English
Received 22.05.2024, Revised 05.09.2024, Accepted 25.10.2024
In the face of modern challenges, particularly the limitations of statistical data, Ukraine encounters difficulties in accurately assessing the scale of the shadow economy. At the same time, reducing the shadow economy is a critical step for Ukraine in fulfilling its obligations to the European Union and integrating into the European community. This will promote sustainable development, attract investments, ensure social justice, and enhance the country's competitiveness on the international stage. The aim of the study is to conduct a comprehensive analysis of contemporary methods for assessing and forecasting the shadow economy, as well as to adapt these methods to the specific conditions of limited data in Ukraine. The research provides an analysis of modern methods for assessing the shadow economy and their adaptation to Ukraine's context of limited data. The study examines key classical approaches, such as the household expenditure method, the electricity consumption method, the monetary method, and the cash demand model, along with their limitations in the context of the pandemic, war, and economic instability. To address these challenges, the research proposes the use of modern tools, such as MIMIC models, Bayesian models, and transaction data analysis, which account for incomplete information and allow for the adaptation of shadow economy assessments to Ukraine's realities
econometric modeling; statistical forecasting; modeling with incomplete data; shadow economy; methods adaptation
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