000089929 001__ 89929
000089929 005__ 20210902121651.0
000089929 0247_ $$2doi$$a10.5424/sjar/2020181-15005
000089929 0248_ $$2sideral$$a117925
000089929 037__ $$aART-2020-117925
000089929 041__ $$aeng
000089929 100__ $$aPeci, J.
000089929 245__ $$aRegulatory patterns in international pork trade and similarity with the EU SPS/TBT standards
000089929 260__ $$c2020
000089929 5060_ $$aAccess copy available to the general public$$fUnrestricted
000089929 5203_ $$aAim of study: With the increasing protagonism of non-tariff measures (NTMs) in trade policy, better indexes are needed to depict the prevalence and similarity of NTMs across countries for further use in trade impact assessments.
Area of study: Worldwide, with special focus on the European Union (EU) Material and methods: Using the TRAINS database on NTMs, we calculated and proposed some indicators, stressing both regulatory intensity and diversity, as well as similarity of regulatory patterns between trade partners. Our application focuses on pork trade and main importers, amongst which, the EU is singled out.
Main results: We found a high level of heterogeneity in NTMs’ application, both, in the number and variety of measures. The bilateral similarity was relatively low, such as only 30% of sanitary and phytosanitary measures (SPS) and 20% of technical barriers to trade were shared, providing ground and incentive for discussing trade policy harmonization. Our analysis suggests that SPS regulations prevail in those sectors and countries more engaged in trade, while a negative correlation with tariffs raises protection-ism concerns. Our bilateral indicators rank country pairs according to the similarity of their regulatory patterns. The EU, for instance, is closer in SPS regulations to China or USA than to Canada or New Zealand, which will require actions in the context of the bilateral trade agreements in course.
Research highlights: The low similarity of regulatory patterns evidence the challenges faced by policy makers to streamline technical regulations. For an accurate representation of regulatory patterns and their impact on trade, both uni-and bilateral indicators need to be considered.
000089929 536__ $$9info:eu-repo/grantAgreement/ES/INIA-FEDER/RTA2015-00031-00-00
000089929 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000089929 590__ $$a1.238$$b2020
000089929 591__ $$aAGRICULTURE, MULTIDISCIPLINARY$$b31 / 58 = 0.534$$c2020$$dQ3$$eT2
000089929 592__ $$a0.337$$b2020
000089929 593__ $$aAgronomy and Crop Science$$c2020$$dQ3
000089929 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000089929 700__ $$0(orcid)0000-0001-5470-7528$$aSanjuán, A.I.
000089929 773__ $$g18, 1 (2020), e0102 [14 pp]$$pSpan. j. agric. res.$$tSpanish Journal of Agricultural Research$$x1695-971X
000089929 8564_ $$s835659$$uhttps://zaguan.unizar.es/record/89929/files/texto_completo.pdf$$yVersión publicada
000089929 8564_ $$s1697$$uhttps://zaguan.unizar.es/record/89929/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000089929 909CO $$ooai:zaguan.unizar.es:89929$$particulos$$pdriver
000089929 951__ $$a2021-09-02-09:07:01
000089929 980__ $$aARTICLE