Towards a comparative analysis of olive farmers' technical efficiency: Lessons from Data Envelopment analysis and Fuzzy-set Qualitative Comparative Analysis on small olive farms in Tunisia

Abstract

Considering the economically, socially, and culturally vital character of olive growing in Tunisia, and the very significant proportion of small farmers operating in this sector, especially in rural areas of this country, there is a strong case to examine the performance of small olive farmers in such regions. To do so, this paper uses Data Envelopment Analysis (DEA) to assess small Tunisian olive farmers' efficiency and combines symmetric techniques (OLS and Tobit regressions) with asymmetric technique (Fuzzy-set Qualitative Comparative Analysis (fsQCA)) to identify the main antecedents that might explain the gaps in efficiency among them. The results reveal that there is substantial room for improvements of the technical efficiency of these farmers. Moreover, the regression models show that four determinants individually explain gaps in efficiency among farmers: age, education, access to agricultural credit, and ownership status. The fsQCA results provide four different combinations of conditions leading to high levels of olive farmers' efficiency. They also highlight the strong causal relationship (core conditions) between olive farmers' efficiency and two antecedents in particular: farmer's level of education and ownership status of the land devoted to olive-tree cultivation. This study also provides some valuable policy and managerial implications for farmers, central and regional government agencies promoting and supporting agriculture, and policy-makers.