CORRELATION-REGRESSION RELATIONSHIPS IN THE ANALYSIS OF ARGENTINA’S NATIONAL ECONOMY
Keywords:
Argentina’s Economy, GDP, Correlation, Regression, Econometric Model, Exports, Imports, Demography, Services Sector, Agriculture, Fisher CriterionAbstract
In this paper, a multifactor correlation–regression analysis based on the central statistics of Argentina’s economic system has been performed. It analyzed the statistical relationships of factors that impact the GDP growth, such as imports, exports, the services sector, agricultural value added, population size, and industrial statistics. Linear relations between those factors were established in a pairwise correlation matrix, and the importance of a regression model was determined by the Fisher criterion. The results show that exports and the services sector have the strongest impact on GDP growth in Argentina. The study is a chance for some important scientific and practical implications in terms of assessing Argentina in terms of its development, the extent of its structural potential, and the degree of its macroeconomic stability.
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