Consumer Price Index in the Czech Republic – New Sources and Data Processing

Jaroslav Sixta, Petr Musil
Statistika, 104(1): 89–101
https://doi.org/10.54694/stat.2023.37

Abstract
Consumer price index has been in the centre of interest for many years, since being published in 1990s in the Czech Republic but recent price growth raised more questions on methodology and data sources used in price statistics. Users are interested not only in the figures itself but also in statistical issue influencing interpretation and the quality of consumer price index that is often used as an approximation of inflation rate. The paper introduces price statistics compiled by the Czech Statistical Office and it specifically focuses on data sources and in particular scanner data. The paper explains how advanced statistical methods such as machine learning are implemented in official statistical production. We think that the official statistics is being on the historical junction where modern methods are going to be implemented. Our paper shows the usage of machine learning procedures applied on scanner data within consumer price index. Used method is based on logistic regression and powerful Python solution and that provides fast and high quality results.

Keywords
Consumer price index, scanner data, machine learning, logistic regression