously led to the estimation of a break near the middle of the time series.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1995

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References

REFERENCES

Andrews, D.W.K. (1993) Tests for parameter instability and structural change with unknown change point. Econometrica 61, 821856.10.2307/2951764CrossRefGoogle Scholar
Arnold, L. (1974) Stochastic Differential Equations: Theory and Applications. New York: Wiley.Google Scholar
Bai, J. (1994) Least squares estimation of a shift in linear processes. Journal of Time Series Analysis 15, 453472.10.1111/j.1467-9892.1994.tb00204.xCrossRefGoogle Scholar
Brown, R.L., Durbin, J., & Evans, J.M. (1975) Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society, Series B 37, 149163.Google Scholar
Chu, C.-S.J. & White, H. (1992) A direct test for changing trend. Journal of Business and Economic Statistics 10, 289299.CrossRefGoogle Scholar
Durlauf, S.N. & Phillips, P.C.B. (1988) Trends versus random walks in time series analysis. Econometrica 56, 13331354.10.2307/1913101CrossRefGoogle Scholar
Granger, C.W.J. & Newbold, P. (1974) Spurious regressions in econometrics. Journal of Econometrics 2, 111120.10.1016/0304-4076(74)90034-7CrossRefGoogle Scholar
Hawkins, D.L. (1987) A test for a change point in a parametric model based on a maximal Waldtype statistic. Sankhya¯ 49, 368376.Google Scholar
Hendry, D.F. & Neale, A.J. (1991) A Monte Carlo study of the effects of structural breaks on tests for unit roots. In Hackl, P. & Westlund, A.H. (eds.), Economic Structural Change: Analysis and Forecasting, pp. 95119. New York: Springer–Verlag.10.1007/978-3-662-06824-3_8CrossRefGoogle Scholar
Hinkley, D. (1970) Inference about the change point in a sequence of random variables. Biometrika 57, 117.10.1093/biomet/57.1.1CrossRefGoogle Scholar
James, B., James, K.L., & Siegmund, D. (1987) Tests for a change-point. Biometrika 14, 7183.10.1093/biomet/74.1.71CrossRefGoogle Scholar
Krämer, W., Ploberger, W., & Alt, R. (1988) Testing for structural change in dynamic models. Econometrica 56, 13551369.10.2307/1913102CrossRefGoogle Scholar
Krishnaiah, P.R. & Miao, B.Q. (1988) Review about estimation of change points. In Krishnaiah, P.R. & Rao, C.R. (eds.), Handbook of Statistics, vol. 7, pp. 375402. New York: Elsevier.Google Scholar
Park, J.Y. & Phillips, P.C.B. (1988) Statistical inference in regressions with integrated processes: Part 1. Econometric Theory 4, 468497.10.1017/S0266466600013402CrossRefGoogle Scholar
Perron, P. (1989) The great crash, the oil price shock and the unit root hypothesis. Econometrica 57, 13611401.10.2307/1913712CrossRefGoogle Scholar
Perron, P. (1991) A Test for Changes in a Polynomial Trend Function for a Dynamic Time Series. Manuscript, Princeton University.Google Scholar
Phillips, P.C.B. (1986) Understanding spurious regressions in econometrics. Journal of Econometrics 33, 311340.10.1016/0304-4076(86)90001-1CrossRefGoogle Scholar
Phillips, P.C.B. & Perron, P. (1988) Testing for a unit root in time series regression. Biometrika 75, 335346.10.1093/biomet/75.2.335CrossRefGoogle Scholar
Ploberger, W. & Krämer, W. (1992) The CUSUM test with OLS residuals. Econometrica 60, 271285.10.2307/2951597CrossRefGoogle Scholar
Ploberger, W., Krämer, W., & Kontrus, K. (1989) A new test for structural stability in the linear regression model. Journal of Econometrics 40, 307318.10.1016/0304-4076(89)90087-0CrossRefGoogle Scholar
Talwar, P.P. (1983) Detecting a shift in location. Journal of Econometrics 23, 353367.10.1016/0304-4076(83)90064-7Google Scholar
Wooldridge, J.M. & White, H. (1988) Some invariance principles and central limit theorems for dependent heterogeneous processes. Econometric Theory 4, 210230.10.1017/S0266466600012032CrossRefGoogle Scholar
Yao, Y.-C. (1987) Approximating the distribution of the ML estimate of the change-point in a sequence of independent r.v.'s. Annals of Statistics 15, 13211328.10.1214/aos/1176350509Google Scholar
Zacks, S. (1983) Survey of classical and Bayesian approaches to the change point problem: Fixed sample and sequential procedures for testing and estimation. In Rivzi, M.H. et al. (eds.), Recent Advances in Statistics, pp. 245269. New York: Academic Press.10.1016/B978-0-12-589320-6.50016-2CrossRefGoogle Scholar