INFLUENCE OF TRANSPORT INFRASTRUCTURE ON THE INDUSTRIAL DEVELOPMENT OF THE RUSSIAN REGIONS - E. E. Kolchinskaya (Russian Journal of Economics and Law, 2015)
Objective: to build a model describing the relationship between the level of transport infrastructure development of the region and the level of industrial development in the region. Methods: calculation of the integral indicators of a particular industry development, regression analysis, method of the production function constructing. For regression analysis, the paper uses panel data models with random and fixed effects and the pooled panel data model. To check the quality of the regression model, the Fisher and Student t-tests were used. To test the model for heteroskedastic properties, tests by Park, Glazer, Goldfeld-Quandt and White were applied. Results: models of linear and logarithmic specifications with random and fixed effects were built, as well as pooled panel data models. Significant coefficients of transport infrastructure indicators were obtained in both cases only in the pooled panel data models. The model, which considered the railway density index as one of the characteristics of the transport infrastructure of the region, showed the negative coefficient of this variable. Scientific novelty: for the first time, on the basis of Russian regions statistics, using regression models of panel data, the dependence has been studied between the level of transport development in the region and the dynamics of industrial production in it. As the characteristic of transport infrastructure development, the specially designed integral indicator was used, i.e. the transport enterprises and communications functioning in the region, summarizing several characteristics of enterprises in the industry. Practical value: the obtained results can be used to predict effects of adopting decisions on improving the transport infrastructure in the Russian Federation regions. The results and conclusion can serve as a basis for further research on this topic and be applied in the characterization of the Russian economy. In addition, the results can be used in the educational process in teaching courses related to the Russian economy.