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:: Volume 10, Issue 2 (2-2017) ::
JSS 2017, 10(2): 203-220 Back to browse issues page
The Improve of Two Stage Least Square Method in Regression Model with Endogenous Variables
Omid Akhgari , Mousa Golalizadeh *
Abstract:   (9268 Views)

The presence of endogenous variables in the statistical models leads to inconsistent and bias estimators for the parameters. In this case, several approaches have been proposed which are able to tackle the biase and inconsistency problems only in large sample situations. One of these methods is biased on instrumental variables which causes removing endogenous variables. The method of two-stage least squares is another approach in this case that it has more accurate than ordinary least squares. This paper aims to enhance the accuracy of three methods of estimation based upon least square methodology called, two-stage iterative least squares, two-stage Jackknife least squares and also two-stage calibration least squares. In order to evaluate the performance of each method, a simulation study is conducted. Also, using data collected in 1390 related to the cost and revenue in Iran, those methods to estimate parameters are compared.

Keywords: Regression models, Endogenous and exogenous variables, Two stage least square, Instrumental variables
Full-Text [PDF 2671 kb]   (2566 Downloads)    
Type of Study: Research | Subject: Applied Statistics
Received: 2015/10/28 | Accepted: 2016/04/16 | Published: 2017/03/12
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Akhgari O, Golalizadeh M. The Improve of Two Stage Least Square Method in Regression Model with Endogenous Variables. JSS 2017; 10 (2) :203-220
URL: http://jss.irstat.ir/article-1-414-en.html

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 10, Issue 2 (2-2017) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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