This paper revisits the theory of asymptotic behaviour of the well-known Gaussian Quasi-Maximum Likelihood estimator of parameters in mixed regressive, high-order autoregressive spatial models. We generalise the approach previously published in the econometric literature by weakening the assumptions imposed on the spatial weight matrix. This allows consideration of interaction patterns with a potentially larger degree of spatial dependence. Moreover, we broaden the class of admissible distributions of model residuals. As an example application of our new asymptotic analysis we also consider the large sample behaviour of a general group effects design.

中文翻译：

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具有不可加权重矩阵的QML估计

本文回顾了混合回归，高阶自回归空间模型中参数的高斯拟最大似然估计的渐近行为理论。我们通过削弱施加在空间权重矩阵上的假设来概括先前在计量经济学文献中发表的方法。这允许考虑可能具有更大程度的空间依赖性的交互模式。此外，我们拓宽了模型残差的可允许分布的类别。作为我们新渐近分析的示例应用，我们还考虑了一般群效应设计的大样本行为。