Tests for skewness and kurtosis in the one-way error component model

This paper derives tests for skewness and kurtosis for the one-way error components model. The test statistics are based on the between and within transformations of pooled OLS residuals, and are derived in a conditional moments framework. We derive the limiting distribution of the test statistics for panels with large cross-sectional and fixed time-series dimensions. The tests are implemented using both artificial regressions and bootstrap. The proposed methods are able to detect departures away from normality in the form of skewness and kurtosis, and to identify whether these occur at the individual, remainder, or both error components. The finite sample properties of the tests are studied through extensive Monte Carlo simulations, and the results show evidence of good finite sample performance.