The Paradox of Informalized Growth: Shadow Economy Expansion and Fiscal Erosion in Ethiopia, 1990–2023

Abstract

This study investigates the size, determinants, and fiscal impact of Ethiopia’s shadow economy from 1990 to 2023, addressing a critical gap in understanding how pervasive informality constrains tax policy and revenue mobilization in developing economies. The research employs a sequential three-stage econometric methodology. First, an Enhanced Multiple Indicators Multiple Causes (EMIMIC) model, estimated within a Vector Error Correction Model (VECM) framework, is used to quantify the latent shadow economy, analysing seven cause variables (e. g., tax burden, GDP per capita, government expenditure) and four indicator variables (e. g., self-employment, electricity consumption gap). Second, these estimates are calibrated to construct a shadow-adjusted GDP series. Third, the fiscal implications are rigorously assessed through comparative Autoregressive Distributed Lag (ARDL) models and Diebold-Mariano tests to evaluate differences in tax elasticity and revenue forecasting performance between conventional and shadow-adjusted specifications. The results reveal a dramatic expansion of the shadow economy from 24.79 % to 61.69 % of official GDP over the period. The analysis identifies a paradoxical positive association with GDP per capita (+0.581) and a significant negative relationship with government expenditure (-0.350), while the direct tax burden is statistically insignificant. Fiscal impact analysis demonstrates that accounting for informality alters the long-run tax elasticity estimate by 13.8 %. The recommendations include integrating shadow economy estimates into national accounts and fiscal planning, simplifying tax systems through broad-based digital presumptive regimes, and using public procurement to encourage business formalization. Together, these measures can support a more sustainable and inclusive fiscal framework.