METHODOLOGICAL APPROACHES TO ECONOMETRIC ASSESSMENT OF LOCAL BUDGET REVENUE GROWTH THROUGH LEGALIZATION OF THE SHADOW ECONOMY
Abstract
This article proposes an econometric architecture for estimating how formalization of shadow economic activity affects local budget revenue growth across regions and time. The framework integrates fixed-effects, dynamic-panel, instrumental-variable, difference-in-differences, spatial, threshold, and scenario models while addressing measurement error, endogeneity, tax assignment, and heterogeneous regional capacity using 2021-2025 information. The study demonstrates that credible revenue estimates require a clearly defined formalization variable, tax-specific transmission channels, robust diagnostics, uncertainty intervals, and policy counterfactuals separating gross liabilities from realistically collectible net revenue.
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