Search

In this thesis, I study the local employment multiplier effect; the effect of employment in the tradable sector on employment in the non-tradable sector of the same region. Using a reduced form regression with a shift-share instrument I find a significant local multiplier effect in Metropolitan Statistical Areas in the USA. I show that this result is robust to many different regional definitions, controls and ways of classifying tradable industries. I find larger multipliers for high-wage or high-skilled workers in the tradable sector and I find that most of the jobs created in the non-tradable sector are fulfilled by high-skilled workers who already reside in the region. A replication of the most influential paper in this literature, by Moretti (AER; 2010), demonstrates the sensitivity of his results to six idiosyncrasies of his analysis. To better understand how these local multipliers work, I develop an efficiency wage model with rural-urban migration for the non-tradable sector. In this model, I consider the impact of a shock to employment in the tradable sector in the city and find a positive local employment multiplier effect. The model predicts that attracting tradable jobs to a city has a bigger positive impact on employment in the non-tradable sector in the same city when the unemployment rate is higher. The model also predicts that this increase is driven by a larger multiplier for current inhabitants and that there is no, or even a negative, effect of the unemployment rate on the multiplier for movers. Both these predictions are reflected in the results of my non-parametric analysis of the data. I find similar results for European TL3 regions. Policies that try to increase growth in less favoured regions by stimulating tradable firms to locate in areas with high unemployment, will both reduce disparities between regions and efficiently reduce unemployment across the board.

This dissertation consists of three independent chapters related to the provision (or underprovision) of urban retail amenities. Chapter 1 (co-authored with Daniel Stackman) asks why storefronts remain empty for more than a year in some of the world's highest-rent retail real estate markets. Landlords with vacancies derive option value from two sources of uncertainty. First, increasing downstream retail demand may drive up market rents tomorrow. Second, different tenants may have different willingness to pay for the same space, creating an incentive for landlords to wait for a particularly high rent offer. We construct a dynamic search and matching model capturing landlords' tradeoff between signing a lease today and the option value of waiting, incorporating key market features including asymmetric commitment to the lease term and high move-in costs. We estimate the parameters by matching quarterly vacancy rates, lease-up rates, and tenant exit rates from a comprehensive, high-frequency storefront tracking service, combined with micro data on commercial leases. In a counterfactual exercise, we find that reducing the variance of the match quality distribution by 50% reduces long-run vacancy rates by 33% on average, while reducing the variance of the aggregate state variable has almost no effect. Finally, we use the estimated model to quantify the impact of a retail vacancy tax on long-run vacancy rates, average rents, and social welfare. Vacancies would have to generate negative externalities of $18.72 per square foot per quarter (about 30\% of average rents) to justify a 1% vacancy tax on assessed property values. Chapter 2 (also co-authored with Daniel Stackman) documents the rise of storefront vacancies in prime retail locations, a phenomenon we refer to as high-rent blight, in Manhattan over the 2016 to 2020 period. We then ask whether this increase in the retail vacancy rate can be attributed to a particular feature of commercial mortgage agreements. In a stylized model, we show that banks impose tenancy covenants (which establish rent floors for new leases landlords sign with tenants) in lending agreements to prevent landlords from impairing the value of collateral in the event of default. These clauses short-circuit the price mechanism in times of falling demand for retail space. We present quasi-experimental estimates suggesting that binding rent floors imposed by mortgage covenants substantially reduce the probability that vacant landlords choose to lease out their space. Finally, we estimate a structural model of landlord borrowing, leasing, and default decisions. In a counterfactual exercise, we show that eliminating covenants between 2016 and 2020 would have reduced the February 2020 vacancy rate by 11.4% (1.5 percentage points) relative to its realized level. Chapter 3 (co-authored with Edward Glaeser and Michael Luca) asks how gentrification transforms neighborhood retail amenities. We present a model in which gentrification harms incumbent residents by increasing rental costs and by eliminating distinctive local stores. While rising rents can be offset with targeted transfers, the destruction of neighborhood character can -- in principle -- reduce overall social surplus. Empirically we find that gentrifying neighborhoods experience faster growth in both the number of retail establishments and business closure rates than their non-gentrifying counterparts. However, we see little evidence that gentrification is associated with changes in retail mix or prices -- suggesting limited welfare losses.

Limits to further economic growth became clear to the scientific community, and various alternative development strategies have appeared. One such strategy is degrowth, a socio-economic development concept based on ecological economics and social equity ideas. The main idea of degrowth is to decrease the size of the global economy by fair reductions in global production and consumption levels. Interest in degrowth is constantly increasing, though clear ways of operationalisation of degrowth transitions are still lacking. A degrowth transition requires clear criteria for its implementation, especially in an urban context, to which little attention has been paid so far in degrowth debates. The key research problem addressed in this PhD thesis is how to operationalise the concept of degrowth, especially in an urban context. The main goal of this PhD thesis is to create a set of comprehensive proposals for the operationalisation of degrowth in cities. This thesis consists of an introduction, three related scientific articles published in international journals, and a discussion and conclusions wrapping up the whole series of articles.

This dissertation contains three independent essays in urban economics and international trade, with the aim of understanding geography's impact on spatial location and trade. The first chapter estimates the effect of the sweeping rezoning program initiated by the Bloomberg administration in New York City from 2002 to 2013. Using an instrumental variable strategy incorporating regime change from the 1961 Zoning Ordinance, this paper finds a 10% increase in the floor area ratio (a physical change), defined as the building floor area to the lot size, decreases price per square foot by 1.7% and a 10% increase in the maximum floor area ratio (a policy change) results in a 2.4% decrease in price. The paper uses a spatial general equilibrium model to quantify the aggregate impact of the rezoning policy on low- and high-skilled workers. Counterfactual analysis finds that as a result of the Bloomberg rezoning, GDP increases and price per square foot for residential floorspace drops, contrasting with an increase in residential segregation and increases in welfare only for high-skilled workers. The second chapter, co-authored with Bunyada (Mos) Laoprapassorn, studies the long-term effect of trade on development. We approach this question in the context of the ancient Silk Road, examining whether the locations along the highland Silk Road continue to be relatively more developed than other locations in the highland region along the Inner Asia Mountain Corridor that were not on the ancient Silk Road. We proxy for modern development using high-resolution satellite imagery. To provide a causal effect between proximity to the Silk Road and modern development, we adopt a novel instrumental variable, using a simulated seasonal mobility pattern of the nomadic pastoralists from Frachetti et al. (2017) as an instrument for the locations of the Silk Road sites. We find a significant and robust positive relationship between proximity to Silk Road sites and modern development measures; an increase in the distance to the Silk Road by one standard deviation decreases the night lights intensity by 10.0%. Based on the elasticity of night lights with respect to GDP in the literature, this corresponds to a decrease in GDP of about 4.1%-9.7%. The third chapter, co-authored with Dyanne Vaught, studies the evolution of corporate influence over time on trade agreements and its impact on trade flows. We approach this question using a variety of techniques, from traditional indicators to machine learning methods, and find that corporate influence has been increasing over time in trade agreements. A 10% increase in the proportion of Services and Investment topic in the trade agreements results in 0.19% to 0.92% increase in trade flows. Next, this paper finds that to multinational corporate language has a differential effect on trade flows. Using deep learning methods to score similarity, a 10% increase in similarity to multinational corporation language has a negative effect on trade flows, ranging from -0.3% to -1.2%.

My first chapter studies the origins of gentrification. I propose a mechanism through which a wave of gentrification can be triggered in a neighborhood: the opening of large offices of technology firms. Using information on nine such events and transaction-level housing data, I develop a difference-in-differences strategy that compares house prices in the vicinity of the new office to those in closely-matched neighborhoods slightly further away. I find that property prices rise 11% in treatment areas relative to control areas within two years after the opening. This difference subsides somewhat but remains at +8% five years later. These findings are substantially stronger than in the existing literature and thus suggest that such office openings can have a major impact on their neighborhood. I investigate two mechanisms, agglomeration forces and the development of consumption amenities, through which the impact of a single establishment opening can be amplified and sustained.My second chapter analyses the causes of the shift towards low-income service jobs that American non-college workforce has experience in recent decades. Together with the rise of college-educated workers’ incomes, this has strongly contributed to the overall increase in wage inequality. Two main explanations, routinization and consumption spillovers, have been proposed to explain this occupational shift. Although the determinants of these two theories are highly spatially correlated, studies that have exploited regional variations to identify these mechanisms have so far only considered each explanation in isolation, raising confounding concerns. I highlight these concerns and provide reduced-form evidence that both theories operate simultaneously to drive growth in service employment. To strengthen my case, I extend the structural framework proposed in Autor and Dorn (2013) to include consumption spillovers through non-homothetic preferences. I estimate key parameters and assess the relative importance of each theory using simulations from the model. Relative to a model featuring homothetic preferences, my specification yields 57% more regional disparities in the growth of service occupations, which can be interpreted as the contribution of consumption spillovers. While the routinization hypothesis quantitatively dominates, my reduced-form and structural evidence point to sizeable consumption spillover effects that cannot be neglected.My third chapter studies the effects of liberalizing the use of short-term contracts on the labor market outcomes of all workers. It specifically examines the impact of a 2003 change French jurisprudence. This decision from the French Civil Supreme Court — hereafter called the “reform” — extends the scope of a specific type of temporary contract in France, the CDDU (contrat � dur�e d�termin�e d’usage), to jobs that are not necessarily temporary by nature. This type of contract is allowed in 16 service sectors and is not restricted in terms of length or number of renewals, giving a lot more flexibility to employers than the standard temporary contract does (CDD, contrat � dur�e d�termin�e). I find that this change is associated with an increase in the share of temporary contracts of 2.9 percentage points in the CDDU sectors, while other service sectors only show a 0.7 point increase. This result echoes a frequent finding of temp for permanent substitution in the literature about the deregulation of temporary contract. A second and novel finding is that this reform weighs on young permanent workers’ wages, who experience drop of nearly 4% in their wages over the two years following the reform, and little catch up afterwards. I show some evidence that something changed in the relationship between employers and employees in CDDU sectors: the employer’s bargaining power seems to have risen as the opportunity to substitute temporary contracts for costly and protected permanent ones has increased.

This dissertation consists of three chapters studying environmental, transportation and urban challenges in both domestic and international settings. The first chapter “Do Safety Inspections Improve Safety? Evidence from the Roadside Inspection Program for Commercial Motor Vehicles” provides new insights to the study of regulatory enforcement and compliance by evaluating a key, long-standing national road safety regulation. I find that regulatory efforts to reduce public hazards are undermined when agents respond strategically to enforcement. I compile the most comprehensive database on inspections and accidents involving all 23 million trucks inspected nationwide from 1996 to 2018. Linking inspection and crash history using each truck’s unique vehicle identification number, I implement an event study that tracks a given truck’s accidents shortly before and after inspection. I find a sharp, 44.6% increase in the accident rate immediately following an inspection; the effect lasts for at least 14 days. Further analysis points to an explanation consistent with the Becker (1968) model: because inspectors rarely conduct repeat inspections of recently checked trucks, the drivers of these trucks then drive more carelessly and undertake fewer safety checks, leading to more frequent accidents following an inspection. These compensating behaviors lead to an estimated 1,803 additional accidents per year, costing roughly $1.6 billion. A comparison of different regulatory designs across states shows that alternative policy designs that randomize inspection practices and schedules could reduce accidents. In addition to evaluating regulatory impacts on human lives, in the second chapter, I find that environmental regulations nominally aimed at humans can also provide substantial benefits to other species. In my co-authored article, we provide the first large-scale evidence that air pollution, specifically ozone, is associated with declines in bird abundance in the United States. We analyze bird observations derived from over 11 million eBird checklists. The empirical challenge which I contribute to solving is to model the change in relative bird abundance after adjusting for observer efforts and bird detectability. I then combine the bird observations with data on air pollution and weather. We show that the US Environmental Protection Agency NOx Budget Trading Program, an air quality regulation which limits ozone precursors, delivered substantial benefits to bird conservation. Our estimates suggest that air quality improvements over the past four decades have stemmed the decline in bird populations, averting the loss of 1.5 billion birds, approximately 20 percent of current totals. This suggests that further improvements in air quality could meaningfully contribute to efforts to halt or reverse widespread declines in wildlife populations. The third chapter focuses on the role of financial market frictions in limiting consumption amid fast-rising housing prices in urban China. My co-authors and I use the universe of bank card transaction data in China to measure the impact of housing price changes on household consumption during the most recent housing boom. We show that there is a negative consumption response to housing price increases. The result is driven by the combination of a strong investment incentive in housing and heavy borrowing constraints faced by households. This finding is corroborated by the fact that households increase their savings as housing prices increase. I wrote a theoretical model to explain the channels at work, and proposed the use of lagged land sales as an instrumental variable for housing price. Our paper documents patterns that are in sharp contrast to those in the existing literature focused predominantly on the US; and we highlight the importance of taking into consideration capital market imperfections faced by households in developing countries and emerging markets.

The Low-Income Housing Tax Credit program is by far the largest federal subsidy for affordable housing production in America. There are two types of tax credits in this program and the research typically does not differentiate. The “non-competitive” 4% credit, as opposed to the “competitive” 9% credit, is flying under the radar of researchers and policymakers. Prioritization towards siting in neighborhoods with higher opportunities are often optional, unclear, and unenforceable in the 4% program. The results from this project show that both credits do very little to reduce the patterns of poverty concentration and racial segregation in the United States. Moving into any type of new tax credit unit may notably reduce a subsidized household’s experiences and undermine its ability in translating stable rents into economic mobility. During the most recent decade, some states started to incentivize siting more 9% developments in areas with lower poverty and higher opportunities through the use of Qualified Allocation Plans. State legislators and housing authorities have yet to carry out meaningful oversight and guidance for the 4% program. The finding points to that the tax credit program, particularly with the 4% tax credit, has some unleashed potentials to increase our ability to create housing and neighborhood opportunities for all and advance fair housing goals.

My dissertation consists of three essays. In the first, I systematically document the importance of chance to a fundamental question of economic geography: How did locations develop their specializations in specific manufacturing industries? I show that European immigration to the United States affected the initial location of industries in the late nineteenth century, creating a spatial pattern that remained relatively stable. Immigrants' exposure to specialized manufacturing knowledge and skills depends on their origin. The comparative advantage that came to U.S. counties ``embodied'' in immigrants predicts employment in disaggregated manufacturing industries in subsequent decades. The early establishment of firms in novel industries gave locations first-mover advantage and shaped local manufacturing specialization. Agglomeration forces locked in industries until the present. I address endogeneity issues by exploiting arguably random variation in early immigration enclaves due to the interaction of the aggregate arrivals from European countries, and the movement of the frontier of settlement across U.S. counties.The remaining two chapters consider the importance of individual actors in the realm of politics. My second chapter, co-authored with Max Winkler, studies the incentives for local political leaders when facing an unforeseen threat to their incumbency. The chapter examines the case of the unexpected and short-lived electoral success of the pro-redistribution Populist Party in the 1892 presidential elections. The Populists sought support among poor farmers, regardless of race. This biracial alliance threatened the Democratic establishment in the South, providing it with an incentive to fan racial fears to split the newly formed coalition. Newspapers affiliated with the Democrats spread propaganda of attacks by Blacks on the White community, often involving allegations of sexual assault. Using novel newspaper data, we identify these hate stories and show that they become more prevalent in the years following the 1892 presidential election in counties where the Populists were active. The effect is large and found in newspapers affiliated with the Democrats only. The evidence suggests that the propaganda ``worked'': where newspapers spread more propaganda, the Democrats see more substantial gains in presidential elections in the following decades, long after the Populists left the political arena.The third and last chapter, co-authored with Nico Voigtl�nder, considers the importance of national political leaders for the performance of the states they govern. We create a novel reign-level dataset for European monarchs, covering all major European states from the 10th century until World War I. We first document a strong positive relationship between rulers' intellectual ability and state-level outcomes. To address endogeneity issues, we exploit the facts that i) rulers were appointed according to primogeniture, independent of their ability, and ii) the widespread inbreeding among the ruling dynasties of Europe led to quasi-random variation in ruler ability. We code the degree of blood relationship between the parents of rulers. The `coefficient of inbreeding' is a strong predictor of ruler ability, and the corresponding instrumental variable results imply that ruler ability had a sizeable effect on the performance of states and their borders. This supports the view that `leaders made history,' shaping the European map until its consolidation into nation-states. We also show that rulers mattered only where their power was largely unconstrained. In reigns where parliaments checked the power of monarchs, ruler ability no longer affected their state's performance. Thus, the strengthening of parliaments in Northern European states (where kin marriage of dynasties was particularly widespread) may have shielded them from the detrimental effects of inbreeding.

Against the backdrop of accelerating economic divergence across different regions in advanced economies, political scientists are increasingly interested in its implication on political behavior and public opinion. This dissertation presents three papers that show how local-level implementation of policies and local economic circumstances affect voters' behavior. The first paper, titled "Biting the Hands that Feed Them? Place-Based Policies and Decline of Local Support", analyzed if place-based policies such as infrastructure projects and business support can garner political support in the area, using the EU funding data in the UK. Contrary to conventional wisdom, the findings suggest that relatively educated, well-off voters who pay attention to local affairs turn against the government that provides such programs and become more interested in the budgeting process. Visible and high-profile projects appear to be particularly counterproductive. This goes against the positive findings in the literature about cash transfer or disaster relief, but it is important to remind that very few cases of such place-based intervention have been successful in the context of deflationary spirals in the declining regions. Despite questionable track record in terms of economic impact, such measures are often used to \qq{appease} the voters in economically declining areas; this paper questions its political value of such a project. The second paper, titled "Gone with the Dirty Air? Closure of Polluting Plants, Fracking Sites, and Changes in Local Public Opinion", deal with the impact of the factory closure and fracking ban on the political behavior of the residents in the affected areas in the UK. It turned out that such events are not associated with a strong emotional response against environmentalism, but they evaluated the government according to their economic interest. Homeowners and blue-collar workers in oil-producing areas disapproved of the government after the fracking ban, while homeowners and self-employed people in industrial areas temporarily evaluate the government highly after the shut down of factories, presumably because of the immediate governmental support for the community following the economic malaise. This chapter disputes the prevalent view that unemployment in formerly industrialized areas is creating political backlash and populism surge. It appears that voters' evaluation of the government is economically rational, and there is no indication of emotional backlash or misattribution of responsibilities. The third paper, "Paper 3: Choosing Voters? Partisan Sorting of Voters following Close Municipal Elections in France." deals with the geographic sorting of voters in France, and the findings suggest that people do change their locations in response to local-level politics and policies. While the paper's main focus is sorting according to mayors' partisanship, the fact that people appear to be responsive to tax rates differentials may make policy-induced migration more effective. As economists generally support migration from declining areas to prospering areas, the political factor to hinder or accelerate such domestic migration would be an essential topic, and this paper suggests the electoral motivation of the subnational leaders to influence the migration flow. The crucial common ground of the three papers, in addition to the topic, is that the findings are not in line with the conventional wisdom in the relevant academic fields. Place-based policies are often assumed to garner support in the area, factory closure is associated with anger and political populism, and policy-induced sorting was thought to be insignificant. With rigorous empirical design and careful treatment of the data, this dissertation claims that the literature in political science and urban economics has not found an answer to the critical geographic question today. It calls for further research in how changing economic geography interacts with the political landscape today.

Government policy has a profound impact on many aspects of individual people's lives, limiting, expanding, or changing the choices available to them. My dissertation examines how individuals respond to policy changes through behavioral adaptation and political participation. Policy change is often shaped by political interests and incomplete information that can lead to unintended or unexpected impacts; people must adapt to a changing world that may or not be better for them. In Chapter 1, I study the impact of new market rate and affordable housing construction on nearby housing affordability, displacement, and gentrification. In Chapter 2, I investigate the relationship between government failure and voter turnout after the Flint Water Crisis. In Chapter 3, I examine the role of risk aversion in women's contraceptive choice, demonstrating that women make defensive investments in methods that can shield them from adverse policy change. In each paper, I combine natural experiments with microdata to identify the causal impact of policy change on individual choices. In Chapter 1, I answer a question at the heart of intense debate over how to address housing affordability in San Francisco. How does new construction affect housing prices, displacement, and gentrifcation in the surrounding neighborhood? To separate the causal impact from the well-documented correlation between new development and increasing housing prices, I exploit random variation in the location of new construction in San Francisco caused by serious building fires. These fires are rare and unrelated to trends in rent, displacement, or gentrification, and they increase the probability of construction by a factor of 32. I combine this identification strategy with an original dataset of Craigslist rents, which I create by scraping old rental listings that have been collected by an internet archive nonprofit. Next, I leverage the individual address histories of 1.24 million San Francisco residents to create separate measures of displacement and gentrification. I find that rents fall for housing near the new construction, reducing displacement risk by 17% for nearby renters. At the same time, neighborhood quality improves through increased residential renovations, and gentrification increases as wealthier people move in. In contrast, I show that affordable housing and endogenously located construction do not affect rents, displacement, or gentrification. These findings suggest that building new market rate housing has beneficial spillover effects for incumbent renters, reducing rents and displacement pressures while improving neighborhood quality. In Chapter 2, I study the impact of the Flint water crisis on political participation with coauthor Eleanor Wiseman. Unpacking the motivation to vote is a central goal in political science, political economy, and the pursuit of representative democracy, but it is difficult to study empirically. We examine the impacts of a massive municipal and state government failure that exposed a quasi-random sample of households in Flint, MI to elevated lead in their water. Does personal experience of government quality motivate voting? We combine spatial data on lead exposure with the Michigan Qualified Voter File to explore how the results and timing of household lead tests affect voter turnout. To overcome selection issues, we use a triple differences approach that compares individual turnout for voters with 1) positive versus negative lead test results, 2) who receive their test results before versus after the 2015 mayoral election, 3) for the 2015 mayoral election versus the two mayoral elections before the water crisis. We find that voters who tested positive for lead before the 2015 mayoral election were 3.1 percentage points less likely to vote. However, this average effect masks significant and opposite reactions to lead test results among Black and White voters. We find that Black voters who tested positive before the election became 14.4 percentage points less likely to vote, while White voters who tested positive before the election became 4.5 percentage points more likely to vote. Moreover, we find that the crisis increased turnout, new voter registration, and the preference for a mayoral challenger for Black residents compared to White residents at several times the magnitude of the impacts of individual lead test results. We interpret these findings as evidence that the crisis increased the salience of race, causing divergence in the voting rates and preferences of Black and White voters. Chapter 3 examines the role of the reproductive healthcare policy environment in women's choice of a contraceptive method. Reproductive healthcare policy has become a knife-edge issue in the United States, with narrow legislative majorities passing laws that dramatically change women's access to affordable family planning services and abortion on a state-by-state basis. This paper investigates the role of the policy environment in women's choice of a contraceptive method. I model contraceptive method choice as a dynamic discrete choice under uncertainty about future pregnancy, abortion access, and contraceptive method costs. The model predicts that women are forward-looking and risk averse in their choice of contraception, switching to lower failure-rate methods when they expect abortion access may fall and to longer-lasting methods when they expect costs may rise. Using de-identified patient level data from Planned Parenthood of Wisconsin and Planned Parenthood of Northern New England, I evaluate the impacts of three shocks to the policy environment: Wisconsin's 2015 abortion ban, Vermont's 2016 reproductive healthcare expansion, and the 2016 presidential election. I find strong evidence in support of the model predictions, with the probability of switching increasing by 2-17 percentage points after the policy shocks. Women choose a contraceptive method in response not only to method attributes, but also to the policy environment, making defensive investments in methods that can shield them from adverse policy changes in the future.

This dissertation is comprised of three essays, each dealing with topics in Urban Economics and Applied Microeconomics. In the first chapter, I use a dynamic discrete-continuous choice model to examine the decision to invest in home improvement. In each time period, households face the decision of whether to reoptimize their housing consumption, either through home improvement or by selling their property. The structural model is estimated using a uniquely rich micro-level dataset that encompasses each property in Minneapolis for a period of almost 20 years. I reconstruct the optimal investment policy and choice probabilities as a function of a property's housing quality and neighborhood quality. Then, I explore a counterfactual scenario in which the cost of investment in home improvement is subsidized and show that such a policy would be effective in increasing the predicted level of investment. I find that policies aimed at encouraging home improvement can be a cost-effective tool to leverage private investment in housing renovation, and to promote urban revitalization without displacing the residents of low income neighborhoods. In the second chapter, I investigate how the development of new apartment buildings can affect local property prices. On one hand, increasing the supply of available residential units is expected to lower the price of other housing options in a given area through a substitution effect. On the other hand, apartment building development may produce aggregation economies and other spillovers increasing the desirability of a given neighborhood and in turn property prices. Estimating the net effect under a standard parametric framework is complicated by the non-linear interaction of geographic and temporal distance from the site of construction. I apply a new econometric technique developed by Diamond and McQuade (2019) to non-parametrically estimate the effect of apartment building construction on nearby residential property prices, transforming transaction prices into a price gradient that is a smooth function of time and distance and then numerically integrating over the estimated derivatives to measure changes in property prices. I find that property prices increase with distance from the site of a new development, suggesting that the substitution effect might be stronger than other potential spillovers, although the overall effect varies heterogeneously across different types of neighborhood. In the third chapter, Mark Ponder and I examine the effect of the introduction of light rail transit in Minneapolis. We focus on decomposing the overall impact on local property prices to assess what share is attributable to the direct effect of improved access to public transit and what share is attributable to an indirect spillover effect through the increase in local amenities. After assembling a rich spatial dataset encompassing every residential property in Minneapolis and hundreds of thousands of businesses and neighborhood amenities, we use machine learning techniques to estimate a hedonic pricing surface. We extend the method of Boosted Smooth Trees introduced by Fonseca et al. (2018) to a high-dimensional dataset and to incorporate instrumental variables, allowing us to control for endogenous changes in amenities. Our results indicate that the price of properties located within a half mile of a light rail station increased by around 11.3%. The direct impact of access to the light rail itself is estimated to increase local housing prices by 5.5%, while the estimated spillover due to changes in amenities is quantifiable at 5.8%.

This dissertation consists of three papers on the provision of local public goods. Chapters 1 and 2 consider the criminogenic and social consequences of New York City's ``Stop and Frisk'' program, respectively. In these papers, co-author Andrew Bacher-Hicks and I leverage the quasi-random movement of NYPD police commanders across precincts to identify the causal impact of this policing strategy on crime and long-run educational attainment. We first find that a commander’s predicted effect on stops—--based on data from previous precincts—--is highly predictive of changes in observed stops after that commander enters a new precinct. In Chapter 1, we find that high propensity-to-stop commanders decrease low-level offenses within their precinct. However, we find no corresponding decrease in more serious felony offenses, and find suggestive evidence that within-precinct misdemeanor crime reductions are offset by crime displacement to adjacent neighborhoods. Contrary to the broken windows theory of policing, our findings suggest that stop-and-frisk tactics do not deter more serious criminal behavior. In Chapter 2, we estimate the social impact of stop-and-frisk policing. We find that exposure to high propensity-to-stop commanders in middle school has negative effects on students' high school graduation, college enrollment, and college persistence rates. These effects are concentrated among black students, who belong to the racial group overwhelmingly targeted by police stops. We find evidence of improvements to school safety and positive spillovers for white and Asian students, who are less likely to directly interact with police. Finally, Chapter 3 estimates the impact of top-down local public goods provision on citizen engagement. I leverage the fact that routine street maintenance in Boston is determined according to a well-defined set of criteria---underlying street quality and city geography---to estimate the causal impact of traditional, bureaucrat-driven local public goods provision on citizen requests. I find that exogenous shocks to seasonal street paving decrease requests for future street repairs, while at the same time increasing future requests for non-street public goods. Reductions in requests for future street repairs are primarily driven by the mechanical improvement paving brings to street quality. On the other hand, results for non-street public goods are consistent with the notion that top-down local public goods provision sends a positive signal to citizens about both government effectiveness and responsiveness.

This dissertation consists of three studies of the relationship between neighborhoods, housing policy, and local public schools. In the first chapter I analyze mortgage loans and home val-ues from 2000-2014 to study housing markets in neighborhoods near racially diverse schools. Using a national sample of over 3,600 middle schools, I construct a measure of school de-mographic diversity and estimate how home values and mortgage loan amounts change as diversity increases. For identification I isolate variation in school demographics associated with the quasi-random timing of rental housing development under the Low-Income Housing Tax Credit (LIHTC) program. I find that mortgage amounts rise by nearly 6.7%, holding median home values constant and controlling for changes in local income levels and home buyer socioeconomic character-istics. The magnitude of the eect is consistent for white, black, and Hispanic home buyers, and coincides with a decrease in home values of 2.5% near diversifying schools. The eect is reversed for white home buyers near diverse schools in low-income areas, who borrow less for housing holding home values constant. I present two explanations for these findings, both which shed light on neighborhood wealth, down payment ability, and the consequences of household sorting over local amenities. The second chapter is a joint work with Pat Bayer and Peter Blair. We estimate how much parents value school expenditure and their willingness to finance it through higher taxes. Exploiting plausibly exogenous variation in expenditures and taxes from school finance reforms, we find that a 1 percent increase in taxes to fund education increases house pricesby an economically small and statistically insignificant 0.06 percent. We find larger price changes in regions with less elastic housing supply. Our results provide support the core prediction of Tiebout (1956) that decentralized jurisdictions can eÿciently provide local public goods such as education. The third chapter is a descriptive study of a key provision of the Low-Income Housing Tax Credit Program that reserves certain rental units for families with children. I show that this type of development in particular has an eect on schools that is statistically distinguishable from other types of LIHTC development. I then test whether changes at the school level induced by this provision alter the way districts allocated resources for schooling. The preliminary results of this analysis open the door for future research using more sophisticated inference techniques.

This dissertation studies how heterogeneous agents’ exposure to local markets determines welfare and distributional effects of shocks such as policy interventions. In both chapters recent modeling tools in the international trade literature are applied to the study of spatial inequality in cities and its sources in chapter 1 or scaling up agricultural policy interventions in chapter 2. These tools are used to answer research questions in the context of quantitative general equilibrium models that feature rich heterogeneity but remain tractable. Moreover, the models in this dissertation predict clear relationships between the choices of households, firms and aggregate variables that are disciplined with detailed microdata. The first chapter Two-Sided Sorting and Spatial Inequality in Cities studies a new economic force underlying the spatial sorting of rich and poor households in cities. On the demand side, households with different incomes choose neighborhoods and differ in their expenditures across various local services. On the supply side, service establishments sort into neighborhoods while taking into account proximity to their consumers. This two-sided sorting leads to endogenous differences in the local price index that amplify the concentration of household groups. A recent literature in urban economics has rationalized spatial sorting of households that is left unexplained by local incomes or housing costs by modeling pure amenity spillovers. In this chapter, I quantify the contribution of endogenous price indices to spatial sorting that is usually projected onto such reduced-form spillovers, and study the implications of two-sided sorting for urban policy. To do so, I develop a quantitative equilibrium model of the city that features two-sided sorting and nests many urban models. I estimate the key parameters of the model using detailed microdata for Los Angeles from 1990-2014. I find that spatial variation in local price indices decreases the estimates of reduced-form spillovers by about 30-50 percent. To shed light on the policy implications, I simulate policy counterfactuals, and compare the effects to the existing framework with only reduced-form amenity spillovers. By studying a number of prominent place-based policies in Los Angeles, I find substantially different effects on neighborhood composition and welfare between both models.The second chapter Scaling Agricultural Policy Interventions: Theory and Evidence from Uganda studies the welfare and distributional effects of scaling agricultural interventions in general equilibrium. Interventions aimed at raising agricultural productivity in developing countries have been a centerpiece in the global fight against poverty. These policies are increasingly informed by evidence from field experiments and natural experiments, with the well-known limitation that findings based on local variation generally do not speak to the general equilibrium (GE) effects if the intervention were to be scaled up to the national level. In this chapter, we develop a new framework to quantify these forces based on a combination of theory and rich but widely available microdata. We build a quantitative GE model of farm production and trade, and propose a new solution method in this environment for studying high-dimensional counterfactuals at the level of individual households in the macroeconomy. We then bring to bear microdata from Uganda to calibrate the model to all households populating the country. We use these building blocks to explore the average and distributional implications of local shocks compared to policies at scale, and quantify the underlying mechanisms.

This dissertation explores topics in urban and labor economics, separately and together. In Chapter 1, I explore human capital spillovers between workers and across neighborhoods. I first show that college-educated and non-college workers tend to work in the same Census tracts. I then estimate an economic geography model and find a positive spillover effect of nearby college workers but a negative spillover effect of nearby non-college workers on a worker’s income. Both spillover effects decay very quickly, having no effect beyond three miles. I conduct counterfactual exercises to assess the benefits of a Los Angeles policy. The exercise shows that policies increasing density of college jobs provide benefit to both the targeted and surrounding areas, suggesting an important margin for urban policymakers to influence worker productivity in local areas. Chapter 2 studies the Civilian Conservation Corps (CCC) to provide the first comprehensive assessment of the short- and long-term effects of means-tested youth employment programs. We use digitized enrollee records from the CCC program in Colorado and New Mexico and matched these records to the 1940 Census, WWII enlistment records, Social Security Administration records, and death certificates. Overall, we find significant long-term benefits in both longevity and earnings, suggesting short and medium-term evaluations underestimate the returns of training programs, as do those that fail to consider effects on longevity. Chapter 3 examines the housing market effects of inclusionary zoning policies (IZPs). IZPs have been implemented to spur construction of below-market housing to tackle the issue of housing affordability. They are popular with local governments because the direct costs of creating affordable housing are borne by developers, but their effects are theoretically ambiguous. I set up an empirical strategy that exploits variation in geography and timing in a difference-in-discontinuity framework to examine the effect of New York City’s mandatory IZP on housing supply and prices. I find while transaction prices increase following the policy, building activity also increases. This suggests that models considering IZP as a tax on development are too simplistic and further research is required to disentangle these findings.

This dissertation includes two essays in applied microeconomics. In Chapter 1, I investigate how much people value local government spending. This is important to measure to better inform government policies and theories of public finance and urban economics, especially when considering how to allocate government spending across locations. To estimate this, I build a quantitative spatial general equilibrium model and combine it with the empirical environment of South Korea where I can leverage a quasi-natural experiment of tax policy reforms to estimate the valuation. I find that an extra dollar of local government spending is valued at 75 cents of their private consumption equivalent. Having obtained the estimate, I embed the measurement into a broader model of the South Korean economy and ask a broader question that involves a general equilibrium analysis of the optimal fiscal transfers across locations: what is the best way to transfer tax revenue across locations in the context where this revenue would be used to finance local government spending. What I find is that fiscal arrangements with small redistribution relative to the actual extent of redistribution observed in South Korea would have positive aggregate e˙ects on welfare. However, completely eliminating the transfer scheme would result in a large welfare loss. In addition to these substantive findings, this chapter has a methodological contribution. The key aspect is to account for two forms of mobility: where people choose to live, or migration, and where people choose to work, or commuting, which have been thus far studied separately. Throughout my analysis, I show that accounting for both of these margins of mobility is key to correctly estimating the valuation for local government spending and measuring fundamental parameters in the spatial economics literature, which also appear in my framework, namely the elasticities of migration and commuting with respect to spatial frictions. In Chapter 2, I examine the effects of pro-natalist cash transfers on fertility outcomes in South Korea. I exploit the rich cross-sectional variation in cash-transfer generosity over time using 15 years to identify the causal effects of these transfers on the number of births and their health outcomes. Overall, the results provide evidence that cash transfer is an effective policy measure to increase completed fertility and the number of children every born per woman without adversely impacting infant health outcomes and sex composition at birth. Decomposing the birth rates by parity, I find that cash transfers offered for a specific birth parity only affected the parity-specific birth rates. Furthermore, the cash transfers did not change the fertility rate of adolescents.

In this dissertation, I study topics in the economics of science and innovation using tools from applied econometrics and causal inference.In Chapter 1, I estimate the effect of short-term interactions on knowledge spillovers. Research in labor and urban economics has studied the importance of geographic proximity in reducing search costs and generating human capital spillovers and innovation. I study the colocation of scientists serving as reviewers for the NIH in committees known as study sections. I find that reviewers who serve together as reviewers are more likely to cite each other than reviewers who served at different times up to 10 years later, and that the longer the reviewers overlap, the stronger the effect. This suggests that familiarity with, and not just awareness of, another scientist is an important factor in knowledge diffusionIn Chapter 2, we evaluate the impact of a large, targeted intervention on scientific output. In 2004, California passed Proposition 71, allocating $3 billion over 10 years to supporting stem cell research. We evaluate the effects of this policy using a generalization of the synthetic control method. We find that the policy led to a 20\% increase in publications by the state of California as a whole. This increase in the volume of research drove similar increases in high-impact or novel papers from California. Our results suggest that government can play a substantial role in determining the direction of research.In Chapter 3, I study the effect of budget uncertainty on research activity. In recent years, the U.S. federal budget has been a major source of uncertainty, which potentially impedes economic activity. This uncertainty can induce federal agencies to delay spending until later in the fiscal year. Businesses that rely on public funding may have their funding stream interrupted as a result. I study the effect of funding interruptions on one particular type of economic activity - research - for which exceptionally rich transaction-level data is available. I find that researchers respond to the uncertainty from funding interruptions by spending less in the months leading up to the expiry of funding. Spending is substantially lower in the first month after funding resumes but recovers within 2 months, suggesting that interruptions have a disruptive effect on research even when funds become available. These findings suggest that in addition to the quality of projects, agencies should take into account the continuity of funding when they make research awards.

Does being a non-stop flight away from Silicon Valley help entrepreneurs access venture capital? With its abundance of researchers and investors, Silicon Valley leads the world in entrepreneurship. In Silicon Valley, venture capital investors (VCs) and startups benefit from proximity, forming strong relationships and meeting frequently in person. VCs often choose to focus their operations locally, bringing down the costs of monitoring investments. Not all entrepreneurs can locate themselves in this global hub and without a direct connection to Silicon Valley some may find it difficult to tap into the extensive resources clustered in the region. I show that startups operating in cities with non-stop connections to Silicon Valley benefit immensely from direct flights. I find that this connection matters more for cities outside the U.S. A new daily flight from Silicon Valley to an international city leads to $23 million of additional VC raised by startups in the region.

My doctoral research focuses on the matching theory and its market design application. Specifically, I work on matching with property rights, where property rights not only mean the ownership, but also refer to the ability to determine how the good is used. In the matching with property rights model, an agent who owns a resource can claim how her resource is offered, depending on what she gets from the system. For example, in a housing exchange for vacation, an agent who gets a house with a car will offer her house also with a car. However, if she is assigned only a house without a car, she might refuse to offer a car. This restriction can be thought as a matching with externality, as someone's consuming my resource in certain way affects my utility. With property rights present, it is not clear how we can achieve a desirable outcome while satisfying the rights. I am currently pursuing two main lines of research in this topic that constitute the two chapters dissertation. In Matching with Property Rights: an Application to a Parking Space Assignment Problem, I introduce parking in urban areas as a matching problem. First, I model the street-parking market as a strategic game and show that the set of Nash equilibrium outcomes is equivalent to the set of stable allocations. However, it is not reasonable to expect drivers to reach a Nash equilibrium in the decentralized system due to lack of information and coordination failure. Therefore, I suggest a centralized mechanism that would enable a parking authority to assign available spaces to drivers in a stable way. The model incorporates resident parking spaces, such that visitors could access vacant resident spaces. To use the resident parking spaces, the system needs to protect exclusive property rights over their parking spaces. I show that, however, there is no mechanism that is stable and protects residents' rights. To resolve this issue, I introduce a new concept, a claim contract, and suggest a mechanism that protects property rights, is strategy proof for the drivers, and approximates a stable matching. Besides its market-design focus, this paper handles both priority-based and property right-based assignment, which considered separately in the matching theory literature. In Housing Market with Contracts, I study matching with property rights problem in the housing market framework. To introduce property rights in housing market, I assume the house can be offered in two contractual terms. Property rights requires that when an agent gets a house in a certain term, her house should also be offered as the same term. Moreover, when every agent owns a house, property rights reduces to an equal-term matching. After defining efficiency and core in equal-term domain, I show that, in a housing market with contracts problem, core may be empty. However, there always exists an efficient, individually rational, and equal-term matching in every housing market with contracts problem. Then I present a mechanism that always produces an efficient, individually rational, and equal-term matching. This is the first attempt to model a matching with contract in a exchange economy.

The state of California implements the Regional Housing Needs Assessment (RHNA) program as the central pillar of its statewide housing policy, the Housing Element Law. It determines “fair share” allocations of a region’s forecasted growth in households for each city and county, and directs local jurisdictions to accommodate the allocations in its general plans and zoning capacity.The RHNA process is an attempt to ensure that additional housing units are constructed to accommodate population growth in every part of the state. However, nearly forty years since RHNA was first established, California today faces a housing crisis where vacancy rates are very low and rent and ownership prices have skyrocketed, especially in its coastal metropolitan regions (Alamo and Uhler 2015). While limited studies of the RHNA program have been conducted in the past, none have examined it from a comprehensive and longitudinal perspective.I analyzed data on RHNA allocations and performance for the Southern California Association of Governments (SCAG), a regional Council of Governments that encompasses six counties and is the most populous in the state. Covering the period from 1998 to 2021, I found that high allocations are strongly associated with cities that have lower household incomes, more people of color, and are farther away from downtown Los Angeles. They are also associated with cities having high rates of past household growth. In contrast, housing production was associated only with past household growth and distance from downtown Los Angeles.I conclude that SCAG’s implementation of RHNA reinforces racial and economic disparities of housing growth in the region. I also find that it has a recursive effect over time, maintaining high allocations for cities on the urban fringe while rewarding slow-growth cities with low allocations. The RHNA implementation by the Association of Bay Area Governments (ABAG) displays similar dynamics of disparity (Bromfield and Moore 2017). Major changes to RHNA allocation methodologies are necessary to address these structural inequalities in California’s housing landscape.

Most human decisions are made without consideration for the associated energy use. But our actions, from choices about where to live and how to commute, to the routine decision about when to sleep or whether to go to church, have energy implications. Collectively, these decisions form cities filled with gasoline-consuming cars and dictate when power plants turn on and off. Choices, even when made subconsciously, are made subject to constraints formed by past societies' decisions or attempts to coordinate with family, friends, and colleagues. This dissertation broadly investigates how technologies, norms, and incentives affect human behavior, energy use, and, ultimately, climate change. I develop novel and large datasets to investigate unanswered questions in energy and urban economics.In Chapters 1 and 2, I ask how transportation technology affects urban growth. A broad set of interacting factors, such as physical features and land use policy, cause particular spatial organizations of households and firms in rapidly growing urban areas. Transportation costs and real estate prices drive individuals' decisions about where to work and live. These choices have tremendous welfare implications, costing time and energy, and resulting in externalities including air pollution and traffic congestion. Despite high social costs, there is little empirical evidence about the effect of changes in transportation costs on city structure. I estimate the effects of two transportation innovations - (1) a speed limit increase, and (2) ridesharing services - on residential real estate prices and development. I find that prices respond quickly and significantly to transportation cost changes. Consistent with my theoretical model, an increase in speed limits decreases housing prices by over 3% on average, with the largest effect in the city center. Subsequent housing development is farther from the central city. In contrast, the launch of Uber increases housing prices by over 2% after the first year, with a larger immediate effect in the central city. Housing development occurs closer to the central city after treatment. Both treatments change the ability of households to access surrounding markets. Applying the concept of "market access" from the trade literature, I show that the distribution of business establishments around a property dramatically changes the magnitude of each effect. Chapter 3, co-authored with Solomon Hsiang and Terin Mayer, shows that electricity use can be predicted from human activities. System operators predict electricity loads in order to schedule power plants and allocate transmissions resources to ensure grid reliability. In the long term, forecasting dictates whether new power plants will be contracted or built. We combine hourly data on electricity load with the American Time Use Survey and show that, with just three time-use variables, we can predict over 90% of variation in electricity use. In an increasingly data-rich world, we know more about what individuals' locations and activities, making our finding a potentially valuable tool for improving prediction as well as offering ways to reduce electricity usage by shifting human activity. Chapter 4, also co-authored with Solomon Hsiang, explores energy use on holidays and weekends. Government policies that coordinate labor and leisure have profound economic implications. However, manipulating the structure of our workweek, weekend, and holiday calendar in order to improve economic outcomes is a policy lever that has been largely unused. Setting optimal coordinating mechanisms and allocations may present a useful tool for reducing carbon emissions, particularly if individuals are constrained in the number of days they have available to take coordinated leisure. We provide evidence that there is an environmental externality associated with labor relative to leisure. We empirically estimate the effect of weekends and holidays on electricity loads, vehicle travel, and air travel in the U.S. We observe large reductions in electricity load, air travel, and vehicle travel on many holidays, as well as reductions on surrounding days. Using time use data and exogenous variation in when a holiday is observed, we provide evidence that, beyond labor being less carbon intensive than leisure, agents enjoy less carbon-intensive activities on holidays. Holidays during the summer all result in significant savings. New holidays may be more economically valuable if they are scheduled for hot days that are likely to require high marginal cost generators to meet electricity demand.

Research on the impacts of transport infrastructure is limited, and most of it is either focused on rural areas or on developed areas before modern geospatial technologies were available. This study aimed to fill this gap in transport research by providing a holistic look at the regional changes that occurred due to new transport infrastructure construction in Northwest Arkansas between 1980 and 2011. The National Land Cover Database was used to create a time-series of land cover across the region between 1992 and 2011. These data were then used to predict future growth in the region. Additionally, growth patterns of the four largest cities (Bentonville, Fayetteville, Rogers, and Springdale) were studied, and monocentricity values for the region were calculated to study population movement. Data on income, retail trade, gross merchandise trade, and worker flows were used to economically characterize the region for the time period of study. The results show that development is mostly occurring on top of agricultural land, though higher intensity developments do are often replacing lower intensity uses. A third of all development occurs within a half-mile of a US highway, with a third of these developments occurring within a half-mile of I-540/I-49. The main cities of Northwest Arkansas are expanding their borders at a rate that maintains roughly 50% developed land cover, such expansion and land use track could make for an easily quantifiable measure of urban sprawl that could be combined with other factors to better quantify sprawl than current methods. Economically, Madison County, AR and McDonald County, MO both saw up to 80% permanent drops in economic trade that align with major milestones in the construction of I-540. This is further supported by a ten point drop in residents who chose to work outside of Benton or Washington County once the bypass was completed. Meanwhile, Benton County saw a short-lived doubling of trade, and Washington County saw a smaller, lagged effect that was also not permanent. These findings suggest that the I-540/I 49 created severe spatial and economic competition in the region with no obvious winner.

This dissertation studies the US housing market, banks' behavior under regulations and effects of bank capital constraint on the monetary transmission mechanism. It revolves around understanding the determination of the capital regulations on banks' optimal behavior, as well as quantifying the impact of these regulations on the effectiveness of the monetary policy. The first chapter, “The Impact of Local School Quality on Housing Price Volatility”, studies the effects of local school quality on housing-price booms and busts under the impact of exogenous credit-supply shocks, using school-district-level data in California between 2000 and 2012. The analysis shows that school quality, as an important amenity and utility dividend, reduces the impact of the exogenous shocks and anchors local housing values. The empirical work verifies that better schools make housing prices less volatile. The findings match the analysis of previous research in financial markets, in which there is a similarly negative association between share prices volatility and dividend yields. The second chapter, “How Do the Minimum Capital Requirements Affect Banking Competition and Profitability?”, examines the effect of the Minimum Capital Requirements (MCR) on banks' competition and profitability. The theoretical model shows that, in competitive market, banks trade off the costs and benefits of capital to maximize their profits. The MCR are thus likely to be an important factor on the bank's optimal choice and the target ratios increase with the MCR and decrease with banks' size. This paper also adopts the Industrial Organization (IO) approach to analyze the competitive effects of MCR on the oligopolistic market. Banks may collude to hold even higher capital ratios in the oligopolistic market since the capacity constraints caused by MCR reduce the competition. Using a sample of US banks from 2002 to 2015, the empirical works reveals that the relation between capital and profitability is nonlinear; it is depicted an inverted U shape. The third chapter, “The Effects of Capital Constraints on the Transmission of Monetary Policy: Fama-MacBeth Test”, analyzes the effects of bank capital constraint on the monetary transmission mechanism. The model demonstrates that the monetary transmission is stronger (loan supplies are more sensitive to changes in the monetary policy) if banks are well capitalized. The empirical Fama-MacBeth 2-step test reaffirms that (1) changes in monetary policy matter more for the lending of those banks with higher capital ratios; (2) The capital constraints are intensified during the period of tight money. Both effects are largely attributable to the smaller banks.

These essays contribute towards our understanding of the economics of space. This dissertation is composed of three chapters.Chapter one—Is the rent too high? Aggregate implications of local land- use regulation: Highly productive U.S. cities are characterized by high housing prices, low housing stock growth, and restrictive land-use regulations (e.g., San Francisco). While new residents would benefit from housing stock growth due to higher incomes or shorter commutes, existing residents justify strict local land-use regulations on the grounds of congestion and other costs of further development. This paper assesses the welfare implications of these local regulations for income, congestion, and urban sprawl within a general equilibrium model with endogenous regulation. In the model, households choose from locations that vary exogenously by productivity and endogenously according to local externalities of congestion and sharing. Existing residents address these externalities by voting for regulations that limit local housing density. In equilibrium, these regulations bind and house prices compensate for differences across locations. Relative to the planner's optimum, the decentralized model generates spatial misallocation whereby high-productivity locations are settled at too-low densities. The model admits a straightforward calibration based on observed population density, expenditure shares on consumption and local services, and local incomes. Welfare and GDP would be 1.4% and 2.1% higher, respectively, under the planner??Ễs allocation. Abolishing zoning regulations entirely would increase GDP by 6%, but lower welfare by 5.9% due to greater congestion.Chapter two—The impact of emerging climate risks on urban real estate price dynamics: In the typical asset market, an asset featuring uninsurable idiosyn- cratic risk must offer a higher rate of return to compensate risk-averse investors. A home offers a standard asset’s risk and return opportunities, but it also bundles access to its city’s amenities??Ẻand to its climate risks. As climate change research reveals the true nature of these risks, how does the equilibrium real estate pricing gradient change when households can sort into different cities? When the population is homogeneous, the real estate pricing gradient instantly reflects the “new news”. With population heterogene- ity, an event study research design will underestimate the valuation of climate risk for households in low-risk cities while overestimating the valuation of households in high-risk areas.Chapter three—Entrepreneurship, Information, and Growth: We examine the contribution to economic growth of entrepreneurial marketplace information within a regional endogenous growth framework. Entrepreneurs are posited to provide an input to economic growth through the information revealed by their successes and failures. We empirically identify this information source with the regional variation in establishment births and deaths. To account for the potential endogeneity caused by forward-looking entrepreneurs, we utilize instruments based on historic mining activity. We find that the information spillover component of local establishment birth and death rates have significant positive effects on subsequent entrepreneurship and employment growth for U.S. counties and metropolitan areas. A version of this article was previously published in the Journal of Regional Science as Bunten et al. (2015).

This dissertation explores aspects of identity choice and change in an economic context, and how choice of location can help predict “quality of life”. The first chapter studies the malleability of race for those that are mixed-race. Many modern surveys that collect demographic information now allow one or more racial categories to be chosen for one person. I construct a simple model of racial identity choice which implies that cultural and socioeconomic factors will influence the racial choices of those with multiracial ancestry. Using nationally representative data from the Census and the American Community Survey (ACS) I show that factors such as region, year, age, employment, and wages are associated with race selection among this population. Therefore, measuring socioeconomic outcomes of multiracial groups may be complicated if these same socioeconomic outcomes influence self-reported race. The second chapter examines relative group size, or whether a group is in the minority, a changeable social identity. We study how laboratory-created majorities and minorities interact, and how changing relative group size affects behavior. Our novel design allows us to examine whether two groups of unequal size exhibit differences in levels of trust and of trustworthiness and test whether causing the majority group to become the minority group, and vice-versa, changes behavior. We find that real-world majority race interacts with laboratory-created minority identity. We also find that subjects do not change their behavior when their relative group sizes change; behavior is driven by initial group size differences. In the third chapter we examine variation in local rents, wage levels, commuting costs, household characteristics, and amenities for 2071 areas covering the United States, within metropolitan areas, by density and central-city status. We demonstrate the sensibility of estimating wage levels by workplace, not residence, and recover decentralized rent gradients that fall with commuting costs. We construct and map a willingness-to-pay index, which indicates the “quality of life” typical households receive from local amenities, when households are similar, mobile, and informed. This index varies considerably within metros, and is typically high in areas that are dense, suburban, sunny, mild, safe, entertaining, and have elevated school-funding.

Infrastructure influences both depictions of the ideal city and economic models predicting urban growth. As the common variable, infrastructure investments could promote ideal city values within free market economies. To preserve the countryside and natural lands infrastructure investments must encourage concentrated growth in cities. The city and countryside are codependent. An abstraction between the two zones will lead to the demise of both the city and the countryside. New urban infrastructure should relate to public spaces creating economic, cultural, and social value in dense development. This value is achieved by generating a multiplicity of connections, program, and places within the existing urban fabric. Supporting and facilitating human activity, infrastructure has the ability to create place and suggest future growth. Infrastructure in American cities is often isolated and mono functioning. Constant widening of roadways along with investments in suburban infrastructure increases the supply of land available for development in the periphery of the city. The result is an uncontrolled, unplanned outward growth consuming valuable rural and natural lands. Expanding roadways to accommodate low-density sprawl is like telling a fat man to add another notch to his belt. This money should be used to invest in infrastructure that facilitates growth within the existing urban fabric. To ensure maximum value, this infrastructure should preform multiple uses and relate to public space. A design study preformed in Pensacola, Florida tests the viability of this new infrastructure. As North America’s first European settlement, Pensacola’s growth can be charted from the founding of the centralized historic city to the sprawling metropolitan area that surrounds it today. Implementation of water taxi and ferry systems will encourage dense development around existing harbors within the metropolitan area. A retrofit of Pensacola’s post-industrial waterfront supports this system while simultaneously providing a recreational and cultural amenity for the city.

This dissertation consists of three independent chapters. Chapter 1 examines the determinants and welfare implications of the increased geographic of workers by skill from 1980 to 2000. I estimate a structural spatial equilibrium model of local labor demand, housing supply, labor supply, and amenity levels. The estimates indicate that cross-city changes in firms' demands for high and low skill labor were the underlying forces driving the increase in geographic skill sorting. I find that the combined effects of changes in cities' wages, rents, and endogenous amenities increased well-being inequality between high school and college graduates by a significantly larger amount than would be suggested by the increase in the college wage gap alone.

In this set of essays, I grapple with issues related to the core questions of urban economics. Why are people so heavily clustered in urban areas? Why do some cities grow while others decline? What explains where people live within urban areas? My first essay focuses on understanding patterns of racial segregation within metro areas. One factor that has long been hypothesized to contribute to this divide, but has proven difficult to test empirically, is that local zoning regulations have an exclusionary impact on minority residents in some neighborhoods. I focus on variation in block-level racial composition within narrow bands around zone borders within jurisdictions. My results imply a large role for local zoning regulation, particularly the permitting of dense multi-family structures, in explaining disparate racial location patterns. The second essay returns to core issues of agglomeration and the role of cities. The fact that wages tend to be higher in cities, and that this premium grows with density, has been seen as strong evidence for urban agglomeration forces enhancing productivity. In modern data this density premium seems only to exist in areas with above average levels of human capital. Agglomeration models emphasizing learning and knowledge spillovers between workers in close proximity seem most compatible with the data. Finally, I investigate the impact of local governance structure on urban growth over the last 40 years. Some economists have touted the virtues of competition between fragmented local governments in efficient provision of local public goods, while regionalists have pointed to the need to coordinate planning and infrastructure across jurisdictions, and warned of the impacts of fractionalization on segregation and sprawl. While cities with regionalized governments have grown more rapidly, a small set of strong historical correlates with local government density can account for this. Impacts on segregation are more robust.

The present thesis is comprised of four essays that address important gaps in passenger- and cargo-airline research. Seminal studies in airline economics that rely on cross-section methods make critical homogeneity assumptions and preclude time-specific effects. The essays in this thesis use panel data, which allow for certain assumptions made by cross-sectional studies to be relaxed, while shedding light on the intertemporal features of air transport. The first chapter investigates the cost structure of air cargo carriers by applying a total cost model used in passenger-airline studies. Using quarterly panel data (2003-2011) on the domestic operations and costs of FedEx Express and UPS Airlines, empirical results indicate that the air cargo industry exhibits increasing returns to traffic density and constant returns to scale. Accounting for carrier-specific differences in cost structure and network size, FedEx is found to be more cost efficient than UPS (a finding that is reversed when network size is not controlled). Individually, UPS exhibits substantial economies of density and constant returns to scale while FedEx's cost structure is characterized by weak economies of density and constant returns to scale. Both carriers exhibit economies of size.The next three chapters embody papers that use quarterly panel data of city-level air traffic, airline delay, and socioeconomic variables. Spanning 10 years (2003-2012), the panel structure of the data permits the use of fixed effects to control for city-specific heterogeneity.The second chapter presents a paper prepared for the Airport Cooperative Research Program (ACRP). The study demonstrates the within-city traffic impacts of urban size, employment composition, and wages, providing new insights into the determinants of passenger and air cargo traffic. The essay also confirms that airport traffic is proportional to population, and that service-sector employment and higher wages induce passenger travel and goods movement. A city's share of manufacturing employment, however, only impacts air cargo traffic. Passenger enplanements exhibit more sensitivity to the proportion of urban workers providing non-tradable services, compared to the share of workers in tradable service jobs.The third chapter, co-authored with Andre Tok, examines the determinants of air cargo traffic in California. The study uses a shorter 7-year panel (2003-2009), and shows that service and manufacturing employment impact the volume of outbound air cargo. Total (domestic) air cargo traffic is found to grow faster than (proportionally to) population, while wages play a significant role in determining both total and domestic air cargo movement. Metro-level air cargo tonnage are also forecasted for the years 2010-2040, indicating that California's total (domestic) air cargo traffic will increase at an average rate of 5.9 percent (4.4 percent) per year in that period.The final chapter is co-authored with Volodymyr Bilotkach, and it provides the first evidence on the impact of airline delays on urban-sectoral employment. Controlling for unobserved city-specific differences, the empirical estimates of the effects of air traffic on total employment are comparable to previously reported measures. However, service-sector employment is found to be less sensitive to air traffic than other studies suggested. New evidence confirming that delays have a negative impact on employment is also provided, a finding that is robust to various model specifications.

In the midst of the Great Recession, cities across the country were impacted in a variety of ways, and most saw rapid increases in foreclosures. This report uses a conceptual framework composed of three elements, stressors, vulnerability, and resiliency, to look at the implications of foreclosures for cities. First, factors that cause foreclosures in the 100 largest Metropolitan Statistical Areas are examined. Then this report looks specifically at the economic impact of foreclosures. Using multiple regression analyses, the findings suggest that foreclosures have negative economic impacts and can be considered a stressor on a city’s economy. The application of this stressor has implications for a city’s vulnerability and resiliency. To some extent, local authorities have limited authority and capacity to prevent foreclosures. Therefore, this report also explores alternative approaches that cities can take to increase economic resiliency and competitiveness in the context of stressors such as foreclosures.

This dissertation consists of two essays. The connecting theme for this body of work is social interaction. I define social interaction, for this dissertation, as non-market based face-to-face interaction between individuals where each is interested in a response. The first contribution investigates the relationship between social interaction and neighborhood population density. I use the exogenous variation in a set of geological instruments to predict the neighborhood population density. The results suggest that an increase in neighborhood population density increases some types of social interaction. The second contribution brings social interaction into a standard urban consumer theory model, the Alonso-Muth model.

This dissertation comprises three chapters examining the economics of the housing and land markets. In “A Model of Sales, Prices, and Liquidity in the Housing Market,” I use a search and matching model of the housing market to address three main questions. First, what model of search and price determination best describes the housing market? Second, can a general equilibrium model generate the observed correlations between housing market variables? Third, what shocks have driven the historical behavior of the housing market? A model of competitive search is more likely than a model featuring random search and bargaining. Simulated data from the model qualitatively matches the correlations between housing market time series. Finally, the recent housing boom and bust were associated with an increase and subsequent decrease in the pool of eligible buyers, in addition to unrealized expectations of higher future productivity, the estimated size of which suggests a role for unwarranted optimism on the part of housing market participants. In “Metropolitan Land Values and Housing Productivity,” David Albouy and I present the first nationwide index of directly-measured land values and investigate their relationship with housing prices. Construction prices and geographic and regulatory constraints increase the cost of housing relative to land. On average, one-third of housing costs are due to land, and the elasticity of substitution between land and other inputs is one-half. Conditional on input prices, housing productivity is low in larger cities. The increase in housing costs associated with greater regulation appears to outweigh any benefits from improved quality-of-life. In “Price and Time to Sale Dynamics in the Housing Market: the Role of Incomplete Information,” I propose a model of the house-selling process in which sellers possess incomplete information regarding the state of the market. This model generates a negative correlation between house prices and time on market, a result that can persist even when realtors possess complete information. I construct an empirical measure of homeowner misperceptions regarding the state of the housing market, and show that sales volumes are negatively correlated with an increase in homeowners’ perceptions of house prices relative to actual market conditions.

The chapters of this dissertation examine efficiency failures in three areas of applied microeconomics: experimental economics, public finance, and game theory. In each case, we look at ways to resolve these failures to promote the public good. The first chapter, “An Experimental Test of the Pigovian Hypothesis,” looks at two different policies designed to reduce congestion in a common-pool resource (CPR). We present an experiment with training and a simplified decision task and find that subject behavior converges to the Nash prediction over a number of periods. A Pigovian subsidy effectively moves subject behavior to the pre-subsidy social optimum. Finally, we find a significant but non-persistent effect of information provision in moving subjects toward the social optimum. The second chapter, “Apples to Apples to Oranges,” looks at efficiency and equity failures across states resulting from public expenditure. This chapter introduces an extension of the Representative Expenditure System that uses regression methods and both state and metropolitan statistical area (MSA) level data, allowing for comparability of input costs, service requirements, and levels of need. The regression-based results are robust across state- and MSA-level formulations, although state-level approaches overestimate need for larger, less populous states. All regression-based results diverge from previous workload-based approaches. The third chapter, “Evading Nash Traps in Two-Player Simultaneous Games,” looks at efficiency failures in two-player simultaneous games. This chapter presents two new concepts: “détente” and “no-initiative,” in which players consider their own strategies and other-best-responses. We discuss their efficiency and descriptive properties across a set of simultaneous games.

This computable general equilibrium model determines the interactions of profit-maximizing firms from three different industries with each other and with utility-maximizing residents. Using a fixed-point equilibrium methodology, the size and tolls for the transportation system are determined to minimize total transportation costs, including land costs, tolls, and the value of residential travel time. Three industries are modeled: manufacturing, retail, and services. Their interactions are determined by parameters derived from U.S. Input-Output data. Because the model includes multiple industries and the retail industry, three modes of traffic travel are evaluated: commuting traffic, shopping traffic, and freight traffic. Two technological changes are analyzed: smart transportation and changes in firms’ production functions. The model finds that smart transportation systems do save significant transportation costs, but provide only a slight increase in utility. As firms continue to use more services, the deficit dividend declines and the loss in utility levels is minimized. Resident preferences also change over time. The most beneficial change, in terms of decreasing deficit dividend and increasing utility levels, is an increased preference for leisure time. A desire for larger lots leads to population decentralization. Two policies are also reviewed: the closing of the trade deficit and zoning. When the trade deficit is closed, the manufacturing sector increases in size and industrial production decentralizes. Zoning can be modeled with only one restricted industry or multiple restricted industries, an extension in the literature. Residential-only zoning with a minimum land rent above zero creates a city with vacant land. Asymmetric zoning is found to have more negative effects on residents than symmetric zoning.

Firms seeking sites for new or expansion plants rely on their ability to assess the benefits and costs generated by locating operations in a given state. State governments strive to understand the issues important to firms who are seeking a site for new operations or branch plants. They do so because attracting branch plants and new firms is critical to their economic growth. In addition to factors traditionally considered important to industrial location decisions (energy prices, wage levels, unionization, taxes, and public services), this study also considers the impact of the average level of education attained by the population of a state. Specifically, this study hypothesizes that the average level of education attained by a state's labor force significantly affects the location decisions of firms oriented toward local inputs. Results indicate that educational attainment is a significant determinant of where firms in the transportation industry decide to locate or expand operations. However, educational attainment is not a significant determinant for the electronic equipment industry. Wage and unemployment levels are significant factors for both industries. With the exception of educational attainment and tax levels, the results do not vary across industries. Since industries such as transportation equipment seem to place a premium on states with a relatively high level of education attainment, states wishing to attract this type of companies may find it beneficial to encourage higher education, both for the well-being of its residents and for the economy of the state.

This dissertation focuses on the functions and roles of two intermediate cities within an international economic system. Wallerstein's "world systems" model is used as a framework for studying changes that occur in a resource frontier region and its two cities as demand for regional resources increases on the world market. The cities, Samarinda and Balikpapan, are located in East Kalimantan, a resource-rich province of Indonesia. East Kalimantan's involvement in the world economy is paralleled by the Indonesian government's interest in provincial resources. Samarinda, the provincial capital and center of timber processing, and Balikpapan, the regional petroleum refining center, experienced rapid economic and demographic growth during the 1970s as they became centers of political and economic control over regional resources. A qualitative "urban system" model, adapted from Nijkamp, is used to analyze urban changes catalyzed by the arrival of multi-national timber and petroleum corporations and the dominant role of the national government. The study concludes that the future of resource frontier cities, such as Samarinda and Balikpapan, ... more dependent upon world market demand for regional resources and government policies aimed at resource management and marketing than it is upon explicit urban regional development policies.