Dynamics of price level changes in the Visegrad group: comparative study

Abstract

AbstractIn Poland, as in many other countries, to measure inflation, expressed both by the CPI and HICP, the Laspeyres price index with weights from the base period is used. Thus calculated index does not take into account changes in the consumption structure which are caused by changes in prices in the analysed time interval (i.e.: a year). Therefore, in countries where the CPI is determined based on the Laspeyres index, there is a high probability of its bias due to substitution of goods, but not only. The value of the CPI or HICP should approximate the real inflation as accurately as possible, among others, because these indicators are used to index nominal values in the economy, which in turn is important in price decisions made by enterprises. Searching for an answer to the question about the possibility of effective reduction of the measurement bias in measuring inflation, the authors conducted an empirical study whose main aim was to assess diversity of the level of inflation in the Visegrad countries at different levels of aggregation, with particular emphasis on the scale of the bias in measuring inflation resulting from substitution of goods. The study concentrated on determining the size of differences arising from the change in the index formula used when estimating the level of inflation. The article consists of six parts in which sources and types of bias in inflation measurement are discussed, index formulas divided into weighted and unweighted ones are reviewed, statistics on inflation in the Visegrad countries are presented in a dynamic approach, and the results of empirical research are presented and discussed. For the purpose of the research part and the need to perform a comparative analysis, data on the HICP value from the Eurostat database from the years 2011–2018 were used. Therefore, it seems that both the choice of the calculation formula and the level of data aggregation in the analysis of inflation is significant in its estimates.