An essay on the multidimensional statistical methods to characterize the entrepreneurial context in Russian regions


Obraztsova O.I.

Сand. Sci.(Econ.), Assoc. Professor, Moscow School of Economics at the Lomonosov Moscow State University, Moscow, Russia olga_obraztsova@rambler.ru

Popovskaya E.V.

Сand. Sci. (Engineering), Senior Analyst, Laboratory for Entrepreneurship Research at the National Research University Higher School of Economics, Moscow, Russia e_popovskaya@rambler.ru

ID of the Article: 6650


For citation:

Obraztsova O.I., Popovskaya E.V. An essay on the multidimensional statistical methods to characterize the entrepreneurial context in Russian regions. Sotsiologicheskie issledovaniya [Sociological Studies]. 2017. No 4. P. 93-106




Abstract

This paper constructs a multidimensional typology that captures the contextual feature of Entrepreneurial Framework Conditions (EFC) across Russian regions. An overview of entrepreneurship research priorities in last decades shows that entrepreneurship’s nature, extent and contribution to economic growth depend on the context in which it occurs. Contextual approach provides a deeper insight into adult’s intrinsic incentives to become entrepreneurial that vary according to the regional “matrix” in which individuals exist and develop. We consider a problem statement, principles of interpretation, multidimensional statistical methodology and its perspectives for entrepreneurship research in the regional context. We proved that databases from the official statistics and microdata of adult population social surveys in this area need to be combined to develop a body of evidence-based knowledge on entrepreneurial context. The contextual approach was interpreted in terms of factor analysis (FA) as a statistical method to regroup interrelated variables into a limited set of unobserved factors based on a shared common variance and dimension reduction. The essential aim of analysis was a “parsimony” enabling to discover the simplest method of interpretation for Rosstat data on the regional EFC. On the base of FA procedure we identified 3 latent factors (instead of the primary set of 144 regional economic and social indicators) that can be interpreted as “Well-being”, “Investment problems” and “Social problems”. These unobservable variables could not be directly measured but they are hypothetical constructs represented a surrounding medium of entrepreneurship. The reduced database was applied for two-step clustering set of 79 Russian regions covered by GeoRating Survey in 2011 (FOM, about 60 thous. of respondents, 18 variables harmonized with Global Entrepreneurship Monitor Questionnaire) into three homogeneous regional clusters by the type of entrepreneurial context. The first cluster consisted of 6 prosperous regions; the rest regions were determined as disadvantaged areas and subdivided into clusters of “The lack of investment” regions and of “The most socially deprived” regions. Using multidimensional statistical methodology on the base of comparable and geographically coherent regional statistics on EFC in conjunction with adult population surveys microdata, the paper argued, one might consider and explain barriers and stimuli of entrepreneurship development in compliance with special regional features of entrepreneurial context reflected in terms of proposed typology. It is found that the type of entrepreneurial context determines the more of an indirect influence on individuals’ decision to be entrepreneurial. The different regional clusters that are homogeneous by the entrepreneurial context show peculiar factors influencing individuals’ optimism or pessimism on business prospects in a region both for entrepreneurial and non-entrepreneurial population.


Keywords
entrepreneurial activity; entrepreneurship research; contextual approach; multidimensional statistical methods; factor analysis; cluster analysis; cross-regional comparisons; entrepreneurial framework conditions

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Content No 4, 2017