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 …

This paper introduces an estimation procedure for a random effects probit model in presence of heteroskedasticity and a … likelihood ratio test for homoskedasticity. The cases where the heteroskedasticity is due to individual effects or idiosyncratic … heteroskedasticity. Furthermore, the power of the test increases with larger individual and time dimensions. The robustness analysis …

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 …

panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error … heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random …

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 …