Structural and informational absences in irrigation data: a Bayesian zero-inflated approach applied to Minas Gerais, Brazil - dos Santos Fachinelli Ferrarini, Angel (Italian Review of Agricultural Economics, 2026)
Minas Gerais is Brazil’s second-largest state in terms of irrigated area, with expansion potential exceeding 1 million hectares. Yet 16% of municipalities reported no irrigation in 2019, revealing a paradox between potential and local absence. This study investigates the determinants of irrigation absence using a Bayesian zero-inflated model with a truncated Student’s t-distribution. The results indicate that the baseline probability of a structural zero is approximately 12%, but this probability decreases to 4% in municipalities located in the São Francisco Basin or those with potential irrigable area. In contrast, municipalities with agricultural gross value added below the state average show substantially higher probabilities of structural zeros (around 38%). In the extended specification, the interaction between basin location and potential irrigable area reduces the probability of structural zeros to about 1%, indicating a strong combined mitigating effect. By distinguishing structural from informational constraints, this study provides actionable insights for targeted policy interventions aimed at promoting sustainable and efficient irrigation expansion.