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Generalized Laplace Inference in Multiple Change-Points Models

Alessandro Casini, Pierre Perron

arXiv 28 Mar 2018 · Mathematics — Statistics Theory · 2 citations (OpenAlex)

arXiv:1803.10871 · PDF · DOI · OpenAlex · Extracted main text

Abstract

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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79
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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Casini, A. and P. Perron (2020) Continuous record asymptotics for structural change models self1.000115100%
2Bai, J. and P. Perron (1998) Estimating and testing linear models with multiple structural changes0.93221881%
3Yao, Y (1987) Approximating the distribution of the ML estimate of the change-point in a sequence of independent random variables0.92843100%
4Ibragimov, A. and R.Z. Has'minski (1981) Statistical estimation: asymptotic theory0.9098575%
5Bai, J (1997) Estimation of a change-point in multiple regression models0.88022668%
6Casini, A. and P. Perron (2020) Continuous record Laplace-based inference in structural change models self0.8749567%
7Elliott, G. and U.K. Müller (2007) Confidence sets for the date of a single break in linear time series regressions0.87472100%
8Chernozhukov, V. and H. Hong (2003) An MCMC approach to classical estimation0.81142100%
9Buehler, R.J (1959) Some validity criteria for statistical inferences0.73732100%
10Casini, A (2020) Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstati… self0.73732100%

Showing the top 10 of 79 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Continuous Record Asymptotics for Change-Point Models0.81142
2Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models0.69361
3Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference0.51121
4Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models0.51121
5Prewhitened Long-Run Variance Estimation Robust to Nonstationarity0.40511
6Change-Point Analysis of Time Series with Evolutionary Spectra0.40511