Analysis of the technical efficiency of Nile perch (Lates niloticus) fishers in the Tanzanian portion of Lake Victoria: A stochastic frontier analysis

Abstract

The Nile perch fishery sector in Tanzania is important for enhancing the livelihoods and food security for the majority of people living near the Tanzanian portion of Lake Victoria. Despite continued government efforts and other institutions, including the Food and Agriculture Organization (FAO), Lake Victoria Fisheries Organization (LVFO), European Union and World Bank regarding the management of Lake Victoria, the Nile perch fishers have remained relative inefficient in regard to improving their fish catches. The Nile perch small‐scale fisheries sector in particular faces a challenge regarding how to improve production performance while, at the same time, ensuring a sustainable level of fisheries resources. This reality necessitates the measurement and analysis of artisan fishers’ technical efficiency. Accordingly, the present study analyses Nile perch fishers technical efficiency, using a stochastic production frontier (SPF) model based on the sample of 268 Nile perch fishers in the Tanzanian portion of Lake Victoria. The translog stochastic frontier model results indicate the technical efficiency of Nile perch fishers range between 61% and 80%, with an overall average technical efficiency of 75%. This finding implies that, based on existing fishery resources, the current quantity of Nile perch catch can be improved efficiently by 25%, a reality highlighting mismanagement of the lake's fishery resources. The quantity of bait and petrol and the number of hooks used per trip are the most important fishing inputs, indicating a positive Nile perch fishing output–input elasticity. To address the Nile perch fisher inefficiency, it is important to provide subsidized inputs such as outboard engines and mesh gillnets. Provision of access to affordable credits will enable fishers to purchase less destructive fishing inputs and improve the current structure of fishery organizations.

Can producer groups improve technical efficiency among artisanal shrimpers in Nigeria? A study accounting for observed and unobserved selectivity

“…Therefore, a 10% increase in any of these inputs would increase TOTALCAP by 7.92% (ENGINEOPER), 1.02% (FUELCOST), 1.80% (LEADERSEMP), and 0.60% (USEFULSEINE). This result is supported by findings from other African fishing subsectors where motorized canoe, fuel, skipper, and seine are the main fishing inputs that significantly contribute to fishery capture (Esmaeili 2006;Lokina 2009;Mkuna and Baiyegunhi 2019;Sesabo and Tol 2007).…”

“…CONN production functions display increasing returns to scale (1.06-1.13), similar to fishers around Lake Victoria in Tanzania (Mkuna and Baiyegunhi 2019), MEM production functions suggest the opposite (decreasing returns to scale) with estimations ranging between 0.84 and 0.93. This result indicates that CONN and MEM are in the first and second stages of the production function curve, respectively, and that MEM would need to reduce the usage of inputs, especially the number of engines and fuel, to be scale-efficient.…”

“…In Africa, fisher groups also bear the responsibility for alleviating supply and marketing challenges (Adetoyinbo and Otter 2020;Mkuna and Baiyegunhi 2019). By acting collectively, fishers can deploy groups' economies of scale, superior information access and effective management of fish resources to enhance their technical ability, productivity, and welfare.…”

Analysis of the Technical Efficiency of European Sea Bass Farms in Turkey: A Stochastic Frontier Production Function Approach

“…A meta-analysis was performed with the results of previous studies to compare the production efficiency of the sea bass farms in Turkey with the aquaculture farms in developing and developed countries, also EU countries. The average technical efficiency coefficients of aquaculture farms in developing countries (Bangladesh 77.0%, China 79.0%, Croatia 82.0%, Ghana 74.0%, Malaysia 79.0%, Nigeria 79.5%, and Tanzania 75.0%) were calculated as 77.9%, and in developed countries (Cyprus 99.0%, France 89.0%, Greece 86.0%, Italy 84.0%, Slovenia 83.0%, Spain 93.0%) was 89.0% (Filli et al, 2016;Iliyasu et al, 2016;Yin et al, 2017;Aktar et al, 2018;Onumah et al, 2018;Ajiboye et al, 2019;Baruwa and Omodara, 2019;Mkuna and Baiyegunhi, 2019;Ashley-Dejo et al, 2020). The average technical efficiency coefficients of aquaculture farms in European Union countries were reported as 89.1% by Fernández Sánchez et al (2020).…”

Impact Of Nile Perch (Lates Niloticus) Overfishing On Technical Efficiency Of Fishers In Lake Victoria Tanzania

“…This is because most of fishers in Lake Victoria are at least members of fishery organization particularly co-management organization known as beach management unit (BMU). Therefore, being a member of fishery organization, fishers tend to depend more on the information and training they receive from the organization and sometimes this can hinder their individual innovations in the context of fishing activities (Mkuna and Baiyegunhi, 2019a). Also, Tam et al, (2018) noted that in absence of fishing organizations emphasis of individual and group innovations, fishers may not be motivated and this might affect their individual productivity.…”