Abstract
The assessment of technical efficiency in the agricultural sector and the influence of exogenous (environmental) variables on the production process has been a major topic of economic research especially for managers and policy makers. The methological innovation of the present study involves the impact of environmental variables on efficiency and the utilization of panel data for the empirical analysis. This has been pursued using full nonparametric robust frontier techniques (the alpha-quantile estimator) and a panel data set of olive growing farms in Greece from the Farm Accountancy Data Network of the EU. According to the empirical results, the ratio of owned to total land, the ratio of family to total labor, the degree of specialization, and a farm’s location have a statistically significant impact on performance, which is not constant but varies over the 2006 to 2009 period considered.
Highlights
The assessment of technical efficiency (TE) provides information to managers and to policy makers about differences in performance among production units and the potential for improvements
The empirical analysis in this study relies on information from the Farm Accountancy Data Network (FADN) of the European Union (EU) which is an important tool for agricultural policy analysis and simulation
The production inputs (X) include: (a) total labor; (b) total land under olive trees; (c) fertilizers and pesticides; and (d) other costs4
Summary
The assessment of technical efficiency (TE) provides information to managers and to policy makers about differences in performance among production units and the potential for improvements. Economic research on this important topic has evolved largely around two alternative approaches, namely, the parametric and the nonparametric. Stevenson, 1980; Battese & Coelli, 1988). The parametric models require restrictions on the shape of the production frontier (benchmark) and on the underlying data generation process They lack robustness in cases where the functional forms of the frontier and/or the error structure are not correctly specified. The estimation of nonparametric frontier models has been, until recently, pursued through envelopment techniques such as the Data Envelopment
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
