Testing for Heteroskedasticity in Fixed Effects Models

Testing for Serial Correlation in Fixed-Effects Panel Data Models

In this paper, we propose three new tests for serial correlation in the disturbances of fixed-effects panel data models. First, a modified Bhargava, Franzini and Narendranathan (1982) panel Durbin-Watson statistic that does not need to be tabulated as it follows a standard normal distribution. Second, a modified Baltagi and Li (1991) LM statistic with limit distribution independent of T , and, ...

Seasonal Heteroskedasticity in Time Series Data: Modeling, Estimation, and Testing

Seasonal heteroskedasticity refers to regular changes in variability over the calendar year. Models for two different forms of seasonal heteroskedasticity were recently proposed by Proietti and by Bell. We examine use of likelihood ratio tests with the models to test for the presence of seasonal heteroskedasticity, and use of model comparison statistics (AIC) to compare the models and to search...

Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression

The conventional heteroskedasticity-robust (HR) variance matrix estimator for cross-sectional regression (with or without a degrees-of-freedom adjustment), applied to the fixed-effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than 2) as the number of entities n increases. We provide a bias-adjusted HR estim...

Integrated Conditional Moment Testing of Conditional Heteroskedasticity Models∗

In this paper we propose a consistent Integrated Conditional Moment (ICM) test of the functional form of a conditional heteroskedasticity model, for example a GARCH specification, which is asymptotically independent of the ICM test of the specification of the underlying conditional expectation model, under the null hypothesis that both models are correctly specified.

Testing for Reduction to Random Walk in Autoregressive Conditional Heteroskedasticity Models