Quantifying Phytosanitary Barriers to Trade

Hugh R. Bigsby

Abstract
This paper presents a model for quantifying quarantine-related trade barriers by combining the two basic components of pest risk assessment, probability of establishment and economic effects, into a single management framework, Iso-Risk. The model provides a systematic and objective basis for defining and measuring acceptable risk and for justifying quarantine actions relative to acceptable risk.

Introduction
One of the outcomes of the Uruguay Round of the General Agreement on Tariffs and Trade (GATT) was the provision for reductions in a range of trade barriers, such as tariffs, export subsidies, and domestic price supports, that were able to be converted into “tariff-equivalent” levels of protection. The key success of this approach was that different “quantifiable” trade barriers could then be compared, reduced, or negotiated in a common framework of tariffs.

What remained to be resolved were a range of trade barriers that were largely nonquantifiable in terms of tariff-equivalent levels of protection. These barriers, termed 'technical barriers to trade (TBT), include rules and standards directed at health, safety, or the environment. One of the most prevalent type of TBT is that related to plant health.

Within this context, a particular issue is how to choose an appropriate level of protection (ALP) or justified quarantine measure. The major problem here is the lack of a system that can convert diverse technical or scientific barriers related to plant health into a common framework that would allow comparison of quarantine measures within a trade or economic forum.

This paper presents a risk analysis system, iso-risk, that combines the key elements of risk analysis, probability of occurrence, and economic impact into a single system that provides a quantifiable measure of the level of protection associated with a quarantine measure.

Iso-Risk Framework
The major problem presented by TBTs is the absence of a system that can adequately combine the key features of risk analysis, risk of introduction, and economic consequences in a way that facilitates comparison and negotiation. An important component of assessing risk or levels of protection is a methodology that uses both economic effects and probability of introduction to manage risk. A common way for these two factors to be combined is to calculate “Pest risk” as

Pest Risk = Economic Effect x Probability of Introduction

Presented this way, pest risk is the expected value of the economic effect of a pest introduction during the time period for which the probability of introduction has been assessed. Using this definition for pest risk, risk management options would be considered in the context of some benchmark or acceptable level of pest risk (equivalent to ALP) and the need to alter the probability of introduction or the economic consequences of establishment to reduce the risk to an acceptable level.

The Iso-Risk framework can be illustrated using Figure 1. Pest 1, with an economic impact of EI₁ and a probability of establishment of r₁, has a pest risk of PR₁, where

PR₁ = EI₁ x r₁

Pest 2 has an economic impact of EI₂ and a probability of introduction of r₂. As seen in Figure 1, different pests, with different potential economic consequences and probability of introduction may still share the same value of pest risk. Both PR₁ and PR₂ lie on the same line, where all combinations of EI₁ x r₁ have the same value (hence, the iso-risk line). Note that in Figure 1, the iso-risk line is straight only when both the x and y axes are plotted with logarithmic scales.

Figure 1. Iso-Risk Framework

A key requirement for carrying out risk assessment, or determining entry conditions, is a predetermined benchmark level of pest risk or ALP, from which to base decisions. In Figure 1 there will be an infinite number of iso-risk lines representing different levels of pest risk, with higher iso-risk lines indicating higher pest risk. Iso-risk lines allow pests to be compared with each other, and compared with a particular acceptable level of pest risk. This ability to compare in turn provides the basis for determining appropriate actions. In particular, the result of pest risk management should be a pest risk that does not exceed the ALP, with a reasonable level of confidence. In the context of Figure 1, because all points on an iso-risk line have the same expected value, the ALP represents the highest iso-risk line that will be accepted by a quarantine authority.

Given this definition, evaluating individual pests against an ALP is simple. If the pest risk of a particular pest is greater than the ALP, actions should be taken to reduce pest risk to the ALP. For example, in Figure 1, a pest with a pest risk of PR₃ would be subject to actions to reduce the risk to acceptable levels while a pest corresponding to PR₄ falls within acceptable limits, and requires no additional quarantine actions.

Summary
Use of both the probability and consequences of a particular event to express risk appears in many areas of risk analysis. The iso-risk framework discussed here follows this approach to develop a method for quantifying quarantine decisions in a way that allows for objective analysis and comparison of risk.

Although many quarantine risk assessments focus on the risk associated with a particular pest, similar to what has been presented in this paper, it is important to recognize that trade restrictions and most pre-entry quarantine measures are directed at entire commodities rather than particular pests. The important distinction here is that commodities with more types of pests will represent a greater risk, per unit, than commodities with fewer types of pests. A purely pest-based analytical approach, although useful for some types of analyses, such as categorizing pests into quarantine and nonquarantine, may not give a measure of the overall risk associated with a commodity.

Commodity-based risk assessments, such as those produced by the USDA (1996) rely on assessments of each pest associated with a commodity. The logical extension of the iso-risk analysis is to extend it to a commodity level. The ALP for a commodity can be defined by considering the ALP for each individual pest of the commodity. Extension of the iso-risk analysis to commodities can be found in Bigsby (1996, 2001) and Bigsby and Whyte (1998, 2000).

Bigsby, H. R. 2001. Quantifying Phytosanitary Barriers to Trade. In The Economics of Quarantine and the SPS Agreement; K. Anderson, C. F. McRae, and D. Wilson, eds. Biosecurity Australia, Canberra and Centre for International Economic Studies, University Adelaide.

Bigsby, H. R. 1996. Enhancement and Further Development of the Economic Impact Assessment Modules. Final Report for NZMAF.

Bigsby, H. R., and Whyte, C. F. 2000. Quantifying Phytosanitary Barriers to Trade. Interdisciplinary Food Safety Research, N. Hooker E. Murano, eds. CRC Press, Boca Raton, FL (in press publication).

Bigsby, H. R. and Whyte, C 1998. A Model of the Appropriate Level of Protection for New Zealand's Quarantine Security. MAF Policy Draft Technical Paper, Wellington.

USDA 1996. Pathway-Initiated Pest Risk Assessment: Guidelines for Qualitative Assessments, version 4.0. USDA-APHIS-PPQ, Riverdale, MD.