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How to model a negligible probability under the WTO sanitary and phytosanitary agreement?

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      <subfield code="a">Powell, Mark R.</subfield>
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      <subfield code="a">How to model a negligible probability under the WTO sanitary and phytosanitary agreement?</subfield>
      <subfield code="c">Mark R. Powell</subfield>
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      <subfield code="a">Since the 1997 EC  Hormones decision, World Trade Organization (WTO) Dispute Settlement Panels have wrestled with the question of what constitutes a negligible risk under the Sanitary and Phytosanitary Agreement. More recently, the 2010 WTO Australia  Apples Panel focused considerable attention on the appropriate quantitative model for a negligible probability in a risk assessment. The 2006 Australian Import Risk Analysis for Apples from New Zealand translated narrative probability statements into quantitative ranges. The uncertainty about a negligible probability was characterized as a uniform distribution with a minimum value of zero and a maximum value of 10-6. The Australia  Apples Panel found that the use of this distribution would tend to overestimate the likelihood of negligible events and indicated that a triangular distribution with a most probable value of zero and a maximum value of 10-6 would correct the bias. The Panel observed that the midpoint of the uniform distribution is 5 × 10-7 but did not consider that the triangular distribution has an expected value of 3.3 × 10-7. Therefore, if this triangular distribution is the appropriate correction, the magnitude of the bias found by the Panel appears modest. The Panel's detailed critique of the Australian risk assessment, and the conclusions of the WTO Appellate Body about the materiality of flaws found by the Panel, may have important implications for the standard of review for risk assessments under the WTO SPS Agreement.</subfield>
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      <subfield code="w">MAP20077000345</subfield>
      <subfield code="t">Risk analysis : an international journal</subfield>
      <subfield code="d">McLean, Virginia : Society for Risk Analysis, 1987-2015</subfield>
      <subfield code="x">0272-4332</subfield>
      <subfield code="g">10/06/2013 Volumen 33 Número 6 - junio 2013 , p. 972-983</subfield>
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      <subfield code="y">MÁS INFORMACIÓN</subfield>
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