功能SAC模型:在空间计量经济学中的应用

IF 0.4 Q4 STATISTICS & PROBABILITY

SOUTH AFRICAN STATISTICAL JOURNAL Pub Date : 2020-04-16 DOI:10.37920/SASJ.2021.55.1.1

A. Aw, E. Cabral

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引用次数: 1

摘要

空间自回归组合（SAC）模型在地理、经济、人口学、区域科学等各个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，允许因变量和扰动的空间相互作用。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。通过最大似然估计方法来估计模型的参数。进行了模拟研究以评估所提出的方法的性能。例如，该模型被用来建立塞内加尔失业与文盲之间的关系。

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Functional SAC model : with application to spatial econometrics

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.

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来源期刊

SOUTH AFRICAN STATISTICAL JOURNAL STATISTICS & PROBABILITY-

CiteScore

0.30

自引率

0.00%

发文量

期刊介绍： The journal will publish innovative contributions to the theory and application of statistics. Authoritative review articles on topics of general interest which are not readily accessible in a coherent form, will be also be considered for publication. Articles on applications or of a general nature will be published in separate sections and an author should indicate which of these sections an article is intended for. An applications article should normally consist of the analysis of actual data and need not necessarily contain new theory. The data should be made available with the article but need not necessarily be part of it.