Subscribe Now Subscribe Today
Science Alert
FOLLOW US:     Facebook     Twitter
Curve Top
Journal of Applied Sciences
  Year: 2011 | Volume: 11 | Issue: 16 | Page No.: 3015-3021
DOI: 10.3923/jas.2011.3015.3021
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail
Multicollinearity Problem in Cobb-Douglas Production Function
Maryouma Enaami, Sazelli Abdul Ghani and Zulkifley Mohamed

The Cobb-Douglas Production Functions (CDPF) are among the best known production functions utilized in applied production analysis. The estimation of production functions in general and CDPF in particular, presents many additional problems. Multicollinearity arising in least squares estimation of the CDPF is not new. It is a problem that emerged with the model itself. In this study an estimation method for CDPF parameters by partial least squares path modeling (PLS-PM) is developed. It solves the attendant multicollinearity problem. The newly developed method is then applied to agricultural production data obtained from Al- Kufra Agricultural Production Project, Libya. The results from the model strongly suggest that the measures like composite reliability and goodness-of-fit represent their respective latent constructs well. Consequently, a further investigation of the model is pursued and an analysis on PLS-PM is performed.
PDF Fulltext XML References Citation Report Citation
  •    Determinations of Total Factor Productivity with Cobb-Douglas Production Function in Agriculture: The Case of Aydin-Turkey
  •    Some Data Reduction Methods to Analyze the Dependence with Highly Collinear Variables: A Simulation Study
  •    RETRACTED: An Efficient Estimation Procedure For Determining Ridge Regression Parameter
  •    Determinants of Growth in Government Expenditure: An Empirical Analysis of Nigeria
How to cite this article:

Maryouma Enaami, Sazelli Abdul Ghani and Zulkifley Mohamed, 2011. Multicollinearity Problem in Cobb-Douglas Production Function. Journal of Applied Sciences, 11: 3015-3021.

DOI: 10.3923/jas.2011.3015.3021








Curve Bottom