Research purpose. In order to implement the optimal metropolitan governance model, it is important to understand the conditions under which this or that model is economically effective. There is a need to develop a quantitatively justified methodology for choosing the optimal metropolitan governance model for different types of metropolitan areas. It has been emphasized in some federal documents of Russia, for example, in the “Recommendations for the selection of pilot projects for approbation and improvement of mechanisms for managing the development of metropolitan areas in the Russian Federation”. Materials and methods. Domestic researchers (N. Zubarevich, K. Gonchar, etc.) and foreign researchers (Glaeser Edward L., Nakamura, Ciccone A., Hall R., etc.) carried out the study of quantitative relationships between the economic growth of cities and the characteristics of cities.However, for metropolitan areas, the analysis of the relationship has not yet been implemented between the outpacing economic growth of the metropolitan area relative to the average country values (labor productivity and GDP per capita), the institutional factor (the type of metropolitan governance model), andthe non-institutional factor (population size). To identify the dependencies we are interested in, we used the OECD statistical database and OECD researches to identify the metropolitan governance model in the sample of metropolitan areas in the world. The sample in this research was 87 metropolitan areas in Europe and was divided into groups, depending on the population and the introduced metropolitan governance model. For each group, a correlation-regression analysis was performed and a weighted average was calculated from the indexes of the economic growth. As the leading index of the economic growth, labor productivity was used, as the final - GDP per capita. Then a comparison was made between the real value of economic growth in each surveyed metropolitan area and the expected value when implementing different metropolitan governance model. If the comparison showed the non-optimality of the implemented model for some index of the economic growth, then the values of the economic growth in the metropolitan area and the national average were compared. As a result, a recommendationwas given for the metropolitan area on the degree of need for the management reform and an optimal metropolitan governance model was selected. Results. Based on the revealed regularities, we have created a methodical approach to choose the optimal model of metropolitan governance according to the population size. It can be used as a tool to justify metropolitan governance reform. The advantage of the approach is the use of real quantitative data that reduces the degree of subjectivity in decision-making Conclusion. The methodical approach is tested on the example of eightmetropolitan areas (Lublin, Palermo, Krakow, Paris, Stuttgart, Madrid, Geneva, and Linz). It was revealed that there is no metropolitan governance model, which is always more efficient for all objects. As the result of the analysis for Geneva, the degree of need for management reforms was described as “high” with a recommendation for a transition to a decentralized metropolitan governance model. For Linz, Stuttgart and Madrid, the degree of need for reform is characterized as “low” with a recommendation for a transition to decentralization (Stuttgart) and centralization (Linz and Madrid). The rest of the metropolitan areas of the sample do not need reforms.
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