Exploring the Efficiency of Smallhold Coffee Farms in Senator Ninoy Aquino, Sultan Kudarat: A Mixed-Methods Study

Abstract

Coffee farming in Sultan Kudarat, Philippines, faces persistent productivity challenges driven by rising input costs, aging tree stock, and limited access to financial and extension services. Yet empirical evidence on the technical efficiency of smallholder coffee farms in this region—and on the farm-level and socioeconomic determinants of that efficiency—remains absent from the published literature. This study assessed the relative technical efficiency of 50 registered smallholder coffee farmers in Senator Ninoy Aquino, Sultan Kudarat, using a mixed-methods design that integrated Data Envelopment Analysis (DEA) with binary logistic regression and qualitative documentary analysis of inefficient decision-making units (DMUs). The DEA model specified coffee bean yield (kg) as the single output variable and farm size (m²), labor cost (PhP), fertilizer (kg), pesticides (L), herbicides (L), and technology and equipment cost (PhP) as inputs. Under the constant returns to scale (CRS) assumption, the mean technical efficiency score was 0.682, rising to 0.995 under variable returns to scale (VRS). Scale efficiency averaged 0.682, with 72% of DMUs operating below optimal scale under increasing returns to scale (IRS) and only 28% achieving full CRS efficiency. Binary logistic regression confirmed that none of the twelve socioeconomic determinants—including age, gender, education, civil status, household size, farming experience, landholding, off-farm activities, credit access, extension services, infrastructure access, and livestock ownership—significantly predicted technical efficiency status at the α = 0.05 level (Pseudo R² = 0.1229). Qualitative responses from the two worst-performing DMUs revealed three interconnected categories of constraint: input cost escalation and capital inaccessibility, climate-related production shocks, and structural socioeconomic disadvantages in credit and infrastructure access. The findings indicate that scale expansion in factor inputs—particularly farm size, labor, and capital—represents the primary pathway to efficiency improvement for currently sub-optimal DMUs, and that institutional interventions addressing credit access, infrastructure investment, and climate risk management are essential for sustainable productivity gains in this sector.