In the State of Ohio, the electric regulatory landscape permits local governments to become energy suppliers to residents and small businesses through community choice aggregation (CCA). Some CCAs provide enrollees 100% renewable electricity. Concurrently, the federal government offers an income tax credit (ITC) for the purchase of a solar array. With policy incentives, it is important to ensure they encourage behavior beyond the baseline scenario without the ITC. This is known as “additionality.” Renewable aggregation programs may crowd out the benefits of the ITC, violating additionality. This paper assesses additionality of the ITC in the context of Ohio’s CCA programs. The actual additionality can depend on whether renewable energy is already being supplied to the site of a solar array. Hence, we study the relationship between CCA and solar adoption probability to determine whether tax incentives are additional. Using panel data methods and post-estimation simulations, we discern if additionality is violated where these programs overlap. We find aggregation programs increase the probability of solar adoption and that $0.79 of every dollar spent on the income tax credit in Ohio is non-additional. This will help policymakers determine the efficacy of funds allocated to their programs.

In this paper, I discuss dual collective action problems in which a resource pool has simultaneous common pool and public good aspects in its usage, such as hunting (consumption) and conservation of wildlife. I then implement laboratory experiments to evaluate how spillovers between the two related uses of nature affect the consumption and conservation habits of stakeholders. The Nash predictions suggest that even the most selfish of profit-maximizing agents have an incentive to provide equally towards resource consumption and conservation when resource spillovers are present. Results from laboratory experiments are consistent with this hypothesis. As a policy intervention, I introduced and later revoked a common pool licensing policy based on U.S. hunting and fishing licensing. Under the same theoretical framework, removing a common pool licensing policy would increase welfare for all resource stakeholders. Contrary to this, experimental evidence indicates no overall change in welfare.

We revisit the nonconsensual econometric works – although the natural resource curse may have flourished – on the relationship between natural resources and economic performance. We first question the two terms of the relationship. We consider the role of institutions (separately and in interaction with the variable of interest) and of a number of usual or new control variables (income inequality and current account). The model, based on development accounting, is tested using four econometric techniques on the full sample (130 countries, 1990–2019) and by sub-samples according to per capita income, illustrating the non-linearity of the relationship. Three stylized facts emerge: first, the overall results converge towards a strong blessing of resource rents on GDP per capita. This can be explained mainly by the role of these rents in countries with very high GDP per capita. Second, institutional variables significantly mitigate the negative effect or reinforce the positive effect of these resources on development. Finally, among the categories of resources considered, it is the oil rent that favors this strong natural resource blessing. The effects of the observed categories may offset each other. Detailed analyses of estimation’s results in sub-samples and articulated with the results of the full sample are also proposed.

Concentration in animal-based protein industries in the United States continues to garner the interest of policymakers, researchers, and consumers alike. We assess the impacts of industry concentration on animal productivity and downstream prices in the US broiler chicken industry between 1991 and 2019. We compile a dataset that matches annual, plant-level information on ownership and sales for all poultry processing facilities in the United States with market-level wholesale composite prices and bird yields. Consolidation over the last three decades has greatly contributed to industry concentration, leading to higher wholesale composite broiler prices (16.3%) and gains in animal productivity (2.4%).

The objective of our paper is to provide an explanation for the lack of joint adoption by farmers of cleaner technologies in banana production, specifically fallow period (FP) and disease-free seedlings (DFS). Our hypothesis is that while these technologies are synergistic from an agronomic and environmental perspective, and thus efficient from a social interest perspective, they are substitutable rather than complementary from a farmer’s private interest perspective. In other words, farmers receive lower returns from adopting both technologies together than from adopting them in isolation. To test this hypothesis, we present a unified empirical framework for assessing complementarity. We estimate a structural model of complementarity that overcomes the unobservable heterogeneity bias found in previous models using a database of 607 banana farmers in the French West Indies. Our results support our hypothesis, showing a substitution effect between FP and DFS rather than a complementarity effect. Moreover, we observe a contrasting profile of adopting farmers: smallholders who are reluctant to change adopt FP, while more specialized farmers who anticipate a pesticide ban adopt DFS. A public policy that promotes joint adoption should compensate smallholders for the cost of the DFS technology, while compensating more productive farmers for leaving their land fallow.

We analyze the equilibrium conditions in which contracts are desirable for firms (buyers) with various levels of management efficiencies procuring a factor input under two levels of quality from supplies. The quality of the factor input, which affects production efficiency, may be known to the buyer; the efficiency of the firm is not known to the supplier. We estimate, using principal-agent models, that firms with high-management efficiency do not have the incentive to pay a quality premium to suppliers, but firms operating with low management efficiency are willing to offer a price premium for quality. The model is applied to the question of preconditioning cattle for the feedlot.

In 2023 all Supplemental Nutrition Assistance Program (SNAP) participants were allowed to start grocery shopping online. This paper provides the first answer to the question: What is online shopping worth to the SNAP participant in dollars? Using meal-kit pricing and time-use data, an implicit wage rate and dollar value distribution are estimated for time saved in home food production from online grocery shopping. We report the 95th, 75th, 50th, 25th, and 5th percentile results. We simulate saving 50%, 75%, and 90% of grocery shopping time and estimate the savings per hour per meal. For example, if online shopping saved 75% of shopping time, the median saving per hour per meal would be $2.59. If a family of four made 15 to 30 meals a month, this corresponds to an implicit 5% to 11% increase in the benefits per month due to the time saved. The implicit wage rate provides simple and elegant economic insights into many aspects of food production and consumption not obtainable by just considering the money price.

Supplemental Nutrition Assistance Program (SNAP) makes an exception to its rules, which allows elderly and/or disabled individuals, their spouses, as well as homeless beneficiaries, to buy hot prepared food from restaurants if they live in a state that participates in the Restaurant Meals Program (RMP). Using the staggered countywide adoption timeline in California, coupled with a stacked difference-in-differences empirical strategy, I examine the intent-to-treat (ITT) nutritional effects of RMP on the elderly population. Overall, I find no evidence that obesity rates for the elderly are any different in counties with RMP versus those without RMP. I can statistically rule out moderate effects. Additional evidence from some of the early-adopting counties suggests that RMP is associated with a reduction in food insecurity among the elderly.

Farmers make pest and disease management decisions without facing the social costs derived from their input choices. But given the sizable externalities involved, there is a rationale for government intervention. We model the profit-maximizing problem of a representative farmer by specifying a functional form for the damage function that incorporates the biological impact of the pathogen-vector system on yield as well as the abating impact of insecticides on the vector population. We use citrus greening disease in Florida as a case study because farmers there adopted an insecticide program that caused toxicity per acre to increase by 472%. Our simulation results show that a tax rate based on toxicity provides farmers with a strong incentive to substitute highly toxic chemicals with less toxic alternatives. Such a tax is also more efficient relative to a quantity-based tax that achieves a similar reduction in toxicity because it results in a significantly lower reduction in farmers’ yield and profit.

For almost eight decades, productivity in the United States agricultural sector has substantially increased, in large extent due to the adoption of technological innovations. Despite the increased utilization of technology, questions remain regarding which producers are more likely to adopt a greater number of technological innovations. This research seeks to understand how commodity diversification strategies, farm characteristics, producer perceptions of risk, conservation, information sources, climate adaptation, and producer demographic characteristics are associated with technology adoption among beef cattle producers in the Southeast United States. Utilizing data from an online survey and an Ordered Probit model, we show that beef cattle producers who also produce fruit have an increased probability of adopting a greater number of technologies. The opposite effect is found for other commodities such as vegetables, row crops, and other livestock. Policy recommendations are also discussed.

We estimate the value of water quality improvements for recreational activities on and near the Brandywine Creek in Delaware. We divide water-based recreational activities into two groups: water-contact and non-water-contact. We then consider the behavioral change of the recreationists in each group when faced with water quality improvements posed in a stated preference (contingent behavior) survey. We use five common physical attributes of water quality in the contingent behavior analysis: water clarity, catch rate of fish, safety of eating fish, safety for swimming, and ecological health. The survey was constructed in such a way that each of these attributes of water quality is valued. The per-trip value for water quality improvements ranged from $4 to $63 for contact use and from $4 to $29 for non-contact use depending on which and how many attributes of water quality improve. Even though we measure sizable benefits, rough cost estimates appear to make it difficult for incremental improvements to exceed costs unless attribute improvement is widespread.

Commodity index trading in futures markets is a relatively new investment strategy whose consequences are not fully understood. This paper tests the hypothesis that long-only, passive index trading in agricultural futures markets influences futures prices. Vector Autoregressive (VAR) models are a common empirical research approach for analyzing index trading. Factor-Augmented Vector Autoregression (FAVAR) models are a new approach to analyzing index trading. FAVAR models can incorporate a large data set into the traditional VAR framework. Using a FAVAR model improves the analysis by including additional market factors relevant to futures price formation. Models were estimated for 13 agricultural commodities (corn, soybean, soybean oil, soybean meal, soft red winter wheat, hard red winter wheat, cotton, cocoa, sugar, coffee, live cattle, feeder cattle, and lean hog) from January 2006 to December 2022. The results demonstrate the added value of FAVAR models in explaining the dynamics between prices and index trading. The conclusions are similar to other findings that prices lead index positions; however, adding demand-related data through a FAVAR model allows for a better understanding of market dynamics.