Applications of Generalized Method of Moments Estimation
By Jeffrey M. Wooldridge. 2001
573 citations recorded by the source corpus.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/1afc1d1bc87f17c5471c218904f3ce8b8fe90d4b
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In Economics and Econometrics
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Citations in the corpus
- Generating artificial light curves: revisited and updated (2013, methodology): “…extreme long-tailed distributions, one can use appropriate methodologies developed for such purposes, such as the method of generalised moments (Wooldridge 2001), the method of cumulants (Frisken 2001) and the method of factorial moments (Bialas & Peschanski 1986) the latter being particularly…”
- Does the presence of independent and female directors impact firm performance? A multi-country study of board diversity (2016, methodology): “3.2 Methodology We test our hypotheses with the generalized method of moments (GMM) (Hansen 1982) regression which directly computes standard errors that are robust to heteroskedasticity of unknown form (Wooldridge 2001, 2002).”
- ARMS TRADE, MILITARY SPENDING, AND ECONOMIC GROWTH (2007, methodology): “The GMM estimator is convenient for estimating interesting extensions of the basic unobserved effects model when unobserved heterogeneity interacts with observed covariates, according to Wooldridge (2001).”
- Can Banks in Emerging Economies Benefit from Revenue Diversification? (2011, unknown): “However, if either heteroskedasticity or serial correlation is present a Generalized Method of Moments procedure can be more efficient than the fixed effects estimators ( Wooldridge 2001 ).”
- The Dynamic Implications of Foreign Aid and its Variability (2005, methodology): “The reasons for using GMM are twofold (Wooldridge, 2001): first, variables measured with error tend to have a bias toward zero; second, OLS does not account for the standard errors in the first-stage estimator.”