Integrated volume shows how automation transforms informal labour and fiscal dynamics, indicating complex economic shifts.
This integrated volume presents a unified structural analysis of how automation reshapes the global shadow economy, forced labour markets, and macro‑fiscal dynamics. Across three complementary studies, we show that automation does not eliminate informal or coercive labour proportionally. Instead, it restructures them. Paper I demonstrates that automation compresses the volume of informal employment while leaving economic value—output, revenue, productive capacity—largely intact. Accessible automation tools enable capital‑augmented micro‑production, producing labour‑output decoupling and a transition from large informal factories to dispersed automated micro‑units. Paper II introduces the automation–coercion frontier, showing that automation suppresses forced labour in sectors where automated production becomes cheaper than coerced human labour. This suppression is sector‑specific: manufacturing and logistics cross the frontier early, while agriculture, domestic work, construction, and deep‑sea fishing remain structurally resistant, creating concentration risks. Paper III formalises the resulting macro‑paradox: as automation reduces informal employment, official unemployment rises, government expenditure increases, and the required tax rate on the observable formal sector rises—even though aggregate productive capacity declines far less. A four‑variable dynamic model captures this divergence between statistical deterioration and underlying productive continuity. Together, these studies show that automation does not shrink the shadow economy or forced labour uniformly. It transforms them—technologically upgrading informal production, suppressing coercion where automation is cost‑competitive, and generating new sociological and fiscal pressures where displaced workers become statistically visible while automated informal output remains hidden. The goal is structural analysis, not policy prescription.
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Oleg Zmiievskyi (2026) studied this question.
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