arXiv 14 Sep 2020 · Mathematics — Statistics Theory · publishedStatistics & Probability Letters (2020) · 23 citations (OpenAlex)
arXiv:2009.06621 · PDF · DOI · OpenAlex · Extracted main text
The Frisch--Waugh--Lovell Theorem states the equivalence of the coefficients from the full and partial regressions. I further show the equivalence between various standard errors. Applying the new result to stratified experiments reveals the discrepancy between model-based and design-based standard errors.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Angrist, J. D. and Pischke, J.-S (2008) Mostly Harmless Econometrics: An Empiricist's Companion | 1.000 | 7 | 4 | 100% |
| 2 | Andrews, D. W. K (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation | 0.644 | 2 | 2 | 100% |
| 3 | Andrews, D. W. K. and Monahan, J. C (1992) An improved heteroskedasticity and autocorrelation consistent covariance matrix estimator | 0.644 | 2 | 2 | 100% |
| 4 | Liang, K.-Y. and Zeger, S. L (1986) Longitudinal data analysis using generalized linear models | 0.644 | 2 | 2 | 100% |
| 5 | Lumley, T. and Heagerty, P (1999) Weighted empirical adaptive variance estimators for correlated data regression | 0.644 | 2 | 2 | 100% |
| 6 | MacKinnon, J. G. and White, H (1985) Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties | 0.644 | 2 | 2 | 100% |
| 7 | Newey, W. and West, K (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix | 0.644 | 2 | 2 | 100% |
| 8 | Newey, W. K. and West, K. D (1994) Automatic lag selection in covariance matrix estimation | 0.644 | 2 | 2 | 100% |
| 9 | Zeileis, A (2004) Econometric computing with HC and HAC covariance matrix estimators | 0.644 | 2 | 2 | 100% |
| 10 | Imbens, G. W. and Rubin, D. B (2015) Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 31 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | The Yule-Frisch-Waugh-Lovell Theorem | 0.961 | 9 | 3 |
| 2 | The Yule-Frisch-Waugh-Lovell Theorem for Linear Instrumental Variables Estimation | 0.909 | 16 | 5 |