heteroskedasticity robust standard errorsheterosked asticity robust standard errors 异增塑性稳健标准误差 重点词汇 robust强健的;坚固的;强劲的;耐用的;结实的;强壮的;坚定的;富有活力的 errors错误;差错;谬误; error的复数©2022 Baidu |由 百度智能云 提供计算服务 | 使用百度前必读 | 文库协议 | 网站地图 ...
Heteroskedasticity- robust inference in linear regressions. Communications in statistics - Simulation and Com- putation 39, 194-206.Lima V C, Souza T C, Cribari-Neto F, et al. Heteroskedasticity-robust inference in linear regression[J]. Commu- nications in Statistics-Simulation and Computation, ...
76, No. 1 (January, 2008), 155–174HETEROSKEDASTICITY-ROBUST STANDARD ERRORS FORFIXED EFFECTS PANEL DATA REGRESSIONJ AMES H. S TOCKHarvard University, Cambridge, MA 02138, U.S.A., and NBERM ARK W. W ATSONWoodrow Wilson School, Princeton University, Princeton, NJ 08544, U.S.A., and ...
Inlinear regression analysis, anestimator of the asymptotic covariance matrixof the OLS estimator is said to be heteroskedasticity-robust if it converges asymptotically to the true value even when the variance of the errors of the regression is not constant. In this case, also the standard errors,...
Since the advent of heteroskedasticity-robust standard errors, several papers have proposed adjustments to the original White formulation. We replicate earlier findings that each of these adjusted estimators performs quite poorly in finite samples. We propose a class of alternative heteroskedasticity-robust...
Robust Standard Errors for Robust:强大的稳健标准误差 热度: 标准误差对效应量解释的影响 热度: Introduction to Fixed Effects Methods - SAS:介绍了固定效应方法的SAS 热度: Heteroskedasticity-RobustStandardErrorsforFixedEffectsPanelDataRegression May26,2006 ...
the Bayesian estimator can be made to look very similar to the usual heteroskedasticity-robust frequentist estimator. Bayesian estimation is easily accomplished by a standard MCMC procedure. * Department of Economics, 2127 North Hall, University of California, Santa Barbara, CA 93106, email: startz@...
Heteroskedasticity-robust elasticities in logarithmic and two-part models 来自 EconPapers 喜欢 0 阅读量: 35 作者:Hertz, Tom 摘要: Logarithmic models are widely used to study highly skewed positive outcomes, either alone or in combination with an equation that first distinguishes between zero and non...
Their method, however, is not generalizable to dynamic panel data models, although heteroskedasticity-robust inferences have natural relevance to dynamic models due to the requirement of serial uncorrelatedness for model identification. In the present paper, we provide a solution for instrumental ...
Comment: On p. 307, you write that robust standard errors “can be smaller than conventional standard errors for two reasons:the small sample bias we have discussed and their higher sampling variance.” A third reason is that heteroskedasticity can make the conventional s.e. upward-biased. ...