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Policy makers have to choose between different potentially risk-reducing instruments regulating agri-food trade. Analysing the meat sector, the paper aims at identifying least trade distorting regulations for different policy goals relevant to the SPS agreement. For this purpose, a non-linear gravity model is estimated by Poisson pseudo-maximum likelihood and applied to a panel data set at HS 4-digit level. Regulations are distinguished by a frequency approach allowing to identify the least trade distorting regulation for each policy objective. The results suggest significant differences of trade impacts between types of sanitary regulations.


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