Adaptive estimation of heteroskedastic error component models

This paper checks the sensitivity of two adaptive heteroskedastic estimators suggested by Li and Stengos ( 1994) and Roy ( 2002) for an error component regression model to misspecification of the form of heteroskedasticity. In particular, we run Monte Carlo experiments using the heteroskedasticity setup by Li and Stengos ( 1994) to see how the misspecified Roy ( 2002) estimator performs. Next, we use the heteroskedasticity setup by Roy ( 2002) to see how the misspecified Li and Stengos ( 1994) estimator performs. We also check the sensitivity of these results to the choice of the smoothing parameters, the sample size, and the degree of heteroskedasticity. We find that the Li and Stengos ( 1994) estimator performs better under this type of misspecification than the corresponding estimator of Roy ( 2002). However, the former estimator is sensitive to the choice of the bandwidth.