In this paper, we propose a robust approach against heteroskedasticity, error serial correlation and slope … used panel heteroskedasticity and autocorrelation consistent (HAC) variance estimator of the pooled estimator under random …

In this paper, we propose a robust approach against heteroskedasticity, error serial correlation and slope … used panel heteroskedasticity and autocorrelation consistent (HAC) variance estimator of the pooled estimator under random …

This paper evaluates the performance of the Breusch-Pagan LM test and the White test for heteroskedasticity in fixed … differences model for different variance functional forms, degrees of heteroskedasticity and sample sizes. Monte Carlo results … identifying heteroskedasticity than the Breusch-Pagan test, even if we are able to identify the actual functional form of the …

conditions (with or without a unit root), and error characteristics (homoskedasticity or heteroskedasticity of different forms …

) heteroskedasticity and nonlinearity in the relation between the error-ridden covariate and another, error-free, covariate in the equation …

allowance for heteroskedasticity is generally important. The solution is a Fuller (1977) like estimator and standard errors that … are robust to heteroskedasticity and many instruments. We show that the estimator has finite moments and high asymptotic …) under homoskedasticity, and has much lower bias and dispersion under heteroskedasticity, in nearly all cases considered. …

The paper introduces two estimators for the linear random effects panel data model with known heteroskedasticity …. Examples where heteroskedasticity can be treated as given include panel regressions with averaged data, meta regressions and …

The paper considers two estimators for the linear random effects panel data model with known heteroskedasticity …. Examples where heteroskedasticity can be treated as given include panel regression with averaged data, meta regression and the …