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Continuous Record Laplace-based Inference about the Break Date in Structural Change Models

Alessandro Casini, Pierre Perron

arXiv 1 Apr 2018 · Econometrics · publishedJournal of Econometrics (2020) · 6 citations (OpenAlex)

arXiv:1804.00232 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Building upon the continuous record asymptotic framework recently introduced by Casini and Perron (2018a) for inference in structural change models, we propose a Laplace-based (Quasi-Bayes) procedure for the construction of the estimate and confidence set for the date of a structural change. It is defined by an integration rather than an optimization-based method. A transformation of the least-squares criterion function is evaluated in order to derive a proper distribution, referred to as the Quasi-posterior. For a given choice of a loss function, the Laplace-type estimator is the minimizer of the expected risk with the expectation taken under the Quasi-posterior. Besides providing an alternative estimate that is more precise|lower mean absolute error (MAE) and lower root-mean squared error (RMSE)|than the usual least-squares one, the Quasi-posterior distribution can be used to construct asymptotically valid inference using the concept of Highest Density Region. The resulting Laplace-based inferential procedure is shown to have lower MAE and RMSE, and the confidence sets strike the best balance between empirical coverage rates and average lengths of the confidence sets relative to traditional long-span methods, whether the break size is small or large.

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55
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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
1Elliott, G., Müller, U.K (2007) Confidence sets for the date of a single break in linear time series regressions1.000113100%
2Bai, J (1997) Estimation of a change-point in multiple regression models1.00084100%
3Casini, A., Perron, P (2020) a self1.00053100%
4Bai, J., Perron, P (1998) Estimating and testing linear models with multiple structural changes self0.92843100%
5Chang, S.Y., Perron, P (2018) A comparison of alternative methods to construct confidence intervals for the estimate of a break date in linear regression models self0.92843100%
6Chernozhukov, V., Hong, H (2003) An MCMC approach to classical estimation0.87472100%
7Casini, A., Perron, P (2019) Structural breaks in time series self0.84333100%
8Ibragimov, A., Has'minski, R.Z (1981) Statistical estimation: asymptotic theory0.84333100%
9Casini, A., Perron, P (2020) b self0.64441100%
10Casini, A (2018) Tests for forecast instability and forecast failure under a continuous record asymptotic framework self0.64422100%

Showing the top 10 of 55 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 Models1.00053
2Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference0.58531
3Prewhitened Long-Run Variance Estimation Robust to Nonstationarity0.51121
4Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models0.51121
5Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework0.40511
6Backward CUSUM for Testing and Monitoring Structural Change with an Application to COVID-19 Pandemic Data0.40511
7Change-Point Analysis of Time Series with Evolutionary Spectra0.40511