Essays in Greenhouse/Nursery Economics

This dissertation focuses on the greenhouse and nursery industry in the United States. Two major issues are explored: irrigation and plant disease. The first two essays examine wireless soil-moisture sensor networks, an emerging technology that measures soil moisture and optimizes irrigation levels in real time. The first essay describes a study in which a nationwide survey of commercial growers was administered to generate estimates of grower demand and willingness to pay for sensor networks. We find that adoption rates for a base system and demand for expansion components are decreasing in price, as expected. The price elasticity of the probability of adoption suggests that sensor networks are likely to diffuse at a rate somewhat greater than that of drip irrigation. In the second essay, yields, time-to-harvest, and plant quality were analyzed to measure sensor network profitability. Sensor-based irrigation was found to increase revenue by 62% and profit by 65% per year. The third essay investigates greenhouse nursery growers’ response to a quarantine imposed on the west coast of the United States from 2002 to present for the plant pathogen that causes Sudden Oak Death. I investigate whether growers choose to 1) improve their sanitation practices, which reduces the underlying risk of disease without increasing the difficulty of detecting the pathogen, 2) increase fungicide use, which also prevents disease but makes existing infections much harder to detect, or 3) change their crop composition towards more resistant species. First, a theoretical model is derived to formalize hypotheses on grower responses to the quarantine, and then these predictions are empirically tested using several public data sources. I do not find evidence that growers improve their sanitation practices in response to the quarantine. I do, however, find evidence that growers heavily increase their fungicide use in response to a quarantine policy that requires visual (as opposed to laboratory) inspection for the disease before every crop shipment, suggesting that the quarantine may have the adverse effect of making the pathogen harder to identify. I also do find evidence that growers shift away from susceptible crops and towards resistant crops.

Agriculture, Environmental Incentive Payments, and Water Quality in the Chesapeake Bay

Nonpoint sources (NPS) pollution from agriculture is the leading source of water quality impairment in U.S. rivers and streams, and a major contributor to lakes, wetlands, estuaries and coastal waters (U.S. EPA 2016). Using data from a survey of farmers in Maryland, this dissertation examines the effects of a cost sharing policy designed to encourage adoption of conservation practices that reduce NPS pollution in the Chesapeake Bay watershed. This watershed is the site of the largest Total Maximum Daily Load (TMDL) implemented to date, making it an important setting in the U.S. for water quality policy. I study two main questions related to the reduction of NPS pollution from agriculture. First, I examine the issue of additionality of cost sharing payments by estimating the direct effect of cover crop cost sharing on the acres of cover crops, and the indirect effect of cover crop cost sharing on the acres of two other practices: conservation tillage and contour/strip cropping. A two-stage simultaneous equation approach is used to correct for voluntary self-selection into cost sharing programs and account for substitution effects among conservation practices. Quasi-random Halton sequences are employed to solve the system of equations for conservation practice acreage and to minimize the computational burden involved. By considering patterns of agronomic complementarity or substitution among conservation practices (Blum et al., 1997; USDA SARE, 2012), this analysis estimates water quality impacts of the crowding-in or crowding-out of private investment in conservation due to public incentive payments. Second, I connect the econometric behavioral results with model parameters from the EPA’s Chesapeake Bay Program to conduct a policy simulation on water quality effects. I expand the econometric model to also consider the potential loss of vegetative cover due to cropland incentive payments, or slippage (Lichtenberg and Smith-Ramirez, 2011). Econometric results are linked with the Chesapeake Bay Program watershed model to estimate the change in abatement levels and costs for nitrogen, phosphorus and sediment under various behavioral scenarios. Finally, I use inverse sampling weights to derive statewide abatement quantities and costs for each of these pollutants, comparing these with TMDL targets for agriculture in Maryland.

Using Quantitative Methods to Explore Political Leverage, Trade Policy, and Food Security: A Case Study of the Middle East

This dissertation explores why some states consistently secure food imports at prices higher than the world market price, thereby exacerbating food insecurity domestically. I challenge the idea that free market economics alone can explain these trade behaviors, and instead argue that states take into account political considerations when engaging in food trade that results in inefficient trade. In particular, states that are dependent on imports of staple food products, like cereals, are wary of the potential strategic value of these goods to exporters. I argue that this consideration, combined with the importing state’s ability to mitigate that risk through its own forms of political or economic leverage, will shape the behavior of the importing state and contribute to its potential for food security. In addition to cross-national analyses, I use case studies of the Gulf Cooperation Council states and Jordan to demonstrate how the political tools available to these importers affect their food security. The results of my analyses suggest that when import dependent states have access to forms of political leverage, they are more likely to trade efficiently, thereby increasing their potential for food security.