Bootstrap bias-adjusted GMM estimators
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Publication:1929388
DOI10.1016/J.ECONLET.2006.01.026zbMath1254.91616OpenAlexW2053264059MaRDI QIDQ1929388
Publication date: 8 January 2013
Published in: Economics Letters (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10174/8424
Applications of statistics to actuarial sciences and financial mathematics (62P05) Monte Carlo methods (65C05) Statistical methods; economic indices and measures (91B82)
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Empirical likelihood block bootstrapping ⋮ Moment-based estimation of nonlinear regression models with boundary outcomes and endogeneity, with applications to nonnegative and fractional responses
Cites Work
- Empirical likelihood and general estimating equations
- Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures
- Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators
- Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators
- More Efficient Bootstrap Computations
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