Essays on innovation in the U.S. corn and soybean seeds

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2021-08
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Lee, Seungki
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Moschini, GianCarlo
Clancy, Matthew
Crespi, John
Kedagni, Desire
Lence, Sergio
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Economics
Abstract
This dissertation, composed of three essays, looks at the economic consequences and environmental implications pertaining to innovations in the U.S. corn and soybean seed industries. The three essays study distinct but interrelated themes, including (1) the economic value of seed trait development and an associated extension program, (2) the role of innovation in the context of climate change, (3) environmental impact by the interplay between pesticide use and genetically engineered (GE) variety adoption. The first essay quantifies the economic value of seed traits resistant to soybean cyst nematodes (SCNs) and an associated agricultural extension, Iowa State University SCN-resistant Soybean Variety Trials, that is designed to promote the adoption of this trait. In the framework of nested-logit demand estimation, farmers’ seed choices in Iowa and northern Illinois during 2011-2016 are analyzed at a market level. Based on the demand estimates, the research finds fairly large farmers’ willingness-to-pay for a variety tested by the extension program as well as the SCN resistance trait. In addition, through a counterfactual analysis where the studied extension program and SCN resistance trait are absent, this study estimates the total value of SCN-resistant varieties and associated ISU-SCN information at 326 million dollars over the time and region of the analysis. About one third of this surplus is captured by seed suppliers, and two thirds are held by farmers. The second essay examines the yield gain from GE maize adoption and uses it as a yardstick to gauge the scope of innovation required to adapt to anticipated damage from future climate change. The research draws on the observed county-level maize yields and historical weather data in the contiguous U.S. from 1981 to 2016, which encompasses the entire period from introduction to virtual complete adoption of GE varieties. The model estimates from the historical data disclose a large productivity gain (ranging from 14 to 19 bushels per acre) from the first-generation GE varieties (specifically those embedding insect-resistant traits). Subsequently, the yield model is then used to forecast future expected yields given climate change projections from twenty large-scale models and two warming scenarios (RCP45 and RCP85). The yield projections show that expected climate change is associated with significant yield shortfalls by mid-century, and larger shortfalls still by the end of the century. The mean effects over the 20 climate models show that the scale of these yield gaps, by the end of the century, ranges from about 2.7 to 6.3 times the total yield gains due to GE varieties (depending on the warming scenario considered). In the third essay, pesticide usage is investigated with consideration on GE variety adoption so as to expose the environmental impact of GE technology. This study primarily concentrates on toxic loads instead of pesticide quantity by using two advanced (mammalian) toxicity metrics with different durational focuses: short term (acute hazard quotient) and long term (chronic hazard quotient). A fixed-effects regression is carried out based on a rich plot-level dataset on seed and pesticide choices of U.S. maize and soybean farmers during 1998-2016. Overall, the results show that GE adoption has contributed to lessening the mammalian toxicity in pesticides used by GE adopters concerning both acute and chronic risks. Interestingly, the saving in the toxicity-weighted pesticides by glyphosate-tolerant variety adopters in both soybeans and maize has steadily diminished, implying the rise of glyphosate weed resistance. On the other hand, no such clear pattern was observed with respect to the differential insecticide use of insect-resistant maize adopters.
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