Principal Component and Factor Analysis of Macroeconomic Indicators
Journal Title: IOSR Journal of Humanities and Social Science - Year 2018, Vol 23, Issue 7
Abstract
Although macroeconomic variables have long been studied, many economists and researchers have often neglected the preliminary study of the variables regarding their similarities and differences. This paper adopted the principal component and factor analysis to assess nine macroeconomic variables by finding out the level of redundancy among them from the correlation matrix and grouping indicators with higher similarities into the same factors. Scree plots of principal components suggest grouping indicators into three factors. We then estimated the unrotated and rotated factor loadings withboth PCAand MLE estimation methods. Results from the PCA were gratifying since we obtained extreme loadings after the Varimax rotation. Out of the nine macroeconomic indicators, sixindicator were loaded on factor one, two were loaded on factor two and one was loaded on factor three.
Authors and Affiliations
Felix Atanga Adongo, John Amo Jr. Lewis, James Chukwubudom Chikelu, Martin Osei
Keywords
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- EP ID EP419599
- DOI 10.9790/0837-2307100107.
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