This paper derives the best linear unbiased prediction (BLUP) for an unbalanced panel data model. Starting with a simple error component regression model with unbalanced panel data and random effects, it generalizes the BLUP derived by Taub (1979) to unbalanced panels. Next it derives the BLUP for an unequally spaced panel data model with serial correlation of the AR(1) type in the remainder disturbances considered by Baltagi and Wu (1999). This in turn extends the BLUP for a panel data model with AR(1) type remainder disturbances derived by Baltagi and Li (1992) from the balanced to the unequally spaced panel data case. The derivations are easily implemented and reduce to tractable expressions using an extension of the Fuller and Battese (1974) transformation from the balanced to the unbalanced panel data case.

中文翻译：

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使用不平衡面板数据进行预测*

本文推导出非平衡面板数据模型的最佳线性无偏预测（BLUP）。从具有不平衡面板数据和随机效应的简单误差分量回归模型开始，它将 Taub (1979) 导出的 BLUP 推广到不平衡面板。接下来，在 Baltagi 和 Wu (1999) 考虑的剩余扰动中，它推导出具有 AR(1) 类型序列相关性的不等距面板数据模型的 BLUP。这反过来扩展了具有 AR(1) 类型剩余扰动的面板数据模型的 BLUP，由 Baltagi 和 Li (1992) 从平衡到不等距面板数据情况导出。使用 Fuller 和 Battese (1974) 从平衡到不平衡面板数据案例的转换的扩展，这些推导很容易实现并简化为易于处理的表达式。