Show simple item record

dc.contributor.authorSuzuki, Nobuhiro
dc.contributor.authorKaiser, Harry M.
dc.date.accessioned2018-08-21T17:09:43Z
dc.date.available2018-08-21T17:09:43Z
dc.date.issued2000-09
dc.identifier.urihttps://hdl.handle.net/1813/57838
dc.descriptionWP 2000-11 September 2000
dc.description.abstractIn this paper, we develop a theoretical and practical measurement of the degree of market distortion due to price discrimination for export subsidies by state trading enterprises (STEs). The model is applied to existing STEs in Canada, New Zealand, and Australia. Based on FAO price data and U.S. Department of Agriculture elasticity estimates, the empirical results indicate that the exporting STEs exert some market power for subsidized exports in Australia, New Zealand, and Canada. However, the degree of market power is far from the extreme monopoly case. The degree of distortion is highest for Canadian dairy exports, but the export subsidy equivalents (ESEs) are larger in Australia and New Zealand due to significantly higher export volume in these two countries relative to Canada. The results suggest that these exporting STEs play a significant role in providing effective export subsidies. While Canada's special milk class system that prices milk substantially lower for export has already been judged to be an export subsidy by the WTO court, our results indicate that other exporting STEs should also be examined. However, in order to have more accurate estimates of the distortions caused by STEs, price data from the exporting STEs is required.
dc.language.isoen_US
dc.publisherCharles H. Dyson School of Applied Economics and Management, Cornell University
dc.titleMeasuring the Degree of Price Discrimination for Export Subsidies Generated by State Trading Enterprises
dc.typearticle
dcterms.licensehttp://hdl.handle.net/1813/57595


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • Working Papers
    Working Papers published by the Charles H. Dyson School of Applied Economics and Management, Cornell University

Show simple item record

Statistics