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Region: Economics and Sociology

2021 year, number 3

MINIMIZING THE SOCIAL LOSS FUNCTION BY FINDING A COMPROMISE AMONG THE GOALS OF REGIONAL ECONOMIC POLICY

A.O. Baranov1,2, V.N. Pavlov1
1Institute of Economics and Industrial Engineering, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
2Novosibirsk National Research State University
Keywords: social loss function, compromise among economic policy goals, the problem of finding minimal social losses in a dynamic formulation

Abstract

The article deals with minimizing social losses associated with the inability to achieve all the set goals amid limited economic policy instruments that managers of the socio-economic system can actually use. We give a critique of the currently available approaches to minimizing the social loss function. Then we provide an example of how economic policy instruments were implemented nationwide in Russia between 2018 and 2019. It was a period when the Bank of Russia’s application of monetary policy instruments aimed at achieving a single goal only, the one related to inflation, had not been coordinated with an increase in VAT by the Ministry of Finance. Using the AD-AS model, we show a negative impact of these decisions on both economic and investment growth rates, which in their turn have a long-term effect on economic growth. The problem discussed in this paper is relevant at the regional level: when establishing regional development roadmaps, it is essential to achieve an optimal combination of short-term and long-term goals. The authors present a model for minimizing the social loss function (SLF) as a mathematical programming problem. Within this proposed problem, we outline an approach to finding the optimal solution that provides the maximum approximation to achieving not only short-term but also long-term goals of economic policy for a particular time with consideration to the restrictions on the use of its tools. Since minimizing the social loss function is carried out for an interval, the article introduces a concept of “bliss trajectory" in contrast to the “bliss point" category used in the theory of economic policy for solving static optimization problems. We also describe how to solve such a problem with the conditional gradient method and give a step-by-step algorithm for this kind of solution.