On Seemingly Unrelated Regression Model with Skew Error

DOI

10.2991/jsta.d.210126.002How to use a DOI?

Keywords

Seemingly unrelated regression; Endogenous variable; Exogenous variable; Skew-normal distribution

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.

Copyright

© 2021 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Omid Akhgari
AU  - Mousa Golalizadeh
PY  - 2021
DA  - 2021/02/08
TI  - On Seemingly Unrelated Regression Model with Skew Error
JO  - Journal of Statistical Theory and Applications
SP  - 97
EP  - 110
VL  - 20
IS  - 1
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.210126.002
DO  - 10.2991/jsta.d.210126.002
ID  - Akhgari2021
ER  -