Modeling scenarios for increasing the investment attractiveness of the processing ingustry of the Republic of Tatarstan

Regional and branch economy
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Abstract:

The article discusses a methodological approach to the selection of investment-attractive sectors of regional economies in conditions of risk and uncertainty. The current situation in the national economies in the world is due to the serious influence of the pandemic on all economic processes taking place in the economy. This kind of destabilization of the economy and public life was difficult to predict and, moreover, it was difficult to quickly develop measures to overcome the crisis and eliminate its consequences. The global pandemic and the economic crisis caused by the pandemic once again prove the presence of a risk component in business activities. In addition, the current crisis indicates the need to create universal methods for early recognition and rapid overcoming of crises. The issue of managing economic systems under conditions of risk and uncertainty is becoming especially important in modern realities, at the macro level, as well as the micro and meso levels. At the same time, one of the urgent tasks facing the regional governance structures of Russia is the issue of attracting borrowed funds to the economy and industry. The proposed method for identifying investment-attractive industries in the region under conditions of risk and uncertainty has been tested on the example of the manufacturing industry of the economy of the Republic of Tatarstan. The manufacturing industry occupies a significant share in the industrial profile of Tatarstan and has the greatest impact on the economy. We analyzed the period of 2014‒2018 and gave indicators for 2017‒2018 according to the all-Russian classifier of types of economic activity, which was in force until 2016. The research used the scenario method. During the study, three scenarios were modeled: pessimistic, neutral and optimistic. We determined the localization coefficient to select commercially viable industries. Using the pessimistic scenario, we modeled an aggregate conditional level of risk inherent to the entire manufacturing sector of the region’s economy. The individual investment risk of each type of economic activity in the manufacturing industry is determined through the neutral and optimistic models.