Projects Funded for 2020-2021

The Role of Land Reform in Chilean Agricultural Exports

  • Ashish Shenoy

Abstract

Specific Objectives:
Chilean fruit production grew by 12% per year from 1997-2007, and the country is currently one of the world's leading fruit exporters. This project evaluates the role that Chilean agricultural land redistribution in the 1960's and 1970's played in the subsequent adoption of fruit production.

Summary of Results:
In the 1960's and early 1970's, progressive land redistribution efforts in Chile reassigned ownership of roughly 13 percent of the nation's agricultural land. Municipality-level analysis indicates that redistribution was associated with greater area devoted to vineyards and less to forestry by 1997, suggesting that land reform increased the intensity of fruit cultivation. These results were derived using digitized records of plots redistributed during land reform. Comparable data on
non-reform plots exists in undigitized format, and digitizing these records provides a path forward for future research that evaluates the effect of land redistribution at a more granular level.

The Impacts of Wildfires on Water Utilities and Communities in California

  • Mehdi Nemati
  • Samane Zare

Abstract

Specific Objectives of the Project:

  • Assess water utilities wildfire risk, with a specific focus on rural and agricultural communities;
  • Establish an association between water utilities’ vulnerability level to wildfires with water utilities’ and communities’ characteristics; and
  • Estimate short- and long-run effects of wildfires on households’ bottled water and water purifying products purchases, with a specific focus on rural and agricultural communities.

Summary of Results:
The project is completed for the first and second objectives, and a paper is submitted to the Journal of Water Resources Management. For the third objective, data is collected and merged/cleaned, but we are still working on refining the results. We do not have a working paper for this objective yet. Summary of the results from the first and second objectives are listed below.

Wildfires have occurred more frequently and are more devastating in California, and quantifying their impact on water utilities, which potentially may lead to water availability and water quality threats, is essential. This is especially important for water utilities whose characteristics are susceptible to wildfires. Due to the unpredictable nature of wildfires, drinking-water utilities face a considerable challenge in developing plans and strategies for managing floods and treating polluted water. Information and tools are needed to help water storage and treatment managers better prepare for the impacts of wildfires.

Our study quantifies these impacts by measuring the effects of wildfire on each water utility service area, based on the exposure frequency and the extent of acres burned by wildfires that occurred in each water utility service area, and by calculating the severity of the wildfire. Our quantitative models take into account the nature of the censoring and selection biases on wildfire data and show an association between water utility characteristics and the level of vulnerability to wildfire risks.

As a result of the cross-sectional estimation of the OLS, Tobit, and Heckman models, we found that wildfire severity increased in areas of (1) government-owned utilities vs. private-owned utilities; (2) utilities relying on surface water vs. those relying on groundwater; (3) utilities relying on local water sources vs. those relying on purchased water; (4) utilities located in Southern vs. Northern California; (5) utilities located on the coast vs. inland California; and (6) utilities in highly populated areas vs. non-populated areas.

Our findings can potentially inform public land managers and water utilities by identifying which water utilities are most vulnerable to wildfires based on their characteristics. They also show the potential characteristics of water utilities that are highly likely to experience changes in potential water availability and quality degradation immediately following a wildfire. Our research reveals that utilities more vulnerable to wildfires will require more strategic management decisions. It also suggests that the countermeasures on wildfires should be different depending on the characteristics the utility has. For example, based on an assessment of wildfire severity, by identifying the utilities and their locations of greatest risk, the relevant institutes could set costs associated with wildfire damage and mitigation activities.

Wildfire management and reducing the risk of wildfires are problems not only for the U.S. Forest Service or other public land management utilities but many other entities, such as water utilities. To help solve this pressing issue, partnerships are needed to help identify landscapes with hazardous vegetation and implement effective land management strategies by federal, state, local municipalities, communities, and nongovernment utilities. From this point of view, our study findings may help inform public land managers about possible shared stewardship partnerships with water utilities to leverage resources and expertise to reduce hazardous vegetation on shared landscapes, thus reducing wildfire risk.

The Impacts of Maritime Emissions Standards

  • Jamie Hansen-Lewis
  • Michelle Marcus

Abstract

Specific Objectives of the Project:
1. Evaluate the impact of maritime emissions standards on air quality in California and in other coastal states
2. Relate and test the equivalence of ex-ante and ex-post methods of air quality policy evaluation
3. Examine the role of maritime emissions on a range of potential outcomes, such as agricultural yields, worker productivity, and infant health, in California

Project Report/Summary of Results:
1. We found that maritime fuel standards, specifically the 2012 Sulfur Emissions Control Area (ECA), led to reductions in fine particulate matter concentrations (PM2.5). On average, the policy resulted in an 0.35 microgram per cubic meter (3.8%) improvement in PM2.5 (p=0.002). We failed to find evidence that the policy predicted trends in air quality in the years prior to implementation (pre-trends).
The data indicated that air quality improvements differed significantly in locations where the jurisdiction of the policy was less than the full 200 nautical miles. Whereas locations with the full jurisdiction had relatively consistent improvements, areas with partial jurisdiction, which included southern California and Florida, had marked improvements in the initial year of the policy and the year the policy became more stringent, but little improvement in intervening years.

2. Overall, we rejected the equivalence of the ex-ante predictions from the EPA and ex-post observations. For a one microgram per cubic meter planned improvement in PM2.5, we estimated PM2.5 fell 0.45 micrograms per cubic meter on average.
Notably, we detected differences in the performance of the ex-ante predictions between areas with full jurisdiction and areas with partial jurisdiction. For the full jurisdiction locations, we failed to reject the equivalence of the ex-ante predictions and ex-post observations. For the partial jurisdiction locations after the initial years, we rejected the equivalence of the ex-ante predictions from the EPA and ex-post observations.

One explanation for this result is that the ex-ante predictions do not account for behavioral changes in reaction to the policy. Ships are best situated to subvert the policy where the jurisdiction is small because they do not need a large route detour to use highly polluting fuels. For example, within 80 miles of Imperial county, a location of significance for Californian agriculture, ships could continue polluting. These findings indicate that transport model predictions commonly employed to justify pollution regulation work well in a world without behavioral modification but also risk significantly overstating the realized impact of regulation.

3. Thus far, we have examined the impact of the fuel standards on the rate of low infant birthweight and community demographics. We found significant improvements in the rate of low infant birthweight. The policy was associated with an 2.2% fall in the rate low birthweight (p<0.001). We also failed to find evidence that the policy treatment predicted trends in infant heath in the years prior to implementation (pre-trends). In a robustness check, we found that the policy was associated with changes in the demographic composition of mothers. This result indicates that a change in the composition of mothers, rather than air quality, contributed to the improvement in infant health associated with the policy. We are still evaluating the salience of the air quality changes from this policy to determine if the demographic change was a result of the policy or a result of an unobserved factor that coincided with the policy.

The Impacts of COVID-19 on the Farm Labor Supply and Farming Decisions in California

  • J. Edward Taylor
  • Bryan Little
  • Sara Neagu-Reed
  • Diane Charlton

The Impacts of Climate Change on Global Grain Production, Accounting for Adaptation

  • Michael Anderson
  • Andrew Hultgren
  • Solomon Hsiang

Abstract

Specific Objectives of the Project:

The project’s objectives were to answer the following research questions:

1. Under a wide range of climate models and GHG policy futures, what will be the geographically distinct impacts of climate change on yields of key agricultural products (maize, soy, rice, wheat, sorghum, and cassava)?

2. What is the role of farmer adaptation to a changing climate, as well as changing incomes, in mitigating the effects of climate change on yields?

3. How much do the costs of farmer adaptation offset any adaptation gains they might realize?

Summary of Results:

Over the time period of the GF grant we estimated the responsiveness of spring and winter wheat to temperature and precipitation shocks, accounting for heterogeneity over local climate (long-run temperature and long-run precipitation), local income, and local access to irrigation. We additionally completed a Monte Carlo uncertainty analysis of the impacts of climate change on yields of six staple crops at global scale, accounting for adaptation: corn, soybean, rice, wheat, cassava, and sorghum. We found that adaptation is at least partially protective for all crops, but global productivity losses ranging from 25-45% percent (point estimates) persist for all crops except rice, for which adaptation is fully protective.

The Effects of a Declining Farm Labor Supply on Fruit and Vegetable Production in California

  • Pierre Mérel
  • Zachariah Rutledge

Abstract

Specific Objectives of the Project
1. To quantify the extent to which decreases in the supply of farm workers affect the quantity of fruit and vegetable crops produced in California.
2. To determine how reductions in the supply of farm workers affects the number of acres of fruits and vegetables that can be harvested in California.
3. To quantify how much farm revenue is lost because of reduced access to farm workers in California.

Project Report/Summary of Results
Recent studies point to a decline in the U.S. farm labor supply driven by demographic and structural changes in Mexico, increased U.S. border security measures, and a decline in the number of farm workers willing to engage in follow-the-crop migration, which has reduced the geographic reach of local farm labor markets. A smaller farm labor supply has the potential to reduce access to safe and healthy produce, increase the nation’s reliance upon foreign producers, and reduce the profitability of U.S. farm operations. In order to examine the extent to which changes in the farm labor supply may affect crop production, we estimate panel regressions using a rich set of production and employment data from California counties.

This study brings together three datasets pertaining respectively to crop production, farm employment, and weather. Our empirical strategy deploys fixed-effects panel regression
models at the crop-county-year level of aggregation, where the regressor of interest measures county-year farm employment during the peak harvest season. The identifying
variation comes from differences across counties in the evolution of employment about smooth county-level trends, net of weather effects. The fact that crop employment, an equilibrium value, is used as the explanatory variable in place of the underlying yet unobserved labor supply variable causes important identification challenges. We use an equilibrium displacement model to gain insight into the bias likely to affect our empirical estimates. Our regression results reveal statistically significant upper bounds for the
effects of labor supply shifts on the production of hand harvested fruit and vegetable (FV) crops, but, as expected, not on that of mechanically-harvested nut or field crops.

Our empirical results indicate that a ten percent decrease in the farm labor supply (in terms of the number of workers willing to supply labor at a given price) causes at most a 4.2% decrease in hand-harvested FV production in the top 10 producing counties, which together produce 86% of the value of all labor-intensive crops in the state. Reduced production is primarily channeled through a decrease in the number of acres harvested (- 2.8%), although we also uncover small yield effects (-1.4%). Impacts on the total value of production appear to be concentrated in the top 5 counties (Monterey, Fresno, Tulare, Kern, and Ventura). There, a ten percent decrease in the farm labor supply causes at most a 5.5% decrease in production value.

Although the bounds for FV production are economically meaningful, they indicate that the impacts of a declining farm labor supply will likely be limited in the foreseeable future. These effects are perhaps best exemplified by focusing on the top 5 producing counties, which produce 67% of the value of all labor-intensive crops in the state. Recent estimates suggest that the U.S. farm labor supply is shrinking by about one percent each year. A decline in the farm labor supply of that magnitude in the top 5 counties could cause a loss of 60,000 tons of hand-harvested FV each year. Under the assumption that the decrease in hand harvested FV production is not replaced by the production of other crops, production value losses of an additional 0.55% per year for the 69 crops we consider in those counties could add up to as much as $3.8 billion, or 3.0% of the total value of production, over the course of a decade. Our analysis also suggests that harvest mechanization could provide an alternative to the use of hand-harvest labor in a time of labor scarcity, provided that technologies are advanced enough to prevent unacceptable damage to fragile FV crops.

The Effectiveness of Reforestation: The Tradeoff between Climate Change Mitigation and Adaptation

  • Dalia Ghanem
  • Daria (Dasha) Ageikina

Abstract

Specific Objectives of the Project:

The initial goal of the project was to assess the optimality of public reforestation projects in the context of both climate change mitigation and adaptation efforts in California and the U.S. We aimed to analyze the tradeoff between the climate mitigation value of afforestation and its cost in terms of wildfire risks. During the project, the objective became more specific. The focus shifted to the CARB’s Compliance Offset Program U.S. Forest Projects. The main final objective of the paper was to investigate whether the program’s design suffers from adverse selection that could lead to the program’s inefficiency.

Summary of Results:

In the program under consideration, an individual or an organization can get carbon offsets for engaging in one of the three activities: reforestation, improved forest management, or avoided conversion of forested land to other uses (such as residential areas or agricultural land). The main aim for each of them is to achieve a sustainable long-term growth of forests and maintain the stocking of trees at the project's designated land at a high level. The Compliance Offset Program does consider that wildfires might affect the forest projects and hence reverse the carbon sequestration. It treats the wildfire risk just like any other risk that can interrupt the project. To insure against such risks, the Air Resources Board maintains a Forest Buffer Account. Each project operator must contribute a part of their awarded carbon offsets to the Account. If an unexpected wildfire burns down the trees in the project area, the project operator will not lose the already awarded credits. The Account is insurance against such cases for both project operators and for the Program itself.

Our concern about this insurance-like buffer account was the potential adverse selection due to the essentially flat wildfire risk suggested by the program. We created a simple economic model of risk-neutral agents deciding whether to participate in the program. The model predicts that the potential forest projects with higher wildfire risks might be more likely to opt into the program because it provides partial insurance against wildfires. This adverse selection of the projects would make the Compliance Offset Program inefficient. First, the expected carbon sequestered, or the number of offsets supplied to the Cap-and-Trade market might not be optimal. For instance, fewer projects might participate, making carbon sequestration too low. In health insurance, it would correspond to a case when the equilibrium premium is too high, resulting in the lack of low-risk buyers. Second, the overall program will not be cost-effective because it could use more low-risk projects to sequester the same amount of carbon. Third, if high-risk projects increase the wildfire risks of the areas around them even more, it might put communities in danger and create other welfare effects.

To see empirically whether adverse selection is present in the program, we used open access data on the U.S. Offset projects, available on the ARB's website. At the time of the empirical analysis, 147 projects participated, but the program is ongoing, and more projects join each year. In our analysis, we used 79 projects because of the access to the GIS data for the other 68 of them. We compared the estimated fire risks of the projects' locations to the fire risks in the comparison group of other eligible lands. The data on fire risks comes from the USDA Forest Service.

We could not find any statistically significant adverse selection as of now. However, we did not fully finish the analysis yet, and the project is still in progress. Possibly, we did not detect adverse selection due to a small sample of the projects. We still need to estimate the locations of the remaining 68 projects. The total acreage of all 147 projects should be around 10 million acres. The second factor might be a comparison group of eligible lands. We are yet to refine the comparison group and exclude all potential lands that have a low chance of participation regardless of the fire risk of the project.

Recent Water Quality Policy and Agriculture

  • Joseph Shapiro

Abstract

Specific Objectives of the Project:
Re-examine the economic logic that the US Environmental Protection Agency used to justify the Navigable Waters Protection Rule; use machine learning and artificial intelligence algorithms to determine the scope of these water quality regulations.

Project Report/Summary of Results:
The first component resulted in a published publicly available report that received media coverage. It also resulted in a peer-reviewed journal article in Science.

The second component trailed a number of graduate students, and resulted in a preliminary set of results and series of meetings with senior staff at the US Environmental Protection Agency to convey the approach and initial results. This is an ongoing project that will involve research and policymaker outreach over multiple years as the EPA revises the Clean Water Act.

Quantifying Spatially Resolved Agricultural Runoff Based Nonpoint Source Pollution in California Waterways

  • J. Keith Gilless
  • Peiley Lau

Predicting Demand for Plant-Based Meat

  • Meredith Fowlie
  • Hal Giuliani Gordon

Pasture, Rangeland, and Forage Insurance Program: Risk Management Implications for California Ranchers

  • Tina Saitone
  • James Keeler

Abstract

Specific Objectives of the Project:
The specific objectives of this project are twofold: i) estimate the basis risk (i.e., residual risk remaining after insurance) associated with the U.S. Department of Agriculture (USDA) Risk Management Agency’s (RMA) Pasture, Rangeland, and Forage (PRF) Insurance; and ii) determine the degree to which PRF Insurance mitigates forage-production-related risk for ranchers in California based on varying levels of risk aversion.

Summary of Results:
Agricultural producers who are reliant upon rangelands and pasturelands are some of the most vulnerable to weather-related risk given their dependence on climate-sensitive resources. Index-based insurance products, like the Pasture, Rangeland, and Forage Insurance Program, are considered to be an adaptation strategy for mitigating climatic risks. Given that indices are imperfect predictors of losses, residual (basis) risk persists. This study quantifies basis risk and assesses insurance contract quality for nearly 63 million acres of rangelands in California. Basis risk can be summarized by considering false negative probabilities – the probability that an insured producer suffers a loss without receiving an indemnity payment. On California rangelands the false negative probabilities associated with one (both) of insured time intervals failing to indemnify a loss range from 31% - 46% (14% - 25%). When indemnities were paid, in 36% of the cases the payments are not sufficient to compensate for forage-related losses; the average shortfall in indemnity-related compensation ranged from $1.74/acre to $2.73/acre depending upon the location and underlying value of forage.

Land Use and Water Impacts of Cannabis Cultivation

  • Katrina Jessoe
  • Michele Baggio

Abstract

Specific Objectives of the Project
The objectives of this proposal are to empirically estimate the effect of the legalization of cannabis cultivation on agricultural labor, agricultural land prices, agricultural land use and water quality in California.

Summary of Results
Funding from the Giannini Foundation allowed us to begin to assemble a panel dataset comprised of satellite imagery data at a 30mx30m for agricultural land parcels in Humboldt and Mendocino counties spanning the years 1995 to 2020. We also constructed data on the cannabis laws in each county of California, including activities that are permitted and the date that these laws took effect. In our next stage of research, we will designate water bodies, forested land, roads and cannabis using a machine learning approach.

Investigating COVID-19 Pandemic Effects in California’s Urban/Rural (Metro/ Micro Central and Non Central) Counties’ Mobility and Businesses

  • Sofia Villas-Boas
  • James Sears

Impact of the U.S.-China Trade War on California Agriculture

  • Colin Carter
  • Sandro Steinbach
  • Jiayi (Carol) Dong

Abstract

Specific Objectives of the Project:
In 2018 the U.S. government started a trade war with China and other trading partners. In response to import tariffs imposed by the U.S., China and other countries responded with retaliatory import tariffs, explicitly targeting U.S. agricultural exports. This study investigated the consequences of retaliatory tariffs on the agricultural and food industry in California. We had two specific objectives. First, we measured the ‘net’ impact of the retaliatory import tariffs on California’s agricultural and food exports. Second, we measured the extent to which U.S. federal trade-war subsidies offset producer losses arising from the retaliatory tariffs.

Project Report/Summary of Results:
The U.S. substantially increased a number of import tariffs in 2018, precipitating a trade war that was very costly to U.S. agriculture, given its dependence on international trade. The losses arose because a number of trading partners retaliated with import tariffs targeted at U.S. agricultural exports. The U.S. government then created a Market Facilitation Pro-gram (MFP) to compensate U.S. farmers for trade war losses. We have found that except for cotton and rice, California farmers were not made whole by the MFP payments. California’s producers of tree nuts, dairy, and processed fruits and vegetables were the biggest losers.
Our research concludes that the U.S. government under-estimated the overall economic losses incurred by California’s agricultural and food producers due to the 2018 trade war. While the MFP program overcompensated some farmers, others faced substantial trade-war losses that outweighed MFP payments. Particularly export-oriented food processors were heavily affected by retaliatory tariffs but received no compensation from the U.S. government. The unequal treatment of agricultural and food producers impacted by the 2018 trade war is a pattern also observed in other states. However, these inequalities are more pronounced in California than in any other state. California’s producers focus on high value-added products and have a significant stake in reducing trade barriers everywhere and in particular in China. We believe the MFP payments may have jeopardized international trade arrangements because the excessive payments violated U.S. farm subsidy commitments to the World Trade Organization (WTO), and this could be challenged at the WTO. This means the effects of the trade war may drag on.

Impact of SGMA on Crop Mix in California

  • Bruce Babcock
  • Dat Tran

Abstract

Specific Objectives of the Project:
Develop appropriate datasets and modeling framework to be used to estimate SGMA impacts.
Develop the modeling capability to simulate changes in crop mix in the San Joaquin Valley and to carry out the simulations.

Project Report/Summary of Results:
We developed a new approach for estimating supply elasticities for California tree crops. The purpose was to obtain reliable elasticities to populate PMP models of water basins in the San Joaquin Valley. Supply elasticities are estimated by regressing observed lagged acreage changes on estimated demand shifts and then converting the resulting regression coefficients into a price elasticity using the assumption of rational expectations. Estimated demand shifts can be estimated from observed prices and quantities if demand elasticities are known. We estimated possible ranges in demand elasticities from observed, unique, events that shifted demand. The supportable range of annual demand elasticities and the most likely elasticities are shown in Table 1 for important California tree crops.

Table 1. Estimated Elasticities of Demand for Citrus and Tree Nut Crops

CropLikely RangeMost Likely Elasticity
Almonds[-0.15, -0.45]-0.40
Lemons[-0.20, -0.60]-0.40
Mandarins[-0.30, -0.70]-0.50
Fresh Navel Oranges[-0.30, -0.70]-0.50
Pistachios[-0.30, -0.70]-0.50
Walnuts[-0.10, -0.30]-0.20

California acreage and supply elasticity estimates for almonds, mandarins, pistachios, and walnuts are shown in Table 2. Estimated U.S. corn and soybean elasticities are also shown to facilitate a comparison of estimates made using our new approach and estimates made using more traditional approaches.

Table 2. Calculation of Supply Elasticity from Acreage Response and Demand Elasticity (1980–2019)

Crop

Elasticity of
Acreage to Demand

Demand ElasticitySupply Elasticity
Corn0.305-0.35 & -0.250.154 & 0.110
Soybeans         0.281-0.350.137
Almonds0.540-0.400.470
Mandarins0.611-0.500.785
Pistachios0.733-0.501.373
Walnuts0.541-0.200.236

Evaluating Optimal and Second-Best Nitrogen Regulations in California

  • James Sallee
  • Connor Jackson

Abstract

Specific Objectives of the Project
The goal of this project is to analyze the efficacy, efficiency and equity of plausible regulatory policies that seek to reduce nitrogen emissions from agricultural soils.

Summary of Results
The research team used the funds to develop new understandings and create a research agenda around the use of biogeochemical models to perform policy analysis and an emissions inventory related to greenhouse gas emissions from synthetic fertilizer use in croplands.

We are actively collaborating with a social scientist at UC Berkeley to build a new tool based on the biogeochemical model, DayCent. We have (after some delay) gotten full approval to access the necessary survey data from the USDA. We have vetted our research questions with several experts. We are now building the computer code that will enable us to create the tool that will serve as the basis for our policy analysis and simulation. This ongoing work is being supported by a new Giannini grant, and we have identified several extramural grants to provide additional support.

In the meantime, we have some preliminary conclusions from our research pertaining to the magnitude of the greenhouse gas emissions costs from the use of fertilizers, which we are summarizing in a piece to be sent to ARE update this fall.

Estimation of Demand and Price Aggregators: Application to US and California Household Scanner Data

  • Thibault Fally

Abstract

Specific Objectives of the Project
1. Combine detailed data on nutrients and food expenditure (Nielsen, FCD-USDA and Label insight).
2. Model and estimate the functional form of demand with price aggregators.
3. Examine implications for price elasticities and substitution effects.
4. Publish the final article in a top refereed journal, as well as a summary in the ARE Update.

Project Report/Summary of Results
We have cleaned and matched three main sources of data: Nielsen Home scanner data, FDC-USDA data, and Label Insight data. The Nielsen data provide information on shopping trips and items purchased at the barcode and household level. FDC-USDA data provide information on ingredients and other product characteristic at the barcode level. Label Insight data covers similar information for a larger availability of barcodes. Merging the three data sources has been challenging due to non-conformity of barcode definitions (e.g. number of digits, presence of check digit) but we managed to cover more than 85% of household food expenditures for some of the years (excluding generic store brands). We are still working on constructing price aggregators and estimating demand using these aggregators.

Effects of Federal Milk Marketing Orders on U.S. Imports and Exports of Dairy Products

  • Daniel A. Sumner
  • Tristan Hanon

Abstract

Specific Objectives of the Project
Production of a dissertation investigating the effects of the Federal Milk Marketing Orders on international trade in dairy products.

Summary of Results
This project is investigating the effects of the U.S. Federal Milk Marketing Orders (FMMOs) on trade in dairy products. The FMMOs implement price discrimination in the beverage milk market and redistribute gains to milk producers through blend pricing. Higher returns for dairy farmers increase the quantity of milk supplied to the market, while high prices in the beverage milk market reduce quantity demanded, leading to increased quantity in the dairy product manufacturing sector. Over the past two decades the U.S. has become a net exporter of dairy products, and this project investigates the role played by the marketing orders in that transition.

The research funded by this grant focused on the movement of farm milk and trade in dairy products within the United States. The marketing orders set regional prices for beverage milk, influencing the price received by milk producers in that region. This paper uses recent developments in the trade literature to model the process by which milk is delivered to different regions across the U.S and how dairy products are distributed to buyers. The dairy product market will include domestic demand from across the U.S. as well as demand facing the U.S. from the international market. We use simulations to compare a baseline scenario with the FMMOs in play to counterfactual scenarios that remove the regional price discrimination and revenue pooling.

The model of interstate trade will be supported by a second paper focused on empirical estimation of dairy product demand. Whether U.S. dairy policies have an impact on the international dairy product market depends on whether the U.S. faces a downward sloping world demand curve for tradable dairy products. This paper will use an econometric model of U.S. net exports and exogenous shifts in marketing order policies to estimates the world demand curves for tradable dairy products.

This research will be extended to an international scope to investigate the impacts of FMMO policies on international trade more broadly. While the model of interstate trade allows dairy product manufacturers to export products to the international market, the impacts of the FMMOs on that market are not explicitly modeled. The international trade model with consider U.S. imports and exports in the context of the global market for dairy products. This paper will focus on the U.S. shift from net importer to net exporter of dairy products and the extent to which changes in FMMO policies caused that shift.

Alongside the main goals of this project, it was a natural extension to study the impacts of the COVID-19 pandemic on the dairy industry. In the early stages of the pandemic school and restaurant closures impacted demand for dairy products, and milk producers reacted to falling prices by reducing production. Milk and dairy product prices were volatile throughout 2020. We initially focused on explaining these impacts in the western states for a publication in the Western Economic Forum. We outlined the government response to the pandemic and payments received by the dairy industry in 2020. This study was expanded to use forecasting methods to evaluate the magnitude of the impacts relative to historical data. There are outstanding questions to investigate, such as the impact of government purchasing programs on the market for dairy products, so we are developing a follow-up project to study these questions.

Economics Impact of the November 2018 Romaine E. coli Outbreak: Lessons for California Moving Forward

  • Kristin Kiesel
  • Ashley Spalding

Abstract

Specific Objectives of Project
On November 20, 2018, health agencies in the U.S. and Canada issued a food safety alert, advising consumers, retailers, and restaurants not to eat, serve, or sell any romaine lettuce or mixed salads containing romaine due E. coli. The Leafy Greens Marketing Agreement (LGMA) and other industry produce associations joined in this call on the same day, urging an industry-wide voluntary withdrawal of all romaine lettuce in marketing channels and inventory. On November 26, the United States Centers for Disease Control (CDC) and Food and Drug Administration (FDA) updated warnings to specify avoidance of romaine lettuce harvested from central and northern California. On January 9, 2019, the CDC declared the outbreak over, and Adam Bros. Inc. farm in Santa Barbara County was identified as the source of the outbreak.

Food-safety issues capture the attention of the media and consumers. Regulators face the challenge of balancing human health and welfare against the economic consequences of alerts and recalls. While farmers, handlers, food-service firms and retailers are all affected economically by a food-safety incident, the magnitude of financial losses and their determinants and distribution have been rarely studied over the entire supply chain. We use a unique combination of public and proprietary datasets to estimate the direct and indirect effects of this highly publicized outbreak on sales of romaine as well as other leafy greens for all of these supply chain actors. We further provide an estimate of the overall social welfare loss and discuss the magnitude of economic losses, incentives faced by supply chain actors, and implications for government regulation.

Project Report/Summary of Results
We decomposed damages into those associated with changes in prices for product that was sold during the outbreak and its aftermath, and those associated with romaine that could not be harvested, processed, and sold due to the outbreak and its aftermath. USDA, Agricultural Marketing Service data on farmgate prices, proprietary wholesale price data for the food service and retail marketing chains, and Nielsen retail scanner data allowed us to estimate changes in prices and quantities along the supply chain associated with the outbreak and its aftermath. We then use these results to estimate romaine prices and quantities in the ``but-for world'' that would have unfolded had the incident not occurred. The comparison of prices and quantities in the real-world and but-for-world scenarios for growers, handlers, and retailers reveal who benefited and who lost as a consequence of the incident. Recent changes in the structure of the produce industry and data limitations led to an estimation of damages under several scenarios and whenever possible, we consider additional losses or offsetting gains in other leafy greens categories.

For both romaine leaf and hearts, our regression results indicate spot-market prices were higher through the first six weeks of the outbreak than in the “but-for world,” indicating growers with romaine that was safe to sell during the outbreak was sold at a substantial premium. Price effects were negative during the remainder of the study period for romaine hearts and through week 1 of the post-outbreak period for romaine leaf, potentially due to decreases in demand for romaine and/or increases in the supply of safe romaine as warnings were removed from various growing regions. Further regressions found positive effects for contract prices paid to growers.

Regressions estimating quantity and price effects for food service wholesalers indicate that, relative to the “but-for world,” there were large decreases in the quantity of romaine sold to food service providers in the first week of the outbreak followed by smaller decreases through week 10 of the post-outbreak period. Similar to growers, wholesalers were initially able to capture a premium for safe romaine, but premiums were both smaller and more short-lived than for growers. Average prices paid to wholesalers increased weeks 2 through 4 of the outbreak by 24% to 41%, followed by moderate decreases in price through to the end of the post-outbreak period.

On the retail side, we estimated price effects for both wholesalers and retailers and quantity effects for retailers. For wholesalers, there is a negative price shock in week 2 of the outbreak in all categories followed by nonexistent or small and positive price increases relative to a no-outbreak scenario. We found modest or nonexistent retail price effects, with the largest effects being for romaine hearts. This is consistent with the fact that retail base prices are relatively stable in the short term. We find decreases in retail sales relative to the “but-for world” associated with nearly every week of the study period. The decreases are most pronounced in week 2 of the outbreak. While decreases in sales associated with the early weeks of the outbreak can be partially attributed to retailers removing unsafe product from shelves, the persistent decreases in sales throughout the post-outbreak period indicate consumers shifted consumption away from products containing romaine.

Based on the econometric results, we estimated that total romaine industry damages range from $52.7 million (grower contact prices vary, and buyers bear all pipeline damages) to $177.1 million (grower contract prices are fixed, and handlers bear all pipeline damages). Based on information regarding the extent of pipeline damage-sharing in each channel and contract price provisions, our most representative estimate of damages is $105.3 million. Cross-commodity effects for iceberg lettuce provided some offsetting gains. Food service firms can change the composition of their orders, like consumers in the store, but unlike retailers ordering bagged salad mixes. Iceberg lettuce producers obtained an estimated $11.5 million in benefits, likely due to such substitutions.

In addition to industry losses, there were losses sustained elsewhere in the economy. Particularly, we considered the effect of the outbreak on the welfare of consumers of romaine and suppliers of inputs to the romaine industry. Our estimated additional social losses range from $48.5 million to $59.9 million depending on the elasticity of demand for romaine lettuce.

In summary, our analysis provides two striking insights. First, the greatest losses occur in the retail marketing channel at the handler-retailer level of exchange, with an overwhelming share of losses in the retail channel. Second, growers gain from the food-safety incident, netting $4.3 million in our most representative estimate. These imply that as long as LGMA membership is voluntary and some handlers choose not to join, a subset of industry players are likely to be disproportionately imposing costs on the entire industry. Second, growers, who are in almost all cases the source of a food-safety incident, do not have a direct financial incentive to improve their practices to reduce the chance of an incident.

Do Eucalyptus Trees Increase Wildfire Spread and Threaten California Agriculturalists?

  • Maximilian Auffhammer
  • George Pardee Jr.

Abstract

Specific Objectives of the Project:
(1) Estimate whether eucalyptus trees increase wildfire spread relative to other land use types, including other forest, cropland, or rangeland.
(2) Assess wildfire threat to California agriculturalists from eucalyptus trees

Project Report/Summary of Results: We exploit exogenous variation in wind direction to estimate whether eucalyptus trees increase fire spread. Contrary to popular belief, we find no evidence that eucalyptus trees increase total burn area relative to other forest types. Using the full sample of 188,926 fires in California between 1992 and 2015, we estimate that eucalyptus trees decrease total burn area by 8.8 percentage points. When we restrict the sample to the 7% of fires that burn more than 10 acres (0.04 km2), the effect of eucalyptus is indistinguishable from zero (0.8 percentage point decrease with a standard error of 0.6 percentage points). We conclude that California agriculturalists face little fire threat from eucalyptus trees. Removing eucalyptus trees does not appear to be an effective strategy for mitigating the threat of wildfires in California.

Do Beekeepers Value Cover Crop Use in Almond Production?

  • Brittney Goodrich
  • Jerrod Penn

Abstract

Specific Objectives of the Project
Cover crops have been proposed as a strategy to improve soil health in many crops, conserving water and mitigating effects of climate change (Pathak et al., 2018). In almonds, it has been suggested that bee-friendly cover crops could improve the health of honey bee colonies, adding another potential benefit to this conservation practice. Despite the numerous benefits of cover crops in almonds, less than 6% of growers use cover crop practices (Almond Board of California, 2015). Concerns regarding the economic return from cover crops are one of the top reasons for low cover crop adoption in the United States (CTIC and SARE, 2017). Because honey bee nutrition may be improved by cover crops, the use of cover crops may also provide an economic return to the beekeeper. It has been assumed that beekeepers will be willing to accept a discounted almond pollination fee if cover crops are grown in an almond orchard (DeVincentis et al., 2020). The objective of this project is to determine the size of discount beekeepers would be willing to accept for different cover crop mixes in order to facilitate wider adoption of cover crops in almonds.

Summary of Results
Using an online survey and a discrete choice experiment, we investigate and monetize the value of cover crops and other pollination contract components to commercial beekeepers who annually participate in almond pollination services. The analyzed sample of 81 commercial beekeepers represents approximately 19% of hives demanded for 2020-21 season.

We find that beekeepers value certain cover crop mixes, additional pesticide protections and up-front payment in their pollination agreements. Overwhelmingly beekeepers were willing to accept lower pollination fees for cover crop mixes that contain Brassica plants (e.g., mustards and canola) that bloom prior to and during almond bloom and were not willing to accept lower fees for a cover crop mix composed of legumes (e.g., clovers) that would not begin blooming until toward the end or after almond bloom.

Pesticide protection had the highest economic value to beekeepers: they were willing to give up $8 per colony in additional revenue to have a guarantee that almond growers would not tank mix pesticides and only apply fungicides at night when bees are not flying. For reference, the average pollination fee beekeepers reported receiving in 2021 was $189 per colony. Beekeepers were willing to give up $6.60 in revenue per colony if the grower plants the Brassica cover crop mix, and $5.60 per colony if the grower plants a cover crop mix that contains multiple species of brassicas, legumes and grains. If the beekeeper was paid 40% of their total pollination fee in advance of almond bloom, they were willing to give up $3.50 per colony in revenue. Assuming the preferred contract is adopted, beekeepers would be willing to accept a pollination fee per colony that is $18 lower than the standard agreement without those options, constituting a 10 percent reduction in the 2021 average fee reported by beekeepers. Using the industry standard of two hives per acre, this translates to a discount to the grower of $36 per acre.

Our findings show that there is potential for almond growers and beekeepers to work together to make mutually beneficial improvements in their almond pollination contracts. Importantly, two key improvements relate to additional pesticide restrictions and cover crops, practices likely to improve honey bee colony health and potentially lower abnormally high colony loss rates beekeepers have experienced over the last decade. High colony loss rates can severely impact beekeeping revenues from almond pollination, harming the economic sustainability of the U.S. commercial beekeeping industry. Thus, improved colony health will lead to a more stable supply of pollination services for almonds and other crops that bloom after almonds.

Distribution of Federal Support to U.S. Farmers

  • Ethan A. Ligon

Demand for Plant-Based Products: Implications for California Agriculture and Agribusiness

  • Richard Sexton
  • Stamatina Kotsakou

Cooperative and Market Approaches to Regional Salinity Nonpoint Pollution Control: Application to the San Joaquin Valley (SJV), California

  • Ariel Dinar
  • Nigel Quinn

California’s Organic Agricultural Production

  • Rachael Goodhue
  • Hanlin Wei

Abstract

Specific Objectives of the Project:
• Complete a report that presents statistics on California’s organic agricultural production and the structure of the organic industry at the farm level using CDFA organic registry data
• Analyze the evolution of the industry’s structure utilizing the registry data and other data on organic acreage in California

Project Report/Summary of Results:
California’s organic agricultural production generated over $3 billion in farmgate sales in 2016, the most recent year in which detailed production information was available. Milk, strawberries, carrots, winegrapes and table grapes had the highest sales. Over 3,100 organic operations registered with the state. Over half of these operations produced fruit and nut crops. A majority of organic operations are in coastal regions. Organic operations have grown larger over time.

Assessing the Feasibility of GM Labeling: The Case of Bt Eggplant in Bangladesh

  • David Zilberman
  • A Ahsanuzzaman
  • Carly Trachtman

Assessing Measurement Error in Remotely Sensed Land Use Data for Economic Applications

  • Ellen M. Bruno

Abstract

Specific Objectives of the Project:
The goal of this project was to investigate the implications of measurement error in remotely sensed land-use data for accurately pinning down parameters in economic analyses relevant to California agriculture. Data products that identify land use and crop categories from satellite imagery are commonly used in research and planning models, but they inevitably contain classification errors. To understand the implications of remote-sensing land use products for accurately pinning down economic parameters, I systematically compared different land use data products for California and evaluated the magnitude of the measurement error relative to detailed field surveys.

Summary of Results:
Measurement error in derived data products is known to pose challenges for inference. When the error is non-classical, which is often the case with satellite data, then it can introduce bias in parameters that are otherwise well-identified. Knowledge about the nature of the error becomes important for credible inference. To better understand the implications of remote-sensing land-use products for accurately pinning down economic parameters, this paper first assesses the accuracy of two different remotely sensed land-use data products with California coverage by comparing them against field surveys from an agricultural region on the California coast. I then systematically compare the two across the state, a geography that features a diversity of crops unlike the rest of the United States. I find that overall accuracy varies widely between the two datasets - 4.7% to 5.9% in one and 77.8% to 87.25% in the other, depending on the year. This validation exercise illustrates the nature and magnitude of the measurement error in California, with important implications for policy.

A New Method to Jointly Estimate Yield Response and Crop Choice

  • Mark Agerton
  • Matthieu Stigler

Air Pollution Exposure and Agricultural Worker Productivity

  • Tim Beatty
  • Alexandra Hill

Abstract

Specific Objectives of the Project:

  • Distribute Fitbit activity trackers to workers on 3 strawberry farms in California.
  • Construct measures of temperature and pollution from gridded temperature and satellite data.
  • Merge the activity tracking and pollution data with hourly productivity of strawberry harvesters to examine the immediate, lagged, and cumulative effects of pollution on both activity and productivity.
  • Obtain measures of activity and caloric exertion for agricultural laborers in California.

Summary of Results:
This project was significantly impacted by the COVID-19 pandemic. We were unable to access our field sites during in 2020 and 2021, which shifted the deployment of our data collection exercise until July 2022. During the grant period we acquired and developed all materials necessary to go to the field.
Accomplishments to date:

  • IRB approval and all consent materials and survey instruments in both English and Spanish.
  • Fitbit movement trackers were acquired and Fitibase software to manage real time data collection as well as sending reminders to participants was piloted.
  • Code to create pollution and temperature measures during the planned intervention was obtained.

Short-Term Impact of the Trade War on U.S. Soybean Futures Prices and Spreads

  • Jeffrey Perloff
  • Shuo Yu

Abstract

Specific Objectives of the Project
We quantified the short-term impact of tariffs and the corresponding relief payments on soybean futures prices.

Summary of Results
Due to the 2018–2019 trade wars, U.S. agricultural and food products have suffered eight waves of retaliatory tariffs from Canada, China, Mexico, the EU, and Turkey. The COVID-19 pandemic further isolated the economies in 2020. We studied the futures market effects of these tariffs on various U.S. crops, particularly soybeans.

We estimated reduced-form regressions of real futures prices or spreads on retaliatory tariffs and a set of event indicators to quantify the short-term impact of retaliatory tariffs and the corresponding relief payments on soybean prices. We controlled for the COVID-19 epidemic, related U.S. government direct payments, weather shocks, and information from USDA reports. Our analysis used price data from the Barchart website, tariff data from official documents published by the tax bureaus of each country and the World Trade Organization (WTO) Tariff Download Facility (TDF) database, USDA World Agriculture Supply and Demand Estimation Reports, and weather data from the Google earth engine from 2004 to 2020.

We found that a 25% increase in a retaliatory tariff, holding projections and weather variables constant, decreased the real futures price by 14.25% while the tariff was in place. The effect on the futures price spread grew with the length of the spread. It reached its peak at a one-year spread. Thus, the price pass-through of the tariff increase was large, and farmers suffered from the retaliatory tariff in the short run.