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Estimation of a Structural Break Point in Linear Regression Models

Yaein Baek

arXiv 9 Nov 2018 · Econometrics · 1 citations (OpenAlex)

arXiv:1811.03720 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This study proposes a point estimator of the break location for a one-time structural break in linear regression models. If the break magnitude is small, the least-squares estimator of the break date has two modes at the ends of the finite sample period, regardless of the true break location. To solve this problem, I suggest an alternative estimator based on a modification of the least-squares objective function. The modified objective function incorporates estimation uncertainty that varies across potential break dates. The new break point estimator is consistent and has a unimodal finite sample distribution under small break magnitudes. A limit distribution is provided under an in-fill asymptotic framework. Monte Carlo simulation results suggest that the new estimator outperforms the least-squares estimator. I apply the method to estimate the break date in U.S. real GDP growth and U.S. and UK stock return prediction models.

Citation extraction

37
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appendix boundary found by appendix_titled_section at “Appendix A” · 59% of the source is main text. Read the extracted text to check this.

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., and Müller, U. K (2007) Confidence sets for the date of a single break in linear time series regression1.00073100%
2Jiang, L., Wang, X., and Yu, S (2017) In-fill asymptotic theory for structural break point in autoregression: A unified theory., Singapore Management University, Scho…0.97413592%
3Bai, J (1997) Estimation of a change point in multiple regression models0.92810580%
4Jiang, L., Wang, X., and Yu, S (2018) New distribution theory for the estimation of structural break0.92843100%
5Bai, J., and Perron, P (1998) Estimating and testing linear models with multiple structural changes0.8947371%
6Amemiya, T (1985) Advanced Econometrics0.81142100%
7Bai, J (1994) Least squares estimation of a shift in linear processes0.81142100%
8Bai, J., Lumsdaine, R. L., and Stock, J (1998) Testing for and dating common breaks in multivariate time series0.73732100%
9Casini, A., and Perron, P (2019) Continuous record Laplace-based inference about the break Date in structural models., arXiv preprint arXiv:1804.002320.73732100%
10Paye, B. S., and Timmermann, A (2006) Instability of return prediction models0.69381100%

Showing the top 10 of 37 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 Laplace-based Inference about the Break Date in Structural Change Models0.40511