2018 (15), №3

Modeling of Factors of Innovative Development for Russian Regions



For citation: 

Pushkarev, A. A.,Vasilyeva, R. I. & Nagieva, K. M. (2018). Modeling of Factors of Innovative Development for Russian Regions. Zhurnal Economicheskoj Teorii [Russian Journal of Economic Theory], 15(3), 540- 544


This paper is devoted to a theoretical and empirical study of the factors influencing the innovative development of Russian regions. We hypothesize that innovative indicators depend not only on generally recognized economic factors, but also on a number of other, less studied indicators. Within the framework of the study, the authors analyze current research and group the factors of innovative development. Based on the preliminary analysis, we carry out an empirical study of economic, innovative and social indicators at the regional level. The analysis covers 68 regions of Russia for the period from 2001 to 2014. The empirical analysis consists in constructing a series of panel regressions with fixed effects, the index of the number of patented studies as a dependent variable, and the heuristic optimization of the composition of the regressors of these models. The main results of the analysis are as follows. We have identified five groups of regional factors that potentially affect innovation: the level of human capital, the quality of infrastructure and agglomeration effects, healthy competition, investment attractiveness, and involvement in the foreign economic activity. The estimates obtained in the course of econometric modeling demonstrated significant positive effects of the indicators of infrastructure and human potential on the innovative activity of a region. Another important conclusion in the construction of the econometric model is the including in the optimal specification of the model at least one indicator from each of the five theoretically formed groups of factors. This indicates the empirical applicability of such a classification.

Andrey Alexandovich Pushkarev — Senior Lecturer, Department of Econometrics and Statistics, Ural Federal University named after First President of Russia B. N. Yeltsin (Ekaterinburg, Russian Federation; e-mail: a.a.pushkarev@urfu.ru).

Rogneda Ivanovna Groznykh — PhD student, Research Assistant, Department of Econometrics and Statistics, Institute of Economics and Management, Ural Federal University (Ekaterinburg, Russian Federation; e-mail: rogneda.groznykh@ urfu.ru).

Karina Mahir-kizi Nagieva — PhD student, Ural Federal University named after First President of Russia B. N. Eltsin (Ekaterinburg, Russian Federation; e-mail: nagieva1995@list.ru).