A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
Abstract
This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.
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The robustness of the findings is further supported by the Newey and West (1987) t-statistic.
“The robustness of our findings is further supported by the Newey and West (1987) 𝑡 -statistic, as presented in Table IA 1 of the Internet Appendix.”
From ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy? (2025) · cites this paper as Newey and West (1987)
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- Authors
- Newey, W. K., & West, K. D.
- Affiliations
- National Bureau of Economic Research (US)
- Venue
- Econometrica
- Publisher
- JSTOR
- Published
- 1987-05
- Volume
- 55
- Issue
- 3
- Pages
- 703
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2117178635
- Cited by
- 16,936
- References
- 0
- Citations by year
- 2026: 1207 · 2025: 818 · 2024: 783 · 2023: 809 · 2022: 771 · 2021: 800 · 2020: 761 · 2019: 722 · 2018: 708 · 2017: 693 · 2016: 647 · 2015: 682 · 2014: 688 · 2013: 637 · 2012: 677
- FWCI
- 48.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Econometrica (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Keywords
- asymptotic covariance matrix
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