Statistically grounded commonalities and peculiarities of Ukrainian and British residential property markets evolution in recent years of unrest

Abstract

This paper presents a statistically grounded comparative analysis of residential property market evolution in the United Kingdom (2007–2025) and Ukraine (2019–2025) amid disruptive events, including the Global Financial Crisis, Brexit, COVID-19, and the war in Ukraine. Applying a harmonized probabilistic framework to large-scale datasets, the study models price distributions using log-normal laws and evaluates volatility via dispersion metrics. For proper comparative analysis, the initial data sets collected for the UK and Ukraine residential property markets, which exhibit contracting types of economies, were processed identically using a detailed mat-stat methodology developed. It includes data filtering for duplicates, outliers, and basic metric homogeneity. As such, the price per square meter of the property area was chosen. Following initial data preprocessing and filtering, empirical density distribution functions of housing prices were analysed. In both markets, the log‑normal distribution was identified as the closest theoretical model for the cost per square meter of residential property. Such a character was confirmed through Pearson χ² tests. Based on results collected, the role several influential factors was identified. This includes regional polarization, market size evolution with particular attention to the market’s key parameters dynamics under the influence of encompassing turbulences. In all cases, the analysis provided was performed in a deterministic and probabilistic manner. In this regard, the coefficient of variation, jointly with dispersion, proved a sensitive indicator of underlying instability, rising sharply in Ukraine. While both countries experienced volume and price shifts under pressure, the UK market’s volatility normalized faster, signaling greater resilience and structural maturity. Findings confirm that while both markets exhibit right-skewed initial distributions, their responses to shocks diverge. The UK displays cyclical dynamics where volatility widens during shocks and narrows during stabilization. Conversely, the Ukrainian market demonstrates persistent, heightened volatility and strong spatial polarization driven by wartime security risks. The analysis proves that dispersion-based indicators, particularly the coefficient of variation, capture market resilience more effectively than average prices. This comparison offers a replicable template for analyzing how structurally different markets absorb overlapping shocks, providing key insights for policymakers and investors.