METHODOLOGY FOR ASSESSING THE SHADOW ECONOMY: FOREIGN EXPERIENCE AND MODERN APPROACHES

This article presents a systematic comparative analysis of the principal methodological approaches employed in assessing the shadow economy, encompassing direct survey-based methods, indirect macroeconomic indicator methods, and model-based econometric approaches — most notably the Multiple Indicators Multiple Causes (MIMIC) model and the Dynamic General Equilibrium (DGE) framework. Drawing on empirical evidence from Italy, Brazil, South Korea, and Estonia, the study examines how rigorous measurement methodology underpins effective policy intervention. Special attention is given to the applicability of these approaches to transition economies, with a particular focus on Uzbekistan. The findings indicate that no single method achieves universal accuracy; rather, an integrated approach combining the MIMIC model with the currency demand method yields the most robust estimates in developing and transition country contexts. The study also identifies emerging methodological challenges posed by digitalization and cryptocurrency transactions, which render conventional indicators increasingly insufficient. Practical policy recommendations are advanced for strengthening shadow economy monitoring in Uzbekistan, including the establishment of a dedicated statistical unit, harmonization with OECD and IMF standards, and targeted formalization incentives.本文针对影子经济（shadow economy）评估所采用的主要方法论路径开展系统性对比分析，涵盖直接调查法、间接宏观经济指标法以及基于模型的计量经济学方法——其中尤以多指标多因（Multiple Indicators Multiple Causes, MIMIC）模型与动态一般均衡（Dynamic General Equilibrium, DGE）框架最为典型。本研究依托意大利、巴西、韩国及爱沙尼亚的实证数据，探讨严谨的测度方法论如何为有效的政策干预提供支撑。研究特别关注上述方法在转型经济体中的适用性，重点聚焦乌兹别克斯坦。研究结果显示，尚无单一方法可实现普适性精准测度；相较而言，将MIMIC模型与货币需求法相结合的整合路径，在发展中国家及转型经济体场景下可生成最稳健的估算结果。本研究同时识别出数字化与加密货币交易带来的新兴方法论挑战，传统测度指标因此愈发难以满足需求。最后，本文针对强化乌兹别克斯坦的影子经济监测工作提出了切实可行的政策建议，包括设立专属统计机构、与经济合作与发展组织（OECD）及国际货币基金组织（IMF）的标准接轨，以及推出针对性的正规化激励措施。