METHODOLOGICAL ASPECTS OF ASSESSING THE HIDDEN ECONOMY IN THE DIGITAL ECONOMY

Abstract

The hidden economy remains one of the most complex and pressing challenges for modern states, undermining tax collection, distorting statistical data, and reducing the effectiveness of economic policy. In the era of digital transformation, new methodological approaches are required to accurately assess the scale and dynamics of the hidden economy. This paper explores the methodological aspects of measuring hidden economic activities within the framework of the digital economy, where the growing role of information technologies, e-commerce, and financial innovations significantly reshapes both formal and informal markets. The study reviews classical models such as the MIMIC (Multiple Indicators Multiple Causes) approach and dynamic stochastic general equilibrium (DSGE) modeling, while also examining their applicability to digitalized environments. Special attention is paid to the integration of big data, electronic payment systems, blockchain technologies, and digital footprints into hidden economy measurement methodologies. The paper emphasizes that traditional survey-based and indirect indicator methods are no longer sufficient in capturing rapidly evolving informal digital transactions.