Agricultural Trade Performance and Potential: A Retrospective Panel Data Analysis of US Exports of Corn and Soybeans

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dc.contributor.authorGrossen, Grace Elizabethen
dc.contributor.committeechairGrant, Jason H.en
dc.contributor.committeememberRamsey, A. Forden
dc.contributor.committeememberMarchant, Mary A.en
dc.contributor.departmentAgricultural and Applied Economicsen
dc.date.accessioned2019-08-23T08:00:42Zen
dc.date.available2019-08-23T08:00:42Zen
dc.date.issued2019-08-22en
dc.description.abstractThere are a variety of international issues that disrupt the global trade market, an important one being national policies on the regulation of genetically modified organisms, or GMOs. Many crops have been genetically modified for reasons from herbicide resistance to correcting dietary shortfalls. This study evaluates the United States' exports of corn and soybeans from 1998 to 2016 to identify unusual shocks in trade values. In particular, this study quantifies how the importers' policy stance on the GMO issue impacts bilateral trade values. I estimate a gravity model with both ordinary least squares (OLS) and Poisson pseudo maximum likelihood (PPML) estimations. Residual analysis is used to assess the difference between actual trade and the trade levels predicted by the models. The results suggest that anti-GMO policies reduce trade values by an average of 11%. The largest difference between predictions and actual trade values is seen in corn exports to the European Union. Between 1998 and 2016, this forgone trade in corn was valued at $52.7 billion, which is $2.77 billion per year on average. This value is similar to the annual average value of U.S. exports of corn to Japan in the same period, $2.46 billion. The results have important implications for the agricultural industry. For developing nations, adoption of GMO crops could increase productivity and help alleviate poverty. Ultimately, the decision to adopt is up to the consumer, so the factors of consumer knowledge and opinions of GMOs are not to be ignored.en
dc.description.abstractgeneralThere are a variety of international issues that disrupt the global trade market, an important one being national policies on the regulation of genetically modified organisms, or GMOs. This study evaluates the United States’ exports of corn and soybeans from 1998 to 2016 to identify unusual drops in trade values. In particular, this study quantifies how the importers’ policy stance on the GMO issue impacts bilateral trade values. I estimate a gravity model with various estimation methods. Residual analysis is used to assess the difference between actual trade and the trade levels predicted by the models. The results suggest that anti-GMO policies reduce trade values by an average of 11%. The largest difference between predictions and actual trade values is seen in corn exports to the European Union. Between 1998 and 2016, this forgone trade in corn was valued at $52.7 billion, which is $2.77 billion per year on average. This value is similar to the annual average value of U.S. exports of corn to Japan in the same period, $2.46 billion. The results have important implications for the agricultural industry. For developing nations, adoption of GMO crops could increase productivity and help alleviate poverty. Ultimately, the decision to adopt is up to the consumer, so the factors of consumer knowledge and opinions of GMOs are not to be ignored.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:21635en
dc.identifier.urihttp://hdl.handle.net/10919/93225en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectPanel dataen
dc.subjectcorn and soybeansen
dc.subjectagricultural tradeen
dc.subjectgravity modelen
dc.titleAgricultural Trade Performance and Potential: A Retrospective Panel Data Analysis of US Exports of Corn and Soybeansen
dc.typeThesisen
thesis.degree.disciplineAgricultural and Applied Economicsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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