Managing innovation activity factors in Russian regions through econometric modeling

Abstract

The paper aims to identify the main innovation activity factors in the Russian regions using econometric analysis. Assessment of the current state of the innovation environment in the Russian Federation reveals that there is a number of problems impeding innovation growth, which affects the country’s position in international rankings. The methodological basis of the research includes the theoretical principles of innovation economics, innovation management and regional development. There is a plethora of approaches to modeling the factors of innovative development of countries and regions, as well as to measuring innovation. In the article, we analyze patent activity in Russia’s regions and stimulating factors. The information base includes Rosstat panel data for 1999–2015 in 77 subjects of the Russian Federation. To optimize the set of variables of the econometric model, the authors apply a genetic algorithm. We find that factors reflecting human capital, financial performance of enterprises, market competition, ownership and general macroeconomic indicators of regions affect the indicators of patent activity. The research results can be used to formulate recommendations for improving regional innovation policy. In particular, it is reasonable to encourage the management and research staff of organizations to design and introduce innovations, develop venture business, promote active interaction of business with universities and research institutes, as well as strengthen international cooperation.

Keywords

• management
• innovation
• innovation activity
• genetic algorithm
• econometric model
• russian regions