An Investigation of Spatial and Temporal Concepts in U.S. Corn and Soybean Markets
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Date
2009-04-16
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Abstract
Spatial and temporal issues are often important concepts within agricultural economics research. Understanding these issues and developing models that incorporate spatio-temporal frameworks can lead to more accuracy in answering important economic questions. This thesis uses the spatio-temporal framework to analyze topics that pertain to modeling disease risk of soybeans, estimating welfare effects from wind-borne diseases, and examining price transmissions in North Carolina soybean and corn markets. First, economic impacts of soybean rust in the United States are examined by using zero-inflated count-data models that are
adjusted for potential endogeneity between inspections and infection finds. Past soybean rust finds and inspections in the county and in the surrounding counties, weather and overwintering conditions, and plant maturity groups and planting dates are all found to be significant aspects of determining soybean rust. These results are then used to accordingly price annual insurance contracts that cover soybean rust damages. Next, welfare impacts of wind-borne disease outbreaks in the United States are investigated under two alternative indemnification policies.The standard insurance program and a proposed check-off and mitigation scheme are compared, and simulation estimates are provided for a soybean rust outbreak in the U.S. soybean industry. The results indicate that welfare benefits may be as high as $1.7 billion under the check-off and mitigation plan. Finally, linkages between spatially separated corn markets and soybean markets in North Carolina are analyzed by extending the constant threshold autoregressive model, which is the methodology found in the current literature. The more
flexible asymmetric variable thresholds model, which allows the transaction costs neutral band to vary according to external factors, statistically outperforms the alternative
specifications, might better represent long time series data, and indicates that the constant threshold models can underestimate the time-to-convergence and magnitude of a price shock in linked markets.
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Keywords
spatio-temporal, invasive species, price linkages, threshold autoregressive
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Degree
PhD
Discipline
Economics
