Abstract Food industries drive economic growth, yet their substantial within-sector variation remains poorly understood. This study examines heterogeneous socio-economic impacts across nine food industry sectors using continuous difference-in-differences methodology applied to panel data from Catalonia (2015–2022), covering 64 industries economy-wide. Our continuous treatment captures establishment growth intensity, enabling sector-specific impact estimation. The analysis reveals high heterogeneity: Other Food Products generates employment increases substantially above the economy-wide average, while Dairy Products exhibits large negative effects. Spillover analysis was inconclusive due to severe multicollinearity among related sector measures, leaving cross-sector transmission as an open question. Value chain analysis reveals upstream suppliers generate significant multiplier effects across downstream industries. Robustness checks – including alternative weighting schemes, COVID-period sensitivity analysis, and export intensity controls – confirm that the observed heterogeneity is structural rather than driven by measurement choices or external shocks. These findings suggest that uniform industrial policies may be inadequate for the food industry, highlighting the potential value of differentiated sector-specific approaches. The methodological framework provides a replicable template for examining heterogeneous Industry 4.0 impacts across industries and regions.
Khezri-nejad-gharaei et al. (2026) studied this question.