Agricultural & Resource Economics Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2739
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Item Essays on Climate Change Impacts and Adaptation for Agriculture(2013) Ortiz Bobea, Ariel; Just, Richard E; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Over the past twenty years economists have developed econometric approaches for estimating the impacts of climate change on agriculture by accounting for farmer adaptation implicitly. These reduced-form approaches are simple to implement but provide little insights into impact mechanisms, limiting their usefulness for adaptation policy. Recently, conflicting estimates for US agriculture have led to research with greater emphasis on mechanisms including renewed interest in statistical crop yield models. Findings suggest US agriculture will be mainly and severely affected by an increased frequency of high temperatures with crop yield suggested as a major driver. This dissertation is comprised of three essays highlighting methodological aspects in this literature. It contributes to the ongoing debate and shows the preeminent role of extreme temperature is overestimated while the role of soil moisture is seriously underestimated. This stems from issues related to weather data quality, the presence of time-varying omitted weather variables, as well as from modeling assumptions that inadvertently underestimate farmers' ability to adapt to seasonal aspects of climate change. My work illustrates how econometric models of climate change impacts on crop production can be improved by structuring them to admit some basic principles of agronomic science. The first essay shows that nonlinear temperature effects on corn yields are not robust to alternative weather datasets. The leading econometric studies in the current literature are based on a weather dataset that involves considerable interpolation. I introduce the use of a new dataset to agricultural climate change research that has been carefully developed with scientific methods to represent weather variation with one-hour and 14 kilometer accuracy. Detrimental effects of extreme temperature crucially hinge upon the recorded frequency at the highest temperatures. My research suggests that measurement error in short amounts of time spent at extreme temperature levels has disproportionate effects on estimated parameters associated with the right tail of the temperature distribution. My alternative dataset suggests detrimental temperature effects of climate change over the next 50-100 years will be half as much as in leading econometric studies in the current literature. The second essay relaxes the prevalent assumption in the literature that weather is additive. This has been the practice in most empirical models. Weather regressors are typically aggregated over the months that include the growing season. Using a simple model I show that this assumption imposes implausible characteristics on the technology. I test this assumption empirically using a crop yield model for US corn that accounts for differences in intra-day temperature variation in different stages of the growing season. Results strongly reject additivity and suggest that weather shocks such as extreme temperatures are particularly detrimental toward the middle of the season around flowering time, which corrects a disagreement of empirical yield models with the natural sciences. I discuss how this assumption tends to underestimate the range of adaptation possibilities available to farmers, thus overstating projected climate change impacts on the sector. The third essay introduces an improved measure of water availability for crops that accounts for time variation of soil moisture rather than season-long rainfall totals, as has been common practice in the literature. Leading studies in the literature are based on season-long rainfall. My alternative dataset based on scientific models that track soil moisture variation during the growing season includes variables that are more relevant for tracking crop development. Results show that models in the literature attribute too much variation in yields to temperature variation because rainfall variables are a crude and inaccurate measure of the moisture that determined crop growth. Consequently, I find that third of damages to corn yields previously attributed to extreme temperature are explained by drought, which is far more consistent with agronomic science. This highlights the potential adaptive role for water management in addressing climate change, unlike the literature now suggests. The fourth essay proposes a general structural framework for analyzing the mechanisms of climate change impacts on the sector. An empirical example incorporates some of the flexibilities highlighted in the previous essay to assess how farmer adaptation can reduce projected impacts on corn yields substantially. Global warming increases the length of the growing season in northern states. This gives farmers the flexibility to change planting dates that can reduce exposure of crops during the most sensitive flowering stage of the crop growth cycle. These research results identify another important type of farmer adaptation that can reduce vulnerability to climate change, which has been overlooked in the literature but which becomes evident only by incorporating the principles of agronomic science into econometric modeling of climate change impact analysis.Item An analysis of regulatory decisions on food-use pesticides under the Food Quality and Protection Act(2012) Newcomb, Elisabeth Jo; Cropper, Maureen L; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)To ensure the safety of older pesticides used in the United States, the EPA required the reregistration of pesticide uses which were first introduced before 1984. Using a dataset of reregistration outcomes for 2722 pesticide uses applied to food crops, I analyze the extent to which these decisions were determined by chronic health risks, pesticide expenditures, and other factors. I find that the dietary health risks associated with pesticides are had greater influence on actions to reduce dietary and occupational exposures than on pesticide cancellations. High population dietary risks are associated with higher rates of pesticide cancellations, though these results are insignificant. There is evidence that the EPA was more responsive to child and infant dietary risks: values above the EPA's threshold of concern were more than 10% more likely to be cancelled than those that were not (significant at the 10% level). The effects of cancer risks on EPA actions are more ambiguous, though this may be due to data limitations. The less safe pesticides are for handlers, the more often they are cancelled, but pesticide safety has a more significant correlation with reentry intervals. A one percent decrease in the safety of a pesticide to handlers predicts a reduction in reentry interval of 1.6 days (significant at the 5% level). Expenditures on individual pesticides have a strong relationship with pesticide reregistration, with an additional half million dollars in expenditures predicting a 2% increase in the probability of reregistration (significant at the 1% level). Expenditures are not so correlated with reentry intervals or changes in pesticide tolerances. After accounting for dietary risk and pesticide expenditures, Monsanto and Dow were most likely to have uses reregistered. Though there was some concern that small crops with low pesticide expenditures would suffer extra cancellations, small crop uses were no more likely to be cancelled than large crop uses. Mentions of individual pesticides in the media had no apparent relationship with the outcome of reregistration decisions.Item Learning-by-Doing and Contracts in New Agricultural Industries(2004-05-24) Choiniere, Conrad Joseph; Lichtenberg, Erik; Agricultural and Resource EconomicsThe dissertation develops a theoretical model to examine the effects of limited liability contracting on learning-by-doing and capital investment within a new agricultural industry. The theoretical model applies to many new bio-based industries, where novel crops are being used to produce goods, such as chemicals and energy, which would not be considered traditional agriculture. Limited-liability contracts create an environment of moral hazard in learning investment and adverse selection in the production of the intermediate good. These two features of the contracting environment present difficulties for the principal to benefit from the learning-induced cost reductions realized at the intermediate stage of production. Thus, the principal under-invests in the industry and requires less of the intermediate good. Reduced feedstock orders decrease the incentives for the agent to invest in learning, and so the ultimate cost of production of the intermediate good is higher than optimal. The dissertation adapts the theoretical model to construct a simulation of investment and production decisions within an industry for the generation of electricity using biomass. The results of the simulation show that an industry formed around limited liability contracts realizes project scales 25-30% smaller than optimal. Learning-induced cost reductions in the production of biomass are 20% less than predicted by engineering analyses. Limited-liability contracts raise the price paid by the principal for the feedstock by 25% above optimal. The analysis reveals that the price of electricity necessary for a project to break even is 5% higher under limited liability contracts. Sensitivity analysis illustrates that the problem of underinvestment increases under conditions favorable to grower learning. A capital subsidy paid to processors that invest in technology encourages over-investment in capital relative to feedstock utilization. The Renewable Energy Production Credit or a feedstock subsidy paid to growers increase project scales by about 30%, yet they are still 20% smaller than optimal. These subsidies do not have a significant impact on the price of the feedstock to the processor. The government may seek to explore policies that encourage forward vertical integration in the industry.