Journal of Applied Economic Research
ISSN 2712-7435
Application of Neural Networks for Forecasting Inflation: New Opportunities
Balatskiy E.V., Yurevich M.A.
Abstract
The article presents an overview of the latest achievements of neural networks in relation to the problem of inflation forecasting. It is shown that in many cases the accuracy of the forecasts obtained by neural network methods is higher than the accuracy of the forecasts obtained by traditional methods of economic science. Neural networks beat econometric instruments in accuracy of calculations, but lack meaningful theory. This contradiction can be eliminated by combining two types of predictive tools. In the article the authors propose a two-step model of short-term inflation forecasting. The essence of the authors’ approach is to build a small (five-factor) econometric model of inflation, which has good statistical characteristics and provides an adequate theoretical explanation of the modeling process, but it does not allow for predicting the monthly rate of inflation with high accuracy. The authors show that this problem is typical of modern macroeconomics and is an individual manifestation of the so-called fundamental problem of data attribution in macro models. The problem has no solution in the framework of traditional macroeconomic models. In this regard, to improve the accuracy of forecasts the application of a neural network makes it possible to refine the calculations and bring their quality to the required level. The advantages of the proposed scheme are discussed in the conclusion.
Keywords
inflation; consumer price index; Central Bank; econometrics; regression analysis; neural networks.
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About Authors
Balatskiy Evgeny Vsevolodovich – Doctor of Economics, Professor, Director of the Center for Macroeconomic Research of the Financial University under the Government of the Russian Federation, Moscow, Russia (125167, Moscow, Lenin-gradsky Prospect, 49), Chief Researcher, Central Economics and Mathematics Insti-tute, Mos-cow, Russia (117418, Moscow, Nakhimovsky Prospect, 47); e-mail: evbalatsky@inbox.ru.
Yurevich Maxim Andreevich – Junior Research Fellow, Center for Macroeconomic Research of the Financial University under the Government of the Russian Federation, Moscow, Russia (125167, Moscow, Leningradsky Prospect, 49); e-mail: maksjuve@gmail.com.
For citation
Balatskiy E.V., Yurevich M.A. Application of Neutral Networks for Forecasting Inflation: New Opportunities. Bulletin of Ural Federal University. Series Economics and Management, 2018, Vol. 17, No. 5, 823-838. DOI: 10.15826/vestnik.2018.17.5.037.
Article info
Received August 2, 2018; Accepted September 4, 2018
DOI: http://dx.doi.org/10.15826/vestnik.2018.17.5.037
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