Using the EPA's Storage and Retrieval (STORET) database on water quality indicators at the county level for the 1993-2006 period, this study focuses on the relationship between broad types of land use and some of the main water quality indicators. It finds, among other things, that (a) land use intensity in agricultural activities (as captured by the values of crops and livestock production per unit of land area) positively and significantly influence the levels of total suspended solids, phosphorus, ammonia, and fecal coliform, while negatively affects the levels of cadmium and selenium, (2) urban land use (residential, commercial, and industrial) (as captured by population density) positively impacts the levels of arsenic, magnesium, chromium, fecal coliform but negatively affects the PH level, and (3) the levels of fecal coliform, nitrate, zinc, and copper rise with income per head up to a certain point and then tend to decline as income rises.

The objective of this research is to estimate the damages to irrigated agriculture from salinity and limited drainage conditions in the San Joaquin Valley, California and in particular, to the farms along the Westside. A hedonic property value model of farmland valuation is developed to analyze the relationships between sales prices on 1,914 agricultural parcels sold between 2004-2010 (in and around the SJV) and groundwater depth and groundwater salinity while controlling for environmental, economic, and institutional factors. We collected sales price and parcel characteristic data on approximately 1900 farms in Tulare, Fresno, Kings, Kern, Merced, Napa, San Luis Obispo, Riverside, Monterey and Imperial countries. Salinity and drainage problems often arise in situations where a highly saline water table, which along the westside of the Central Valley has resulted from a lack of drainage opportunities, threatens soil quality and crop production. One way to possibly illustrate how the lack of drainage services and salinity impacts farmland values is to compare the elasticities of groundwater salinity across three agricultural regions—the Central Valley, the Central Coast, and the North Coast—where the Central Valley has a significant area of farmland confronting high water tables due to the lack of drainage services. Results show that the elasticity of groundwater salinity for the Central Valley is -0.13 and is highly significant, whereas the elastic ity of groundwater salinity for the North Coast and Central Coast is 0.13 and -0.09, respectively, although the North Coast estimate is not statistically significant. Alternatively, we also estimate the impact of changes in groundwater depth for different levels of salinity. Categorizing groundwater salinity as low (EC<.6 dS/m), moderately low (EC<.6 dS/m), moderately low (.6<EC<1dS/m), moderately high (1<EC<2 dS/m), and high (2<EC<11 dS/m), we find that the elasticity of groundwater is 0.08 (and statistically significant) when it is categorized as high salinity, 0.06 (and statistically significant) when it is categorized as moderately high salinity, -0.06 (and statistically significant) when it is categorized as moderately low salinity, and -0.48 (and statistically significant) when it is categorized as low salinity. These results suggest that the more saline the groundwater source, the less valuable the land. In fact, when groundwater salinity levels move from moderately low levels to moderately high levels, farmland values increase with depth to the water table; conversely, and what is typically found in the literature, as depth to the groundwater table increases, land values decrease (e.g., Schlenker et al. 2007). In conclusion, our results suggest that assessments as to the value of groundwater to irrigated agriculture must be conditioned by the quality of the groundwater.

A growing body of economics research projects the effects of global climate change on economic outcomes. Climate scientists often criticize these articles because nearly all ignore the well-established uncertainty in future temperature and rainfall changes, and therefore appear likely to have downward biased standard errors and potentially misleading point estimates. This paper incorporates climate uncertainty into estimates of climate change impacts on U.S. agriculture. Accounting for climate uncertainty leads to a much wider range of projected impacts on agricultural profits, with the 95% confidence interval featuring drops of between 17% to 88%. An application to African agriculture yields similar results.

In general, conventional and organic growers have different pest management options. When pest and/or natural enemy populations move across fields, organic and conventional growers' pest management decisions may affect nearby growers. This project demonstrated that California citrus growers' pest management decisions are affected by the pesticide use of nearby growers. Specifically, when nearby growers use pesticides toxic to A. melinus, a natural enemy of California red scale, citrus growers are more likely to treat for California red scale using an insecticide. Other findings included (1) Citrus growers' information sources are a significant determinant of whether or not they utilize biological control in their IPM programs, and (2) More educated growers, growers with more citrus acreage, and growers with higher-valued citrus crops are more likely to use biological control

We have analyzed the impact of damage uncertainty on optimal mitigation policies in the integrated assessment of climate change. The common approach to analyze uncertainty had been a Monte Carlo simulation averaging deterministic paths. A proper treatment of stochasticity, however, requires a model where decision makers take decisions under uncertainty. For this purpose, we constructed a close relative of the integrated assessment model DICE in a recursive dynamic programming framework. Our recursive approach allows us to model persistent uncertainty and to disentangle effects of risk, risk aversion, and aversion to intertemporal substitution. We show that the common Monte Carlo approach underestimates the effects of damage uncertainty on optimal policies. Moreover, a comprehensive risk evaluation has to distinguish between risk attitude and the propensity to smooth consumption over time. The asset pricing literature has shown that this more comprehensive risk analysis eliminates a multitude of asset pricing puzzles. We show that, in the climate context, the same disentanglement implies a major increase in the optimal abatement of greenhouse gases. The project also served as a starting point for a follow up project that analyzes ambiguity and tipping points in the integrated assessment of climate change.

This Giannini funded project investigates whether information costs prevent consumers from making healthier food choices under currently regulated nutritional labels in a market-level expe riment. Implemented nutritional shelf labels reduce information costs by either repeating information available on the Nutritional Facts Panel, or providing information in a new format. We analyze microwave popcorn purchases using weekly store-level scanner data from both treatment and control stores in a difference-in-differences and synthetic control method approach. Our results suggest that information costs affect consumer purchase decisions. In particular, no trans fat labels significantly increase sales, even though this information is already available on the package. Low calorie labels significantly increase sales, while correlated low fat labels significantly decrease sales, suggesting that labeling response may also be influenced by consumers' tast e perceptions. Finally, combining multiple claims in a single label reduces the effectiveness of the implemented labels. Our results provide direct implications for changes to the format and content of nutritional labeling currently considered by the Food and Drug Administration. Co author is Professor Kristin Kiesel. The paper has been published in the International Journal of Industrial Organization.

Anecdotal reports suggest that the USDA Farm Service Agency's Direct Loan Program (DLP) discriminated against minority farmers. We collect data from the Economic Research Service's Phase III Agricultural and Resource Management Survey (ARMS) between 1992 and 2007, and find evidence consistent with these claims. We document a difference in the percentage of direct loans going to minority farmers and the percentage of minority farmers in the ARMS sample. However, one cannot attribute this difference to discrimination without accounting for the loan application process—minority farmers may be less likely to apply for a loan. To address this, we develop a cohesive empirical approach using the NASS Agricultural Census, ARMS and FSA Administrative data to analyze discriminatory practices and other facets of the DLP such as its impact on graduation to the commercial loan sector. Results were communicated to USDA representatives and presented to academic audiences, including the Giannini Foundation Student Conference.

The development and deployment of an animal identification (ID) and traceability system nationwide is necessary to protect the health of the human population and animal agriculture industry and to minimize the economic losses due to an animal disease outbreak. In addition, an efficient animal ID system is a necessary precursor to a food safety and traceability system.

While the costs of the system are relatively easy to measure, the accurate measurement of the benefits of such a system is a challenge for several reasons. First, it is necessary to separate the primary and secondary benefits of the system, because we are only interested in measuring the primary benefits of the system. Second, under the National Animal Identification System (NAIS), voluntary participation required adoption of the system where primary benefits do not exist and where only secondary benefits provide value. Third, the evaluation of the secondary benefits varies depending on the type of animal operation, the size of the operation, and the individual needs of the operation. Fourth , the primary benefits of the system are non-excludable and therefore develop characteristics of a public good with associated free rider problems.

This paper outlines the network effects and network externalities associated with the system, the measurement of the primary and secondary benefits of the system and potential solutions to the free rider problems.

The objective of the project was to identify the impact of ground level Ozone pollution of yields of California's main field and perennial crops.

We have completed an econometric model, which regresses county level yields by crop on ozone concentration and county and year fixed effects. We show a significant nonlinear impact of ozone concentration on yields of soybeans and corn. A fter instrumenting for Ozone concentrations using an indicator of the county level NOx control program, we show that the estimated effects are larger than in the OLS regression.

Protected areas play an important role in conservation schemes around the world. We explore the role that protected areas play in providing important ecosystem services in terms of watershed protection, storage of important scientific information and mitigation of the negative impacts associated with natural disasters via soil erosion control, regulation of the hydrological cycle and early warning system implementation among others. We explore how particular management schemes within specific protected areas may impact the level of provision of these ecosystem services via a general model which then will be used to simulate the final level of ecosystem service provision with data obtained from the US National Park Service and other agencies. Initial findings and theoretical justification were presented at the First Latin American Congress for National Disasters which took place in November, 2010.

A grocery store that sells to brand-name loyal customers and to price-sensitive customers must decide whether to carry both name-brand and private-label products and how much to charge. Introducing a private label may either raise or lower the price that a store charges for a brand-name product. As the number of customers that are price sensitive increases, a store may be more likely to carry a private label, but the prices of both the private label and brand-name may rise. As the reservation price of price-sensitive consumers rises, the price differential between the brand name and private label first falls; but if the reservation price rises further, the store may stop carrying the private label. Given price-sensitive consumers, a store may charge a higher price for the brand name than that which would maximize profit if it sold to only brand-loyal customers.

Genetically modified (GM) varieties were introduced in the mid-1990s, mostly for pest control, and have been adopted widely for corn, soybeans, cotton, and canola. Using data on acreage with and without this technology as well as on output at the national level over a period of 20 years in 125 countries, we were able to isolate the impacts of technology, changes over time, and differences in productivity among countries. We have found that the adoption of GM technology has increased the per-acre yield of cotton more than 100 percent in developing countries and by more than 20 percent in developed countries. The per-acre yield of corn increased by 50 percent in developing countries and by 15 percent in developed countries. The acreage of soybeans more than doubled. Thus, GM technologies have contributed significantly to the reduction in food prices and have enabled growing food demands to be met.