Assessing the Level of Ukraine’s Shadow Economy Under Martial Law and Identifying Key Influencing Factors - Poplyuyko, Ya. V.; Melnyk, M. O. (Statistics of Ukraine, 2025)
The article examines the problem of assessing the level of the Ukrainian shadow economy under martial law. It explores the methodologies used by Ukrainian and foreign researchers to estimate the size of the shadow economy. The main consequences faced by countries with high hidden economic activity are highlighted. The essence of direct and indirect methods for assessing the shadow economy is analysed. The paper outlines the advantages and disadvantages of the most used approaches, including questionnaire surveys, expert assessments, discrepancies in GDP and employment, enterprise unprofitability, electricity consumption, the ‘household expenditures – retail turnover’ method, and monetary approaches.Performed calculations according to the Ministry of Economy methodology to evaluate these methods' applicability under wartime conditions, characterized by limited data availability. The absence of official statistics prevented the use of the household expenditures – retail turnover method.The indicator calculated using the electricity consumption method showed significant atypical fluctuations, which indicates a distortion of the estimate and the inapplicability of this approach in the current environment. The results obtained from three of the four applicable methods were aggregated into an integrated index and analysed over time.The theoretical analysis of the causes of the shadow economy allowed the identification of its key determinants. To empirically evaluate the factors influencing the shadow economy, a correlation matrix was constructed using the latest data for 2021–2023. The matrix included independent variables such as the Corruption Perceptions Index, the Rule of Law Index, the Financial Development Index, the Ease of Doing Business Index, inflation, and unemployment. The results revealed that inflation and perceived corruption have the strongest positive correlation with the level of the shadow economy. Based on the correlation analysis, selected variables for a regression model that can be used to forecast the level of the shadow economy based on inflation and corruption indicators when official data is limited. Effectively reducing the shadow economy in Ukraine is possible only through implementing a sound anti-inflationary policy and eradicating corruption. In further research, the model will be extended to include other factors.