Commodity bundle and inflation dynamics homogeneity by regions

Abstract

Introduction. Regional heterogeneity is among the factors that could define efficiency of central banks’ inflation targeting monetary policy. Purpose. The paper aims at assessing the impact of a commodity bundle structure of the RF constituents on regional inflationary processes by clustering based on regional consumer price indices and share of goods and services in the commodity bundle. Materials and Methods. The paper refers to k-means clustering. Results. The study shows that the commodity bundle structure affects inflation rate and volatility. A food share in the commodity bundle is the key distinguishing feature. The regions with a higher share of food in the commodity bundle are characterized with higher inflation volatility, while the regions with a higher share of services and non-foods in the commodity bundle reveal lower inflation volatility. The cluster with a high share of food in the commodity bundle is dominated by comparatively poor regions. The other cluster mostly consists of regions with million-plus cities. This indirectly confirms Engel’s law. It is worth noting that we could divide regions into two constant groups in 2016–2020, although in 2021 and 2023 we observed significant changes in the cluster centers determined by a change of a region’s consumption model. If a food share in region’s population spending declines and a spending share of such items as cars, travelling, and leisure goes up, then inflation volatility decreases. Conclusion. The shift from one cluster to another presupposes that population of the region should decrease their food expenditures and increase the consumption of goods and services which satisfy high-level needs. This is likely to reduce inflation volatility in Russia on the whole. Keywords: inflation volatility, Engel’s law, inflation, cluster analysis, policy rate, k-means clustering method, heterogeneity, commodity bundle, food commodities, household spending, regional economic analysis