Detecting the Shadow Economy Through Big Data Signals: a Correlation and Risk-Ranking Approach for the Republic of Armenia
Year: 2026
Type: article
Abstract: Shadow economies impose serious costs on public finances, distort competition, and erode the social contract between citizens and the state. In transition economies like Armenia, accurately measuring informal economic activity is a persistent challenge because conventional statistical methods rely on self-reported data that conceals the very activity they seek to measure. This paper proposes a practical, transparent framework for shadow economy detection using big data signals and a composite risk-ranking model that requires no advanced statistical software to replicate. Using data from Armenia's ten administrative regions (marzes) over the period 2015–2023, the study constructs four observable big-data indicators: the VAT compliance ratio, the cash-to-deposit ratio, the business formalization rate, and a nighttime luminosity score derived from satellite imagery. Descriptive statistics characterize indicator distributions across time and geography. A Pearson correlation matrix indicates the strength and direction of associations between indicators and an established shadow-economy benchmark. A Shadow Economy Risk Rank (SERR) is then constructed by assigning ordinal scores to each marz on each indicator and summing them into a composite ranking. The results reveal strong negative correlations between formalization and luminosity indicators and shadow economy intensity, and strong positive correlations for cash usage. The SERR ranking closely mirrors independent MIMIC-based estimates, validating the approach. Northern and northeastern marzes - particularly Lori, Tavush, and Gegharkunik - consistently rank as the highest-risk, while Yerevan and Kotayk register the lowest informal activity pressure. The framework offers a methodologically accessible, data-driven tool that Armenian fiscal authorities can implement using existing administrative data sources, with direct implications for audit targeting and compliance promotion policy.
Author: SYUZANNA MUSHEGHYAN
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W7204169041