Domestic Ban Versus Border Rejections: A Case of Oman’s Fish Exports to the EU

Abstract

The decline of Oman's fish exports to the European Union (EU) since mid-2000s has caused legitimate concerns among policy makers and exporters. However, the potential reasons for the decline have not been fully elucidated. To ascertain the underlying causes of such decline, this article empirically examines the relative significance of potential economic and policyrelated factors such as border rejections influenced by health and safety measures, supply and demand capacities, domestic ban, domestic structural changes, and exchange rate fluctuations on Oman's fish exports to the EU. The results obtained from the dynamic unbalanced panel data model for the period 2000-2013 indicate that fish exports to the EU markets have been influenced by the domestic ban on export, domestic structural changes, and exchange rate fluctuations rather than by border rejections. These findings provide important signal to policy makers of the respective countries in designing adaptive policy approach to address such influences.

Do Regulatory Measures Necessarily Affect Oman’s Seafood Export-Supply?

“…Therefore, the results provide support to Research Hypothesis 1 only for the EU market. This is consistent with the findings by Bose et al (2019) who noted the domestic export ban rather than the border rejections by the EU countries has acted as a significant barrier to fish exports to the EU. A recent study conducted by Al-Busaidi et al (2017) stated that the share of Oman's end products going to lucrative markets such as the EU, the United States, and Japan declined due to the exports ban on specific species.…”

“…In the case of New Zealand lobster export to Japan, Bose and Galvan (2005) noted that 39% of the gap between the actual and desired level was covered in each period. For the EU market case using yearly data, Bose et al (2019) found that 1.92 1.94 Heteroscedasticity B-P-G: χ 2 = 1.58 (df = 10) (p = .14) B-P-G: χ 2 = 7.43 (df = 9) (p = .59) ARCH: χ 2 = 1.00 (df = 1) (p = .32) ARCH: χ 2 = 0.64 (df = 1) (p = .42) FSB (2001FSB ( -2015.…”

“…Recently, Bose et al (2019) noted that the performance of seafood exports measured in terms of quantity and value in the EU market has deteriorated during the past years (see Figure 1). This type of decline in export to high-value markets such as the EU has important economic implications for the sector as it has a negative impact on foreign exchange earnings.…”

“…The demand for such government intervention was influenced by the lack of availability of preferred fish and high fish prices in the domestic market. Therefore, the application of this quantitative export restraint measures was decided by the government to protect domestic consumers' interests and ensure availability of these preferred species in the domestic market and thereby to reduce inflationary pressure on fish prices (Bose et al, 2019). In 2011, the demersal trawl fishery stopped its operation due to a ban imposed on demersal trawl fishing.…”

Trade in Intermediates and Agro-Food Value Chain Integration: The Case of the Arab Region

“…The theory was enhanced by adding a multilateral resistant variable that reflects the average distance of a country from all other countries. In the more recent literature, the gravity model was applied to a variety of trade issues, including trade integration patterns (Rasoulinezhad & Jabalameli, 2018;Rasoulinezhad et al, 2020), energy exports (Rasoulinezhad & Jabalameli, 2019), agro-food exports (Crescimanno et al, 2013), and fishery exports (Bose et al, 2019). Following the literature, the model to be estimated in this study takes the following empirical form:…”