Browsing by Author "Timmins, Christopher D"

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This dissertation is an empirical study of gentrification. Chapter 2 studies the link between gentrification and displacement, identifying the social groups most likely to be displaced and the impacts on those displaced groups using reduced form analysis. Chapters 3 turns to model residents' re-optimization decisions in housing market, investigating the welfare impacts and distributional consequences of environmental gentrification. Chapter 4 extends the distributional analysis into dual market sorting including both housing market and labor market.

Over the past several decades, cities across the U.S. have experienced gentrification and the associated socio-demographic shifts. With urban policies and shocks come to improve neighborhood conditions, neighborhood improvements lead to property market appreciation and further trigger gentrification. As this phenomenon has accelerated, concerns about gentrification-induced displacement and its impacts on incumbent residents have grown. Residents of different tenure status (renting vs. owning) and socioeconomic conditions are differently impacted by neighborhood improvements induced property market responses and also value neighborhood improvements quite differently. The possibility that property market appreciation and residential sorting make environmental improvements onerous for some residents suggests the potential of an urban policy which intended to offer welfare gain to low-income residents and renters by improving their living conditions, may actually make them worse off moving into worse neighborhood due to property market changes and residential sorting and further exacerbate social inequality and make vulnerable groups have less future outcome.

Chapter 2 studies the link between gentrification and displacement, identifying the social groups most likely to be displaced and the impacts on those displaced groups. The results provide evidence of displacement, showing that lower-income renters are significantly more likely to exit from gentrifying neighborhoods. Moreover, they tend to move to neighborhoods with significantly lower school quality and higher crime rates and have a higher probability of changing jobs and receiving lower incomes. Owners, however, are more likely to remain in gentrifying neighborhoods, benefiting from the increased amenities and rising home values. In stark contrast to renters, when these owners do move, they convert those capital gains into improved living conditions. These results provide direct evidence of how housing tenure defines the welfare consequences of environmental improvements.

Chapter 3 measures the differential welfare impacts of environmental policies across household groups. To account for property market responses and re-optimization of residential housing decisions, a dynamic model of housing decisions with endogenous tenure status (renting vs. owning) and forward-looking residents is used. The model extends the distributional analysis in four previously overlooked dimensions: differential impacts of property market appreciation on renters and owners, preference heterogeneity over public amenities, wealth accumulation corresponding to property market changes, and expectations in dynamic housing decisions. The model is estimated taking advantage of an exogenous and unexpected environmental shock and employing a unique data set (L.A.FANS Data) tracking residents? locations and tenure choices in Los Angeles County from 2000 to 2007. The results show that environmental improvements have regressive welfare impacts and favor owners more than renters. Welfare impacts can be reduced for renters and can be changed from positive to negative for low-income renters incorporating housing market responses and residential sorting. In contrast, owners of all incomes benefit more due to the capitalization of environmental improvements incorporating housing market responses. Provided that renters are more likely to be low-income earners and people of color, the differential welfare results in this paper raise the concern of environmental justice in policy design and evaluations.

Except environmental shocks/policies as the drivers of gentrification, the public sector can play an important role in neighborhood transformation through investing in physical infrastructure, structuring land use decisions, and incentivizing local business, which impact residents' choice in both housing market and labor market. Chapter 4 investigate the role of public transportation investment (new rail transit lines) on neighborhood gentrification. The massive investment in metro rail transit aims to reduce congestion and pollution, to improve transit access to regional amenities and work opportunities. It can also spur housing appreciation and labor market expansion, which induce residents' re-optimization in both housing market and labor market. Evidence show that construction of new metro rail lines increases public transportation users in both tracts with new metro rail stations and tracts with interacting metro rail stations, increase local housing price and expand residents' choice set in labor market. This paper will further develops a structural model to investigate residents' re-optimization in both housing market and labor market corresponding to neighborhood changes induced by transportation improvements to access the potential distributional impacts of transportation infrastructure improvement on residents' welfare.

This dissertation consists of three essays in economics of crime. The first chapter examines the relationship between economic inequality and crime, and provides a new theoretical explanation and empirical evidence. Economists traditionally explained the empirical relationship between inequality and crime in terms of differentials in potential criminal gains. As inequality increases, low-income individuals are likely to be left with little increase in their legitimate earnings potential but much larger increases in potential criminal gains, because there are now more wealthy potential victims who possess goods worth taking. This increase in potential criminal gains for the disadvantaged population then results in higher crime rates. While simple and intuitive, this explanation is inconsistent with the high concentration of crime victimization among the poor who offer the least potential gains to offenders. After a careful empirical analysis using recent panel data on large U.S. counties, I find evidence that the previously-reported empirical link between inequality and crime at the county-level masks two opposing effects of economic inequality underneath; crime is positively linked with economic segregation across neighborhoods, but negatively correlated with local inequality. One immediate implication of this finding is that introducing greater economic inequality, or income variability, in highly disadvantaged neighborhoods may reduce local crime, instead of increasing crime.

In the second chapter, I examine the impact of the North Carolina sex offender residency restriction on recidivism and residential outcomes of sex offenders. Sex offender residency restriction aims to reduce the danger of repeat sex offense against children by prohibiting sex offenders from living near child-related facilities. But existing research finds little evidence that the restriction lowers the risk of sex offense recidivism, and predicts that the restriction may have adverse impacts on sex offenders' community reintegration, residential stability and employment prospects, which may increase the likelihood of recidivism among sex offenders. Taking advantage of the individual-level information on North Carolina offenders' criminal and residential histories and potentially exogenous variations in sex offenders' timing of release and proximity of former residences to nearest child-related facilities, I test the hypothesis that the residency restriction causes sex offenders to be more likely to be involved in general recidivism. Estimation results indicate that the North Carolina sex offender residency restriction indeed adversely influences sex offenders' likelihoods of overall recidivism, as well as causing them to be more likely to live in high-poverty neighborhoods.

The last chapter, a joint work with Professor Philip Cook, explores the relationship between school entry age, education and crime. It has been well-documented that students who are older than their classroom peers tend to outperform their younger peers in standardized tests. On the other hand, older students are also associated with a higher rate of high school dropout, likely due to the presence of the age threshold after which students are allowed to drop out from school. Given the strong relationship between education and crime, it is of great interest the extent to which the relative educational advantages and disadvantages associated with students' relative age influences their criminal outcomes. Our analyses exploit a plausibly exogenous variation in the age in which students are enrolled in third grade, caused by the minimum age requirement for school entry in North Carolina. Based on the sample of North Carolina students, we find strong evidence that students who are relatively older than their classroom peers tend to do better in standardized reading and math tests and are more likely to be enrolled in advanced courework during the periods of primary and secondary education. Consistent with the gap in academic achievement while at school, children who are relatively older are less likely to be involved in criminal offense as juveniles. On the other hand, we also document that relatively older students are less likely to graduate from high school, and have a higher likelihood of offending as adults, likely reflecting the difference in the level of educational attainment. Our finding that the timing of school entry are associated with important costs and benefits in children's educational and criminal outcomes may have important policy implications on the optimal school entry and exit ages.

The development and dissemination of new technologies are key components of economic progress. This dissertation studies these processes in the context of hydraulic fracturing, one of the most influential technologies to come to the energy market in decades. While hydraulic fracturing has up-ended energy markets, its improved use was not easy to predict or straightforward to achieve. Furthermore, its improvement has taken place in various competitive but regulated markets, ensuring that useful empiric data has been collected throughout. The two main chapters of the dissertation study, in related hydraulic fracturing contexts, how the availability of information from rival firms affects firm decision making.

Chapter 2 examines the drilling and fracture-input decisions in North Dakota's Bakken Shale in order to study the interaction between dynamic decision making and the possibility of social learning. The chapter first confirms that operators have changed their input decisions over time in a manner that is consistent with learning about how to better use the fracturing technology. It then develops an estimates an econometric model to quantify how much the possibility of learning from other firms' wells adds to one's own option value for an undrilled well. I find that this incremental value is small in practice, but could be dramatic in other situations, and demonstrate the role that different policies can play in improving it.

Chapter 3 considers the effects of a 2012 law in Pennsylvania mandating the disclosure of the chemicals used in each hydraulic fracturing treatment. My coathors and I take advantage of a unique dataset of chemical input decsions for wells treated prior to the disclosure law taking effect. We find that operators' chemical choices following disclosure tend to be more similar to each other, in a manner consistent with copying. We further find that this copying can have some economic value -- those wells that copy more productive firms enjoy higher productivity than those that do not. Finally, there we find evidence that firms reduce innovative activity in the wake of the disclosure law. These findings suggest that regulators face a tradeoff between discovery and dissemination of new knowledge when they write disclosure regulations.

This dissertation consists of two main chapters studying different topics in politicaleconomy with a specific focus on interactions between citizens and their government.

Political economists have long been puzzled that growing levels of inequality inthe U.S. have had little effect on income redistribution, especially when compared to European countries that have adopted more redistributive economic systems. The lack of electoral support for greater income redistribution goes against the predictions of the fundamental median-voter theorem in political science. My work contributes to a large body of work in preference for redistribution literature by studying the role of private economic benefits on individual voting decisions. Using new causal machine learning methods with the Survey of Income and Program Participation, I identify structural differences in the provision of welfare benefits between Republican and Democrat presidents for various demographic groups. Combining these estimates with voting data from the General Social Survey, I can identify how people vote with respect to their private economic benefits. The results in this chapter support the idea that economic benefits positively affect individuals’ probability of voting for a particular candidate.

In another question, I study the interaction between citizens and a political leader.A government led by the political leader implements a policy, and the outcome of the policy is uncertain. There is a number of reasons why the policy outcome can be uncertain. It can be due to the impossibility of conducting a meticulous study or an experiment. Also, it can be caused by the misalignment of incentives which is inherent in policy-making (e.g., lower-level officials are not accountable to the electorate in the same way the leader is). Although the policy to be implemented is common knowledge, neither citizens nor the leader can predict its outcome due to a lack of expertise. Once a policy is implemented, citizens, not the leader, directly observe its outcome. I show that a leader driven by a desire to get reelected can impose wasteful signaling on citizens (interpreted as protests to replace a biased official or bad outcomes).

This thesis focuses on multiple themes in the field of public economics with intersectionsin development economics, environmental economics, and political economy. The overarching themes of this work are focuses on the city, institutions, and economic and environmental justice. The first chapter examines on the impact of lead abatement laws on eviction. The second chapter evaluates Myanmar’s National Community Driven Development Program. The final chapter examines the role of one’s representative on their home’s price. An abstract of each chapter is as follows:

Lead paint in old houses is the leading cause of leadpoisoning in children under 6 today. To combat this problem, several states have passed lead abatement laws, forcing landlords to remove lead in the homes they rent if tenants have children under the age of 6. However, these laws have unintended consequences, causing landlords to evict tenants rather than abate lead. I use a difference-in-differences approach while employing various model specifications with various fixed effects and sets of controls to examine the impact of Ohio’s 2003 lead abatement law on eviction rates. Using newly collected data from the Eviction Lab at Princeton University, I find that the passage of Ohio’s lead abatement law sharply increased targeted evictions. Due to the law’s passage, the average census district in Ohio faced an increased eviction rate of roughly 0.457 points, corresponding to an additional 13.93 evictions a year. These impacts are highly statistically significant, sizeable, and economically meaningful, indicating that policy makers should incorporate distributional consequences when designing future lead abatement laws in order to avoid unintended consequences and ensure equitable outcomes.

Community driven development (CDD) has become acommon method of distributing aid throughout the developing world. Founded on two guiding principles, decentralization of the aid distribution process and empowerment through participation, CDD programs encourage community involvement in all steps of the development project. We evaluate Myanmar’s National Community Driven Development Program (NCDDP) by implementing a regression discontinuity design in sampling that takes advantage of the discontinuous cutoff in program receipt at the township border by sampling matched pairs of villages across program borders. We find that CDD successfully delivers village infrastructure, in line with the results of previous CDD evaluations. Moreover, in contrast to previous findings in the literature, we find large positive effects of CDD enrollment on the diversity and quality of local governance structures and greater participation of women and ethnic minorities. Finally, we provide novel evidence that these changes in local governance are associated with detectable improvements in local public goods provision beyond the scope of the CDD program, as measured by village-level responses to the Covid-19 pandemic. In particular, CDD villages enact more significantly more of the recommended measures to contain the spread of disease. These results provide evidence that CDD participation Congressional and state representatives and their parties use their political power to send kickbacks to their districts, providing funding for public goods and targeted investment within their district. However, representatives do not have an equal ability to do this, as those with longer tenure, important committee posts, and in more competitive districts have the ability to send more kickbacks to their districts. I estimate the impact of one's representative and district, at the state house, state senate, and congressional level, on housing prices using the 2010 redistricting to identify the impact of one's representative on housing prices. I first develop a model of political competition and housing prices with testable implications to bring to the data. Using data from InfoUSA, containing roughly 130 million housing transactions per year, from 2006 to 2014, combined with data on state and federal representatives, I identify and examine the impact of one's representative on housing prices using multiple methods, including location fixed effects, a regression discontinuity design, and an instrumental variables design. I find that "packing" districts so that they are not competitive is not only used to dilute voting power, but dilute local wealth as well, that more powerful representatives use that power to increase the value of their constituents' homes, and that representatives in the party in control of the respective house are able to use this power to send kickbacks to their constituents. Not only does partisan gerrymandering come at a social and political cost, but a great economic cost as well.

This dissertation focuses on non-market valuation of environmental goods, using housing values and residential location decisions to infer the value of local environmental quality. It makes two contributions to the literature:

First, it explores the role of expected longevity in environmental risks valuation in a framework where individuals face multiple mortality and morbidity risks.The presence of background mortality risk from the causes unrelated to pollution reduces the willingness to pay for environmental risks reduction, because the competing risk lowers the chance that the consumer will be alive to benefit from environmental quality improvements. Using data from the Health and Retirement Study, we find that individuals with shorter expected lifespan are more likely to reside near toxins-emitting facilities. The effect of the longevity expectations is significant as compared to other determinants of environmental risk exposure identified in the previous literature, such as level of education, race, and wealth. These findings imply that the expected longevity can be an important source of heterogeneity in environmental risks valuation.

Second, we find evidence that owner-assessed home values "lag behind" market prices, and that this lag has the potential to substantially alter values ascribed to local amenities using property-value hedonic techniques. We hypothesize that long-standing homeowners lack an incentive to gather recent information on housing markets, and that their ignorance is reflected in the bias in their self-reported housing values. We first demonstrate that bias in self-reported home values is significantly correlated with tenure. We then examine how tenure length affects homeowners' valuation of changes in a particular local amenity — exposure to sites on the EPA's National Priorities List (i.e., the Superfund program). We find that recent movers report a value of a site's deletion from that list (signaling the end of the Superfund remediation process) that is 30-50% greater than that expressed by long-standing owners. This difference is significant and can have important implications for the results of cost-benefit analysis.

Preference heterogeneity is a driving force in the evolution of urban landscape. Combined with historical conditions, it can perpetuate existing inequality through residential sorting. This dissertation contributes to the literature in residential sorting and hedonic valuation to understand how preference heterogeneity affects location decisions and social welfare.

In chapter 1, I estimate the hedonic prices of particulate matter and nitrogen oxide using panel data from Glasgow, Scotland under a variety of functional form assumptions. I find that housing prices are the most elastic with respect to PM2.5 and the least elastic with respect to NOx. The hedonic price for all pollutants decreased from 2001 to 2011. At the median pollutant level, housing price elasticity of PM2.5, PM10, and NOx are -0.2 to -0.46, -0.17 to -0.48, and -0.05 to -0.3 respectively.

Chapter 2 examines the long term effects of neighborhoods on shaping individuals' religious attitudes and quantifies the implications for inequality. I develop and estimate a residential sorting model using new individual-level panel data in Glasgow, Scotland. I allow the marginal utility for neighborhood religious composition and marginal utility of income to vary by the individual's current income and childhood religious background. I find those with Catholic and non-Christian childhood backgrounds have much stronger religious homophily than those with Protestant/secular childhood background, and this religious homophily contribute to the intergenerational persistence of poverty traps.

Chapter 3 uses a household survey in Lahore, Pakistan to estimate a model of joint work and commuting mode choice accounting for heterogeneity in preferences and opportunity costs. Detailed information on individual trips across the city allows me to calculate the commute times for all neighborhood-to-local labor market combinations. I find that a nested logit model where individual are assumed to choose between work locations then choose commuting mode provides a good fit for the data. Estimates from the nested logit model suggest that travel time is a disamenity across all education levels, but less so as education level rises. The marginal willingness to pay (MWTP) to reduce commuting time by one minute per day ranges from 104 to 168 Rupees depending on education level.

This dissertation is an empirical study of the livestock industry and its environmental impacts on residents. Concentrated animal feeding operations, abbreviated as CAFOs, are livestock production facilities where large numbers of animals are raised in confined spaces. Although the hog and poultry industries provide jobs and economic benefits, they also produce significant air pollution, contaminate waterways, and affect people's quality of life. North Carolina (NC) is currently the third largest hog producing state in the nation and also hosts a high concentration of poultry farms. Most of the animal farms are located in the eastern area of the state, which is also the area where many low-income people and people of color (POC) reside.

Because of environmental pollution produced by CAFOs, local real estate markets could be affected. Chapter 4 examines how having CAFOs nearby could affect housing price. In this co-authored paper, we utilize housing transaction data from CoreLogic and study the impacts of CAFOs on housing price. We consider co-location of hogs and poultry and separately examine the impacts for houses on private wells and community water systems as water contamination is channeled as an important exposure route. Results show significant housing price reductions for nearby housing properties. The costs increase disproportionately for really large CAFO exposure and are even larger for the houses with private wells. We find that being exposed to the highest levels of exposure to hogs could cause housing price decreases ranging from 13% to 50% for houses with private wells, while only a 13% to 27% price decrease for community-water-dependent houses, depending on the distance between CAFOs and the residential property.

In NC, most of the farms are located in the eastern region, where many communities of color and low-income populations live, and such high concentration raises environmental justice concerns. Chapter 5 explores the relationship between race and income and exposure to CAFOs. In this co-authored paper, we collect information on both hog and poultry farms, use novel micro-data from InfoUSA, and investigate how exposure varies by both income and race. We find POC are more likely to be exposed to both hogs and poultry. Results show strong evidence of high exposure for low-income Hispanic households, compared to white households. Higher income helps reduce the exposure gap for Hispanics, but does not similarly help Black residents, suggesting such uneven exposure patterns are more related to race other than class.

Climate change brings another challenge to CAFOs. During the past two hurricane events in NC, Hurricane Matthew (2016) and Hurricane Florence (2018), CAFOs caused large damages to local communities and contaminated neighborhood drinking water sources. In my job market paper, I first use individual demographic data from InfoUSA to examine household's out-migration behaviors after floods. Results suggest floods make people move out, especially for those with CAFOs around or with private wells. Besides out-migration behaviors, this study also examines how household race and income composition change after floods. Results show more lower-income and POC households move into flooded areas, especially places near animal farms, after floods. Such migration patterns highlight equity concerns under climate change and in the future hurricane events.

The dissertation consists of three chapters related to the low-price guarantee marketing strategy and energy efficiency analysis. The low-price guarantee is a marketing strategy in which firms promise to charge consumers the lowest price among their competitors. Chapter 1 addresses the research question "Does a Low-Price Guarantee Induce Lower Prices'' by looking into the retail gasoline industry in Quebec where there was a major branded firm which started a low-price guarantee back in 1996. Chapter 2 does a consumer welfare analysis of low-price guarantees to drive police indications and offers a new explanation of the firms' incentives to adopt a low-price guarantee. Chapter 3 develops the energy performance indicators (EPIs) to measure energy efficiency of the manufacturing plants in pulp, paper and paperboard industry.

Chapter 1 revisits the traditional view that a low-price guarantee results in higher prices by facilitating collusion. Using accurate market definitions and station-level data from the retail gasoline industry in Quebec, I conducted a descriptive analysis based on stations and price zones to compare the price and sales movement before and after the guarantee was adopted. I find that, contrary to the traditional view, the stores that offered the guarantee significantly decreased their prices and increased their sales. I also build a difference-in-difference model to quantify the decrease in posted price of the stores that offered the guarantee to be 0.7 cents per liter. While this change is significant, I do not find the response in comeptitors' prices to be significant. The sales of the stores that offered the guarantee increased significantly while the competitors' sales decreased significantly. However, the significance vanishes if I use the station clustered standard errors. Comparing my observations and the predictions of different theories of modeling low-price guarantees, I conclude the empirical evidence here supports that the low-price guarantee is a simple commitment device and induces lower prices.

Chapter 2 conducts a consumer welfare analysis of low-price guarantees to address the antitrust concerns and potential regulations from the government; explains the firms' potential incentives to adopt a low-price guarantee. Using station-level data from the retail gasoline industry in Quebec, I estimated consumers' demand of gasoline by a structural model with spatial competition incorporating the low-price guarantee as a commitment device, which allows firms to pre-commit to charge the lowest price among their competitors. The counterfactual analysis under the Bertrand competition setting shows that the stores that offered the guarantee attracted a lot more consumers and decreased their posted price by 0.6 cents per liter. Although the matching stores suffered a decrease in profits from gasoline sales, they are incentivized to adopt the low-price guarantee to attract more consumers to visit the store likely increasing profits at attached convenience stores. Firms have strong incentives to adopt a low-price guarantee on the product that their consumers are most price-sensitive about, while earning a profit from the products that are not covered in the guarantee. I estimate that consumers earn about 0.3% more surplus when the low-price guarantee is in place, which suggests that the authorities should not be concerned and regulate low-price guarantees. In Appendix B, I also propose an empirical model to look into how low-price guarantees would change consumer search behavior and whether consumer search plays an important role in estimating consumer surplus accurately.

Chapter 3, joint with Gale Boyd, describes work with the pulp, paper, and paperboard (PP&PB) industry to provide a plant-level indicator of energy efficiency for facilities that produce various types of paper products in the United States. Organizations that implement strategic energy management programs undertake a set of activities that, if carried out properly, have the potential to deliver sustained energy savings. Energy performance benchmarking is a key activity of strategic energy management and one way to enable companies to set energy efficiency targets for manufacturing facilities. The opportunity to assess plant energy performance through a comparison with similar plants in its industry is a highly desirable and strategic method of benchmarking for industrial energy managers. However, access to energy performance data for conducting industry benchmarking is usually unavailable to most industrial energy managers. The U.S. Environmental Protection Agency (EPA), through its ENERGY STAR program, seeks to overcome this barrier through the development of manufacturing sector-based plant energy performance indicators (EPIs) that encourage U.S. industries to use energy more efficiently. In the development of the energy performance indicator tools, consideration is given to the role that performance-based indicators play in motivating change; the steps necessary for indicator development, from interacting with an industry in securing adequate data for the indicator; and actual application and use of an indicator when complete. How indicators are employed in EPA’s efforts to encourage industries to voluntarily improve their use of energy is discussed as well. The chapter describes the data and statistical methods used to construct the EPI for plants within selected segments of the pulp, paper, and paperboard industry: specifically pulp mills and integrated paper & paperboard mills. The individual equations are presented, as are the instructions for using those equations as implemented in an associated Microsoft Excel-based spreadsheet tool.

There is growing evidence suggesting that neighborhoods play a crucial role in the accumulation of human capital and have tremendous effects on the opportunities available to people who live in them. The fact that selecting a neighborhood where to live has become one of the main economic choices that a household makes has raised concerns that some household may be systematically excluded from the most beneficial areas, which may contribute to the persistence of inequality. This dissertation studies two important factors that have been limiting the ability of households in the United States to choose where to live: discrimination and exorbitant housing prices. Chapter 2 and chapter 3 study two possible solutions that have been proposed to help increase the availability of affordable housing for rental and for purchase respectively: nonprofit housing development and community land trusts. Chapter 4 studies a channel that has been systematically excluding minority buyers from desirable neighborhoods: discrimination by real estate agents.

Chapter 2 examines the neighborhood spillover effects of rental housing development by nonprofit and for-profit developers in Philadelphia. Nonprofits, which receive public subsidies and prioritize affordability goals over profit maximization, are believed to produce significant benefits to surrounding neighborhoods. The study finds that nonprofit development has localized effects, with slightly higher home values and lower moving probabilities for households within 200m of the development, but no detectable effect on income. At a greater distance (between 600 and 800m), there are slightly less positive effects on house values and slightly more positive effects on moving probability compared to for-profit development.

Chapter 3 examines the effect of Community Land Trusts (CLTs) on neighborhood composition and affordability. CLTs are nonprofit organizations that buy and resell houses at subsidized prices while retaining ownership of the land and leasing it to homeowners with long-term agreements to maintain affordability. The study finds evidence that neighborhood housing values decrease in the vicinity of CLT properties and so does the probability of displacement decreases for Black and Hispanic households, suggesting that CLTs help residents at higher risk of displacement to remain in their neighborhood.

Chapter 4 investigates the impact of real estate agents on housing market outcomes, with a particular focus on discriminatory behavior. Real estate agents play a critical role in the housing market, and any discriminatory behavior on their part could perpetuate historic segregation patterns. The chapter aims at distinguishing steering (discrimination) from preference-based sorting by developing a statistical discrimination test.

This dissertation consists of three studies on the economics of drug abuse, criminal activity, and enforcement. The first essay seeks to understand the impacts of enforcement actions taken against doctors on the supply of prescription opioids, black-market prices, and health outcomes. Exploiting plausibly exogenous variation in the timing and location of controlled substance license audits, I find that cracking down on a single doctor decreases county-level opioid dispensing by 10\%. This decline in legal supply persists across space and time and results in a 44\% increase in the black-market pill price. Significant heroin substitution also occurs, yet for each additional heroin overdose death, there are two fewer non-heroin opioid overdose deaths. The mortality declines are strongest among young and prime-aged men. These results highlight a novel tradeoff policymakers should consider when attempting to address drug abuse through targeted supply-side enforcement: reductions in the flow of new users must be balanced against the harm that arises when existing users substitute to more dangerous drugs.

The second chapter provides evidence on the incentives of police. More specifically, using geocoded crime data and a novel source of within-city variation in punishment severity, I am able to shed light on enforcement behavior. I find that in parts of a city where drug sale penalties were weakened, there is a 13\% decrease in drug arrests within a year; there is no displacement of non-drug offenses and majority black neighborhoods have a larger decline in drug arrests. If offenders were significantly deterred by harsher penalties, as the law intended and standard models of criminal behavior predict, there should have been an increase in drug sale arrests. My results are therefore consistent with police treating enforcement effort and punishment severity as complementary. I also find that city-wide crime and drug use do not increase following the weakening of drug sale penalties. Taken together, my results call into question the ``War on Drugs'' view of punishment and suggest that certain types enforcement can be reduced without incurring large public safety costs.

The third chapter investigates how rebel groups choose between funding strategies using a unique panel dataset on the activities of 297 groups. I find that when the world price of a natural resource they exploit rises, rebel groups substitute away from extortion, smuggling, kidnapping, and theft. These results suggest that policies attempting to shut down these groups by cutting their main sources of funding may produce harmful unintended consequences in the short run.

Natural gas extraction is a prevalent and growing source of energy supply in the United States and around the world, and the focus of my research is understanding the natural gas leasing market that allows firms to amass rights to the mineral estate from which they extract natural gas. In Texas, a major source of natural gas resources, the mineral rights are privately owned, and firms must negotiate with private landowners for the rights to drill for and extract those minerals. The negotiated leases are legally binding contracts that restrict firm behavior during the drilling and production phases of natural gas well development. The leases that firms and landowners sign are critical in protecting them against exposure to health risks and the other negative features of drilling activity (noise, disruption, etc.). The research presented quantifies the value of these leasing contracts and models the leasing market between firms and landowners bilaterally negotiating the contents of the leases. The first piece studies a mechanism that models how firms negotiate with individual landowners and identifies the observable characteristics driving their decision-making, both where to sign a lease and with which landowner. The second piece captures the value of more protective leasing contracts for the landowners using a property value hedonic method. The third piece explores whether the leasing quality is equitably distributed across all types of households living in Tarrant County Texas, my area of study. Below I detail the the methods and questions addressed by each chapter individually.

As a consequence of technological innovation in the oil and natural gas industry over the last 20 years, firms have increased access to oil and natural gas reserves trapped in tight-shale formations. New wells are now drilled in more densely populated regions. In the first chapter, the lease negotiations between firms and landowners are modeled as a two-sided, one-to-many matching model where firms' preferences over sets of parcels are complementary. With this model, I study the direct and indirect effects of firms' geographic market concentrations. Firms value concentration directly because it shortens the time between leasing mineral rights and profiting from natural gas sales. Lease concentration also has an indirect effect: firms with higher concentrations are able to sign less costly leases, suggesting that concentration leads to market power. I use the estimated model to analyze the effects of changes in the market structure and policies that restrict the quality of leases signed. I am able to predict the effects of these policies on firms' and landowners' values of negotiating, and the changes in the spatial distributions of leasing behavior. I find that homogeneous and high quality leases increase landowners' values, while the effect for firms is ambiguous, and overall, fewer leases are signed when all leases are restricted to be homogeneous.

Royalty payments are a potential source of benefit to homeowners, and contractual restrictions on firms' drilling and production activities that are negotiated in leases are an important tool by which the industry is regulated. This chapter demonstrates how the value of lease clauses to homeowners can be recovered from the hedonic price gradient in the market for split-estate houses. Additionally, we show how split-estate status can be recovered from lease records and transaction data using string matching techniques. However, we note that the distribution of split-estate house prices is truncated, which may engender selection bias. We show how the dual-gradient hedonic model can be used to recover an expression for the willingness-to-pay for lease clauses using the full-estate housing market. Combining data describing both the full and split housing markets overcomes any potential selection problems and yields consistent estimates of the willingness-to-pay for lease clauses. Our hedonic results provide a measure of the benefits to homeowners from the regulations negotiated in leases and suggest that factors affecting the outcomes of lease negotiations will have pecuniary impacts on homeowners. Further, we use our willingness-to-pay measures to construct an index of lease clause quality that is used to test an environmental justice hypothesis: are there significant differences in lease quality across race groups after conditioning upon income and other observable factors.

Finally, the third chapter explores factors driving the tract-level, heterogeneity in lease quality for mineral rights owners transferring their mineral rights to natural gas firms for the purpose of drilling and extracting natural gas. The data consists of tract-level aggregates of lease terms, our measures of lease quality, and tract-level census data from leasing. We find that greater lease quality is negatively correlated with higher concentrations of minority households when controlling for tract-level characteristics. Based on our findings, we propose policies reducing the observed heterogeneity in lease quality, and subsequently, reduce exposure to the negative effects of living nearby active well sites.

In the first chapter of this dissertation, I outline a hedonic equilibrium model that explicitly controls for moving costs and forward-looking behavior. Hedonic equilibrium models allow researchers to recover willingness to pay for spatially delineated amenities by using the notion that individuals "vote with their feet." However, the hedonic literature and, more recently, the estimable Tiebout sorting model literature, has largely ignored both the costs associated with migration (financial and psychological), as well as the forward-looking behavior that individuals exercise in making location decisions. Each of these omissions could lead to biased estimates of willingness to pay. Building upon dynamic migration models from the labor literature, I estimate a fully dynamic model of individual migration at the national level. By employing a two-step estimation routine, I avoid the computational burden associated with the full recursive solution and can then include a richly-specified, realistic state space. With this model, I am able to perform non-market valuation exercises and learn about the spatial determinants of labor market outcomes in a dynamic setting. Including dynamics has a significant positive impact on the estimates of willingness to pay for air quality. In addition, I find that location-specific amenity values can explain important trends in observed migration patterns in the United States.

The second chapter of this dissertation describes a model which estimates willingness to pay for air quality using property value hedonics techniques. Since Rosen's seminal 1974 paper, property value hedonics has become commonplace in the non-market valuation of environmental amenities, despite a number of well-known methodological problems. In particular, recovery of the marginal willingness to pay function suffers from important endogeneity biases that are difficult to correct with instrumental variables procedures [Epple (1987)]. Bajari and Benkard (2005) propose a "preference inversion" procedure for recovering heterogeneous measures of marginal willingness to pay that avoids these problems. However, using cross-sectional data, their approach imposes unrealistic constraints on the elasticity of marginal willingness to pay. Following Bajari and Benkard's suggestion, I show how data describing repeat purchase decisions by individual home buyers can be used to relax these constraints. Using data on ozone pollution in the Bay Area of California, I find that endogeneity bias and flexibility in the shape of the marginal willingness to pay function are both important.

Finally, in the third chapter of this dissertation, I combine the insights of the Bajari-Benkard inversion approach employed in second chapter with more standard estimation techniques (i.e., Rosen (1974)) to arrive at a new hedonic methodology that allows for flexible and heterogeneous preferences while avoiding the endogeneity problems that plague the traditional Rosen two-stage model. Implementing this estimator using the Bay Area ozone data, I again find evidence of considerable heterogeneity and of endogeneity bias. In particular, I find that a one unit deterioration in air quality (measured in days in which ozone levels exceed the state standards) raises marginal willingness to pay by $145.18 per year. The canonical two-stage Rosen model finds, counter-intuitively, that this same change would reduce marginal willingness to pay by $94.24.

This dissertation investigates the non-market value of environmental quality in several contexts with attention paid to equilibrium effects. Chapter One contributes to the ongoing debate concerning the effect of various actions taken by the U.S. Environmental Protection Agency under CERCLA, commonly known as the Superfund Program, on housing prices. The study differs from national sample analyses and site-specific analyses by providing policy-relevant estimates of the hedonic price function in a particular region for the average site. Further, an estimate of the effect on housing prices is given for each of the major events that occur under a typical Superfund remediation. Using house and time-varying census tract fixed effects, I find a 7.3% increase in sales price for houses within 3 km of a site that moves through the complete Superfund program. The analysis gives evidence of positive price appreciation for housing markets and serves as a lower bound for measuring remediation benefits. Chapter Two proposes a new dynamic general equilibrium model of residential location choice with social spillovers and uses it to evaluate the equilibrium consequences of changes in pollution exposure. In particular, I investigate the hypothesis of ``minority move-in,'' which postulates that disproportionate exposure to pollution results from minorities and low-income households trading off such exposure for lower housing costs. Second, I address the question of whether economic incentives caused by differences in willingness to pay across socioeconomic status can explain why polluters disproportionately locate near disadvantaged populations in order to minimize expenses from collective action bargaining over the negative externality. Simulations indicate ``minority move-in'' likely does account for some of the imbalance in exposure to pollution across socioeconomic status. Further, general equilibrium estimates reveal that equilibrium sorting behavior widens the gap in willingness to pay for environmental quality between minority and white households, and between high and low-income households. The disparity in general equilibrium willingness to pay to avoid toxic emissions provides economic incentives for polluters to target disadvantaged populations. Chapter Three investigates how information contained in the U.S. Environmental Protection Agency's Toxic Release Inventory program affects prices in the housing market. First, I use a reduction in the reporting requirement threshold in 2001 as a quasi-experiment to determine whether prices change for existing firms who, as a result of the change, must report. Second, the existence of a reporting threshold creates a discontinuity in treatment than can be exploited. I estimate a regression discontinuity model that assumes that site unobservables are balanced in a neighborhood of the discontinuity. Using a difference-in-differences estimator for the first specification, I find that listing a site in the Toxic Release Inventory lowers prices by 3.1% within a three kilometer radius of the site, and that the effect is stronger at shorter distances. The regression discontinuity model produces qualitatively similar results that are smaller in magnitude but still significant. The results suggest that households to capitalize the information contained in the Toxic Release Inventory. However, since the treatment sites under consideration have virtually no emissions, these results do not contradict previous findings in the literature that toxic air emissions are unrelated to prices. Rather, they suggest that households might be concerned about the dangers of toxic chemicals that might result from an emergency or catastrophic accident.