arXiv 31 Jan 2022 · Econometrics · 1 citations (OpenAlex)
arXiv:2202.00141 · PDF · DOI · OpenAlex · Extracted main text
We revisit classical asymptotics when testing for a structural break in linear regression models by obtaining the limit theory of residual-based and Wald-type processes. First, we establish the Brownian bridge limiting distribution of these test statistics. Second, we study the asymptotic behaviour of the partial-sum processes in nonstationary (linear) time series regression models. Although, the particular comparisons of these two different modelling environments is done from the perspective of the partial-sum processes, it emphasizes that the presence of nuisance parameters can change the asymptotic behaviour of the functionals under consideration. Simulation experiments verify size distortions when testing for a break in nonstationary time series regressions which indicates that the Brownian bridge limit cannot provide a suitable asymptotic approximation in this case. Further research is required to establish the cause of size distortions under the null hypothesis of parameter stability.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Kulperger, R., Yu, H., et al (2005) High moment partial sum processes of residuals in garch models and their applications | 0.811 | 4 | 2 | 100% |
| 2 | Aue, A. and Horváth, L (2013) Structural breaks in time series | 0.737 | 3 | 3 | 67% |
| 3 | Phillips, P. C. B. and Durlauf, S. N (1986) Multiple time series regression with integrated processes | 0.644 | 2 | 2 | 100% |
| 4 | Bai, J (1997) Estimating multiple breaks one at a time | 0.644 | 2 | 2 | 100% |
| 5 | Bai, J. and Perron, P (1998) Estimating and testing linear models with multiple structural changes | 0.644 | 2 | 2 | 100% |
| 6 | Chu, C.-S. J., Stinchcombe, M., and White, H (1996) Monitoring structural change | 0.644 | 2 | 2 | 100% |
| 7 | Katsouris, C (2021) Sequential break-point detection in stationary time series: An application to monitoring economic indicators self | 0.644 | 2 | 2 | 100% |
| 8 | Pitarakis, J.-Y (2004) Least squares estimation and tests of breaks in mean and variance under misspecification | 0.644 | 2 | 2 | 100% |
| 9 | Phillips, P. C. B (1987) Time series regression with a unit root | 0.585 | 3 | 1 | 100% |
| 10 | Cavanagh, C. L., Elliott, G., and Stock, J. H (1995) Inference in models with nearly integrated regressors | 0.585 | 3 | 1 | 100% |
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