A meta‐analysis of aquaculture technical efficiency studies

Abstract As the world population grows, the aquaculture sector faces challenges in the use of production systems to ensure the adequacy of the food supply. Technical efficiency analysis has been shown to be useful for improving resource management and production. This study provides a literature update and uses meta‐regression analysis to examine the variations in aquaculture mean technical efficiency (MTE) scores based on 101 studies published from 1998 to 2023. The findings show that studies with larger model dimensions, different output measures, an input‐oriented model specification and that analyse the exogenous variables of efficiency scores, freshwater aquaculture, and European data produce a narrower variance in MTE scores. In contrast, studies that use panel data and nonparametric data envelopment analysis (DEA) generate wider variance in MTE scores. As a result of these investigations, the findings suggest the importance of selecting appropriate variables and sample sizes for efficiency estimates. Robustness checks of efficiency scores from the DEA and stochastic frontier analysis (SFA) approaches are recommended for future studies. Different policies and regulations should be implemented in different countries and across different farming systems.