| Аннотация | Identification of development trends and growth potential of Russian regions in the new conditions requires the elaboration of advanced approaches to modeling the main economic indicators. The aim of the article is to carry out an econometric modeling and analysis of the GRP of the Nizhny Novgorod Region using data from twin regions. The selection of twin regions was based on the similarity of industry structures, level of development and trends. Using panel data for 16 regions of the Nizhny Novgorod Region cluster for 2000–2023, the Cobb – Douglas functions with lagged variables were constructed, estimated by the maximum likelihood method with correction for group heteroscedasticity. As a result of the modeling, a positive influence of supply factors (accumulated fixed assets, current investments, number of employees), demand factors (income per capita in the past period) on the current GRP was established. The scale and structure of budget expenditures of the region also play an important role in increasing the GRP in the cluster under consideration. The average annual key interest rate of the Bank of Russia, as well as its change, have a negative impact on the GRP. In addition, the GRP of the cluster regions is positively related to the price of Brent crude oil, which indicates the historical dependence of the Russian economy on the oil sector, and the dollar to ruble exchange rate, which affects the price component of the GRP through the pass-through effect, as well as import substitution processes. The obtained results can be the basis for designing forecasts and scenarios for the development of the region in the future, determining the consequences of regulatory impacts at the regional level and the effects of uncontrolled macroeconomic parameters. Further development of the study is possible through the inclusion of high-frequency data, the elaboration of models with more advanced specifications, including structured and aggregated ones, as well as separate modeling of the inflationary and real components of GRP, which together will allow for the creation of more accurate short-term forecasts
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| Ключевые слова | region, gross regional product, econometric modeling, factors, clustering, twin regions, budget expenditures, key rate of the Bank of Russia
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