Search

Plant-based milk alternatives have gained significant attention in recent years, transitioning from a niche market to the mainstream. This dissertation studies the economic impacts of the introduction and wide availability of plant-based milk alternatives on prices and quantities of cow’s milk products and the implications for price policy for farm milk.Chapter 2 examines the implications of the introduction of refrigerated almond milk for the price and quantity of fluid cow’s milk and soymilk products sold in retail stores. The entry of almond milk—accounting for about 70% of the quantity share in the plant-based milk market in 2020—into refrigerated shelves was a key to the substantial growth of plant-based milk products in the 2010s. This chapter uses the staggered rollout of refrigerated almond milk across retail stores, mostly between 2008 and 2010, to assess its impact. Empirical results, using recently developed econometric methods, show that soymilk experienced a short-run 6% quantity fall, and organic cow’s milk and lactose-free cow’s milk saw 3% declines, whereas conventional cow’s milk demand remained largely unaffected. These quantity effects align with expectations that products that are expected to be more substitutable for almond milk experienced greater reductions in quantity. The estimated effects indicate that the annual per capita quantity of cow’s milk and soymilk decreased by 0.055 to 0.086 gallons. During the 2008–2010 period, the annual per capita quantity of refrigerated almond milk increased by 0.152 gallons, suggesting refrigerated almond milk expanded the overall milk market rather than merely cannibalizing demand for other milk types. Price declines were less than 1% for all product categories.Chapter 3 explores the extent to which recent declines in consumption of retail fluid cow’s milk products are attributable to the availability of plant-based milk. Chapter 3 presents estimates of discrete-choice demands for many cow’s milk and plant-based milk products. The econometric estimation uses household purchase data and matches it with store-level scanner data to represent the households’ choice sets. The supply side is modeled as an oligopolistic market where processors follow Bertrand-Nash price competition. The estimated demand parameters generate own- and cross-price elasticities of demand for plant-based milk and conventional, lactose-free, and organic cow’s milk. With all these models and estimates, the chapter uses counterfactual simulations to find that the removal of all plant-based milk products from the choice set causes a 23% increase in the retail quantity of organic cow’s milk, 16% for lactose-free cow’s milk and 11% for conventional cow’s milk. Over the 2006 to 2020 period, the availability of plant-based milk products accounted for 38% of the historical decline in U.S. cow’s milk consumption.Chapter 4 explores the implications of the farm milk price policy. By using the demand parameters and the marginal costs of processing cow’s milk and plant-based milk estimated in Chapter 3, this chapter conducts two milk price policy simulations: (1) an increase in the price of farm milk used for fluid products, as recently recommended by the USDA and (2) the removal of the longstanding above-market farm milk pricing regulation. Results show that increasing the price differentials would raise the price of conventional cow’s milk by about 4% and reduce the retail quantity by about 3.6%, placing further pressure on the already declining consumption of fluid cow’s milk. However, changes in the relative prices between cow’s milk and plant-based milk, induced by the USDA price regulations, are not the primary factor for the declining consumption nor the key to revitalizing the demand.

In this dissertation, I explore and empirically evaluate the management of an endemic disease in Chile's salmon aquaculture industry. Chile is the world's second-largest producer of farmed salmon and the largest supplier of salmon to the United States. However, the industry has struggled to manage endemic, transmissible diseases that threaten industry productivity. This has driven the industry to utilize antibiotics at a rate that has raised concern among public health and environmental communities. Given the ongoing challenges from endemic pathogens, what avenues are available for balancing disease management with antibiotic stewardship? One way to address the spread of pathogens is through coordinated action between farms. In the first chapter, I evaluate a spatially explicit disease management program that forces all farm sites within the same neighborhood to coordinate their production activities. Theory suggests that this system will be most effective when transmission between neighborhoods is low because it reduces the likelihood of immediate re-infection at the start of the coordinated production cycle. I evaluate the extent to which pathogens spread between neighborhoods, exploiting exogenous variation in the timing of production cycles induced by the disease management policy. I do not find any evidence of spillover between neighborhoods, suggesting that the spatial scale of the policy is appropriately matched to the spatial scale of transmission. To account for the possibility of a behavioral response that could mitigate observed disease prevalence, I also test for changes in the propensity and intensity of antibiotic use that might be caused by the variation in pathogen pressure. However, I find no evidence of such effects. In the second chapter, I turn toward the private incentives for disease control, specifically antibiotic use. The incentive to apply antibiotics is determined by its effectiveness at reducing losses from disease. To simulate counterfactual disease control policies, it is therefore necessary to accurately estimate the effectiveness of antibiotic treatments in a farm setting. However, several econometric challenges are associated with measuring the effectiveness of treatment using observational data. Using an epidemiological model with endogenous antibiotic applications, I illustrate how self-selection into treatment adds bias to an empirical estimate of a structural parameter critical for counterfactual simulation of disease dynamics. This bias is driven by the behavioral feedback between treatment and stochastic features in the epidemiological model that are unobserved by the econometrician. When producers self-select into treatment based on these unobserved features, conventional models tend to underestimate treatment effectiveness. I illustrate an alternative estimator based on the control function approach and conduct a Monte Carlo experiment to illustrate its efficacy. I then apply the estimator to data from the Chilean salmon farming industry to illustrate how the estimator can be used in practice. In the final chapter, I simulate the impacts of targeted reductions to antibiotic use to explore the tradeoffs between disease management and antibiotic stewardship. To do this, I solve for the dynamically optimal antibiotic treatment schedule in the presence of disease transmission between individuals on a farm and between farms. To capture the effect of the neighborhood coordination policy, I parameterize the disease pressure from other farms in a time-varying manner consistent with coordinated production cycles. I then simulate the impacts of various antibiotic reduction policies that feature varying levels of effectiveness and expected implementation costs. Each of the restrictions causes a non-uniform shift in the timing of treatment in the production cycle, an effect that is ultimately consequential for the disease-related externality. I find that the most cost-effective instruments for private individuals also tend to generate the largest externalities.Each chapter is supported by data obtained from the Servicio Nacional de Pesca y Acuicultura (SERNAPESCA), the national regulatory authority for Chile's aquaculture industry. These data are collected as part of a mandatory reporting requirement and provide georeferenced, weekly observations on the production status and veterinary health of all of the industry's fish farms. Critically, these data also include prescriptions for antibiotics applied for a wide range of purposes, including the treatment of Salmonid Rickettsial Syndrome (SRS), which is caused by the endemic pathogen \textit{Piscirickettsia salmonis}. Although these data have been used in past epidemiological studies, this dissertation is the first to utilize these data for economic analysis. In some cases, I pair this database with supplementary data, drawing upon publicly available information on policy borders and coastlines that are central to the empirical investigation in the first chapter.

Rice production in Cambodia faces increasing challenges due to climate variability, with frequent droughts and floods threatening yields and exacerbating food insecurity. This thesis investigates the feasibility of introducing rainfall-based index insurance as a risk management tool for rice producers in Battambang, Cambodia. The study evaluates the potential welfare benefits of six different index insurance contracts using the Relative Insurance Benefit (RIB) methodology, which compares the economic benefits of index insurance to those under perfect yield insurance and no insurance scenarios. Using CHIRPS rainfall data and yield data from a recall survey, resulting low RIB measures are explained based on variability in rice yields attributable to rainfall, the relationship between self-reported weather experiences to those detected by the index insurance contracts, and how indemnity events depict the basis risk involved in these products. Drawing from focus group discussions and key stakeholder interviews, the study considers additional feasibility factors such as farmer access to information and the role of trust in the agri-insurance sector of Cambodia. The findings suggest that while index insurance offers potential benefits to rice producers, significant challenges remain, particularly when a high quality, rainfall-based index insurance contract that improves farmer welfare is the end goal. Recommendations are provided to guide future efforts in developing and scaling up index insurance in Cambodia, with an emphasis on improving the accuracy of rainfall-based indices and enhancing farmers’ trust in these products.

Three promotional branches have supported the second generation of plant-based meat, i.e., of the products that mimic the texture, the appearance, and the flavor of animal meat: protection of animal welfare, of the environment, and of consumers’ health through the reduction of animal meat consumption. The goal of this study was to understand whether consumers view plant-based meat as a way to reduce meat consumption and, in turn, benefit their health and the environment. The present study addresses this question using a dataset that consists of house- holds’ protein purchases over time, combined with household demographic and health information. The data contain detailed information on 127,606 U.S. households’ meat purchases, along with their demographic and medical information, from 2012 to 2022. Since not every household in the panel responded to the health survey, a separate analysis was conducted for the households which provided this information. Two econometric approaches are used in this study: a double-hurdle model and an Almost Ideal Demand System for proteins with a censored regression. The first approach breaks a household’s decision to consume a product into two processes (“hurdles”): the decision to participate, and, conditional on participating, the decision of how much to consume. The second model sheds light on the substitution patterns between the plant- based meat and the animal proteins. Results from this study show a clear upward trend on the market availability of plant-based alternatives. However, even in the most recent years, where the sales of these products have reached their peak, their share in stores is less than 5% of the total meat products and their price is consistently the highest of all proteins throughout years. The vast majority of households are nonconsumers of plant-based meat and, although this percentage is decreasing over time, 80% of the panel households did not purchase any plant-based meat product up to 2022. From the consumption patterns across years it is evident that the adoption of plant- based meat does signify a household’s intention to reduce meat consumption overall. The households that permanently adopted plant-based meat over the years reduced meat consumption by 10% and increased seafood consumption by 13%. Overall, the expenditure on proteins (plant-based meat included) increased by 29% which implies that households increased the variety of proteins with plant-based meat but did not fully replace an animal protein with it. The key results from the double hurdle model estimation suggest that only about one-third of the household panelists considered participation in the plant-based meat mar- ket segment. The estimated average share willing to consider plant-based meat varied from 25% to 36% with an average of 29%. The analysis showed that the prices of substiute proteins had a positive effect on the plant-based meat segment participation decision, but the price of plant-based meat itself tended to have little effect on participation. Education of the primary shopper was a strong positive determinant of participation, and consumers who expressed concern about food and pursued an ingredient-conscious diet were significantly more likely to participate in the plant-based meat segment. In terms of the second hurdle, the expenditure decision, the price of plant-based meat is consistently negatively correlated with expenditure, but the effect is not always statistically significant. The prices of the protein substitutes tend to be more significant determinants of expenditure on plant-based meat. The price of beef in particular is consistently and significantly associated with higher expenditure on plant-based meat. Household income is also significantly associated with higher plant-based meat consumption in the full panel. Demographic variables that play a consistent role in explaining plant-based meat expenditure include having a female primary shopper, having a more highly educated primary shopper, having household members who express concerns about health and who pursue an ingredient-conscious diet. Conversely household size does not tend to have a consistent and significant impact, nor do the politics of the state of residence or the age of the primary shopper. Finally, households experiencing health problems tend to spend less on plant-based meat, other factors constant. The censored regression model yielded estimation results that complement the results from the double hurdle model. Results of this estimation revealed that all five of the proteins studied in this analysis have near unitary expenditure elasticities, meaning that as household expenditures on proteins increases, expenditures on each protein rise in a nearly proportional manner. Plant-based meat demand was price inelastic in both the main sample and health-survey sample, but the demand was more elastic (indeed, near unit elastic) for the health-survey panel, suggesting some fundamental differences in behavior for the subgroup that chose to provide health information relative to the full panel. Compensated and uncompensated cross-price elasticities differed considerably due to strong income effects for all proteins in the system except plant-based meat. Estimated cross-price effects for the traditional proteins were consistent with prior meat demand studies. Importantly, results indicated that plant-based meat and beef are net complements based upon the compensated (Hicksian) cross-price elasticities, a finding at odds with the common belief that plant-based meat can become a significant substitute for beef in consumers’ diets, thereby leading to reduced methane emissions and other harmful environmental effects associated with cattle production. This finding is consistent with Zhao et al. (2022) and may indicate that plant-based meat products are consumed by some members in the household and beef by others while they are both served at the same meal. An increase in the price of beef reduces the amount of beef consumed by the household and, in turn, this affects the quantity of plant-based meat consumed. This finding casts major doubt on what appears to be an article of faith among those who believe plant-based meats can cause consumers to substitute away from animal meats.

Natural disasters and plagues have marked the course of human history, and remain among the greatest challenges and threats to economies and society. This dissertation uses a number of publicly-available datasets and natural experiments to explore how exposure to natural disasters affect households and societies in low- and middle-income African countries, with a particular focus on effects over time in agricultural communities. The disasters I study include desert locust swarms, floods, and the COVID-19 pandemic. In Chapter 1, I study the long-term effects of transitory agricultural shocks on the risk of violent conflict across Africa and the Arabian Peninsula using local variation in the areas exposed to desert locust swarms. In Chapter 2, I explore issues of measurement in determining what communities have been exposed to floods and how the use of different flooding definitions affects conclusions about the medium-term impacts of flood exposure on the incomes and activities of households in agricultural communities in Nigeria. In Chapter 3, I use a natural experiment during the COVID-19 pandemic to analyze how changes in household childcare burdens affect adults' labor supply in Kenya.My first chapter studies how transitory agricultural shocks affect the local risk of violent conflict over time. I answer this question using data on conflict events desert locust swarms across 0.25 degree grid cells in Africa and the Arabian peninsula from 1997-2018. Using modern difference-in-differences and event study approaches, I compare areas exposed to a desert locusts swarm--a localized agricultural disaster--at some point during this period to nearby areas with similar underlying risk of exposure. Local variation in exposure is caused by swarm flight patterns along their migratory paths during major outbreaks, characterized by daily downwind flights of over 100km. I find that having been exposed to a locust swarm significantly increases the average annual probability of violent conflict in a cell by 0.8 percentage points (43%). This is a very large effect, equivalent to the effect of a 1.6 degree C higher temperature in the same year. Effects persist for at least 14 years and are driven by swarms arriving in crop cells during the main growing season.I interpret the results using a model of occupational choice to explore income-related mechanisms. Persistent increases in conflict following a localized disaster suggest a decrease in the opportunity cost of fighting in affected areas. In line with this, I find that swarm exposure significantly reduces cereal yields in subsequent years, building on previous studies finding persistent effects of locust exposure on measures of household well-being and agricultural profits. Such effects indicate a permanent income mechanism for this severe transitory shock. This mechanism is not sufficient to explain the pattern of long-term impacts on violent conflict risk: the feasibility of engaging in violent conflict also matters. Increases in conflict risk are concentrated in years with active fighting groups in neighboring areas who may recruit or coerce individuals to join in violent conflict. Conflict therefore increases only when the reduced opportunity cost of fighting is combined with opportunities to fight. Patterns of long-term impacts on violent conflict are similar for severe droughts, indicating the mechanisms are not specific to locust shocks. Long-term impacts of transitory economic shocks on conflict risk add further motivation for policies mitigating the risk of such shocks and promoting household resilience and long-term recovery.My second chapter explores how extreme weather events affect livelihood decisions of agricultural households over time, focusing on the devastating 2012 floods in Nigeria. I use nationally-representative panel household survey data together with satellite imagery to analyze how exposure to the 2012 floods affects household labor supply and income in subsequent years. I first show that identification of flooding exposure varies depending on whether survey reports or MODIS satellite imagery are used. Differences in characteristics of communities identified as flooded by only one definition imply specific measurement issues for each. These results indicate that more attention is needed to considering how flooding is defined and measured, and whether there are different impacts of exposure to different types of floods.As in Chapter 1, I use a difference-in-differences design comparing changes in outcomes over time for households in communities exposed to flooding in 2012 against households in non-exposed communities that had a similar risk of flooding.I find no effects of flood exposure on engagement in wage employment or on total household income but a small significant increase in the probability of experiencing food insecurity using both definitions. The value of crop production falls, driven by a decrease in the value of commercial crops, while staple crop production either increases or remains stable. Using a MODIS-based flooding definition, I find that households exposed to floods significantly increase non-farm enterprise income relative to non-exposed households, as they reallocate labor from crop production to existing businesses. Using a survey-based definition, I find that flooding causes some farm households to become engaged in non-farm enterprise but without significantly increasing enterprise income while some non-farm households begin production of subsistence crops, with limited returns. The results emphasize that survey and satellite measures capture different types of flooding-related events which accordingly have different effects on exposed households. Studies of the impacts of floods should carefully consider their choice of flooding measure and the type of flooding they are most interested in analyzing.My third chapter, coauthored with Dennis Egger and Utz Pape, identifies the impact of a shock to childcare and child labor on adult labor supply and intra-household allocation of productive activities in the context of COVID-19-related school closures in Kenya. Using nationally-representative bi-monthly panel data, we compare changes in labor supply after schools partially reopened in October 2020 for adults with children in a grade eligible to return against adults with children in adjacent grades. We find that a child returning to school increases adults' weekly work hours by 29% in the short run, concentrated among the most flexible margins of adjustment, particularly household agriculture.Contrary to evidence from high-income settings, overall effects are not gendered. However, equal average labor supply responses for women and men are driven by different mechanisms particular to low- and middle-income settings. Women free up more time than men when childcare burdens fall but specialize more in childcare when returning students were net caregivers to younger siblings during school closures. Women also shoulder more of the reduction in child agricultural labor when students return to school, and shift from non-agricultural work into household agriculture (more easily combined with care of younger children). A back-of-the-envelope calculation suggests that school closures account for at least 40% of the overall drop in labor supply during the pandemic in Kenya, and a fall in GDP of 2.6%. Our results suggest policies increasing childcare access could substantially increase adult labor supply in low- and middle-income countries.Climate change is increasing not only global temperatures but also the frequency and severity of extreme weather events. Globalization has made societies around the world more connected but also more vulnerable to the spread of pests and disease. Yet there is little evidence on how such disasters affect households in low-income countries over time, and how they affect labor and livelihood decisions of poor farm households in particular. The three chapters of my dissertation combine publicly-available data, economic theory, and rigorous identification based on modern econometric methods to contribute to policy discussions around mitigation and adaptation to climate change, structural transformation, and civil conflict, among the greatest concerns for policymakers in Africa and around the world.

Perhaps the most central insight of development economics is that, absent a complete set of perfect markets, households' economic activities cannot be neatly ``separated" into those of a profit-maximizing firm and a utility-maximizing consumer (Singh et al., 1986) In particular, risk-averse farm households face a tradeoff between maximizing farm profits and smoothing consumption across states of the world. Balancing these motives is important not only for these households, who constitute a massive share of the world's poor, but for aggregate productivity as well. However, little is known about how to diagnose the market failures that create these tradeoffs, quantify their costs, and prescribe robust policies to address them. This dissertation seeks to provide methodological and empirical progress from the micro to the macro levels. Chapter 1 focuses on identifying how distinct market failures affect aggregate productivity in Thai agriculture. Agricultural markets often fail to allocate resources efficiently across farm households in developing countries. However, policymakers require knowledge of which markets fail and how the distortions they generate are correlated. In this chapter, I use data from rural Thailand to characterize how distortions in land, labor, credit, and insurance markets each contribute to factor misallocation. I use moments in household consumption and production data to separately identify these distortions and then quantify their impacts on aggregate productivity through an equilibrium model of misallocation. I find that the efficient allocation would increase aggregate productivity by 31% relative to the status quo, while only 15% (7%) gains could be achieved by eliminating financial (input) distortions in isolation. Positive interaction effects from addressing multiple distortions simultaneously account for the remaining 9% TFP gains. Meanwhile, other common methods would produce larger estimates of misallocation and suggest that a financial market intervention would decrease aggregate productivity. Accounting for multiple correlated distortions is therefore crucial for measuring misallocation and designing policies to address it. In Chapter 2, coauthored with Ethan Ligon, we move from Thailand to Northeastern Nigeria and move from the growing season to the lean season spanning harvests to study another important tradeoff between consumption smoothing and investment. In particular, we conduct a randomized control trial offering postharvest loans (PHLs) to farm households in Gombe State. The purpose of these loans is to enable households to shift from exhausting grain stocks and buying them back at high prices to becoming net arbitrageurs. While such programs have increased household incomes in Kenya (Burke et al., 2019)and Tanzania (Channa et al, 2022), their theory of change relies on grain prices rising, which is a highly uncertain proposition across sub-Saharan Africa. During our study period, prices of maize and other major crops stayed flat. While we find that the loans induced households to store more crops later into the season, we do not find significant effects on sales or overall welfare. While this is an example of the downside risk of PHLs being realized, we also use a simple model of intertemporal arbitrage to show how ex ante risk can have ambiguous effects on the demand for PHLs, depending on whether households are more vulnerable in states with high vs. low prices. Chapter 3, based in part on work coauthored with Ethan Ligon, focuses on production function estimation when input choices are distorted. These estimators, which are used to estimate the production function in Chapter 1, extend the canonical approach in industrial organization (Ackerberg et al., 2015; Gandhi et al., 2020), to risk-averse producers facing imperfect markets. In particular, they proxy for unobserved productivity by inverting the demand function for a flexible input from the setting with profit-maximizing firms in competitive markets to risk-averse households, possibly facing distorted input markets. The method involves combining consumption and production data to model input demands as a function of unobserved productivity and a stochastic discount factor, which includes the covariance between production shocks and consumption at harvest. Essentially, the consumption side of the household's problem provides information to help us identify the production side. Three main specifications are considered: the canonical Cobb-Douglas with Hicks-neutral shocks, a heteroskedastic generalization of Cobb-Douglas that allows for differentially risky inputs, and a dynamic multi-stage Cobb-Douglas featuring sequential shocks. The differences across specifications show the importance of accounting for risk, both overall and input- and stage-specific, to consistently estimate production functions and draw inferences about efficiency and misallocation. Together, these three chapters show how better understanding households' tradeoffs between productivity and consumption smoothing can improve policies to address both micro-level food insecurity and macro-level productivity.

In my dissertation, I explore the welfare implications of market imperfections in agrifood systems, focusing on agricultural production and food consumption. For the agricultural production part, I examine how imperfections in the land rental market may influence the welfare gains of securing land ownership in Latin American countries, where land ownership distributions are highly unequal. My theoretical and empirical analyses suggest that potential landlords may face a trade-off between investing in land-attached capital and renting out land following an improvement in land ownership security. This situation may emerge when tenants do not adequately take care of landlords’ land-attached capital under short-term land rental contracts. A critical contributing factor could be non-security barriers to long-term land rental contracts, such as legal caps on land leasing durations and landlords’ preferences for flexible, short-term contracts. Numerical results indicate that these non-security barriers in the land rental market could hinder land access for the rural poor, thereby disproportionately reducing their welfare gains from securing land ownership. For the food consumption part, I examine the increasing market power in the US food retail sector through the lens of consumer demand. Using IRI and NielsenIQ scanner data, my co-authors and I find that store-level price elasticities of demand for food items have been decreasing, allowing grocery stores with local market power to charge consumers higher markups. Interestingly, one prominent reason for this trend is the rise in income.

On December 13, 2004, the Zero Deforestation Law made deforestation illegal in Eastern Paraguay. Deforestation did not stop, however the law may have decreased deforestation. Most deforestation in this region is conducted to clear land for agriculture. In this dissertation, I conduct three analyses to investigate patterns of deforestation in Eastern Paraguay and the impact of this law on aggregate deforestation, predictors of deforestation, and post-deforestation agricultural land uses.The first analysis investigates drivers of deforestation in Eastern Paraguay before the Zero Deforestation Law. I use satellite-derived deforestation data in a linear probability model to investigate how physical and anthropological land characteristics are correlated with forest loss between 2001 and 2004. I find that physical land characteristics including slope, elevation, soil group, and ecoregion were useful for predicting deforestation. Only some anthropological land characteristics predicted deforestation. Distances to towns or roads were not correlated with deforestation. Proximity to patchy forest cover, such as in areas of existing agricultural clearings, was correlated with more deforestation. The second analysis investigates whether deforestation fell after the Zero Deforestation Law was implemented, and whether the relationship between land characteristics and deforestation changed. I use a linear probability model on a panel dataset of deforestation and land characteristics. My results show that deforestation fell by around a quarter after implementation. In addition, the predictive power of some drivers of deforestation weakened. One relationship reversed. Pre-policy, deforestation was more likely with less tree cover nearby, while post-policy, deforestation was more common near more densely forested areas, possibly indicating a desire to hide. My results cannot be explained by other events that took place during this time, and they provide strong evidence that the Zero Deforestation Law successfully lowered deforestation in Eastern Paraguay. The third analysis investigates how these decreases in deforestation post-policy were distributed across small-scale subsistence-oriented agriculture, large-scale commodity-oriented agriculture, and large-scale cattle ranches. Data does not exist on post-deforestation agricultural land use, so I generate my own data using a three-step process. First, I manually identify the post-deforestation land use for randomly sampled deforested locations in Eastern Paraguay. Second, I use these observations to train random forest models that predict post-deforestation land use from physical and anthropological land characteristics. Third, I use these models to generate land use predictions for all pixels deforested in Eastern Paraguay within four years before or after the Zero Deforestation Law came into effect. I find that the decrease in deforestation after implementation can mostly be attributed to a decrease in deforestation for large-scale agriculture. Clearing for large-scale agriculture fell by over 60%, from 34 thousand hectares annually on average before the policy to 12 thousand hectares annually on average after the policy. This was due to a composition effect, under which different locations were deforested after the policy was implemented than before, and a land use effect, under which the same deforested locations were used for different agricultural classes in the pre- and post-policy periods. Levels of deforestation for rangeland and small-scale agriculture remained relatively steady between the pre- and post-policy periods.

Coffee is a perennial crop that plays an essential role in many emerging countries’ economies. It is estimated that the coffee value chain provides a livelihood for about 125 million people worldwide, including 25 million smallholder producers in developing countries (Krishnan, 2017). Coffee farmers, however, have experienced a number of threats in recent decades, including volatile coffee prices and rising production costs. Under the changing climate, additional challenges will be posed to small coffee producers, which may further threaten their economic viability. The most noted effect of climate change is rising temperature, which provides favorable environments for coffee pests and diseases, including coffee berry borer and coffee rust. Climate change also increases the likelihood of extreme weather events such as drought, frost, and flood, and the impact of such events on coffee plantations can be severe, including loss of trees. As such, understanding how this core industry will be impacted by climate change is critically important. This dissertation investigates the impacts of climate change on coffee production, a critical economic commodity in many developing countries. Through a panel fixed effects econometric modeling approach, this research analyzes how climatic variables such as temperature and precipitation influence coffee yields, particularly focusing on the differential effects during various growth stages of coffee plants. This study also utilizes projections from global climate models through the 21st Century to project the impacts of future climatic conditions on coffee yields.The research estimates a weather-yield response model that captures the heterogeneous weather effects by including variables across critical coffee growth stages such as the blooming, fruit bearing and harvesting phase. The weather variables of interest include growing degree days (GDDs), harmful degree days (HDDs), freezing degree days (FDDs), precipitation, number of dry days, and coefficient of variation of precipitation.In Brazil, the study reveals pronounced biennial variations in coffee yields, with GDDs positively affecting yields during the blooming stage, whereas HDDs exacerbate yield losses during the same period due to extreme heat. Additionally, my results indicate that prolonged dry periods before the blooming season benefit yields up to a threshold, beyond which yields may be adversely impacted by extended drought conditions. Conversely, in Colombia, coffee yields lack the pronounced biennial variation seen in Brazil. In terms of temperature effects, GDDs during the flowering and harvesting periods positively influence yields, and precipitation during the fruit-bearing stage negatively affects yields .The dissertation also explores the role of elevation in moderating the impacts of weather variables on coffee production. It finds that in Brazil higher altitudes increase the susceptibility of coffee yields to negative climatic impacts due to the cultivation of different coffee varieties that vary in their response to temperature and moisture levels. In contrast, in Colombia, elevation does not significantly differentiate the impact of climatic variables on coffee yields.Under IPCC’s middle of the road emission scenario, municipalities in most states are projected to see a drop in yield, ranging from 3% to 13% by the end of the century. On the contrary, Municipalities in Mato Grosso do Sul will benefit from the climate change, which would result in a 19% yield increase in the far future. The primary drivers include changes of GDDs and HDDs during blooming and harvesting periods, with mixed effects on future yields.This dissertation examines the profound and varied impacts of climate change on coffee production in Brazil and Colombia, two of the world’s leading coffee producers. The findings underscore the necessity for adaptive strategies tailored to specific regional and varietal characteristics to mitigate the adverse effects of changing climatic conditions. Moreover, these results provide valuable insights that could be extended beyond Brazil and Colombia to understand the broader implications of climate change on coffee-producing regions worldwide.

U.S. agricultural policy strives to boost farm incomes and secure the nation's food supply, yet new policies are also tasking agriculture with reducing or offsetting the country's greenhouse gas emissions. California's Low Carbon Fuel Standard uses a system of tradable compliance credits to incentivize the consumption of alternative fuels instead of fossil fuels. These credits provide additional value for the production of agricultural biofuels including ethanol. My dissertation examines the effects of the LCFS on commodity prices by first building a spatial corn market model of ethanol plants selling to California and then empirically estimating the pass-through of LCFS credit values changes in local corn prices. I find that the LCFS could be providing a competitive advantage in the corn market to ethanol plants with lower emissions, and these plants only pass-through around 40\% of LCFS credit value changes to local corn farmers as a result. Moreover, policymakers across the globe see working farms as a possible carbon sink through increasing the carbon sequestered in cropland soils. The Inflation Reduction Act of 2021 provides billions of dollars to USDA programs that tangentially influence carbon sequestration. However, soil carbon sequestration is a complex process that cannot be easily influenced by policy. I review the scientific literature on soil carbon sequestration and relate it to economic research on environmental externalities. While practices like no-till or biochar can increase carbon sequestration on agricultural lands, effective policy design faces substantial challenges due to heterogeneity, costly measurement, and uncertainty.

Agricultural water supplies are shrinking in California as an effect of a changing climate and groundwater regulations. Farmers have been adapting their practices to cope with this reality over the past many decades, but will need to do more to cut production costs as the price of water rises. One of the cost-saving techniques farmers employ when resources are scarce is to leave a portion of their land idle. Farmers could insulate from climate risk better by using their land for purposes with more predictable profits and less water needs per acre. Solar energy generation is sometimes used by farmers as a profitable alternative to traditional crop cultivation, and would create more consistent returns for the owner. This analysis identifies over 90,000 acres of active agricultural land in the San Joaquin Valley that would benefit from transitioning to solar generation. The lands identified could add 10-12 GW of solar energy generating capacity per year to the San Joaquin Valley’s existing 3GW.

In the face of escalating global climate change, the need to mitigate greenhouse gas emissions has never been more pressing. Agriculture is a major source of greenhouse gas emissions, but is also gaining recognition for its potential role to reduce atmospheric carbon dioxide by sequestering carbon in the soil. A recent French initiative called 4 per mille states that if farmers were to increase soil organic carbon (SOC) on their fields by 0.4% per year, that would be enough to offset all annual anthropogenic greenhouse gas emissions and stop further increases in atmospheric carbon dioxide. This initiative highlights that only a small percentage increase in SOC over a large area of land can yield substantial environmental benefits.Government and industry stakeholders are beginning to recognize the potential for SOC, and are in the early stages of developing carbon markets for SOC. But there are still important scientific and economic questions to be answered. These questions call for further research on how to accurately measure SOC, understand soil capacity for additional carbon sequestration, and how different farm management practices affect SOC and what their associated private and public benefits are. The topic of carbon markets has garnered significant attention due to recent government initiatives promoting climate-smart agriculture and private investment in carbon offset programs. In this dissertation, I bridge the gap between research conducted by soil scientists, who focus on modeling and sampling techniques to better measure SOC, and the work of economists, who concentrate on policy design and the valuation of environmental benefits. My methodology addresses the challenges of accurately measuring soil carbon and examines how these models can be used to inform policy design and efforts to establish sustainable carbon markets in agriculture.This dissertation examines, in three chapters, the relationship between carbon sequestration, farm management practices, and agri-environmental policy. I analyze the private and public benefits from carbon sequestration on farms in Saskatchewan from 1998 to 2019. To do this, I employ a novel field-level dataset from the Saskatchewan Crop Insurance Corporation (SCIC) that includes detailed information for each field in Saskatchewan: cropping choice, yield, fertilizer use, crop insurance coverage, and the number of seeded hectares. In Chapter 1, I develop a novel SOC prediction model that builds on the existing models developed specifically for Saskatchewan soils. I examine the case of carbon sequestration in the Saskatchewan prairies, which have experienced substantial increases in SOC over the past 30 years. I use several SOC prediction models to simulate the stock of SOC on fields over time and compare the results. I then compute the external social benefit from carbon sequestration on all insurable hectares by simulating various counterfactual scenarios in which 25%, 50%, and 75% of canola hectares are replaced by summer fallow, representing a reversion to tillage-based systems, and using various values for the social cost of carbon (SCC) ranging from 14 USD/Mg to 185 USD/Mg. During the period 1998–2019, this external social benefit ranges from 481 million to 6 billion USD. Projecting average carbon inputs 150 years into the future yields an estimated external social benefit ranging from 851 million to 30.2 billion USD for the same counterfactual comparisons.In Chapter 2, I use the SOC data simulated in Chapter 1 to determine the effects of increased SOC stocks on crop yield, productivity, and on-farm profit. I use a dynamic panel regression to estimate the shadow value of SOC and find that increased SOC stocks have a statistically significant and a positive affect on crop yields. Performing dynamic simulations, I compute the on-farm and external social benefits from carbon sequestration that are attributed to selecting a particular crop rotation, and compare these benefits across rotations. I find that adoption of the Canola-Spring Wheat-Peas-Spring Wheat crop rotation leads to a 27.5%, 8.2%, and 4.4% increase in long-term average profit in the brown, dark brown, and black & gray soil zones attributable to increased SOC over 32 years. On-farm benefits from increased SOC are lower for crop rotations with lower carbon sequestering capabilities, highlighting the long-term effects on farm profitability and productivity from selecting particular crop rotations. I compute the external social benefit from the adoption of Canola-Spring Wheat-Peas-Spring Wheat rotation relative to Spring Wheat-Fallow-Spring Wheat-Fallow on all insurable hectares in Saskatchewan from 2023 to 2055, and find benefits amounting to 108 billion CAD when employing a SCC of 185 USD/Mg. I find that the external social benefits from crop rotations that include canola rather than pulses or fallow are greater than the associated private benefits. Hence, selecting crop rotations that have greater SOC sequestration potential not only improves on-farm profitability over time, but also generates sizable environmental benefits.In Chapter 3, I assess the effectiveness of second-best policies aimed at increasing the stock of SOC by examining a hypothetical policy that subsidizes additional canola hectares differently for each soil zone in Saskatchewan. To analyze the effect of these subsidies, I develop a simulation model that includes on-farm acreage responses and a SOC state equation to measure changes in SOC stocks due to alterations in land-use. I find that a policy offering optimal subsidies specific to each soil zone for additional hectares of canola, implemented in 2019 and continuing indefinitely for all insured fields in Saskatchewan, generates an external social benefit worth 15.2 billion CAD when the subsidy is set to maximize the net external social benefit (NESB), and 30.4 billion CAD when it is set to maximize the change in total welfare. These benefits are calculated using acreage responses estimated by a nested logit model with field-level data from the SCIC, and an annual carbon rental rate computed using a SCC of 185 USD/Mg. The NESB is the public benefit from carbon sequestered by increasing canola hectares minus policy costs, while the change in welfare is the NESB plus the change in producer surplus. This chapter quantifies the potential environmental and social benefits from implementing second-best policies that aim to increase SOC stocks by subsidizing changes in cropping choices.

Climate change is significantly amplifying the frequency and intensity of natural disasters, transforming them from sporadic events into persistent crises. Extreme heat, hurricanes, tornadoes, wildfires, floods, droughts, and other disasters are not only more common but also more devastating, leading to destruction of ecosystems, human casualties, and substantial economic losses. By analyzing past responses and predicting future trends, economists can help policymakers develop strategies that not only mitigate the financial toll of natural disasters but also enhance the resilience of vulnerable populations. This dissertation explores the intricate dynamics between natural disasters, insurance markets, and climate change, focusing on the state of California. It is structured into three chapters, each examining a distinct aspect of how risk and regulatory responses shape economic behavior and market outcomes in the context of increasing environmental volatility. Chapter 1 investigates the influence of natural disaster risk on migration decisions and demographic sorting based on income and risk preferences, focusing on individual responses to a changing climate. One of the most effective ways to reduce individual exposure to natural disaster risk is to migrate away from risky areas. However, as people migrate away from risk, an opportunity opens for other people to migrate towards it. I study who chooses to move in both directions in rural California, which has experienced a rapid escalation of wildfire risk in recent years. Utilizing a novel measure of wildfire risk derived from California's residual homeowners insurance market, I distinguish the impacts of wildfire risk from other unobserved variables. The analysis reveals that increased wildfire risk prompts a population reshuffling, with lower-income and less risk-averse individuals more likely to migrate into high-risk areas. These findings have significant policy implications, highlighting the challenges of disaster preparedness and recovery among vulnerable populations.Chapter 2 examines the consequences of regulatory interventions for firms in the disaster insurance market amid escalating climate risks. In California, increasing risk of wildfire is fueling an insurance crisis; in May 2023, the largest and fourth largest insurance firms (State Farm and Allstate) suspended all new underwriting activity related to homes and businesses citing increasing wildfire risk. In response, the government implemented a moratorium on insurance non-renewals in zip codes that experience an emergency wildfire for one year following the emergency declaration in an attempt to protect customers and reduce reliance on the insurer of last resort. I present a theoretical model of this adversely selected market with an insurer of last resort and empirically evaluate the non-renewal moratoriums. Through a difference-in-differences methodology, I find that while the moratoriums temporarily reduced insurer-initiated non-renewals, their effects were short-lived, and there was no significant impact on participation in the state's insurer of last resort. These results highlight the limitations of regulatory measures in maintaining market stability under severe climate pressures.Chapter 3 explores the role of government in facilitating climate change adaptation in California's groundwater and surface water markets. Climate models project that in California, droughts and floods will become more frequent and severe and year to year variability in precipitation will increase. In places where water rights have been established, water markets play a critical role in allocating water over space and can smooth climate risk by redistributing water to users that value it the most. While efforts have been made to improve water trading across space, market design has paid relatively less attention to the question of when scarce water resources should be allocated. This chapter examines the effect of water storage constraints on price dynamics in California's surface and groundwater markets, using transactions level water transfer data from 2010 to 2022. I examine recent market activity, including trading volumes and locations, and analyze the spatial and temporal variability in water prices. I find that surface water markets exhibit significant price fluctuations tied to precipitation changes due to limited storage capacity, whereas groundwater markets maintain stable prices, unaffected by such variability. These findings highlight the potential for conjunctive management of surface and groundwater to stabilize water prices and enhance economic welfare by leveraging California's substantial groundwater storage capacity. This study emphasizes the importance of integrated water management strategies to mitigate the economic impacts of climate change on water resources.Collectively, this dissertation provides critical insights into the economic and policy challenges posed by natural disasters and climate change, emphasizing the need for adaptive strategies to manage risk and support vulnerable populations.

In this dissertation, I investigate the determinants of regional production choices,primarily focusing on agricultural commodities, and the aggregate consequences of thosedecisions. The dissertation is guided by the connecting theme of understanding whyregions choose to produce specific commodities and the implications of these choices oninternational trade and development. The study comprises three interconnected chapters,each addressing a different aspect of agricultural and resource economics and internationaltrade.The first chapter examines the clustering of agricultural production in Mexico anddemonstrates that agricultural value chains (AVCs) explain these spatial patterns moreclosely than land suitability alone. The chapter highlights the presence of economies ofscale in AVCs that act as barriers to entry and contribute to the clustering of agriculturalproduction. I use Mexico as a setting, where highly productive, export-oriented agriculturecoexists with subsistence agriculture. The paper develops a general equilibrium modelincorporating intermediaries with market power and large fixed costs of entry. This modelallows me to explore several counterfactuals, such as the impact of climate change onagricultural production and the role of fixed costs in generating patterns of clustering.The second chapter, jointly authored with Thibault Fally, investigates the role ofprimary commodities in international trade, highlighting the potential understatement ofaggregate gains from trade when key features of commodities are ignored. By developing ageneral-equilibrium model that accounts for these features, including low responsiveness ofboth demand and supply to changes in price, reliance on natural resources, and a highconcentration of these natural resources among only a few countries, this chapter offers amore comprehensive understanding of the economic gains from trade. The model and data are used to simulate a number of counterfactuals which confirm that ignoring the specificfeatures of commodities leads to a wide understatement of the gains from trade.The third chapter, jointly authored with Joel Ferguson and Kangogo Sogomo, presents acomputationally feasible approach to remote sensing outcomes at large scale. We develop anovel dimensionality reduction technique to predict agricultural outcomes using onlywidely available, aggregated training data. This methodology is adaptable to variousproblems, including classification of crop types, measurement of forest loss, or urbangrowth, and offers a practical toolkit for researchers and policymakers who require timelyand cost-effective data for decision-making purposes without the need for additionalsources of information. We focus on measuring crop yields, particularly maize yields inMexico, which is important for ensuring food security and informing policies such as foodaid and transfer programs to assist smallholders affected by climatic shocks or better targetresponses to natural disasters in rural areas.Taken together, these chapters provide insights into the determinants of regionalproduction choices, the development of innovative techniques for crop yield estimationthrough remote sensing, and the importance of primary commodities in international trade.By exploring the forces shaping regional agricultural and resource production and thedistribution of scarce natural resources, this dissertation contributes to a more integratedunderstanding of how trade and agricultural and resource sector and play a role in shapingregional economic outcomes. The findings have implications for agricultural policy,international trade, and for regional development.

The Sustainable Groundwater Management Act (SGMA), enacted in 2014, serves as California’s first foray into establishing a comprehensive groundwater management program. Under this legislation, basins are required to mitigate groundwater overdraft to reach sustainable conditions by 2040 or 2042. Reductions in groundwater pumping are anticipated to drive substantial shifts in the San Joaquin Valley’s agricultural sector, which has historically depended on groundwater to provide water for irrigation. This research examines a case study of SGMA implementation in the Kings and Tulare Lake groundwater basins, focusing on potential impacts for agricultural land cover and economics. Publicly available information on spatial cropping patterns, irrigation requirements, and crop production economics as well as overdraft information and historical water availability from Groundwater Sustainability Plans (GSPs) are used to calibrate a hydroeconomic agricultural production optimization model representing the agriculture in the study area. Scenarios integrating overdraft responsibilities with options for surface water trading and groundwater supply augmentation through recharge are modeled to explore potential outcomes for future agriculture under SGMA. Results suggest ranges and distributions for land fallowing and losses of agricultural revenue under a variety of possible scenarios. Findings also highlight the importance of water trading and groundwater recharge programs in meeting sustainability in the basins and barriers to implementing these programs are discussed.

Poverty reduction programs inspired by BRAC's graduation approach aim to develop both tangible productive assets and intangible psychosocial assets such as self-confidence and the aspiration for upward mobility. In the broader global context, recent estimates underscore the urgency of poverty alleviation efforts, especially in a post-COVID-19 world. The surge in extreme poverty, coupled with disproportionate setbacks faced by the vulnerable, emphasizes the necessity of targeted interventions like the graduation approach, including fiscal support.The first chapter of this thesis seeks to enhance our understanding of how psychosocial factors operate and shape the impact of graduation programs. After formulating a set of hypotheses about the effects of psychosocial constraints based on a dynamic optimization model that considers the choice between a low-income casual wage-labor occupation and a higher-earning entrepreneurial activity, this paper utilizes a randomized controlled trial of a graduation program implemented in the pastoralist regions of Northern Kenya. Key empirical findings reveal that the estimated highly favorable average treatment effects conceal significant heterogeneity, as beneficiaries who initially experienced severe depressive symptoms gained little from the program. The saturation design of the RCT also enables the identification of substantial spillover effects on the asset accumulation of women who were not enrolled in the graduation program. Spillovers are also shown to positively impact non-beneficiary women's preference for upward economic mobility, providing a plausible explanation for their capital accumulation despite not receiving direct support from the graduation program. The paper extracts implications from these findings for the cost-effective design and implementation of graduation programs.The second chapter delves into the spillover effects of the REAP program through the female kinship network within local communities. In contrast to the previous chapter, which employed a saturation measure on community-level interaction with treated women to assess the impact of treatment intensity on REAP-eligible women, this study investigates spillover effects on control group women whose relatives benefited from the program. The findings reveal increased business assets, savings, and living standards among non-treated women whose relatives were recipients of the REAP program. Importantly, spillover effects are more pronounced for non-head control female respondents compared to female household heads. The study also draws a comparison between spillover effects at the kinship network and community levels. Similar effects are observed in business assets, with unique spillover effects on savings through the kinship network. Overall, this chapter underscores the significance of network structures in poverty alleviation program spillover effects and calls for inclusive strategies tailored to vulnerable groups and their specific needs. The study enhances our comprehension of local network dynamics and provides insights into the success of interventions within developing economies and the intricacies of spillover mechanisms.The third chapter delves into the long-term impacts of the REAP program in pastoralist regions of Northern Kenya, taking into account spillover effects. The research discovers substantial positive effects of the program on women's productive assets and financial savings even four years into the program. However, severe depressive symptoms among beneficiaries lead to varying treatment effect trajectories. With the inclusion of endline data, the study demonstrates continuous treatment effects, revealing an asset accumulation and savings trajectory that peaked at around 30 months into the treatment and then declined by about 20% by 48 months. A positive trajectory for income over 48 months of the program is also observed. Importantly, the spillover impact found at the midline is not sustained at the endline. The distinctive characteristics of the program, including direct initial cash transfers and collaborative business management, introduce complexities in impact estimation, exacerbated by external shocks such as floods, locusts, and COVID-19. Challenges in measuring jointly owned business assets arise from group-based enterprises. These findings provide insights into the intricate dynamics of poverty alleviation interventions in challenging contexts.

Subsidies are widely criticized in fisheries management for promoting global fishing capacity growth and overharvesting. Scientists worldwide have thus called for a ban on ``harmful'' subsidies, which artificially increase fishing profits. The argument for banning harmful subsidies relies on the assumption that fishing for some fishermen will become unprofitable after eliminating subsidies, incentivizing some to exit and others to refrain from entering. These arguments follow from theories of open-access governance regimes where entry has driven profits to zero. Yet many modern-day fisheries are conducted under limited-access regimes that limit capacity and maintain economic profits, even without subsidies. In these settings, subsidy removal will reduce profits, but perhaps without any discernable effect on capacity or the structure of the fleet. Importantly, there have been no empirical investigations of fisheries subsidy reductions to inform us about their likely quantitative impacts in real-world settings.This dissertation investigates the impact of fisheries subsidy reform on fleet capacity dynamics and structure in the offshore fisheries of Zhejiang Province, China. This study is important for its novelty, the complexity of the policy context, the quality of the data, and the importance of China as a fishing nation-state. China is the world's largest seafood producer and user of harmful fishing subsidies. In 2006, China implemented a fuel subsidy program to insulate fishermen from the sudden shock to diesel prices as the country deregulated its domestic gasoline and diesel markets. But in 2016, China implemented a wide-ranging fuel subsidy reform to reduce fleet size and curb harmful gear use in order to align with new ecological policy objectives. The reform created a unique opportunity to provide the first quantitative investigation of fishery subsidy reductions.The policy setting investigated in this thesis offers several advantages for understanding the potential impacts of harmful subsidy reductions. First, fuel subsidy reductions were allocated across vessels in a manner conducive to a quasi-experimental research design, allowing me to identify the reform's treatment effect on fleet capacity. Second, China's fuel subsidy reform took place within an institutional setting that embodies the complexity of the policy environments in which many future subsidy reforms are likely to occur. In particular, fuel subsidies were just one policy instrument among many others, including a cap-and-trade program for engine power, a buyback (or retirement subsidy) program to encourage exit and fleet capacity reduction, gear regulations, and open-season restrictions. I demonstrate that these other elements conditioned the effect of fuel subsidy reductions in complex but understandable ways that provide insights into how banning harmful subsidies might work globally. My research design is based on a conceptual framework that considers individual-level vessel investment decisions, short-run fleet dynamics, and the long-run bioeconomic equilibrium in a limited-entry fishery. Using structural modeling techniques, I generate refutable hypotheses regarding the impact of subsidy reform on fleet capacity and test these hypotheses using state-of-the-art reduced-form empirical methods. Using a unique vessel-level panel that I assembled from administrative data collected by Chinese authorities, I demonstrate that the subsidy reform led to an increase in individual vessel exit rates. However, the extent to which vessel exits led to power quota retirement, and hence capacity reduction, depended on the simultaneous reforms of a buyback program. Using a model of a cap-and-trade market with a price floor, I am able to separately identify the effects of each component of the reform and show that while subsidy reductions induced exit, the buyback program was the primary contributor to fleet capacity reduction. I also explore the impact of the reform on the structure of the fleet and find an acceleration of capacity reduction of harmful gear and adoption of less intensive fishing gear. Overall, this dissertation highlights the nuanced nature of mechanisms linking subsidy reductions to fleet reduction and restructuring in modern fisheries. In brief, simply removing harmful subsidies may not, as suggested, be a panacea leading to increased conservation of global fish stocks. Indeed, in modern limited entry fisheries like China's trawl fishery, subsidy reductions might have had no effect on capacity reduction without complementary policies like retirement subsidies that induced exiting fishermen to retire rather than replace their vessels. This suggests the need for a strategic design of worldwide fisheries subsidy reforms that carefully accounts for the economic incentives of participants, the complexity of policy environments, and the multiple objectives of fisheries policy.

In this dissertation, I analyze the economic effects of weather, climate change, adaptation, and natural resource scarcity through the lens of agriculture in California. Quality is central to much of agriculture because of its role in price determination and contractual arrangements. Nevertheless, prior work on the effect of weather and climate change on agricultural production mostly focuses on staple crop yields. Ignoring quality will likely bias estimates of the impact of weather and climate change on productivity and farm income. In the first essay, we quantify the effect of temperature exposure and climate change on the revenue of specialty crop growers through two pathways: quality and yield. In contrast to earlier work on irrigated crops, we find extreme temperatures negatively affect both yield and quality leading to reduced grower revenue in a setting where irrigation is the norm. While the yield effect dominates, failing to account for quality significantly underestimates the true effect of temperature exposure on revenue by up to 20%. We predict climate change will significantly reduce yield, quality, and revenue by century's end absent additional adaptation. In the second essay, I investigate how natural resource scarcity affects farmers' decision making. Using a panel of 3,300 irrigated fields in California, I ask whether farmers respond to water scarcity by changing whether they plant, what they plant and how they produce. Novel data provide evidence of the mechanisms by which growers use water more efficiently - insights unattainable in publicly available or survey data. I find that during a water scarce year, growers are more likely to plant earlier, plant fast-maturing varieties, and preferentially plant fields equipped with drip irrigation rather than less water-efficient technologies. Water access drives how growers conserve water: growers with low-priority access rely on more costly margins, such as fallowing or changing growing practices in ways that reduce revenue per acre. This demonstrates that agricultural producers engage in water-saving practices more than what has been previously found and that these practices help growers avoid fallowing, a much more costly response. The first and second essays use proprietary data on California's $1 billion processing tomato industry, which produces nearly one-third of the world's processing tomatoes. Tomatoes are the second-most consumed vegetable in the United States and contain nutrients that are important to human health, but often under consumed. These novel data are collected by a large tomato processor for the purposes of contracting and payment, and include field-level quality, yield, price, and grower practices for many independent farmers operating in California. The third essay returns to the relationship between quality, weather, and climate for a different specialty crop product: wine. Wine is the most differentiated of all agricultural products, with much of the differentiation based on the combination of wine grape varieties and “terroir”: the natural environment in which the grapes are grown. The objective of this study is analyze the complex relationship between collective reputation, climate, weather, and price premia and quality for varietal wine in California. We find temperatures warmer than the regional norm had negative effects on both Cabernet Sauvignon and Chardonnay wine prices and scores. We also find that wines from premier regions are less influenced by deviations in temperature from regional climate. This supports the notion that producers of higher-value wines intervene more to mitigate the negative effects of weather. Quality matters for all agricultural producers but some more than others. Prices of processing tomatoes vary plus or minus 20% in my sample whereas wine grape prices vary by a factor of 50, even for the same variety and vintage produced in the same region. For processing tomatoes, we benefit from detailed and precisely measured data on quality attributes and how they affect grower revenue. Quality variation is arguably more important for wine grapes and wine but also more complex, which makes it more difficult to cleanly link weather effects to attributes that affect prices of grapes and wine. Rather than direct observations of quality attributes, we use expert ratings and recommended retail prices as indicators of wine and wine grape quality. Both papers contribute to our understanding of how weather and climate influence agricultural product quality. Each of these three papers contributes to our understanding of how economic agents are affected by and respond to weather, climate, and climate change. Most of what we know about agricultural production in the face of climate change comes from research on yields of staple crop. This dissertation contributes by analyzing specialty crops that are understudied despite making up 40% of the total value of U.S. crops. Taken together, the research in this dissertation highlights potential harm from a hotter and drier climate absent adaptation.

The fields of environmental and resource economics provide us with the tools that allow us to better understand the world around us and the ways in which humans interact with it. People benefit from goods and resources provided by the environment, but can also harm the environment through externalities created by their economic activity. The utilization of environmental resources often requires government and society to implement policies in order to protect and preserve these resources for the future. This dissertation explores three topics in environmental and resource economics. The first measures an environmental externality caused by urban development and proposes a policy that balances continued development with the welfare of those harmed by the externality. The second explores how people adapt to changes in climate resulting from migration, which may inform us about adaptation to climate change and migration in the future. The third topic studies the effectiveness of policies aimed at protecting marine resources, at a time when marine protection is rapidly expanding.The first chapter, titled "Shadow Prices: Measuring the Cost of Shadows from New Construction in New York City," studies one negative externality of urbanization - the blocking of sunlight by construction - and a policy that can be implemented to ensure a balance between urban development and the welfare of those who are harmed by their reduced access to sunlight. I begin by measuring the externality of urban shadows by estimating the impact of shadows created by new highrise construction on nearby housing prices. Making use of publicly available housing transactions data and building shapefiles for New York City, I create a shadow accumulation model to measure the amount of shadow created by highrises that are cast on residential units in Manhattan in each year for highrises constructed between 2005 and 2014. I then use a differenced regression model with spatial-time fixed effects to estimate the effect of a change in shadows on nearby residential unit sale prices. I estimate that a 10 percentage point increase in average daily shadow received by a unit (e.g. 1 hour of additional shadow in a day with 10 hours of sunlight) is associated with an approximately 3.78% decrease in unit price. Finally, I propose a policy that incorporates this estimate in regulating building height.In the second chapter, titled "Estimating the Relationship Between Inter-Climate Migration and Air Conditioning Adoption," which I coauthored with Leopold Biardeau, we measure the relative increase in residential air-conditioning (AC) adoption rates in states that see higher levels of migration from relatively cooler states, within the contiguous United States. We consider how the average percent increase in Cooling Degree Days (CDDs) by migrants to a given destination state increases the average rate of residential AC adoption in the four decades spanning from the 1960s to the end of the 20th century. We find significant positive effects of the percent increase in CDDs experienced by migrants on rates of air conditioning adoption. To confirm the validity of this relationship, we rely on an instrumental variables approach using origin state determinants of emigration, along with the distance between states, to provide evidence that this result is not the byproduct of a reverse causality relationship in which higher residential AC-adoption levels would be responsible for increased immigration from relatively cooler states. These results provide some insights regarding the expected impact relative temperature changes may have on Climate Change adaptation. In particular, we might expect that an increase in population displacements from warmer countries to relatively cooler ones lead to a lower increase in energy demand for cooling purposes that what would have been anticipated.In the third and final chapter, titled "Evaluating the Effectiveness of Very Large Marine Protected Areas at Deterring Fishing Effort," which I coauthored with Leopold Biardeau and David Zilberman, we study the extent to which Very Large Marine Protected Areas (VLMPAs) have been successful at deterring fishing effort. The last decade has witnessed a considerable increase in the designation of VLMPAs, Marine Protected Areas spanning at least 100,000 km-squared. On paper, these protected areas offer conservation benefits not seen in smaller ones. Yet, their large sizes may constitute a challenge for enforcement. Using on satellite-based data that tracks vessel fishing hours, we find evidence that VLMPAs have, on average, been able to deter fishing effort, although a case-by-case analysis reveals varying levels of success. To better understand the nature of possible illegal fishing in these VLMPAs, we investigate the characteristics of the vessels infringing on the fishing bans in these VLMPAs and find that most of the infractions can be traced back to a few industrialized countries.These three chapters fall back on three important question in environmental and resource economics: What are the environmental externalities associated with economic activity and what policies can be implemented to compensate those harmed while balancing the interest of allowing continued economic activity? How do people adapt to changes in their environment? And finally, how successful are current policies that are designed to protect the environment and its resources? The research contained in this dissertation applies each of these questions in different contexts, and in doing so, helps us to better understand the economics of resources and the environment.

Agricultural production grew dramatically since 1950. While this growth improved food security, it also introduced harmful tradeoffs. A few of those tradeoffs are environmental externalities and market power in food and agricultural markets. The sustainability and resilience of the modern food system require that research and policy carefully weigh the consequences associated with productivity growth. This dissertation evaluates the environmental and supply chain tradeoffs of modern agricultural production. Chapter 1 quantifies costs of nitrate contaminated drinking water, which largely results from agricultural production. Nitrate contamination of drinking water is a widespread environmental concern and threatens human health. The magnitude of the environmental health consequences depend on an individual's ability to avoid exposure. This paper uses an event-study framework to uncover the heterogeneity in avoidance behavior following Safe Drinking Water Act nitrate violations. Using weekly store-level scanner data, I estimate that consumers spend approximately $4.7 million annually on bottled water and soda to avoid nitrate contaminated drinking water. However, consumers in resource-constrained areas exhibit substantially less protective behavior. This leads to 143 additional infant deaths per year relative to areas with less-costly access to safe drinking water. These results underscore substantial costs from nitrate pollution and that these costs are disproportionately distributed to those with less ability to protect themselves.Chapter 2 calculates the groundwater impacts of drought and extreme heat in California agriculture. Adaptation to climate and weather shocks can be costly for producers, but it also may impose negative externalities on vulnerable populations. We study this in the context of groundwater in California and evaluate the effects of annual fluctuations in weather and surface water supplies on agricultural well construction and access to drinking water. Using the population of geocoded wells, we show that farmers respond to extreme heat and surface water scarcity through new well construction. This mitigating behavior by agricultural users imposes costs: Extreme heat and surface water scarcity also lower local groundwater levels and cause domestic well failures. While groundwater extraction helps producers reduce the damage from environmental shocks, it also harms access to drinking water supplies in marginalized communities.Chapter 3 evaluates the efficiency and resilience tradeoffs of different supply chain policies. Recent extreme events and the disruptions they caused have made food supply chain resilience a key topic for researchers and policymakers. This paper provides input into these discussions by evaluating the efficiency and resilience properties of the leading policy proposals. We develop a conceptual model of a prototype agricultural supply chain, parameterize the model based on the empirical literature, and conduct simulations to assess the impacts on resilience and economic welfare of four key policy proposals: (i) intensified antitrust enforcement to improve market competition, (ii) subsidization of entry of additional processing capacity, (iii) prevention of price spikes through anti-price-gouging laws, and (iv) diversification of production and processing across multiple regions. Results show that some of the policies have the potential to improve supply-chain resilience, but their impacts depend on the existing market structure, and resilience gains often come at the cost of reduced efficiency.

Relational contracting (RC) is an important special case of vertical coordination that provides more stability than spot market transactions and more flexibility than vertical integration. Unlike formal contracts that are third-party enforceable, relational contracts are self-enforcing agreements governed by the trading parties' valuations of a potential long-lived economic interaction, and are particularly prominent in countries where institutions for enforcing formal contracts are incomplete. Despite the growing awareness of RC's importance and prevalence, little is known about its value as markets develop, as informal relationships are generally studied in contexts with salient market imperfections.By analyzing the transactions of a large wholesale fresh produce market in China, this dissertation presents evidence of relational contracting inside a well-functioning market. The market exhibits two stylized facts, namely persistent price dispersion across and within individual sellers, and repeated trade between a significant number of bilateral buyer-seller pairs. Motivated by the stylized facts, the conceptual foundations for the economic relationships formed by buyers and sellers via repeated trade are set forth, and testable hypotheses regarding the characteristics of the informal agreements (relational contracts) embedded in these relationships are developed. First, buyers under RC pay a premium to sellers relative to spot market prices. Second, RC price varies with spot market prices; it rises if the market price increases and falls as the market price drops. Third, the RC premium is suppressed under a negative supply shock and is enlarged under a positive supply shock. Fourth, buyers enjoy greater assurance in supply through RC. Last, the value of a relationship is higher as it ages.The empirical analysis provides evidence supporting the hypotheses under a set of definitions of RC and supply shocks. A price premium is found to be charged to RC buyers when compared to their nomad counterparts. In return, RC buyers enjoy a more reliable supply: they are rationed less frequently and less severely than buyers not in an RC. In this regard, the premium that RC buyers pay is essentially a premium for quantity insurance. RC traders adjust RC price as well as RC premium to sustain the relationship under supply shocks on the spot market. As a result, variation in prices is smaller in relational transactions than in that in spot exchanges. Further, the RC premium increases as the relationship accumulates number of transactions, indicating an increase in RC value over time. Together, these findings highlight the value of RC in a well-functioning market by showing that it functions as an informal insurance contract to mitigate quantity and price risks under stochastic supply and volatile prices in the market. The potential of RC as a promising vertical coordination mechanism, even when markets develop and become more efficient, is thus highlighted.

Since the passage of the Agricultural Marketing Agreement Act of 1937, the Federal Milk Marketing Orders (FMMOs) have overseen sales of milk within regions comprising the majority of milk production and processing in the United States. The stated objective of the FMMOs is to support milk producers by establishing minimum prices for farm milk across four end-use product classes and by ensuring farmers are paid a weighted average of the minimum class prices. To the extent that prices paid for farm milk are higher due to FMMO pricing rules than they otherwise would be, milk production is also higher than it would be in the absence of the FMMOs. This dissertation investigates the impact of FMMO pricing rules on the geographic distribution of milk production, inter-regional shipments of farm milk, and the value of manufactured dairy products and dairy product exports. Chapter 1 provides an introduction and Chapter 2 outlines the history of U.S. dairy policy and introduces the regulatory structure of the FMMOs. Chapter 2 also explores regional milk supply and demand through a graphical model based on the foundational literature that describes the incentives to ship raw milk created by FMMO regulations. Chapter 3 introduces methods for calculating inter-regional trade flows in dairy products and feed crops from available data. Finally, Chapter 4 expands on the analysis in Chapter 2 and the data developed in Chapter 3 by developing and calibrating a simulation model of the dairy supply chain in the United States.Milk marketing orders use a system of classified pricing to define minimum prices that buyers must pay based on the intended end use of the milk purchased. This system uses a price differential intended to set the minimum price paid by beverage milk processors above the prices paid for milk used in more heavily processed dairy products. High transportation costs lead to local markets for beverage products with relatively inelastic demand, which allows for this price discrimination to generate additional revenue for dairy farmers. This additional revenue is redistributed through a blend price, a weighted average of the classified prices that ensures all participating dairy farmers in a marketing order region receive a uniform minimum price. These two mechanisms, classified pricing and revenue pooling, were explored in a series of papers in the 1960s and 1970s to show the impact of FMMO regulations on milk production and social welfare. In Chapter 2 I extend these models by incorporating the bilateral trade relationship between two regions, with and without marketing order pricing rules in place, to demonstrate the incentives that lead to farm milk shipments between regions. The model shows that FMMO regulations lead to increased milk production in both regions, greater shipments of farm milk between regions, and more milk used in more heavily processed dairy products rather than beverage products. To the extent that manufactured dairy products are more easily traded internationally, increased production of these products leads to an increase in exports.While some of the data I use in more intensive modeling of regional dairy markets are readily available, detailed information on bilateral trade within the United States is not. Chapter 3 details a method used to interpolate the value of inter-regional trade in dairy products and feed crops using a gravity approach and available data on regional production and consumption. Survey data provides some information on inter-regional shipments but is often unavailable. Gravity models are commonly used in the international trade literature to model bilateral trade between countries, and they have been extended to develop regional trade flow matrices and input-output tables at a sub-national level. Chapter 3 develops and explains substantial data on dairy product and feed crop production, consumption, and inter-regional trade.Chapter 4 develops, calibrates, and presents simulation results from a multi-market equilibrium trade model that shows empirically the extent to which FMMO pricing rules affect the quantity of milk produced in each region, shipments of farm milk between regions, the value of regional production of dairy products, and the value of dairy product exports from each region. The model allows for calculation of welfare impacts after removal of the FMMO pricing rules, from which I determine the impact on buyers of dairy products in the U.S., buyers of U.S. dairy products in the rest of the world, and crop producers. Due to the longstanding nature of the milk marketing order policies, the simulation approach reflects the impacts of removing FMMO pricing rules rather than adding regulation to a previously unregulated system. The model is calibrated to a baseline scenario with FMMO pricing rules in place, then used to explore a counterfactual scenario where the FMMO pricing rules are eliminated, removing classified pricing in each FMMO region.Chapter 4 has four main results addressing the primary research questions investigated in this dissertation. First, milk production declines in each region and falls by 1.3 percent nationally. Second, the total quantity of farm milk shipped between regions declines by 3.1 percent, but with a range of impacts regionally. Third, the value of U.S. dairy products falls by 0.2 percent and the value of dairy product exports falls by 0.3 percent. Finally, buyers of dairy products in the U.S. gain $323 million due to the decline in dairy product prices.