Measuring the time-invariant and time-varying technical efficiency of ports in Tunisia: a stochastic frontier analysis

Purpose - In Tunisia, foreign commercial exchanges are predominantly maintained via ocean freight and accomplished through eight major ports. The latter play a critical role in the Tunisian economy, whereby nearly 30.7 million tons of goods were transited in 2018. Maintaining their efficiency therefore remains a very important objective to achieve. In this context, the present study is designed to investigate the technical efficiency of respective Tunisian ports over the 16-year period (2005–2020). Design/methodology/approach - The stochastic frontier analysis (SFA) method is applied to measure the associated time-invariant and time-varying technical efficiency. Moreover, through technical inefficiency modeling, effects of both rail connectivity and private sector participation in handling activities on technical efficiency have also been accounted for. Findings - The reached results turn out to reveal well that the Tunisian ports appear to operate below their production frontier, noticeably marked by persistent technical inefficiency. Additionally, the relevant estimates tend to confirm the berth variable associated importance in highlighting production related to Tunisian ports. More particularly, our analysis reveals that the private sector’s participation proves to display a significantly negative association with technical efficiency, while the ports’ rail connectivity turns out to demonstrate a significantly positive correlation with technical efficiency. Practical implications - The findings of this study can provide port authorities and policymakers with insights into the technical efficiency of Tunisian ports by identifying best practices, the main factors influencing their efficiency (such as rail connectivity and private sector’s participation) and areas for improvement in these ports. Originality/value - The present study stands as a pioneering attempt to examine the efficiency dimension through the implementation of panel data estimation modeling frameworks, particularly the random-effects and the Battese and Coelli (1995) approaches, applied to measure the technical efficiency of the Tunisian port sector. Similarly, the present study also represents an effective attempt, whereby the effects of exogenous variables, notably the rail connectivity and private sector participation, are thoroughly considered in exploring the technical efficiency of Tunisian ports.