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Impact of Collinearity on Estimated Parameters of CES Production Function

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TLDR
In this article, the authors proposed a method to quantify the impact of collinearity on the estimation of the parameters of the CES production function and applied it to the case of Romania during the period (1960-1979).
Abstract
In many cases, the estimation of the parameters of CES production function is made with the help of Kmenta method. The respective method is frequently criticized especially because of two reasons: the approximation of the parameters is very near on the case of Cobb- Douglas production function and the impact of collinearity on the estimated parameters is usually high. This paper proposes a method to quantify the respective impact considering the values of coefficients of collinear refraction. The proposed improvements in the methodology of estimation and interpretation of CES production function parameters are applied in case of Romania during the period (1960-1979). The respective estimations offer an opportunity to reveal some features of production factors efficiency and their substitution during one of the important period for the base industrial structure building in Romania.

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References
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TL;DR: In this article, a grid search approach is proposed for estimating the traditional CES function with two inputs as well as nested CES functions with three and four inputs, which can be applied in R using the add-on package micEconCES.
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Impact of collinearity on the estimated parameters and classical statistical tests values of multifactorial linear regressions in conditions of o.l.s

TL;DR: In this paper, the impact of collinearity in linear regressions is revealed with the help of the size of alignment coefficients (an indicator proposed by the author), and the conditions when all the alignment coefficients are positive in the case of linear regression with two, three and n ( ) explanatory variables are established.
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