DOI: 10.18503/1995-2732-2025-23-1-190-200
Abstract
Matters of regional price variations, equalization of price growth rates and achieving spatial equilibrium are rising periodically within the single economic space of the country. The relevance of their solution increases in the context of external shocks that determine changes in exchange rates, destruction of supply channels, changes in the structure of added value, etc. With the development of information technology, researchers are increasingly paying attention to new sources of data to predict regional price changes. Fiscal data are becoming one of the information sources generating streams of geographically structured data and, therefore, they are well suited for this purpose. The emergence of such data makes it possible to build more complex forecast models while the increase in the number of observations contributes to the improvement in their statistical significance. The purpose of the work is to determine the sensitivity of spatial autocorrelation prices’ estimates to the choice of a weighting matrix and the level of data aggregation. The study was conducted on data from the online analytics service for retail sales in the Russian Federation (https://prodazhi.rf), which forms a database based on receipts registered by the fiscal data operator “1-OFD”. The dataset contains daily recorded price data for cough and cold medicines (3 brands) and embraces the period from January 1, 2021 to December 31, 2023. It is established that the level of data aggregation (in the form of daily, weekly or monthly values) influences the ability to interpret the results obtained whereas the choice of a particular weight matrix affects the strength of the spatial dependence. The identified dependencies are of interest to a wide range of people involved in issues of spatial measurements as well as problems of regional pricing.
Keywords
sales price, spatial autocorrelation, regional differentiation, level of aggregation, weight matrix
For citation
Timiryanova V.M., Krasnoselskaya D.Kh., Prudnikov V.B., Girfutdinova A.F. Spatial Prices’ Autocorrelation: Sensitivity to the Weighting Matrix Choice and Level of Data Aggregation. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnicheskogo Universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2025, vol. 23, no. 1, pp. 190-200. https://doi.org/10.18503/1995-2732-2025-23-1-190-200
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