Considering innovations as a key factor of economic growth, in this paper we identify main instruments stimulating innovative activity in Russian regions. Since the number of potential factors of enterprises innovative activity and respective hypotheses is large, the process of model selection becomes a crucial part of the empirical implementation. A new efficient solution to this problem is suggested, applying optimization heuristics. The model selection is based on information criteria and the Sargan test within the framework of a log-linear panel data model.

A purpose of this paper is the development of regional socioeconomic systems analysis methodology and analytical instruments. The offered methodology is based on the estimation of regional socioeconomic systems functions and factors of productive forces location and development. The base of this estimation is the analysis of socioeconomic indicators and typological groups of regional systems. The method of this analysis and original instruments of this analysis on the basis of Kohonen's Self-Organizing Maps are proposed. The main stages of the methodology procedure are described. The paper considers execution of this methodology on the example of the Russian regions. Some directions of their socioeconomic development are substantiated.

The objective of this paper is to reveal the impact of spatial concentration of business in the Russian cities on enterprise productivity. The hypotheses are the following: urbanization level and home market potential positively affect enterprise performance; localization economies are positive and start decreasing after some point due to congestion and excessive competition; regional transport infrastructure, business climate and human capital positively affect enterprise performance. We use firm level data augmented with city and regional data. Fixed effects are applied in order to deal with endogeneity. Agglomeration economies are considered in the light of opportunities for knowledge spillovers, input sharing and labor market pooling. Our results confirm that agglomeration economies and home market potential are important for the enterprise performance. We find positive urbanization and diversity economies, while localization economies have an inverted U shape. Results can be used to improve regional policy. For instance, significance of home market potential emphasizes the importance of transport infrastructure. Significance of agglomeration effects implies that if a sufficiently large number of firms work in a city, performance of each firm improves.