Predictive Analytics of Consumer Price Index Dynamics Based on E-commerce Prices

Student: Lipatov Ivan

Supervisor: Mariam Mamedli

Educational Programme: Economics (Bachelor)

Year of Graduation: 2021

This work is one of the applications of the project to collect microdata on online prices of Russian retailers, created to improve the assessment of the official consumer price index, which is conducted by a research team from VTB. This paper reviews the current state of the data and highlights unresolved issues in comparison with research experience from other countries. And on the basis of these data, the method of applying modern machine learning methods to the problem of price forecasting is described in comparison with the methods of price forecasting as time series, which were used in the research literature on the topic, in the search for the best predictive method.

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