Econometric Estimation of Economic Growth by Purchasing management: Neovlassical Models to the Analysis of Qualitative Changes - Ekaterina Ivanovna Kadochnikova; Liliaj Faridovna Zulfakarova; Darja Alekseevna Drozdova; Abdulaev Hawaj-Baudi Salaudiyevich (International Journal of Supply Chain Management, 2019)
Based on the review of theories of economic growth, attention is focused on the sources of regional economic growth by purchasing management. Using linear regression models, a sample of data from 83 Russian regions from 2010 to 2016 reflects the short-term dynamics of regressors influence on the gross regional product growth. On the basis of partial elasticity coefficients, it is empirically revealed that the greatest influence on the gross regional product is exerted by investments in fixed capital, in contrast to the costs of technological innovations. The conclusion about the statistically significant difference in the impact of the volume of investment in fixed capital and the cost of technological innovation on the gross regional product is formulated on the basis of a comparison of the modular values of the boundaries of confidence intervals: if the intervals intersect, there is no statistical difference between the coefficients.Â It is possible to recommend to apply the results to regional authorities in the development of regional economic policy in the field of investment and innovation.Â The assumption that the growth of investment in fixed capital and rising costs of technological innovation increase the gross regional product is empirically confirmed. Investment in fixed capital has a greater impact on gross regional product than the cost of technological innovation. In 2015, 2016 compared to 2010, 2011, 2012, 2013, the impact of investments in fixed assets in the direction of increase, relative to the impact of costs on technological innovation is statistically different. In further studies, to eliminate the bias in the estimates of regression coefficients, it is advisable to expand the range of regressors of the gross regional product, to use econometric models for the analysis of panel data.