Forecasting the gross municipal product taking into account the investment component

Abstract

Modern political and economic conditions require government agencies at all levels to make effective management decisions aimed at sustainable socio-economic development of the country’s territories. The existing division of powers between the federal center, regions, and municipalities allows for the distribution of efforts between different levels of state governance. Key tasks in this regard become adequate assessment, planning, and forecasting of development indicators, which cannot be resolved without applying statistical modeling methods. The question of choosing the main (summary) indicator characterizing socio-economic development at the local level of governance remains debatable. The purpose of this study is to obtain reliable predictive estimates of the indicator characterizing the results of the economy of a municipal entity. To achieve this goal, research tasks were set: to justify a methodology for quantitative assessment of the summary indicator of the economy of a municipal entity; to test the proposed methodology based on state statistics data for municipal entities in one of Russia’s regions; and to justify forecasts of the calculated indicator for each municipal entity in the short term. The information basis of the study is the data from the Territorial Body of State Statistics of the Republic of Bashkortostan for 2012–2022, covering the region as a whole and the cities of Ufa, Sterlitamak, Salavat, Neftekamsk, and Oktyabrsky. The research methodology includes methods of relative values, dynamics analysis, and regression analysis; a classical two-factor (labor and capital) production function of Cobb- Douglas was used to describe the revealed patterns and build a forecast, and trend models was constructed. According to calculations, the trend towards an increase in the gross municipal product of large cities in the region will continue. At the same time, almost 50% of the Republic’s GRP will be produced in Ufa, the total share of large cities in the region in GRP by 2025 will be more than 60%. The scientific novelty of the study lies in the authors’ proposed methodology for calculating the indicator for measuring the results of the economy of a municipal entity, which is an analogue of the gross value added indicator and allows for adjusting the gross regional product. The study’s results can be applied in practice when making management decisions by the leadership of large municipal entities and Russian Federation subjects.

Keywords

• gross municipal product
• gross regional product
• production function
• municipality
• forecasting
• investments
• city economy