For a panel data linear regression model with both individual and time effects, empirical studies select the two-way random-effects (TWRE) estimator if the Hausman test based on the contrast between the two-way fixed-effects (TWFE) estimator and the TWRE estimator is not rejected. Alternatively, they select the TWFE estimator in cases where this Hausman test rejects the null hypothesis. Not all the regressors may be correlated with these individual and time effects. The one-way Hausman-Taylor model has been generalized to the two-way error component model and allow some but not all regressors to be correlated with these individual and time effects. This paper proposes a pretest estimator for this two-way error component panel data regression model based on two Hausman tests. The first Hausman test is based upon the contrast between the TWFE and the TWRE estimators. The second Hausman test is based on the contrast between the two-way Hausman and Taylor (TWHT) estimator and the TWFE estimator. The Monte Carlo results show that this pretest estimator is always second best in MSE performance compared to the efficient estimator, whether the model is random-effects, fixed-effects or Hausman and Taylor. This paper generalizes the one-way pretest estimator to the two-way error component model.

中文翻译：

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双向误差分量模型的预测试估计器

对于同时具有个体效应和时间效应的面板数据线性回归模型，如果 Hausman 检验基于双向固定效应 (TWFE) 估计量与TWRE 估计器不会被拒绝。或者，在 Hausman 检验拒绝原假设的情况下，他们选择 TWFE 估计量。并非所有回归变量都与这些个体和时间效应相关。单向豪斯曼-泰勒模型已推广到双向误差分量模型，并允许一些但不是所有回归量与这些个体和时间效应相关。本文提出了一种基于两个 Hausman 检验的双向误差分量面板数据回归模型的预检验估计器。第一个 Hausman 检验基于 TWFE 和 TWRE 估计量之间的对比。第二个 Hausman 检验基于双向 Hausman 和 Taylor (TWHT) 估计器与 TWFE 估计器之间的对比。蒙特卡罗结果表明，与有效估计器相比，该预测试估计器在 MSE 性能方面始终排名第二，无论模型是随机效应、固定效应还是豪斯曼和泰勒模型。本文将单向预测试估计器推广到双向误差分量模型。