Applied multivariate statistical analysis
Applied multivariate statistical analysis
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This work builds up a complete procedure of using factor analysis as the instrument in the case of relaxing the assumption of the classical model. Paper is focused on the situation when the multicolinearity appears as the dominant problem. This problem is solved by grouping of performance indicators, not only by technical principles, but also according to fundamental postulates of business economic theory. The whole procedure is illustrated by a practical example. The example originates from the real need to analyse and compare the performance of all manufacturing enterprises in the Split-Dalmatian County in 2004. The data set consists of a wide range of performance indicators for 1744 manufacturing enterprises, among which twelve are selected as representative ones. As the entire basic set is the issue of our interest, we find that the enterprises are markedly heterogeneous in terms of the chosen indicators. Therefore previous to comparison they have to be made homogeneous. After such homogenization, using principal components method four factors have been extracted, i.e. all selected variables (performance indicators) have been meaningfully grouped in to factors: activity, liquidity, leverage, economic efficiency. The essential part of analysis is establishing of direct, indirect and overall effects of each independent variable on return on equity as chosen dependent variable.