On Seemingly Unrelated Regression Model with Skew Error

Omid Akhgari, M. Golalizadeh
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引用次数: 0

Abstract

Sometimes, invoking a single causal relationship to explain dependency between variables might not be appropriate particularly in some economic problems. Instead, two jointly related equations, where one of the explanatory variables is endogenous, can represent the actual inheritance inter-relationship among variables. Such typical models are called simultaneous equation models of which the seemingly unrelated regression (SUR) models is a special case. Substantial progress has been made regarding the statistical inference on estimating the parameters of these models in which errors follow a normal distribution. But, less research was devoted to a case that the distributions of the errors are asymmetric. In this paper, statistical inference on the parameters for the SUR models, assuming the skew-normal density for errors, is tackled. Moreover, the results of the study are compared with those of other naive methodologies. The proposed model is utilized to analyze the income and expenditure of Iranian rural households in the year 2009.
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具有倾斜误差的表面不相关回归模型
有时,用单一的因果关系来解释变量之间的依赖关系可能并不合适,特别是在一些经济问题中。相反,两个联合相关方程,其中一个解释变量是内生的,可以代表变量之间的实际继承相互关系。这种典型的模型被称为联立方程模型,其中看似不相关回归(SUR)模型是一个特例。在这些误差服从正态分布的模型参数估计的统计推断方面已经取得了实质性进展。但是,对于误差分布不对称的情况,研究较少。本文研究了在假设误差为偏正态密度的情况下,对SUR模型参数的统计推断。此外,研究结果与其他朴素方法的结果进行了比较。利用所提出的模型对2009年伊朗农村家庭的收入和支出进行了分析。
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
13
审稿时长
13 weeks
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