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By 2050, the U.S. plans to increase solar energy from 3% to 45% of the nation’s electricity generation. Quantifying wildfire smoke’s impact on solar photovoltaic (PV) generation is essential to meet this goal, especially given previous studies documenting sizable PV output losses due to smoke. We quantify smoke-driven changes in baseline solar resource availability [i.e., amount of direct normal (DNI) and global horizontal (GHI) irradiance] at different spatial and temporal scales using radiative transfer model output and satellite-based smoke, aerosol, and cloud observations. We show that irradiance decreases as smoke frequency increases at the state, regional, and national scale. DNI is more sensitive to smoke with sizable losses persisting downwind of fires. Large reductions in GHI–the main PV resource–are possible close to fires, but mean GHI declines minimally (<5%) due to transported smoke. PV resources remain relatively stable across most of CONUS even in extreme fire seasons. Wildfire smoke increasingly covers large swaths of the US at a time when solar energy is rapidly expanding. Yet, average photovoltaic solar resource losses remain modest outside areas immediately near active fires, where plumes are fresh and dense.

The recent legalization of marijuana in several states has led to increased public interest regarding the effect of legalization on crime. Yet, there is limited empirical evidence relating the legalization of marijuana use and distribution to criminal activity. This paper uses a difference-in-differences design to estimate the effect of marijuana dispensary openings on local crime rates in Denver, Colorado. We find that the opening of dispensaries actually decreases violent crime rates in above median income neighborhoods, an important finding in light of increased political debate surrounding legalization. We also find robust evidence that non-marijuana drug-related crimes decrease within a half-mile of new dispensaries but do not simultaneously increase within a half-mile to mile of new dispensaries, with one possible explanation being that legal marijuana sales and hard drug sales are local substitutes. Finally, in line with previous research, we find that vehicle break-ins increase up to a mile away from new dispensaries.

BACKGROUND:Violence is a leading cause of death and an important public health threat, particularly among adolescents and young adults. However, the environmental causes of violent behavior are not well understood. Emerging evidence suggests exposure to air pollution may be associated with aggressive or impulsive reactions in people. METHODS:We applied a two-stage hierarchical time series model to estimate change in risk of violent and non-violent criminal behavior associated with short-term air pollution in U.S. counties (2000-2013). We used daily monitoring data for ozone and fine particulate matter (PM2.5) from the Environmental Protection Agency and daily crime counts from the Federal Bureau of Investigation. We evaluated the exposure–response relationship and assessed differences in risk by community characteristics of poverty, urbanicity, race, and age. RESULTS:Our analysis spans 301 counties in 34 states, representing 86.1 million people and 721,674 days. Each 10µg/m change in daily PM2.5 was associated with a 1.17% (95% CI0.90, 1.43) and a 10ppb change in ozone with a 0.59% (95% CI0.41, 0.78) relative risk increase (RRI) for violent crime. However, we observed no risk increase for non-violent property crime due to PM2.5 (RRI0.11%; 95% CI-0.09, 0.31) or ozone (RRI-0.05%; 95% CI-0.22, 0.12). Our results were robust across all community types, except rural regions. Exposure–response curves indicated increased violent crime risk at concentrations below regulatory standards. CONCLUSIONS:Our results suggest that short-term changes in ambient air pollution may be associated with greater risk of violent behavior, regardless of community type.

We develop a marketing-centric framework for delivering affordable, clean energy to consumers by leveraging the marketing 4 Ps to encourage a bi-directional flow of information between firms and consumers. Using a multimethod approach that covers a consumer survey, field experiment, and a decarbonization simulation to test the various aspects of the framework, our findings point to the need for a “system-wide” solution. Specifically, we examine consumer responsiveness to multiple levers within the 4 Ps, showcase the real effects of a combination of an automated solution and dynamic electricity pricing on behavior, and examine the role of dynamic prices and automation in transitioning to 100% clean electricity. We argue that there are ways to achieve affordable, 100% clean energy that many consumers will adopt. We conclude with a set of research questions examining additional aspects of the 4 Ps that can be leveraged to facilitate the wide-spread adoption of clean energy solutions.

Social interactions are widely understood to influence consumer decisions in many choice settings. This paper identifies causal peer effects in residential water conservation during the summer using variation from movers. We classify high-resolution remote sensing images to provide evidence that conversions of green landscaping to dry landscaping are a primary determinant of the reductions in water consumption. We also find suggestive evidence that without a price signal, peer effects are muted, indicating a possible complementarity between information and prices. These results inform water use policy in many areas of the world threatened by recurring drought conditions.

In this paper, we introduce a previously unused instrumental variable to estimate the elasticity of commercial water demand for firms served by a large municipal utility. We then present evidence that firms are more responsive to one-period lagged average price than marginal price. Finally, we find notable differences in elasticity among different categories of businesses. The findings in this paper are particularly important as water utilities consider how to maintain revenue while coping with limited water supplies and increasing commercial demand.

This paper develops a new approach for estimating willingness to pay (WTP) for public goods using referendum voting data, and we demonstrate the approach by applying it to a series of referenda in California spanning a wide array of public goods. We find a range of annual WTP values for successful propositions from $3.47 per person for children's hospitals to $94.48 per person for transportation infrastructure and management. We also impute the per capita cost of each proposition. Comparing these imputed costs to our WTP measure allows us to infer the upper bound on prices that would still ensure passage of a successful measure. Conversely, this comparison provides an estimate of the decrease in prices that would have been necessary to ensure passage of unsuccessful propositions. In addition, we estimate the relative effects of prices, income, and ideology on the support for public goods.We show that both ideology and economic costs have significant impacts, which stands in contrast to previous work that contends that voting patterns are driven purely by fiscal costs.

In residential electricity consumption, informational interventions such as in-home displays and social-comparisons have been shown to increase the salience of price changes and impact an electricity system: the times when demand is at its highest and conservation is needed most. This paper examines the relative effectiveness of passive and active information interventions on appliance-level, household electricity consumption in two randomized field experiments over a two year period. The first field experiment focuses on critical peak pricing (CPP) on summer days during peak evening hours where the price is higher and the second on off-peak, lower price nights. The contribution of our research is three fold. Our results have important welfare and policy implications. The consumer welfare gain from reduced critical peak consumption over 27 critical peak days applied to the Energy Reliability Council of Texas region is about $39.1 million. Similarly, reducing price during off-peak periods increases consumer welfare by about $ 100 million due to load shifting. Further, our results point to the appliance usage most amenable to energy conservation during critical peak time.

This dissertation combines three essays that explore the economics of energy and the environment. The first essay provides empirical evidence of the theory of the second best. I estimate how policy uncertainty and technology constraints that caused unexpected increases in the Renewable Fuel Standard (RFS) credit price affected U.S. oil refinery wholesale prices, markups, marginal costs, and production decisions. I employ a production function approach, combined with confidential refinery level data, to jointly estimate markups and marginal costs without relying on standard structural assumptions regarding consumer demand or competition. I find that increases in the RFS credit price increased markups and marginal costs for regulated fuels - gasoline - and decreased markups for non-regulated fuels in 2013-2014. This implies that the RFS credit price was more than fully passed onto gasoline prices during this period. I find that refineries also reallocated production to non-regulated fuels in response to increases in the RFS credit price, leading to$35-$ 179 million in leaked emissions damages. Finally, I use the pass-through and markup results to estimate the incidence of policy uncertainty. I find that 94% of the burden of the RFS credit price was borne by gasoline consumers. The second essay examines the theoretical conditions that allow for the findings of the first essay. Specifically, I derive conditions under which regulation, such as the RFS, can increase' profits. The model setup includes imperfectly competitive firms and a competitive fringe. Unlike previous work that depends on the presence of multiple oligopolists, I show that the presence of the cornpetitive fringe relaxes conditions on the elasticity of demand resulting in a potential profit increase for a residual monopolist. Additionally, the competitive fringe may benefit from regulation. The third essay develops a new approach for estimating willingness to pay (WTP) for public goods using referendum voting data. My coauthor and I demonstrate the approach by applying it to a series of referenda in California spanning a wide array of public goods. We find a range of annual WTP values for successful propositions from$2.21 per person for water quality, flood control, and coastal protection to $ 38.85 per person for public school funding. Comparing estimated WTP values for the median and marginal voters provides an upper bound on prices that would still ensure passage of successful propositions. Conversely, this comparison provides an estimate of the decrease in prices that would have been necessary to ensure passage of unsuccessful propositions. In addition, we estimate the relative effects of prices, income, and ideology on the support for public goods. We show that both ideology and economic costs have significant impacts, which stands in contrast to previous work that contends that voting patterns are driven purely by fiscal costs.