Testing for the sandwich-form covariance matrix of the quasi-maximum likelihood estimator

Lijuan Huo () and Jin Seo Cho ()
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Lijuan Huo: Beijing Institute of Technology

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2021, vol. 30, issue 2, No 1, 293-317

Abstract: Abstract This study tests for the sandwich-form asymptotic covariance matrices entailed by conditionally heteroskedastic and/or autocorrelated regression errors or conditionally uncorrelated homoskedastic errors. In doing so, we enable the empirical researcher to estimate the asymptotic covariance matrix of the quasi-maximum likelihood estimator by supposing a possibly misspecified model for error distribution. Accordingly, we provide test methodologies by extending the approaches in Cho and White (in: Chang Y, Fomby T, Park JY (eds) Advances in econometrics: essays in honor of Peter CB Phillips. Emerald Group Publishing Limited, West Yorkshire, 2014) and Cho and Phillips (J Econ 202:45–56, 2018a) to detect the influence of heteroskedastic and/or autocorrelated regression errors on the asymptotic covariance matrix. In particular, we establish a sequential testing procedure to achieve our goal. We affirm the theory on our test statistics through simulation and apply the test statistics to energy price growth rate data for illustrative purposes; here, we also apply our test methodology to test the fully correct model hypothesis.

Keywords: Information matrix equality; Sandwich-form covariance matrix; Heteroskedasticity-consistent covariance matrix estimator; Heteroskedasticity and autocorrelation-consistent covariance matrix estimator; 62J10; 62L05; 62P20 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11749-020-00719-x

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