The Farrar-Glaubar Approach in Testing for Multicollinearity in Economic Data

Authors

  • Akinniyi Alaba Joseph Rufus Giwa Polytechnic
  • Sanni Eneji Ademoh Rufus Giwa Polytechnic

Keywords:

multicollinearity, farrar-glaubar, economic data, variables

Abstract

This research aims at determining the presence of Multicollinearity in a function using farrar-glaubar test approach. In most economic data, there is the presence of Multicollinearity but the severity varies. The degree of this multicollinearity may vary from function to function. However, Farrar-Glaubar test is used to detect the presence and severity of Multicollinearity, location of Multicollinearity, and the pattern of Multicollinearity in a function. How to correct the effect of Multicollinearity was also covered this research. After analyses were done on the collected data, we realized that, Multicollinearity is most pronounced in Economic data.

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Author Biographies

Akinniyi Alaba Joseph, Rufus Giwa Polytechnic

Department of Business Administration & Management
Rufus Giwa Polytechnic, Owo
Ondo State, Nigeria

Sanni Eneji Ademoh, Rufus Giwa Polytechnic

Department of Mathematics & Statistics
Rufus Giwa Polytechnic, Owo
Ondo State, Nigeria

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Published

2017-05-31

How to Cite

Joseph, A. A., & Ademoh, S. E. (2017). The Farrar-Glaubar Approach in Testing for Multicollinearity in Economic Data. International Journal For Research In Business, Management And Accounting, 3(5), 01–17. Retrieved from https://ijrbma.com/index.php/bma/article/view/400

Issue

Vol. 3 No. 5 (2017): International Journal For Research In Business, Management And Accounting

Section

Articles

License

Copyright (c) 2017 gnpublication@

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