Multidimensional Modeling of Socioeconomic Indicators in Khartoum State Using Factor Analysis Technique, 1990 - 2011
[1]
Mozamel Elnair Somi Kakitla, Economics and Rural Development Department, Dalanj University, Dalanj, Sudan.
[2]
Eissa Abaker Mohammed Elhaj, Peace and Development Center, Dalanj University, Dalanj, Sudan.
[3]
Abdelaziz Sulaiman Mastoor, Economics and Rural Development Department, Dalanj University, Dalanj, Sudan.
This paper focuses on utilizing the concept of socioeconomic indicators for expressing its participation in development. Factor analysis through principal component as a statistical technique is used for modeling, it leads to the identification of a small number of socioeconomic dimensions that summarize adequately the information contained in the original set of variables. The new methodology for socioeconomic modeling enables a much more useful characterization of the territory for policy-making purposes. The statistical data of Khartoum State of the Sudan during 1990 – 2011 were used. In this paper 54 variables of seven complex socioeconomic indicators which reduced into three factors using factor analysis technique, these factors are: Multi-indicators factor which, includes natural, health, and demographic indicators. The second is education factor, which explains the impact of education on the agriculture and the livestock. Industry factor, represents the third factor, and clarifies the effectiveness of industry, petroleum and electricity on services.
Factor Analysis, Principal Components, Socio-economic Indicators, Modeling, Khartoum State, Sudan
[1]
Shahla, R., Muhammed, I. K., Faisal, M. Z., & Shumila, R. (2013). Regional Development Assessment Based on Socioeconomic Factors in Pakistan Using Cluster Analysis. World Applied Sciences Journal. © IDOSI Publications.
[2]
Pavel, P., Jiri, K., & Romana, P. (2011). Multidimensional Modeling of Cohesion Regions. International Journal of Mathematical Models and Methods in Applied sciences.
[3]
Ivana, R. B. (2005). Uncovering Regional Disparities - the Use of Factor and Cluster Analysis. The Institute of Economics, Zagreb. Croatia.
[4]
D. N. Lawley, & A. E. Maxwell (1963). Factor analysis as A statistical Method. Butterworths. London.
[5]
Benjamin, F. (1954). Introduction to Factor Analysis. D. Van Nostrand Company, INC. New York.
[6]
Alexander, B. (1994). Statistical Factor Analysis and Related Methods – Theory and Applications. John Wiley & Sons, INC. New York.
[7]
R. A. Reyment, & K. G. Joreskog (1996). Applied Factor Analysis in the Natural Sciences. Cambridge University Press. United Kingdom.
[8]
Richard L. G. (1974). Factor Analysis. W. B. Saunders Company. London.
[9]
Ledyard, R. T. & Robert, C. M. (1997). Exploratory Factor Analysis. Illinois & Ohio State Universities.
[10]
Timothy, A. B. (2006). Confirmatory Factor Analysis for Applied Research. The Guilford Press New York. London.
[11]
Mozamel, E. S. K. Adam, H. T. O. (2011). Journal of ISOSS 2017 Vol. 3 (2), 249-262.
[12]
Wolfgang, H. & L´eopold, S. (2003). Applied Multivariate Statistical Analysis. Method and Data Technology. Berlin.
[13]
Neil, H. T. (2002). Applied Multivariate Analysis. Springer-Verlag New York, Inc.
[14]
Alvin, C. R. (2002). Methods of Multivariate Analysis. John Wiley and Sons, INC. Publication.
