This dissertation investigates the impact of noise pollution on residential properties in the Phoenix metropolitan area. It leverages quasi-random changes in flight paths to and from Phoenix Sky Harbor Airport, focusing on the adoption of the NextGen policy and subsequent flight path reversal upon court intervention. NextGen aimed to reduce flight costs by using computer-algorithm-generated optimized flight paths. In addition to estimating the value of quiet, this dissertation analyzes the distributional welfare impacts of policies that spatially alter noise pollution exposure, residential sorting, and environmental justice. In Chapter 1, the capitalization effect of noise pollution on the housing market is examined. Findings reveal that a mere 1 decibel increase results in a 1% reduction in property values. Furthermore, the chapter examines the distributional impacts of flight path changes across various demographic and socioeconomic characteristics of residents. I find that initially, computer-generated flight paths benefited neighborhoods with a higher proportion of Black residents. However, a court-ordered reversal ultimately left them worse off than before the initial change. Chapter 2 introduces a residential sorting model designed to assess welfare effects and simulate market responses to alternative policies. The estimated average marginal willingness to pay (MWTP) to avoid noise pollution stands at $3,038 per decibel, with variations based on household demographics. Additionally, a Pigouvian tax on airplane passengers to compensate for noise pollution amounts to approximately $16 per one-way flight, notably comparable to the carbon tax for a similar journey. Various counterfactual scenarios regarding noise pollution exposure are explored to inform policy decisions. Chapter 3 addresses two challenges in using property transaction data to estimate the MWTP to residential exposure to noise pollution. First, ignoring information frictions among home buyers may bias estimates of the MWTP for an amenity. Second, changes in the amenity of interest may affect other endogenous amenities, further complicating the identification of MWTP. I address both challenges using a novel instrumental variable based on spatial variation in the salience of noise pollution caused by hourly variation in flight paths due to wind direction. I find the mean MWTP for a one-decibel reduction in noise pollution be $4,742.

There is a growing consensus that environmental hazards and changing weather patterns disproportionately affect the poor, vulnerable, minority communities. My dissertation studies the nature of risk faced by vulnerable groups of individuals, how these risks affect their labor choice, income, consumption, and migration patterns. In Chapter 1, I study how seniors of different racial and income groups respond to information about hazardous waste sites in their neighborhood and their cleanup process. I find white seniors tend to move out at a higher rate when informed about the presence of a waste site as well as when the site is cleaned up compared to non-white seniors. This suggests that neighborhood gentrification exhibits inertia in the manifestation after the cleanup of Superfund sites. I find an assortative matching of seniors to neighborhoods based on their race and income, reinforcing findings in the environmental justice literature. Chapter 2 documents the effect of drought on labor choices, income, and consumption of rural households in India. I find that household consumption, as well as agricultural jobs, declines in response to drought. Further, I find that these effects are mediated by job skills and land ownership. Specifically, I find that households with working members who have completed primary education account for most of the workers who exit the agricultural sector. In contrast, I find that households with farmland increase their agricultural labor share post-drought. Cultural norms, relative prices, and land market transaction costs provide potential explanations for this behavior. Chapter 3 builds a simple model of household labor allocation based on reduced-form evidence I find in chapter 2. Simulation of the calibrated model implies that projected increases in the frequency of droughts over the next 30 years will have a net effect of a 1\% to 2\% reduction in agricultural labor. While small in percentage terms, this implies that 2.5 to 5 million individuals would leave agriculture. An increase in drought will also increase the size of the manufacturing wage subsidy needed to meet the goals of `Make in India’ policy by 20\%. This is driven by the need to incentivize landowners to reduce farm labor.

With the ongoing student debt crisis and the continuing increase in the cost of attending a college or university, there has been an increasing conversation regarding the price of room and board. Prior studies have shown the presence of a relationship between the distance to a location of interest, but few have been done with college campuses in mind. To answer this question, we used the Hedonic Pricing Model in order to isolate the effect that the distance to campus has on the rental price of apartments. Our results showed a clear positive nonlinear relationship between distance to campus and the price of apartment rentals in the area surrounding Arizona State University.

In the first chapter, I study the two-sided, dynamic matching problem that occurs in the United States (US) foster care system. In this market, foster parents and foster children can form reversible foster matches, which may disrupt, continue in a reversible state, or transition into permanency via adoption. I first present an empirical analysis that yields four new stylized facts related to match transitions of children in foster care and their exit through adoption. Thereafter, I develop a two-sided dynamic matching model with five key features: (a) children are heterogeneous (with and without a disability), (b) children must be foster matched before being adopted, (c) children search for parents while foster matched to another parent, (d) parents receive a smaller per-period payoff when adopting than fostering (capturing the presence of a financial penalty on adoption), and (e) matches differ in their quality. I use the model to derive conditions for the stylized facts to arise in equilibrium and carry out predictions regarding match quality. The main insight is that the intrinsic disadvantage (being less preferred by foster parents) faced by children with a disability exacerbates due to the penalty. Moreover, I show that foster parents in high-quality matches (relative to foster parents in low-quality matches) might have fewer incentives to adopt.

In the second chapter, I study the Minnesota's 2015 Northstar Care Program which eliminated the adoption penalty (i.e., the decrease in fostering-based financial transfers associated with adoption) for children aged six and older, while maintaining it for children under age six. Using a differences-in-differences estimation strategy that controls for a rich set of covariates, I find that parents were responsive to the change in direct financial payments; the annual adoption rate of older foster children (aged six to eleven) increased by approximately 8 percentage points (24% at the mean) as a result of the program. I additionally find evidence of strategic adoption behavior as the adoption rate of younger children temporarily increased by 9 percentage points (23% at the mean) while the adoption rate of the oldest children (aged fifteen) temporarily decreased by 9 percentage points (65% at the mean) in the year prior to the program's implementation.

This paper analyzes the correlation between unionization, corporate income taxes, and educational attainment with manufacturing firm locations at the state level across the USA. The paper analyzes the factors that influence firms per capita in a state using the Ordinary Least Squares regression model, with panel data, and fixed effects. The regression takes data from 2012 through 2016 and shows the correlation between unionization, educational attainment, and taxes on firm location. The paper cites Timothy Bartik’s findings (1985) and addresses reasons for changes in results for today’s economy.

This dissertation consists of three essays on public good provision.

The first chapter develops a model of charity’s choice of fundraising method under two dimensions of asymmetric information, quality and purpose. The main implication is a separating equilibrium where higher-quality charities choose to distinguish themselves by using a traditional fundraising method, while lower-quality ones exploit a low-stakes, take-it- or leave-it, ``checkout’’ method. An empirical application reinforced that charities of lower quality are more likely to adopt the checkout method. Despite this, consumers still choose to give in the equilibrium, due to the small requested amount of checkout donations, which disincentivizes serious thinking. Although exploited by lower-quality charities, the checkout method, along with purpose uncertainty, has the potential to alleviate the free-riding problem associated with public good provision and is, therefore, welfare improving.

The second chapter studies why corporations donate to charities and

how their donations affect social welfare. I propose that firms make donations out of an image reason. In a model where two firms compete with each other, charitable donation could attract consumers and also signal firm overall social responsibility. I show that there exists an equilibrium where the high responsibility firm overdonates,

resulting in a donation level closer to the socially optimal

one. This leads to higher consumer welfare due to higher private good

consumption as well as higher public good consumption when overdonation is prominent. Overall social welfare is enhanced. Empirical results support social image as an incentive for firms to donate.

The third chapter examines people's marginal willingness to pay for a change in local public good provision. We use a fixed effects hedonic model with MSA level data to study the effect of crime on local housing price. We explore the 1990s crime drop and use abortion data in 1970s and 1980s as an instrumental variable based on \citet*{donohue2001impact}. One result we find is that a decrease in murder of 100 cases per 10,000 people increases housing price by 70\%. We further translate this result into a value of a statistical case of homicide, which is around 0.4 million in 1999 dollars.