Determinants of Bias-Corrected Technical Efficiency in Saffron Production: ‎Evidence from A Double Bootstrap DEA Approach

This study evaluates the technical efficiency of saffron farms in Torbat Heydarieh and Zaveh Counties, ‎located on northeastern Iran, using a two-stage double-bootstrap Data Envelopment Analysis (DEA) ‎approach. Cross-sectional data were collected from ۱۰۸ saffron producers across six districts, and ‎technical efficiency (TE) scores were estimated under variable returns to scale (VRS) with an input-‎oriented DEA model. The bias-corrected double-bootstrap procedure of Simar and Wilson (۲۰۰۷, ‎Algorithm ۲) was applied with ۱۰۰۰ replications to ensure consistent inference and robust estimation. ‎Results reveal that the Farrell efficiency estimates tend to overstate farm technical efficiency by ‎approximately ۲۵ percent. I detected significant regional disparities in efficiency scores (χ² = ۱۲.۷۴, p < ‎‎۰.۰۵), with the highest mean efficiency observed in Kadkan (۰.۳۲) and the lowest in the Central district ‎‎(۰.۱۷). The truncated bootstrap regression identified an inverted U-shaped relationship between farm ‎age and efficiency, where efficiency initially increases with farm age but declines beyond a certain ‎point. Experience in saffron cultivation had a strong positive and statistically significant effect on ‎efficiency (p < ۰.۰۱), while education level and farmer’s age were not significant predictors. Slack ‎analysis revealed considerable input-specific inefficiencies and spatial heterogeneity in slacks. On ‎average, farms could reduce water use by ۷۰۶.۸۸ m³/ha, land by ۳.۰۴ ha, corm use by ‎۵۲۸.۱۰‎ kg/ha, and ‎labor by ۲۰ person-days/ha without reducing output.‎

کلیدواژه ها:

Data Envelopment Analysis ، Bootstrap Bias Correction ، Technical Efficiency ، Truncated &lrm ، Regression ، Saffron ، Agricultural Productivity