Addressing multicollinearity in regression models: a ridge regression application

Ali Bager, Monica Roman (), Meshal Algedih and Bahr Mohammed

MPRA Paper from University Library of Munich, Germany

Abstract: The aim of this paper is to determine the most important macroeconomic factors which affect the unemployment rate in Iraq, using the ridge regression method as one of the most widely used methods for solving the multicollinearity problem. The results are compared with those obtained with the OLS method, in order to produce the best possible model that expresses the studied phenomenon. After applying indicators such as the condition number (CN) and the variance inflation factor (VIF) in order to detect the multicollinearity problem and after using R packages for simulations and computations, we have proven that in Iraq, as an Arabic developing economy, unemployment seems to be significantly affected by investments, working population size and inflation.

Keywords: multicollinearity; ridge regression method; unemployment rate. (search for similar items in EconPapers)
JEL-codes: C12 C51 J64 (search for similar items in EconPapers)
Date: 2017-06, Revised 2017-06
New Economics Papers: this item is included in nep-ara
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: ADDRESSING MULTICOLLINEARITY IN REGRESSION MODELS: A RIDGE REGRESSION APPLICATION (2017)
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