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Testing for structural change in the dynamic adjustment model with autoregressive errors

Author

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  • Kien C. Tran

    (Department of Economics, University of Saskatchewan, 9 Campus Drive, Saskatoon, Saskatchewan, Canada, S7N 5A5)

Abstract

The dynamic CUSUM test for structural change proposed by KrÄmer, Ploberger and Alt (1988) is investigated when the errors are serially correlated in a linear dynamic model. We show that the dynamic CUSUM test can be modified to allow for serial correlation in the disturbance using the same procedure as in Kao and Ross (1995), and that the modified dynamic CUSUM test retains its asymptotic significance levels. Monte Carlo results suggest that the empirical size of the dynamic CUSUM test is highly distorted while the empirical size of the modified dynamic CUSUM test is fairly robust to the change on the degree of autocorrelation. We also find that the power of the modified test essentially depends on the angle between the mean regressors and the structural shift.

Suggested Citation

  • Kien C. Tran, 1999. "Testing for structural change in the dynamic adjustment model with autoregressive errors," Empirical Economics, Springer, vol. 24(1), pages 61-76.
    • Handle: RePEc:spr:empeco:v:24:y:1999:i:1:p:61-76
    Note: received: April 1997/Final version received: January 1998
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    Cited by:

    1. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2008. "Detections of changes in return by a wavelet smoother with conditional heteroscedastic volatility," Journal of Econometrics, Elsevier, vol. 143(2), pages 227-262, April.

    More about this item

    Keywords

    Autocorrelation · Dynamic cusum · Structural change;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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