The Economics of Forced Labour in Global Value Chains: Advancing Measurement and Theory
Efforts to measure the prevalence of human trafficking, forced labour, and modern slavery have advanced significantly. While such figures provide valuable benchmarks for the scale of the issue, they lack the sectoral and firm-level detail needed to inform accountability and policy design. At the same time, a growing body of empirical research -- including national surveys, sectoral studies, and NGO-led investigations -- offers localized insights that remain fragmented and underutilized.
This paper aims to address that gap by using artificial intelligence (AI) tools to systematically extract, code, and synthesize prevalence data from a wide range of field-based studies. Beyond assembling new data, the project advances a framework for linking prevalence to the structural drivers of forced labour.
Building on Manning’s monopsony model, the paper proposes that estimating labour supply elasticities can reveal degrees of employer power and the threshold at which monopsony conditions tip into forced labour. Data collection on forced labour must also be enriched by incorporating information on firm characteristics, positions within global value chains, and exposure to international trade, which would allow to move beyond descriptive prevalence reporting and towards an explanation of the economic forces sustaining severe exploitation.