Alessandro Casini, Pierre Perron
arXiv 28 Mar 2018 · Mathematics — Statistics Theory · 2 citations (OpenAlex)
arXiv:1803.10871 · PDF · DOI · OpenAlex · Extracted main text
Under the classical long-span asymptotic framework we develop a class of Generalized Laplace (GL) inference methods for the change-point dates in a linear time series regression model with multiple structural changes analyzed in, e.g., Bai and Perron (1998). The GL estimator is defined by an integration rather than optimization-based method and relies on the least-squares criterion function. It is interpreted as a classical (non-Bayesian) estimator and the inference methods proposed retain a frequentist interpretation. This approach provides a better approximation about the uncertainty in the data of the change-points relative to existing methods. On the theoretical side, depending on some input (smoothing) parameter, the class of GL estimators exhibits a dual limiting distribution; namely, the classical shrinkage asymptotic distribution, or a Bayes-type asymptotic distribution. We propose an inference method based on Highest Density Regions using the latter distribution. We show that it has attractive theoretical properties not shared by the other popular alternatives, i.e., it is bet-proof. Simulations confirm that these theoretical properties translate to better finite-sample performance.
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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 | Casini, A. and P. Perron (2020) Continuous record asymptotics for structural change models self | 1.000 | 11 | 5 | 100% |
| 2 | Bai, J. and P. Perron (1998) Estimating and testing linear models with multiple structural changes | 0.932 | 21 | 8 | 81% |
| 3 | Yao, Y (1987) Approximating the distribution of the ML estimate of the change-point in a sequence of independent random variables | 0.928 | 4 | 3 | 100% |
| 4 | Ibragimov, A. and R.Z. Has'minski (1981) Statistical estimation: asymptotic theory | 0.909 | 8 | 5 | 75% |
| 5 | Bai, J (1997) Estimation of a change-point in multiple regression models | 0.880 | 22 | 6 | 68% |
| 6 | Casini, A. and P. Perron (2020) Continuous record Laplace-based inference in structural change models self | 0.874 | 9 | 5 | 67% |
| 7 | Elliott, G. and U.K. Müller (2007) Confidence sets for the date of a single break in linear time series regressions | 0.874 | 7 | 2 | 100% |
| 8 | Chernozhukov, V. and H. Hong (2003) An MCMC approach to classical estimation | 0.811 | 4 | 2 | 100% |
| 9 | Buehler, R.J (1959) Some validity criteria for statistical inferences | 0.737 | 3 | 2 | 100% |
| 10 | Casini, A (2020) Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstati… self | 0.737 | 3 | 2 | 100% |
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