函数SAC模型及其在空间计量经济学中的应用
Functional SAC model: With application to spatial econometrics
摘要：
空间自回归组合（SAC）模型在地理、经济、人口、区域科学等领域的空间数据分析中得到了广泛的研究。这是一个具有标量响应、标量解释变量的线性模型，允许因变量和干扰的空间相互作用。在这项工作中，我们将这种建模方法从标量扩展到函数协变量。模型参数采用极大似然估计法进行估计。仿真研究进行评估所提出的方法的性能。举例来说，该模型被用来确定塞内加尔失业与文盲之间的关系。
英文摘要：
Spatial autoregressive combined (SAC) model has been widely studied in the literature for the analysis of spatial data in various areas such as geography, economics, demography, regional sciences. This is a linear model with scalar response, scalar explanatory variables and which allows for spatial interactions in the dependent variable and the disturbances. In this work we extend this modeling approach from scalar to functional covariate. The parameters of the model are estimated via the maximum likelihood estimation method. A simulation study is conducted to evaluate the performance of the proposed methodology. As an illustration, the model is used to establish the relationship between unemployment and illiteracy in Senegal.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
