VolRC RAS scientific journal (online edition)
22.04.202404.2024с 01.01.2024
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Journal section "Socio-economic research"

A Model for Forecasting the Rate of Consumer Price Index (Inflation): Case Study of the Russian Federation

Alfer'ev D.A.

1 (3), 2016

Alfer'ev D.A. A Model for Forecasting the Rate of Consumer Price Index (Inflation): Case Study of the Russian Federation. Social area, 2016, no. 1 (3). URL: http://socialarea-journal.ru/article/1806?_lang=en

Abstract   |   Authors   |   References
Inflation is one of the key categories of economic theory. Its regulation helps solve various socio-economic problems; and its timely forecasting contributes to the optimal management of economic activities of economic entities. Quantitative assessments of inflation processes are widespread among the provisions of the theory of the time value of money. The correct and reliable estimations of future rates of change in prices of goods and services allow designers to accurately assess the sustainability of their projects, to determine the break-even point and find the optimal price of products, which will contribute to the maximization of profit. In addition, accurate forecasting of inflation rate helps reduce costs in the future, which rise especially during crisis phenomena in economic systems. The present article discusses basic theoretical principles of inflation from the standpoint of theoretical provisions of W. Phillips and proposes a mathematical model of multiple linear regression, which can be used to predict the rate of change in the price index for future periods. In addition, the author of the present article considers theoretical provisions about the share of the unemployed relative to the subject of the research and defines methodological provisions for trend modeling of the process. On the basis of the models constructed, the author obtained the forecasted values of the rate of consumer prices and the unemployment rate for the economy of the Russian Federation for 1999 – 2017; the author also analyzed how these categories would develop in the future. In conclusion, the article offers the options for using the mathematical tools designed by the author, in particular, in the evaluation of innovation investment projects, and those areas with the help of which it can be improved and the mathematical tools can be improved as well. It should be noted that the mathematical regression model developed by the author while improving the estimate values of the indicators can be used to calculate and forecast the natural rate of unemployment, which does not depend on inflation processes and phenomena occurring in the economic and social environment of society


consumer price index, inflation, unemployment rate, multiple regression, trend modeling

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