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Article . 2010
Data sources: Research@WUR
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Article . 2010 . Peer-reviewed
License: Elsevier TDM
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Economic impact assessment in pest risk analysis

Authors: Soliman, T.A.A.; Mourits, M.C.M.; Oude Lansink, A.G.J.M.; van der Werf, W.;

Economic impact assessment in pest risk analysis

Abstract

According to international treaties, phytosanitary measures against introduction and spread of invasive plant pests must be justified by a science-based pest risk analysis (PRA). Part of the PRA consists of an assessment of potential economic consequences. This paper evaluates the main available techniques for quantitative economic impact assessment: partial budgeting, partial equilibrium analysis, input output analysis, and computable general equilibrium analysis. These techniques differ in width of scope with respect to market mechanisms (relationships between supply, demand, and prices), and linkages between agriculture and other sectors of the economy. As a consequence, techniques differ in their ability to assess direct and indirect (e.g. economy-wide) effects of pest introduction. We provide an overview of traits of the available methods to support the selection of the most appropriate technique for conducting a PRA. Techniques with a wider scope require more elaborate data, and greater effort to conduct the analysis. Uncertainties are compounded as methods with greater scope are used. We propose that partial budgeting should be conducted in any risk assessment, while more sophisticated techniques should be employed if the expected gains in insight outweigh the costs and compounded uncertainties.

Country
Netherlands
Related Organizations
Keywords

profitability, management

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    52
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 10%
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