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Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates

Christis Katsouris

arXiv 10 Feb 2023 · Econometrics

arXiv:2302.05193 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose an econometric environment for structural break detection in nonstationary quantile predictive regressions. We establish the limit distributions for a class of Wald and fluctuation type statistics based on both the ordinary least squares estimator and the endogenous instrumental regression estimator proposed by Phillips and Magdalinos (2009a, Econometric Inference in the Vicinity of Unity. Working paper, Singapore Management University). Although the asymptotic distribution of these test statistics appears to depend on the chosen estimator, the IVX based tests are shown to be asymptotically nuisance parameter-free regardless of the degree of persistence and consistent under local alternatives. The finite-sample performance of both tests is evaluated via simulation experiments. An empirical application to house pricing index returns demonstrates the practicality of the proposed break tests for regression quantiles of nonstationary time series data.

Citation extraction

103
references
245
in-text mentions
103
distinct cited
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main-text words

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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
1Andrews, D. W (1993) Tests for parameter instability and structural change with unknown change point1.00063100%
2Katsouris, C. G (2021) Robust structural break tests in predictive regressions with persistent predictors self1.00053100%
3Qu, Z (2008) Testing for structural change in regression quantiles0.98219795%
4Lee, J. H (2016) Predictive quantile regression with persistent covariates: Ivx-qr approach0.93929783%
5Kostakis, A., Magdalinos, T., and Stamatogiannis, M. P (2015) Robust econometric inference for stock return predictability0.92810580%
6Gonzalo, J. and Pitarakis, J.-Y (2012) Regime-specific predictability in predictive regressions0.92843100%
7Gonzalo, J. and Pitarakis, J.-Y (2017) Inferring the predictability induced by a persistent regressor in a predictive threshold model0.92843100%
8Phillips, P. C. B. and Magdalinos, T (2009) Econometric inference in the vicinity of unity0.92419579%
9Galvao, A. F., Kato, K., Montes-Rojas, G., and Olmo, J (2014) Testing linearity against threshold effects: uniform inference in quantile regression0.8434475%
10Goh, S. C. and Knight, K (2009) Nonstandard quantile-regression inference0.8434375%

Showing the top 10 of 103 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
1Quantile Time Series Regression Models Revisited0.81142
2Limit Theory under Network Dependence and Nonstationarity0.51121
3Asymptotic Theory for Unit Root Moderate Deviations in Quantile Autoregressions and Predictive Regressions0.40511
4BOOTSTRAPPING NONSTATIONARY AUTOREGRESSIVE PROCESSES WITH PREDICTIVE REGRESSION MODELS BY CHRISTIS KATSOURIS University of Southampton and University of Exeter0.40511
5Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models0.40511
6Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models0.40511