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International Fisheries Access Agreements and Trade

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Abstract

International fishery access agreements allow fishermen from one country to harvest fish in another country’s waters. We empirically examine why countries sign fisheries access agreements with each other and compare these to the characteristics of countries that choose to undertake international trade. Using a unique global panel dataset, we show that access agreements and fish exports are driven by two key motives: a pattern of comparative advantage in fishing, which depends on fish stocks and fishing capacities; and gravity factors of economic size and distance. Our results suggest that most gravity factors work similarly for the dual pathways of agreements and exports: larger countries that are closer to each other are more likely to sign access agreements or to trade. However, the pattern of advantage is determined differently: source countries with larger fishing capacity are more likely to export fish, while source countries with lower fishing capacity are more likely to sign agreements.

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Notes

  1. In fact, the relative abundance of cod off the North East coast of North America was an important element in the early European settlement of those shores (Kurlansky 1998) as were the whale stocks in the southern oceans for Australia and New Zealand (Prickett 2002).

  2. See commentary by Greenpeace (2012) or in the movie The Cove (2009) for examples of popular perception.

  3. FAO (2018a, b) outline the current and predicted status of global fisheries production.

  4. Vetemaa et al. (2006) consider a case study of Estonian fisheries which faced significant overuse after the collapse of the Soviet Union. In another case study, Bayramoglu and Jacques (2012) document a negative pressure of trade openness on fish stock in Turkish fisheries.

  5. The resource literature also looks at broader international issues related to fisheries. For example, Asche et al. (2015) and Watson et al. (2017) investigate the relationship between food security and evolution of fish trade flows between developed and developing countries. The general consequences of international sharing in fisheries have been examined by McWhinnie (2009) and Rus (2012). There are also multiple case studies of various issues in international trade in fishery products, such as international fish market integration (Tveteras and Asche 2008) and product competitiveness (Hoshino et al. 2015; Norman-Lopez et al. 2013).

  6. See Mbithi Mwikya (2006). Though these sums are small, they make a significant contributions to some of the source economies. For instance, Havice (2010) documents that fisheries access fees contribute 30 to 50% of GDP in Kiribati and Tuvalu.

  7. We use the name European Union for consistency throughout but acknowledge that the name and membership altered across the time period covered in this paper.

  8. For instance, France had reciprocal agreements with both Spain and the United Kingdom whereby vessels from Spain or the United Kingdom were permitted to fish in French waters and vice versa.

  9. Some recent access agreements involve the Japanese government more directly. For example, an agreement with Morocco that establishes Japan’s access for 15 tuna longline vessels in the Moroccan EEZ for an access fee of 49,500 MAD in 2017. We are grateful to an anonymous reviewer for providing us with this recent example.

  10. The Chinese distant water fleet is the largest in terms of the number of fishing vessels but the production capacity is smaller than the capacity of other fishing countries.

  11. Note that our environment is a simple static set-up where the fish stock status does not depend on the catch. Clearly, fish stock status is endogenous in a richer dynamic model of trade in renewable resources.

  12. See Head and Mayer (2014) for an extensive discussion of the gravity literature.

  13. Baldwin and Harrigan (2011) find a similar pattern of zeroes using the US product-level trade data.

  14. If listed as unknown we conservatively code it as non-reciprocal. For multilateral agreements, we take the following approach. The database codes each country within the EU having an agreement with outside parties if the agreement is negotiated under the common fisheries policy. Similarly, each country in the FFA is coded as having an agreement with the USA. We examine this further in the empirical section.

  15. To account for changes in product definitions or mismeasurement, we also considered a specification with trade incidence equal to one if the value of exports was larger than $5000, which did not affect the results. The estimation results are not reported but are available upon request.

  16. The value of the EU partnerships that were dropped in 1984 made up 0.2% of all 1983 trade. While the total value of the EU trade fell by 3.3% from 1983 to 1984, it rose by 13.8% in 1985.

  17. We also generated MTL for the USSR and Yugoslavia by aggregating over the relevant countries prior to 1991 or 1992 as relevant.

  18. The agreements data does not provide details on the targeted species or groups. To categorize even to broad species groups we would need to examine the legal text of each agreement. Unfortunately, not all agreements list the species covered and, moreover, not all agreements are publicly available. The bilateral fish trade data is also not reported at the species-level as it is reported by consumption categories (for example, fresh or frozen). Thus, we are unable to assign targeted or traded species to observations with agreements or trade.

  19. The mixed agreements include various targeted species such as mackerels, cod, pollock, sardines, octopi, pilchards, flatfishes, grenadiers, billfishes, and crabs.

  20. Some reports indicate that in Mauritania and Senegal by-catch in squid and shrimp fisheries can be five times larger than the catch of the targeted species (Bonfil et al. 1998).

  21. The sign and statistical significance of the coefficients of excess capacity for both source and destination countries with an agreement are the same as for the measure of capacity, and other coefficients are very similar as well. Results are available upon request.

  22. The indicator variable for countries sharing a maritime border is constructed by authors. We thank Kofi Otumawu-Apreku for providing valuable research assistance on this point using information from the Sea Around Us Project (2015) and the Flanders Marine Institute (2014).

  23. We drop all “countries” that are still colonies as they typically do not have consistently reported measures of access agreements. This means that we are likely to be underestimating the number of access agreements. For some colony–colonist relationships this will be unfair as the colony may be extremely autonomous with respect to fisheries management and should therefore be considered as separate. However, we had to draw the line somewhere as some states or islands that are part of the same country are also quite autonomous with respect to fisheries management.

  24. The full universe of possible pair-year combinations is greater than our baseline sample as we exclude countries that never had agreements with anyone. This is because landlocked Lesotho not having a fisheries access agreement with landlocked Austria is different than New Zealand not being a source country to Costa Rica. This universe definition issue also arises in the trade literature where Australia not importing apples from Iceland stems from different reasons than Australia not importing apples from New Zealand.

  25. In our empirical analysis, we address a potential concern of sample selection issue by reestimating our empirical model for alternative samples.

  26. Note that we use a 1-year lagged values of Stock, GDP/Capita and Population variables in our estimations, as defined in Table 1.

  27. See Anderson and van Wincoop (2003) for more on the importance of controlling for multilateral trade resistance.

  28. As our data set spans many years, it would be preferable to include time-varying fixed effects for source and destination countries. However, in this case it would be impossible to estimate the effects of all time-varying country-specific variables of our interest such as fish stock status, fishing capacity or GDP per capita.

  29. Estimation results with FFA Source and DWF nation indicators are not reported but are available upon request. We also estimate an alternative specification with all three indicator variables included, which has similar results.

  30. While UNCLOS officially came into force in 1982, a number of coastal countries unilaterally declared 200 nautical mile limits prior to this. An alternative measure using 1977 as the cut-off gives similar results, although sharing a land border becomes statistically significantly negative.

  31. Alternative specifications using 1977 or 1962, the start of our sample, as the cut-off give similar results, available upon request.

  32. The observations with a non-reciprocal agreement are coded as zeroes in this specification, thus, we compare observations with reciprocal agreements to observations with non-reciprocal ones and observations with no agreements.

  33. As the coefficient on population of the destination country is negative, we also estimate a version with GDP, rather than GDP per capita and population. In this estimation, the coefficient on economic size of the destination country is positive.

  34. Similarly to the estimation results for agreements, including the EUmember indicator does not alter the other results.

  35. Alternatives using 1977 or 1962 as the cutoff dates as described in Sect. 5.2 gave similar results.

  36. In this specification, all observations with a two-way trade are coded as zeroes. That is, we compare observations with non-reciprocal fish exports to observations with reciprocal exports and observations with no trade.

  37. In this specification, all observations with one-way exports are coded as zeroes.

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Funding

This work was supported by the Faculty of Professions Momentum Fund, University of Adelaide.

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  1. Waseda Institute for Advanced Study, Waseda University, Tokyo, Japan

    Tatyana Chesnokova

  2. School of Economics, University of Adelaide, Adelaide, SA, 5005, Australia

    Stephanie McWhinnie

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  1. Tatyana Chesnokova
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  2. Stephanie McWhinnie
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Correspondence to Stephanie McWhinnie.

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Chesnokova, T., McWhinnie, S. International Fisheries Access Agreements and Trade. Environ Resource Econ 74, 1207–1238 (2019). https://doi.org/10.1007/s10640-019-00365-4

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