Leverage and covariance matrix estimation in finite-sample IV regressions
AbstractThis paper develops basic algebraic concepts for instrumental variables (IV) regressions which are used to derive the leverage and influence of observations on the 2SLS estimate and compute alternative heteroskedasticity-consistent (HC1, HC2 and HC3) estimators for the 2SLS covariance matrix in a finite-sample context. Monte Carlo simulations and applications to growth regressions are used to evaluate the performance of these estimators. The results support the use of HC3 instead of White’s robust standard errors in small and unbalanced data sets. The leverage and influence of observations can be examined with the various measures derived in the paper.
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Bibliographic InfoPaper provided by Institute for Empirical Research in Economics - University of Zurich in its series IEW - Working Papers with number 521.
Date of creation: Dec 2010
Date of revision:
Two stage least squares; leverage; influence; heteroskedasticity-consistent covariance matrix estimation;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
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- Bun, Maurice J.G. & Harrison, Teresa D., 2014.
"OLS and IV estimation of regression models including endogenous interaction terms,"
School of Economics Working Paper Series
2014-3, LeBow College of Business, Drexel University.
- Maurice J.G. Bun & Teresa D. Harrison, 2014. "OLS and IV estimation of regression models including endogenous interaction terms," UvA-Econometrics Working Papers 14-02, Universiteit van Amsterdam, Dept. of Econometrics.
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