Instability of Financial Return of Regional Economies and Its Determinants

The study is dedicated to assessment of instability of financial return in Russian regions in 2004–2016 and its sources. Instability of financial return was calculated as the variance of the ratio of the balanced financial result to GRP, disaggregated by 11 main economic activities. The portfolio approach by G. Markowitz and W. Sharpe was used for assessment of contribution of various sectors to the overall instability, division of the total risk into intra-sectoral and inter-sectoral components, and identification of directions of optimization of the regional sectoral structures using specified target functions and constraints. In addition, this paper discussed the advantages and limitations of application of the portfolio approach for the analysis of volatility of regional economies. As a result of the study, the evaluations of financial return, risk and efficiency of the Russian regions economies were obtained. The sectorial structure of the volatility of financial return in the Russian regions was determined. We revealed that the financial sector and the real estate operations sector were on an average the main risk enhancers in the Russian regions. The agriculture and fishing, as well as infrastructure industries were main risk mitigators. However, the largest absolute contribution to the financial stability of the Russian regions was made on average by the sectors of extractive and manufacturing industries. The division of risk into intra-sectoral and inter-sectoral components allowed drawing conclusions about the different nature of the diversification of regional economies. Meanwhile, the relationship between the instability of financial return and the generalizing coefficients of diversification has not been confirmed. Based on the comparison of the contributions of various sectors to the overall financial return and risk and calculation of the index of two structures similarity, the degree of deviation of the GRP sectoral structure of its optimal state was determined and the directions for its optimization in the Russian regions were identified. The solution of three optimization tasks (minimizing the risk at a given financial return, maximizing the return at a given risk and minimizing the coefficient of variation of financial return) in the model with built-in constraints allowed to obtain optimal sectoral structures for the three selected regions and to assess their effectiveness from the standpoint of achieving specified function