Improvement of Factor Analysis of Determined Two-Factor Multiplicative Economic Indicators
Volumetric economic indexes calculated by involving two various factors are widely used in the statistical economic analysis. The two-factor models lay the basis for constructing statistical indexes, particularly aggregated ones. A calculation method depends on the choice of methodology to measure the impact of factors on an index, which entails varying approaches to the calculations. The above mentioned issues are widely discussed in the literature devoted to statistical analysis. The discussions are, however, focused on the situations when all the factors have an increasing trend, with decreasing trends being overlooked. The article aims to fill this gap by reviewing possible discrepancies when calculating the impact of a factor change on the statistical index value when the factors have alternative trends. Based on the above goal, the article contains analysis of the deficiencies found in the existing two-factor analysis of volumetric economic models, and offers possible methods for their elimination. The article is quite valuable considering the need to improve the existing statistical approaches to analysis of volumetric economic models. It contributes to analytical, scientific and practical issues related with two-factor models. These models lay the basis for constructing statistical indices that determine methodology for calculating the impact of single factors; in fact, they provide the basis for choice of the method of successive substitutions when calculating the impact of a factor on the index value. In a two-factor model, the impact of each single factor on the total result is calculated by eliminating or calculating the impact of each factor considering the change of both factors. Possible ways to improve the above mentioned calculations are discussed; formulas and graphic presentations of the factors that influence the trend of economic indexes are given. Methods to eliminate double counting of the impact from both factors in a two-factor model are shown. Specifics of the algorithms (formulas) and the derived results are highlighted. The theoretical statements are supported by calculations for possible options of change in factor indicators. The usefulness of the proposed algorithms in academic studies, applied scientific analysis and education is shown.