MACHINE LEARNING IN ECONOMIC RESEARCH

UDC 330.4
DOI: 10.36871/ek.up.p.r.2023.03.02.027

Authors

Elena A. Mayorova,
Plekhanov Russian University of Economics, Moscow, Russia

Abstract

Digital technologies, including machine learning, are creating fundamentally new opportunities for economic research and are gradually replacing traditional methods of data collection and analysis from academic economics. The purpose of the work is to characterize the state of economic research that uses machine learning technologies or considers any aspects of their application based on a review of scientific articles published in Russian Science Citation Index (RSCI) journals. For this, RSCI publications on the topic “Economics. Economic Sciences”. Methods – bibliometric, scientometric, content analysis, systematization. As a result, the most common areas of application of machine learning in economic research, including in terms of industry, have been identified, the most popular types, tasks and mechanisms of machine learning have been identified, and the problems and risks of its use have been summarized. A system of analyzed works is presented, taking in to account the types of machine learning, initial data, scale, industry focus.

Keywords

machine learning, neural networks, artificial intelligence, economics, review, RSCI.