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An Asymptotically F-Distributed Chow Test in the Presence of Heteroscedasticity and Autocorrelation

Yixiao Sun, Xuexin Wang

arXiv 9 Nov 2019 · Econometrics · publishedEconometric Reviews (2021) · 2 citations (OpenAlex)

arXiv:1911.03771 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This study proposes a simple, trustworthy Chow test in the presence of heteroscedasticity and autocorrelation. The test is based on a series heteroscedasticity and autocorrelation robust variance estimator with judiciously crafted basis functions. Like the Chow test in a classical normal linear regression, the proposed test employs the standard F distribution as the reference distribution, which is justified under fixed-smoothing asymptotics. Monte Carlo simulations show that the null rejection probability of the asymptotic F test is closer to the nominal level than that of the chi-square test.

Citation extraction

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appendix boundary found by appendix_titled_section at “Appendix of Proofs” · 56% 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
1Cho, C.-K. and Vogelsang, T. J (2017) Fixed-b inference for testing structural change in a time series regression0.64422100%
2Sun, Y (2013) A heteroskedasticity and autocorrelation robust F test using orthonormal series variance estimator self0.51121100%
3Andrews, D. W. K (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation0.40511100%
4Chow, G. C (1960) Tests of equality between sets of coefficients in two linear regressions0.40511100%
5Giles, D. and Scott, M (1992) Some consequences of using the Chow test in the context of autocorrelated disturbances0.40511100%
6Hwang, J. and Sun, Y (2017) Asymptotic F and t tests in an efficient GMM setting self0.40511100%
7Jansson, M (2004) On the error of rejection probability in simple autocorrelation robust tests0.40511100%
8Krämer, W (1989) The Robustness of the Chow Test to Autocorrelation among Disturbances, pages 45–520.40511100%
9Kiefer, N. M. and Vogelsang, T. J (2002) 2002a Heteroskedasticity-autocorrelation robust testing using bandwidth equal to sample size0.40511100%
10Kiefer, N. M. and Vogelsang, T. J (2002) 2002b Heteroskedasticity-autocorrelation robust standard errors using the Bartlett kernel without truncation0.40511100%

Showing the top 10 of 20 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
1Robust Inference on Infinite and Growing Dimensional Time Series Regression0.40511
2Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models0.40511