The paper is devoted to the development and the new application of the mathematical model of effective capital funds (ECF) formation, which has been offered earlier. These funds are understood… Click to show full abstract
The paper is devoted to the development and the new application of the mathematical model of effective capital funds (ECF) formation, which has been offered earlier. These funds are understood as a part of the capital funds of a macroeconomic object (a branch, a sector, a region, a country) used in the current conditions of market economy. The initial data for the model are gross output, production investments, and labour expenses. The model uses a macroeconomic production function (PF) and the dynamic equation for ECF, which reflects the investment control and depreciation processes. On the basis of this model, we address the problem of a simultaneous assessment of the PF parameters and reconstruction of ECF. This problem increases the adequacy of the PF method assuming rationality of the used production factors as well as solves a new problem — ECF quantitative assessment. Complication of the substantial problem leads to complication of computing process. We overcome this complication attracting the additional information, which reflects the specificity of a concrete entity. We apply this method to a new object covered by the new method of economic analysis — small business (SB). The peculiarity of this sector of the regional and national economy is that its capital funds have no clear definition, and, respectively, there is a lack of their regular and reliable statistical record. The Federal State Statistics Service documents, available to researchers and analysts, characterize small business by the yearly indicators of a turnover, investments into capital funds, and the average number of workers. For the estimation of SB’s capital funds, we offer to use the indicator of ECF. The specified method of ECF estimation and PFs design is applied to the sector of “legal entities of SB†of the Volga and the Ural Federal Regions on the interval of 2005–2014.
               
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