Several tests for heteroskedasticity in linear regression models are examined. Asymptoticrobustness to heterokurticity …, nonnormality and skewness is discussed. The finite sample eliability of asymptotically valid tests is investigated using Monte …

(non-normality) and heteroskedasticity. … distribution including no condition on the existence of moments allowing for heterogeneity (or heteroskedasticity) of unknown form … condition on error moment existence, allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous …

We derive a new matrix statistic for the Hausman test for endogeneity in cross-sectional Instrumental Variables … estimation, that incorporates heteroskedasticity in a natural way and does not use a generalized inverse. A Monte Carlo study … examines the performance of the statistic for different heteroskedasticity-robust variance estimators and different skedastic …

This paper proposes estimating linear dynamic panels by explicitly exploiting the endogeneity of lagged dependent … conditions (with or without a unit root), and error characteristics (homoskedasticity or heteroskedasticity of different forms …

. Its performance is compared with that of standard models of conditional heteroskedasticity such as GARCH. This has … for the A-PARCH model that are derived for the purpose. The role of the heteroskedasticity parameter of the A …

the National Longitudinal Survey of Youth 1979. Accounting for endogeneity increases the estimate of the return to …

, distributed lags and vector autoregressions (VAR), quasi-experiments, and identification by heteroskedasticity (IH). Ultimately …

that address HAC standard errors, weak instruments, LIML and k-class estimation, tests for endogeneity and RESET and …

the National Longitudinal Survey of Youth 1979. Accounting for endogeneity increases the estimate of the return to …

find that accounting for the endogeneity of education in this manner increases the estimated return to education from 6 …