Ameliorating the Gap: Peremptory Challenges, Jury Diversity, and Conviction Rates

By Gabriella Mestre

Background and Research Objective 

       In my thesis, I examine the effect of peremptory challenges, attorneys’ right to reject a certain number of potential jurors without a stated reason, on minority representation in juries and minority conviction rates. Despite efforts by the courts to prevent discriminatory uses of peremptory challenges, research has shown that attorneys disproportionally use these challenges against minorities. This high rate of peremptory challenge use against minorities is associated with a resulting decrease in jury diversity within state trials, which also produces negative trial outcomes for minorities, such as an increase in the minority convictions rate. Because of these important consequences, I examine the direct effects of peremptory challenges on the representation of minorities in juries and its downstream effects on the minority-majority convictions gap.


Data and Methodology

        I exploit the passage of Washington State’s GR 37 bill, which limits the number of peremptory challenges prosecutors can use, in both an event study framework and a differences-in-differences strategy comparing criminal jury trials in King County (KC), Washington and Maricopa County (MC), Arizona from 2016-2022. The data is made up of the minority share of juries in KC, whether the defendant in KC is predicted to be a minority or not, as well as, trial verdicts and trial dates for both counties during the selected time period. My empirical methods include an event study framework only using data from KC to estimate the causal effect of Washington’s GR 37 bill on both the minority share of juries and the minority conviction rate. Next, I estimate the relationship of the policy change on minority conviction rates in KC using a Differences-in-Differences (DD) approach where the control group is made up of criminal cases from MC. Finally, I estimate the same relationships using a DD approach where the control group is made up of White defendants within KC compared to minority defendants within KC. I do this to identify if the policy had differential effects on White versus minority defendants. 



       The evidence regarding the impact of WA’s GR 37 bill on the minority share on juries is striking: the restriction of peremptory challenges significantly increased the minority share on juries and decreased the minority conviction rate, but not significantly. Specifically, after the policy implementation, the average minority share on juries for minority defendants increased by 13.83 percentage points overall and it increased by 10.1 more percentage points when compared to White defendants. Similarly, after the policy implementation, the minority conviction rate decreased on average by 9.5 percentage points overall and it decreased by 3.28 more percentage points when compared to the White conviction rate during that time period. Looking at the cross-county DD, after the policy implementation, the minority conviction rate decreased by 1.08 percentage points more than it did in MC, but this was not a significant decrease. 



       Most plainly, my findings indicate that limiting peremptory challenges appears to have increased the minority share of juries for all defendants and decreased the minority conviction rate. As a result, additional states with similar objectives to Washington’s may seek to reform their peremptory challenge system through a limitation of these challenges to increase jury diversity and potentially remedy the majority-minority convictions gap.


Leveraged Landlords: Life-Cycle Portfolio Choice With Rental Properties, Mortgages, and Margin Calls

By Lucas Szwarcberg

Even though as many as 8% of taxpayers report rental income, the reasons for which individuals invest directly in this sector rather than exclusively holding diversified stock portfolios remain largely unexplored. My thesis investigates the hypothesis that households invest in individual rental properties because they can take out a mortgage to finance a large fraction of the property’s value, without being subject to margin calls as they would if they borrowed from a margin account to buy stocks.


I develop a theoretical model of households’ portfolio allocation between stocks, cash, and rental properties over their earning years, incorporating labor income uncertainty and allowing for both mortgage and stock-margin leverage. Calibrating the model using historical parameters and solving it numerically, I demonstrate that mortgage-funded rental-property investment is particularly appealing for young investors, as their future labor income justifies greater risk-taking.


The model results also show that initial wealth has a non-monotonic effect on the amount of rental housing purchased, because rental-property ownership is most attractive at medium values of wealth, which are high enough to afford the smallest possible property without taking on too much risk and low enough that future income makes leverage highly desirable. In addition, I analyze how the results change depending on parameters such as the rental yield of the property, the riskiness of labor income, and the correlations between assets and income.


My paper describes several implications for my findings. First, this leverage motive for buying individual rental properties may help explain why the majority of rental housing is supplied by households rather than professionally run businesses, even though the latter can achieve greater diversification and economies of scale. Second, there may be an asset-market distortion from the fact that it is usually only possible to take out mortgages (i.e., loans not subject to margin calls) to buy rental properties and not stock indices, thus leading some investors to prefer rental properties even if their pre-leverage returns are comparable to those of stocks. Third, while the use of stock-margin leverage to take on more risk than with regular stock investment has been recommended for young investors by books such as Lifecycle Investing, a greater number of investors may already be employing a similar leveraging strategy through rental-property investment. Fourth, my model shows that higher-income households can purchase rental properties earlier on average and thereby achieve higher risk-adjusted returns, which aligns with an empirical literature showing that the rich earn higher returns on their investments. My findings thus also contribute to the literature on wealth inequality.


In summary, by describing a leverage motive for households’ rental-property investment, my paper uncovers a theoretical justification for the role of rental-property investment in personal finances.

From Urban Form to Friending Bias: Testing Jane Jacobs’ Hypotheses

By George Crowne


In an increasingly fragmented America, the question of how to socially integrate different groups of people is growing in importance. Research has shown that cross-group social integration has effects on a variety of outcomes ranging from educational attainment to overall health to income inequality. One theory for reducing cross-group bias stems from Gordon Allport’s seminal work on the effects of physical intergroup contact. Allport’s theory suggests that under certain conditions, intergroup contact can decrease intergroup biases by reducing the salience of group differences and increasing the frequency and quality of interactions. Additionally, influential work over half a century ago by Jane Jacobs emphasizes the impacts of the urban built environment on mobility patterns and social behavior. But can urban form affect the people with whom we interact? Do interactions caused by effective urban design meet the conditions for Allport’s contact hypothesis?


Hypothesis and Methodology

In my thesis, I empirically examine the hypothesis that the urban built environment can promote interactions between individuals in different socioeconomic groups, and that these interactions can reduce class-based friending bias. To this end, I study three features of the urban built environment that Jacobs’ framework implies might increase random interactions: small city blocks, entertainment place density, and mixed primary-use buildings. I begin by showing that these three features strongly predict experienced cross-class interactions, as measured by individual-level GPS cellphone mobility data. This result reinforces Jacobs’ theory that effective urban form can create random, unplanned interactions. I then turn to the second step in the causal chain: do these random cross-class interactions also increase cross-class social cohesion? I show that experienced cross-class interactions are strongly correlated with greater cross-class relationships, as measured by large-scale Facebook friendship data. Next, I find a similar relationship when I instrument cross-class interactions with the three features of the urban built environment, implying a causal effect of physical interactions on cross-class bias, and supporting Allport’s contact hypothesis.



These results suggest that city design can play a significant role in promoting cross-group interactions and reducing group based bias. By designing cities in ways that promote unplanned interactions we can create opportunities for people from different socioeconomic backgrounds to interact and create cross-class friendships. With approximately 80% of the US population, and a growing fraction of the global population living in cities, these results can have significant implications for upward economic mobility, income inequality, and other positive effects of increased cross-group social integration.

Econ Thesis Class of 2023

Congrats to the amazing Class of 2023 Ec Thesis Writers!  We’re so excited to share some of their work here and at the Poster Session at the Ec Department’s inaugural Undergraduate Conference Highlighting Excellence in Economics Research! If you’re in town, join us Thursday, April 27 (details in various emails from the Department).

Decarbonization in Doubt: Evaluating the Uncertainty of the Indirect Land Use Change Carbon Intensity Estimates of Corn Ethanol

by Katherine Ricca

Background and Research Objectives

The true carbon savings of corn ethanol as a biofuel substitute for gasoline are highly contested. Experts and policymakers alike are unable to agree on the total carbon intensity (CI) for the fuel, a measure of the carbon emissions produced per unit of energy. This uncertainty is largely due to emissions generated by indirect land use change (ILUC), in which changes in agricultural land used to support biofuel production in one region affect land use decisions in others. ILUC CI cannot be measured empirically, therefore the uncertainty largely stems from the assumptions required by modeling, presenting an avenue for estimation improvement. Accurate estimation of the total CI of corn ethanol is critical because key biofuel legislation allocates subsidies based on CI values.


The objective of my thesis is therefore two-fold:

  1. To decompose the uncertainty in ILUC CI estimates produced by assumptions in the field leading ILUC CI modeling framework.
  2. To translate this uncertainty into emissions consequences through a policy analysis of the California Low Carbon Fuel Standard (LCFS).


Dataset Production

To begin, I must construct a dataset of input and ILUC CI output values simulated by the ILUC CI modeling framework. I do so with Monte Carlo analysis, a methodology that assesses the uncertainty of a model by running a series of random trials that vary the values of input parameters to produce different output values.


Objective #1: Decomposing Uncertainty in Modeling

To address the first objective, I regress the varied parameter input values from the Monte Carlo dataset on the ILUC CI output values to determine the impact of each parameter on the final output value of the modeling framework. These relationships are not immediately obvious because the ILUC CI modeling framework consists of a series of models that transform initial inputs through multiple stages.


Results of the regression demonstrate that a single parameter, yield price elasticity, contributes to the vast majority of the variance in ILUC CI estimates. Yield price elasticity captures the response of agricultural yields to changes in commodity prices. Its importance is therefore justified given that increasing or decreasing yield due to price changes will affect the amount of land needed to produce crops for biofuel production, therefore impacting ILUC emissions. Such a strong influence of this single parameter suggests that future research directed at refining the modeling framework should focus funding and time on refining the yield price elasticity value.


Objective #2: Assessing the Policy Impact of Uncertainty

To address the second objective, I leverage three key facts about the LCFS. First, the LCFS defines the total CI of corn ethanol as the sum of direct emissions from production and ILUC emissions. Second, the subsidies of the LCFS are determined based on the total CI assumed for corn ethanol by the policy, with a smaller total CI yielding a greater subsidy. Third, the subsidy incentivizes corn ethanol producers to reduce the direct emissions from their refineries, with a greater subsidy generating greater direct emissions reduction. Together, these three facts demonstrate that the ILUC CI value of corn ethanol assumed by the LCFS directly impacts the emissions reductions incentivized by the policy. If the estimated ILUC CI value is too high or too low, the policy will result in forfeited or excess emission reductions respectively. Through a series of equations defined in my thesis, I can use the ILUC CI estimates from the Monte Carlo dataset to generate a range of potential direct CI reductions, and therefore potential emissions reductions under the policy.


Results suggest that the ILUC CI estimate and thus total CI estimate for corn ethanol currently used by the LCFS legislation is likely larger than the true value, generating a subsidy that is too low. This under-subsidy results in forfeited direct CI reductions and therefore forfeited annual emissions reductions of up to 200,000 MT CO2e. These emissions totals are enough to be concerned and support efforts to refine the ILUC CI value of corn ethanol, yet still small enough to inspire confidence in the LCFS policy. As we look towards goals to achieve net-zero by 2050, this thesis ultimately contributes to the literature supporting the use of biofuels like corn ethanol as part of the energy transition.

The Effect of COVID-19 Eviction Moratoria on School Enrollment

By Rick Brown

In my thesis I quantify the degree to which evictions affect school enrollment. I exploit heterogeneity in state-level eviction moratoria implemented during the COVID-19 pandemic to estimate the impact of evictions on school enrollment. My preferred specification uses a triple difference-in-differences model that examines enrollment changes in high versus low poverty counties in moratoria versus non-moratoria states. I run this model for all observations and then employ a county border pair design that compares schools that are likely similar in unobservable characteristics (e.g. COVID-19 case-counts, labor markets).

Using the triple difference-in- differences model, I ultimately find that moratoria lead to a statistically significant 2% to 2.4% increase in school enrollment in disadvantaged communities. These results are robust to inclusion of state-by-year fixed effects (state fixed effects year fixed effects). I contrast these main results with a simpler event study design that does not exploit the within-state control group. I argue that these alternative specifications are not likely to provide valid estimates during the COVID-19 pandemic because of the rapidly changing policy environment. In addition to this methodological point, the substantive lesson from this analysis is that eviction policies can directly affect the educational attainment of children.


Gender and Advising in Undergraduate Research: Evidence from the Harvard Hoopes Prize

By Sonya Kalara

Do women win the Hoopes Prize, an undergraduate award for thesis-writing at Harvard College, more often than men? Does the gender makeup of the advising team affect the probability that their student will go on to win the Hoopes?

I break down the timeline between enrollment at the college and Hoopes acquisition into three stages: Pathway, Connection, and Evaluation.

  • In the pathway stage, a student is enrolled at Harvard, they choose a concentration, and they choose to write a thesis. Whereas Harvard College at large has a 50/50 gender split, gender representation in different concentrations varies massively.
  • In the connection stage, a student decides to write a thesis, and chooses their advising team. The literature on this topic indicates that students search for same-gender advisors and so we’d expect that gender “dyads” (m/f combinations) would exhibit some skew.
  • Thirdly, in the evaluation stage, a student is nominated for the prize by at least one member of their advising team. Although the nomination phase is crucial, all information about Hoopes nominees is confidential, therefore this piece isn’t directly included in my analysis. Finally, a student is selected for the Hoopes Prize and we expect that this selection from the pool of nominated writers exhibits variance.


Pathway Stage

I compare the number of graduating seniors in each department to the number of thesis writers. This allows me to calculate the average number of women in a concentration that go on to write a thesis as compared to the average number of men. Surprisingly, for all 9 concentrations that I study, women are more likely to write theses than men. Although this result wasn’t statistically significant in all concentrations, the evidence suggests that the rate at which women write theses is not the broken rung in the Hoopes evaluation process.


Connection Stage

Figure 1 shows all of the different pairs between advising teams and students by gender. A further subdivision by concentration is included in the full thesis; the volume of each pair varies widely by department. However, this graph should demonstrate at a general level that there exists some assortative matching.

After establishing that this pattern of seeking same-gender advisors exist within specific concentrations, I used statistics to randomly assign advisors to students. I then compared this “predicted distribution” to the actual rates of student/advisor matching and I find that students search for same-gender advisors, and women are more likely to seek out female advisors in male-dominated concentrations.

Evaluation Stage

Figure 2 shows the proportion of Hoopes Winners in every concentration by gender. I use OLS to investigate how the probability of winning a Hoopes Prize differs by student and advisor gender. First, in most concentrations, there is some baseline probability that women with at least one female advisor will win the prize. The mathematical evidence is mixed regarding the relative (dis)advantage of being a male student and having an all-male advisor team doesn’t appear to be particularly advantageous for female students. Interestingly, it appears that any advantage male students have is almost entirely quashed if they have an all-male advisor team. This evidence indicates that the most productive pairing is between male students and female advisors.

The Effects of Experience and Technological Innovation in the Offshore Wind Industry

By Keshav Rastogi

Offshore Wind Turbines Have Rapidly Grown in Size

In my thesis, I explore the drivers of capital expenditure (CAPEX) reductions in the offshore wind energy sector. Identifying key drivers is important because of how quickly the international and domestic offshore wind industries are projected to grow. By the end of 2018, nearly 23 gigawatts (GW) of offshore wind capacity were installed globally, with 154 to 193 GW projected by 2030.[1]

Specifically, I investigate two hypotheses. One is whether there has been significant learning-by-doing among companies developing (planning and assembling) offshore wind farms and those manufacturing turbines. The other is whether technological innovations among turbine original equipment manufacturers (OEMs) have been primarily responsible for recent reductions in CAPEX. The primary technological advancement has been in the size of turbines, as offshore turbines have become continually larger than their onshore counterparts since the early 2010s. Learning-by-doing is the idea that productivity increases due to accumulated experience.

In order to understand whether there exists learning-by-doing in the offshore wind sector, I model the typical developer’s project design problem, which includes, among others, the variables of interest measuring developer experience, OEM experience, and turbine size. By exploiting the fact that developers frequently have limited agency over deciding the size of their projects, I solve for the developer’s profit maximizing decision and manipulate the resulting equation such that it can be empirically estimated by an OLS regression with fixed effects. I conduct the analysis using data from offshore energy consultancy 4C Offshore covering all fully commissioned, or completed, offshore wind farms. The preferred set of specifications, which control for market selection of low-cost firms, show no statistically significant evidence of learning-by-doing among either developers or turbine OEMs.

In contrast, the empirical results suggest that a doubling in average turbine rating, or size, is robustly associated with a 19 percent decrease in total costs, which corroborates the broad academic and industry-based consensus that larger turbines have been a key driver of CAPEX reductions. In my discussion of the results, I demonstrate how the cost-reducing effects of turbine rating nest within the developer’s decision regarding turbine size at a particular site. I then use these estimates to make projections for the costs of offshore wind farms currently under development globally. With regards to policy, the lack of significant learning-by-doing may make it more difficult to justify demand-based policies such as future installation targets, while the cost-reducing impact of larger turbines may rationalize expanded government-funded research and development efforts.

[1] Musial, Walter, Philipp Beiter, Paul Spitsen, Jake Nunemaker, and Vahan Gevorgian. 2019. “2018 Offshore Wind Technologies Market Report.” U.S. Department of Energy.

Warm Glow from Voting vs. Direct Costs: Evidence from the 2020 Election, Black Lives Matter Protests, and Mail-in Balloting

By Dhruv Mohnot


Social scientists have long been interested in voting as a phenomenon. There is a famous Georg Hegel quote as well: “The casting of a single vote is of no significance when there is a multitude of electors.” Why, then, do people vote? Theoretical work has failed to predict the high turnout we see in elections, since each individual vote is almost certainly inconsequential to the outcome. Empirically, several papers have found that social pressure influences voting patterns. By making voting behavior more salient, voting becomes more popular (internal/social benefits rather than external candidate-level benefits).

My research focuses on two major changes that plausibly influenced the 2020 presidential election outcomes. First, Black Lives Matter protests were a major national phenomenon that may have motivated individuals to vote (by, for example, making voting behavior more relevant in social contexts). Second, the expansion of universal mail-in balloting in several states due to the COVID-19 pandemic allows for a natural experiment investigating the effect of the cost of voting.

Using two quasi-experimental research designs (instrumental variables for protests & difference-in-difference for mail-in balloting), I estimate the effect of these changes on 2020 election outcomes (voter turnout and Republican vote margin).


Interestingly, I find that protests had a very limited effect on both turnout and margin. A one-unit per capita increase in protest size increased Republican margin by 0.03 percentage points and turnout by 0.17 percentage points, a statistically significant result robust to many specifications and interactions. The effect was primarily concentrated in Democratic areas, suggesting that increases in Republican margin were primarily driven by a backlash against the movement. Notably, this is a very small effect size relative to prior papers investigating the effect of protests (e.g. Madestam et al. find huge effects of the Tea Party protests in 2009 on 2010 midterm elections).

Mail-in balloting, on the other hand, has a large effect. Counties that expanded to universal mail-in balloting in this election cycle saw increases in turnout by 2.52 percentage points and Republican margin by 0.45 percentage points, relative to counties that did not change mail-in balloting policies. This is primarily driven by higher voting rates by 65+ individuals in counties that had universal mail-in balloting, suggesting that older voters who feared COVID-19 infection only voted (primarily for Republicans) when voting was safe. Both changes together only explain about 9% of the overall change in turnout in 2020 and likely did not affect the overall election outcomes.


There are several hypotheses for why protests had such a limited effect. My design estimates the locally specific effect of protesting. It is possible that protests were such a nationalized phenomenon that there was no additional locally specific effect of protesting. For example, protests in Portland were immediately broadcast via news networks and social media to all parts of the country, making the Portland specific effect next to nothing.

Alternatively, political polarization has made protests unlikely to change voters’ minds. Instead, national events are filtered through a partisan lens and only affect voter motivation. Republicans were motivated by seeing protests in their backyard, but voters did not change their minds at all.

Ultimately, my paper shows that making voting easier has a much larger effect on turnout than large-scale protests. Though it is unclear if mail-in balloting expansion will remain in place going forward, it does increase voter turnout, as theory would expect. On the other hand, BLM protests did not have a locally-specific effect in the short-term but may precipitate a longer-term realignment of race discussions in the country, leading to longstanding political changes over the next decade.

Attributing Changes in Teen Sexual Behaviors to Reproductive Health Education and Publicly Funded Clinics

By Chelsea Vuong

Background and Motivation:

Adolescents engaged in risky sexual behaviors, such as having multiple sex partners or partaking in sexual intercourse without birth control, have an increased risk of negative reproductive health outcomes. These outcomes can range from acquiring a sexually transmitted disease (STD) to an unintended pregnancy. Moreover, the physical, mental, and intellectual abilities compromised through high-risk pregnancies deeply impact a teen’s adulthood productivity. Therefore, by mitigating the factors that contribute to risky teen sexual behaviors, adult outcomes can be greatly improved. This paper studies reproductive health education and contraceptive usage among teens, as these are two effective factors that help mitigate risky sexual behaviors.


Data and Methodology:

State level data within the United States is used for this analysis.  Reproductive health education and publicly funded clinics are the two independent variables of interest, and no condom or any birth control use among teens are the two dependent variables of interest. Data on condom or birth control use, the primary outcomes of interest, comes from the Center for Disease Control and Prevention’s (CDC) High School Youth Risk Behavior Survey (YRBS). The state level data on publicly funded clinics, one of two independent variables of interest, comes the Health Resources & Services Administration (HRSA) for the total number of federally qualified health centers (FQHCs). The state level data on reproductive health curriculum, the second independent variable of interest, comes from the Sexuality Information and Education Council of the United States (SIECUS).

The first part of the study measures the correlation of FQHCs and reproductive health education on risky teen sexual behaviors using an Ordinary Least Squares (OLS) regression model. Then, an instrumental variable (IV) design is used to address the endogeneity issue with the OLS regression model. The two risky teen sexual behaviors analyzed in this paper are teens not using a condom or any method of birth control during their last sexual intercourse.


Key Findings and Implications:

The IV regression results for FQHCs indicate that there is no statistically significant effect of the number of health centers per 1000 teens on risky teen sexual behaviors. These results may hold strength in the overall context of publicly funded clinics, as publicly funded clinics comprise of FQHCs, Title X-funded clinics, and Planned Parenthood clinics. Since this study only analyzed FQHCs, it merely captured the effects of a portion of publicly funded clinics. To better estimate the impact of funding cuts on publicly funded clinics, data on Title X-funded and Planned Parenthood clinics should also be analyzed.


The IV results for reproductive health education show that mandated sex education, marriage education, and abstinence education were significant at reducing no condom use. For the simulated instrument regression, contraceptive education and education that prohibits abortion instruction were significant towards improving no condom and birth control use. While the findings are mixed, it is likely that continuing any type or mixture of education has potential in improving risky teen sexual behaviors.


Overall, my thesis provides a preliminary look at the multifarious dimensions of risky teen sexual behavior factors. Additional research that builds upon the findings of this study is necessary to develop informed school and state policies that better address teen reproductive health.

Big Names, Bigger Barriers: Firm Reputation as a Barrier to Entry

By Hannah Jo Ellery

The success of a firm depends upon its workers, and thus upon how workers chose which firm to work for. One of the factors which may play a role in this decision is the reputation of the firm under consideration. Indeed, if reputation does play a role, it may have implications for the structures of labor markets and for markets more broadly, as firms which have had more time to build a reputation and rapport—incumbent firms—may have an entrenched advantage in hiring. In my thesis, I explore this possibility: do workers have a preference for firm reputation? What implications does a preference for reputation have for new firms in the labor market? Could prestige become a barrier to entry?

I first build a theoretical foundation for my hypothesis. In order to do so, I study a framework of worker-firm matching in a two-sided matching model, based in part on models of labor market matching introduced in Kelso and Crawford (1982). In this model, workers choose a single job and salary described by a contract, while firms choose multiple contracts, the union of which describes their total workforce.

Into this framework, I introduce reputation, taking as a base work done in Pycia and Yenmez (2017). Namely, I allow workers to care about the success of a company and what other workers think of that company. Notably, this is different from basic matching models, which avoid structures in which workers’ choices depend on the choices of others. When workers care about the success of a company, which depends upon the workers that are employed at that company, equilibrium matchings may not exist; instead, workers may wish to cycle between firms ad infinitum. Indeed, I show that in the context of a labor matching model with agents and utility functions, we cannot introduce a true preference for reputation. If workers’ choices depend on the current status of the labor market, as they would if the worker wants to be employed at a successful firm, equilibria may not exist. Thus, if workers care about the status of their firm, we may not be able to find a matching of workers to firms for the economy.

In spite of this, where equilibria do exist, I show that not only will markets tend to be more concentrated when workers have a preference for prestige, but it will also be weakly more difficult for a new start-up firm to enter a market where incumbents have already developed a reputation.

Second, I begin to show some evidence for such a preference for reputation in the labor market. In particular, I create a data set which collects the alma mater law schools of the employees of five large law firms, as well as the graduation year, hiring year, and former clerkships for each worker. Fortunately, large law firms are ranked explicitly on reputation and prestige in Vault’s annual Law 100 listing. This enabled me to compare the firm’s annual hire quality with their reputation, showing a strong and significant positive relation between reputation and hire quality both across and within firms.

Overall, this combination of theoretical and empirical evidence indicates that firm reputation may indeed play a role in the functioning of labor markets. Future research can help us to determine what industries feel the effects of this barrier the most, and how reputation impacts entry in practice.

Econ Thesis 2021

We’re excited to have an incredible cohort of Class of 2021 Ec Thesis Writers this year!  They deserve a special shout-out for taking on the task of thesis research entirely remotely.  We look forward to sharing their work with you on this site and to hosting our annual Ec Thesis Poster Session in April.  More details coming soon!