This work presents the spatial error model with heteroskedasticity, which allows the joint modeling of the parameters associated with both the mean and the variance, within a traditional approach to spatial econometrics. The estimation algorithm is based on the log-likelihood function and incorporates the use of GAMLSS models in an iterative form. Two theoretical results show the advantages of the model to the usual models of spatial econometrics and allow obtaining the bias of weighted least squares estimators. The proposed methodology is tested through simulations, showing notable results in terms of the ability to recover all parameters and the consistency of its estimates. Finally, this model is applied to identify the factors associated with school desertion in Colombia.

翻译：本研究提出了一种具有异方差性的空间误差模型，该模型能够在传统空间计量经济学框架内，对均值与方差的关联参数进行联合建模。估计算法基于对数似然函数，并以迭代形式整合了GAMLSS模型的应用。两项理论结果展示了该模型相较于常规空间计量经济学模型的优势，并能够推导出加权最小二乘估计量的偏差。通过模拟实验对所提方法进行验证，结果表明其在参数还原能力与估计一致性方面均表现出显著优势。最后，将该模型应用于识别哥伦比亚学生辍学的影响因素分析中。