Determinants of Fish Trade Flows in Africa

Abstract

Given that fish and fishery products are ranked among the most traded food commodities globally, with developing countries accounting for the bulk of the world’s fish exports, the analysis of fish trade flows is of key importance for any policy measure in the fisheries sector. This study evaluates the determinants of fish trade flows by applying the generalized gravity model. Using panel data covering a period of 14 years for 54 African countries, the gravity model is estimated using the Tobit regression to overcome estimation challenges in the presence of zero trade observations. The results suggest that a 1% increase in exporters’ GDP, importers’ GDP, population, exporters’ fish production, and countries sharing a common border increased fish trade flows by 8%, 14 %, 4%, 36% and 60%, respectively. On the other hand, importers’ fish production, and distance reduced fish trade flows by 5% and 17%, respectively. The results further shows that the belonging to ECOWAS, EAC, SADC and AMU has significantly enhanced intra-fish trade flows thereby contributing to gross trade creation for fish. The results indicate that the current demand for fish is very high such that current production is unable to meet the consumption needs. This calls for consolidated efforts in investment and development of the aquaculture sector as an alternative to the dwindling fish supplies from the wild environment. The findings also demonstrate the need for regional blocs to improve the transport networks on the continent by, among others, adopting a regional cooperation strategy centered on infrastructure development.

Analysis of Demand for Fish in Urban Malawi

“…Various attempts have been made to analyse the demand for fish in both developed and developing countries even though research on the demand for fish disaggregated by species is relatively new in the developing countries (Dey, 2000). For instance, in Malawi the few empirical studies on demand for fish have focused on the demand for fish in general (Maganga et al, 2014), the determinants of the demand for various fish products (Nankwenya et al, 2017) and analysing the complementarity and trade-offs in consumer choice and demand for products of two tilapia species (Chikowi et al, 2020). A review of some literature for comparative analysis is presented in the subsequent paragraphs.…”

“…A study by Chikowi et al (2020) looked at how fish attributes, market factors, and consumer characteristics affect consumer choices and demand for tilapia fish in urban Malawi, but it did not disaggregate the fish demand based on the major fish species consumed in Malawi. Another study on the demand for fish in Malawi was done by Nankwenya et al (2017) who analysed factors that affect the demand for four fish products namely; smoked fish, dried fish, tinned fish, and fresh fish. However, just like the study by Chikowi et al (2020), the study by Nankwenya et al (2017) did not disaggregate the demand for fish by fish species even though prices and consumer preferences for different species of fish differ according to the species of fish and fish products (Dey, 2000).…”

“…Another study on the demand for fish in Malawi was done by Nankwenya et al (2017) who analysed factors that affect the demand for four fish products namely; smoked fish, dried fish, tinned fish, and fresh fish. However, just like the study by Chikowi et al (2020), the study by Nankwenya et al (2017) did not disaggregate the demand for fish by fish species even though prices and consumer preferences for different species of fish differ according to the species of fish and fish products (Dey, 2000). This study, therefore, fills this knowledge gap by examining the socio-economic factors that influence the consumption of fish, disaggregated by fish species, in Malawi.…”

Determinants of Seafood Trade in Sri Lanka

“…The gravity model is known as the typical and successful approach for analyzing bilateral trade which has been formulated using the Newton's equation of gravity. Gravity model of trade is popular as the best tool to explain the trade flows using importer and exporter characteristics jointly with the variables which might support or limit the trade (Nankwenya, 2018).…”

“…They have found that the GDPs of trading partners, population, regional trade agreements, and the common border have a positive correlation and distance has a negatively link to the export. Nankwenya et al (2018) have attempted to disclose the fish trade determinants of Africa. They have found that the economic conditions of partner countries, populations, common border and exporter's fish production are positively linked to the exports whereas the fish production of importer and distance between partners are acted as barriers for fish trade of Africa.…”