<p>Decades and policies come and go, and the ominous problem of corruption remains almost unaltered. Some of the most sought-after policies for corruption deterrence focus on institutional reforms aimed at assuring the right and effective access to information, reinforcing rule of law, tackling impunity, and increasing integrity standards for public servants. The aim of this dissertation is to test whether the impact of these policies over corruption is traceable at the subnational level of mexico and the united states. Seeking to accomplish this purpose, statistics measuring corruption, transparency and relevant variables are analyzed through ols regression and correlation methods. The findings point that spite of the evident benefits of transparency for democratic governance, under the methodology selected and with the ensuing subnational statistics, it is not possible to affirm that corruption is noticeable affected by transparency or integrity variables. Implications of these findings ask for a revision on the manner corruption is measured, and to devise which sort of circumstances bolster or thwart transparency´s prowess to cause a dent over corruption.</p> <p> </p>

<p>This dissertation is a collection of three papers. Each paper constitutes a chapter. Each chapter empirically examines an aspect of bias-motivated behavior in the United States. </p> <p>The first chapter studies the impact of penalty enhancement statutes by state legislatures on the incidence of hate crimes in the United States. Penalty enhancements may deter crime, however, the passing of such laws may also increase awareness among law enforcement officials and increase arrests. Using administrative data on hate crimes and a difference-in-differences method that leverages state-level variation in the introduction of legislation, this paper does not find a significant effect of the state enactment of penalty enhancement statutes on hate-crime incidence rates. </p> <p>The second chapter examines whether election timing and election outcomes affect the incidence of crimes motivated by hate and intolerance. Using administrative data and a difference-in-differences design that compares election with non-election years, I show that hate crimes increase by an average of 28 percent in the three weeks around a US presidential election. This effect is larger in recent presidential elections and when there is no incumbent candidate. Second, using a similar design and cross-state variation in the timing of gubernatorial elections, I find no evidence that these state-level elections affect hate-crime incidence. Third, using regression-discontinuity designs based on vote counts, I find that the number of hate crimes is not affected by presidential or gubernatorial election outcomes. </p> <p>The third chapter studies the impact of presidential and gubernatorial election timing on the level of toxicity present on social media platforms such as Twitter. Together with Sameer Borwankar, I empirically determine the extent to which the toxicity of Twitter content changes during election times as compared to non-election times. We randomly sample Twitter users and collect all tweets made by this sample around election time. We use a difference-in-differences identification leveraging election and non-election years. We further focus on toxic content that is motivated by political polarization and examine various bias-motivation categories that come up in this content as well as the variation in the intensity of toxicity between national and local election times.  </p> <p><br></p>

<div>The purpose of this dissertation is to study the effectiveness of public policies in generating fuel savings and emissions reductions. I focus on applying various empirical methods to analyze consumer responses to policy changes on both extensive and intensive margins. This dissertation consists of two chapters.</div><div><br></div><div>In the first chapter, I compare the effectiveness of fuel taxes and product taxes on reducing gasoline consumption of new car buyers. I employ a unified data source for vehicle choice and subsequent vehicle use to estimate a random effects logit demand model that explicitly accounts for vehicle use heterogeneity. My demand estimation suggests that new car buyers fully value the fuel-saving benefits from improved vehicle fuel efficiency when they initially purchase their cars. My policy simulations indicate that high-mileage drivers are more responsive to a change in fuel taxes than to a change in product taxes, even as low-mileage drivers are more responsive to product taxes. By capturing such heterogeneous consumer response to policies, I show that a counterfactual increase of the fuel tax is more effective than a revenue-equivalent product tax in reducing the total gasoline consumption of new car buyers. Further, when accounting for its effects on consumer response on both extensive and intensive margins, a change in fuel taxes has a clear advantage over a change in product taxes in reducing the consumption of gasoline even when the magnitude of tax increase is small. More importantly, a model not accounting for vehicle use heterogeneity understates the fuel saving effects of both policies and misleads us about the relative effectiveness when comparing different policies. </div><div><br></div><div>The second chapter explores how changes in the marginal cost of driving affect consumers decisions about passenger vehicle utilization, as measured by average daily miles traveled per vehicle. This intensive margin of consumer response has important implications for the effectiveness of usage-based policies, such as the fuel tax and the mileage tax, that designed to address externalities of driving. I estimate the elasticity of driving with respect to fuel cost per mile using a large panel data that covers 351 towns and cities in Massachusetts over 24 quarters. While most researchers in this literature apply fixed effects estimators to examine the elasticity of driving, I use a factor model econometric setup to account for unobserved common factors and regional heterogeneity. Residual diagnostics confirm that the factor model setup does a better job of removing the cross-section dependence than fixed effects estimators do. Given low consumer responsiveness to changes in the marginal cost of driving engendered by current usage-based policies, rights-based approaches like congestion charges might be better alternatives to influence vehicle utilization and vehicle ownership.</div>

<div>This thesis consists of three chapters. In the first chapter, I investigate the effects of complexity in various voting systems on individual behavior in small group electoral competitions. Using a laboratory experiment, I observe individual behavior within one of three voting systems -- plurality, instant runoff voting (IRV), and score then automatic runoff (STAR). I then estimate subjects' behavior in three different models of bounded rationality. The estimated models are a model of Level-K thinking (Nagel, 1995), the Cognitive Hierarchy (CH) model (Camerer, et al. 2004), and a Quantal Response Equilibrium (QRE) (McKelvey and Palfrey 1995). I consistently find that more complex voting systems induce lower levels of strategic thinking. This implies that policy makers desiring more sincere voting behavior could potentially achieve this through voting systems with more complex strategy sets. Of the tested behavioral models, Level-K consistently fits observed data the best, implying subjects make decisions that combine of steps of thinking with random, utility maximizing, errors.</div><div><br></div><div>In the second chapter, I investigate the relationship between the mechanisms used to select leaders and both measures of group performance and leaders' ethical behavior. Using a laboratory experiment, we measure group performance in a group minimum effort task with a leader selected using one of three mechanisms: random, a competition task, and voting. After the group task, leaders must complete a task that asks them to behave honestly or dishonestly in questions related to the groups performance. We find that leaders have a large impact on group performance when compared to those groups without leaders. Evidence for which selection mechanism performs best in terms of group performance seems mixed. On measures of honesty, the strongest evidence seems to indicate that honesty is most positively impacted through a voting selection mechanism, which differences in ethical behavior between the random and competition selection treatments are negligible.</div><div><br></div><div><br></div><div>In the third chapter, I provide an investigation into the factors and conditions that drive "free riding" behavior in dynamic innovation contests. Starting from a dynamic innovation contest model from Halac, et al. (2017), I construct a two period dynamic innovation contest game. From there, I provide a theoretical background and derivation of mixed strategies that can be interpreted as an agent's degree to which they engage in free riding behavior, namely through allowing their opponent to exert effort in order to uncover information about an uncertain state of the world. I show certain conditions must be fulfilled in order to induce free riding in equilibrium, and also analytically show the impact of changing contest prize structures on the degree of free riding. I end this paper with an experimental design to test these various theoretical conclusions in a laboratory setting while also considering the behavioral observations recorded in studies investigating similar contest models and provide a plan to analyze the data collected by this laboratory experiment.</div><div><br></div><div>All data collected for this study consists of individual human subject data collected from laboratory experiments. Project procedures have been conducted in accordance with Purdue's internal review board approval and known consent from all participants was obtained.</div>

<p dir="ltr">The rise of digital media has allowed for unprecedented access to information. In particular, people are able to form beliefs based on information sources that span the full spectrum of reputation, information quality, and motivated biases. Such access is a double-edged sword because “with great power, comes great responsibility” (“Spider-Man”, 2002). Heterogeneity in information quality may be due to a variety of factors, and it is often up to the consumer to consider quality signals when evaluating the quality of information. My research explores this complicated process, and contributes to the understanding of how people demand and utilize information in different environments. I do so over three chapters. The first studies how people respond to signals of information quality in a sequential prediction game. In the second chapter, biased incentives are introduced in a prediction game experiment to test how intrinsic and extrinsic biases affect demand and utilization of information. The third chapter contains a survey in which subjects report their valuations of an X account that varies on political affiliation, occupation credentials, and number of followers.</p><p dir="ltr">My first chapter focuses on how subjects respond to signals of information quality. In it, subjects predict which of two urns was randomly chosen in each of 30 rounds. They observe a private ball drawn from the selected urn each round to help them make their prediction. The color of the ball signals the urn it came from. The subjects then sequentially broadcast their belief about which urn was selected for the session without revealing the color of the observed ball. Future subjects can use the previous broadcasts to infer additional information that may help them accurately predict the urn.</p><p dir="ltr">In the control, subjects exhibit very low utilization of previous predictions when informing their own behavior. While consistent with prior research, behaving in such a manner is suboptimal. To experiment on the malleability of subjects’ beliefs about the rationality of others, I implement two novel treatments. In the first, the subjects’ prediction order in the last 15 rounds is determined by their accrued earnings in the first 15 rounds, with highest earners predicting first. The prediction order is similarly determined in the second treatment, except a quiz on conditional updating ability is used. Subjects who score the highest on the quiz predict first. In both cases, the sorting mechanism is explained to the subjects.</p><p dir="ltr">Sorting on earnings yields a modest increase in valuations of previous subjects’ predictions. A much more significant increase is observed when sorting on ability. Additionally, the subjects who make the fewest irrational predictions (ones against the color of the ball when they do not have additional information to suggest otherwise) are the ones who score the best in the ability sort. Placing them at the beginning of rounds increases the entire round’s average earnings.</p><p dir="ltr">My second chapter uses a similar environment to study the role that bias plays in demanding and utilizing information. In it, participants predict which of two states (red or blue) each of 30 rounds was assigned. To aid them, participants observe two predictions from ‘experts,’ who are informed by a private signal with a known precision. Participants can bid to receive additional information about the state from two sources: a private signal and another independent expert’s prediction. Both sources’ precision is known. This method is the first of its kind, and allows for direct comparison between information types. The bid results are revealed once this process is complete. Participants then predict the state.</p><p dir="ltr">Two innovative treatments are implemented to implement bias into the basic environment exogenously. In the first, participants receive a small bonus each time they predict the state is blue. In the second, experts receive the same bonus each time they predict the state is blue instead of the participants. Surprisingly, participants value the private signal and additional expert’s prediction similarly, except when the experts are biased. This is a departure from most research using similar environments, which assume that some sub-optimal behavior can be attributed to mistrust in others’ ability to understand the environment. That assumption may warrant further and more careful evaluation. The most striking valuation behavior is when participants are biased. Their bids are higher when their existing information set already favors their bias, relative to when it is against it. Doing so is antithetical to the rational equilibrium and inconsistent with prior research on confirmation bias.</p><p dir="ltr">Participants generally utilize information obtained from a successful bid at a lower rate when it is against the initial experts than with it. No difference is detected between information sources. This is expected, albeit inconsistent with rational decision-making. One exception is noted. When participants are biased, they use the newly obtained information at a much higher rate when it is consistent with their bias than against it. Doing so is at odds with bidding behavior, as it implies participants bid more to receive information that they utilize less. Participants generally do a much better job of rationalizing and responding to the experts’ bias than their own in the experiment.</p><p dir="ltr">My third chapter is motivated partly by the findings in my first two chapters, using a more contextualized setting. In it, subjects are presented with a series of X account versions. The versions vary on political affiliation, occupation credentials, and number of followers. Subjects are asked to rate how much they would value information from each account version. Subjects value account versions with an unrevealed political party affiliation more than their analogs which report a party affiliation, regardless of the party or the subject’s beliefs.</p><p dir="ltr">A partisan penalty is uniformly implemented. Additionally, credentials are insufficient to overcome bias concerns. The penalty assessed to an account version aligning with a party is similar when the version has high credentials versus when it does not. Followers are also a valuable resource, regardless of political affiliation or credential levels. The marginal value that followers provide is similar for all account versions, meaning that even relative experts in a field should seek validation if they want to be valued by others.</p><p dir="ltr">Previous research would expect subjects to value versions more when they are congruent with their own beliefs, so these findings are surprising. Two groups are identified as the most likely to deviate and value same-typed account versions more: subjects who believe echo chambers are good and subjects who are concerned they have believed fake news in the past. The former group does not require a significant number of followers to highly value a politically congruent account version. The latter value politically unaffiliated accounts even more, but are more skeptical of opposition account versions and are even more sensitive to the number of followers they have.</p><p dir="ltr">These three chapters explore new avenues for researching how biases and expertise are evaluated and responded to. People are generally much better at considering the potential biases that others have than rationalizing their own biases. I also find good news in an era of heightened concern about eroding trust in experts. In each case, subjects respond to signals of expertise, and demonstrate efforts to exploit the information that experts provide.</p>

<p>  </p> <p>My dissertation is composed of three independent chapters in the field of labor economics and international trade. </p> <p><br></p> <p>The first chapter studies marriage market signaling and women’s occupation choice. Despite the general closure of gender disparities in the labor market over the past half century, occupational segregation has been stubbornly persistent. I develop a new model that explains these occupational outcomes through marriage market signaling. Vertically differentiated men have preference over women’s unobservable caregiving ability. Heterogenous women choose caregiving occupations to signal their ability to be caregivers. My model generates unique predictions on the influence of marriage market conditions on women’s occupational choices. I find empirical support for these predictions using longitudinal data on marriage rates, policy shocks to divorce laws, and shocks to the marriage market sex ratio driven by waves of immigration. </p> <p><br></p> <p>The second chapter investigates Covid19 and consumer animus towards Chinese products. Covid19 has tremendously affected all areas of our lives and our online shopping behaviors have not been immune. China is the first country to report cases of Covid19 and suffers from rising animus in the U.S. In this paper, we study consumer animus towards Chinese products post Covid19 using Amazon data. We tracked all face masks sold on Amazon between Sep. 2019 to Sep. 2020, and collect product information that is available to a real consumer, including reviews. By analyzing both seller-generated (e.g., product name, description, features) and user-generated (e.g., reviews and customer Q&A) content, we collect information on the country-of-origin as well as consumer animus for the products. Under a fully-dynamic event study design, we find that the average rating drops significantly after a product is identified as made in China for the first time, while no such drop is found for products with other countries-of-origin. This negative impact is U-shaped, which quickly expands in the first five weeks, and then gradually fades out within six months. An informative-animus review affects the average rating of a Chinese product both directly (through its own rating) and indirectly (through other future ratings), with both mechanisms supported in data. We also provide strong evidence that the drop in average rating is driven by consumer animus instead of product quality. </p> <p><br></p> <p>The third chapter explores how cultural transmission through international trade affects gender discrimination. In this paper, I propose that international trade helps alleviate gender discrimination. With imperfect information on workers’ ability, there is statistical discrimination towards female workers. Through international trade, culture transmits asymmetrically between firms located in countries with different gender cultures. This cultural transmission benefits women because it transmits only in one direction from more gender-equal cultures to less gender-equal cultures. I prove this by linking the Customs data to the Industrial Firms data of China in 2004, and find that Chinese firms trading with more gender-equal cultures hire a higher fraction of female workers and enjoy higher profits. Similar patterns are not found in Chinese firms trading with less gender-equal cultures. The impact of cultural transmission goes beyond the firms engaged in international trade to have spillover effects onto purely domestic firms. Comparing across skill groups, cultural transmission benefits high-skill female workers more.</p>

<div>This research analyzes over 60,000 awarded highway contracts from 18 states throughout the United States. Analysis was performed on the state and aggregate level. The contracts were awarded from the years 2008 through 2018. Statistical analysis utilizing Pearson's Correlation and Ordinary Least Squares regression for each sample was performed to identify each variables relationship between the budget and awarded values.</div><div>The research examined effects of economic indicators, contractor descriptors and yearly/seasonal adjustments These variables included DBE Participation Goal, Number of Bidders, Project Dollar Value, Project Duration, Unemployment Rate, S&P 500 Index, Volatility Index, quarter, and year of project award. The results were examined by using a combination of simple statistical summaries and econometric coefficients called a cost vector. <br></div><div>Summary statistics observed Bid Difference at 8.5% below the Engineer's Estimate. The study observed DBE Participation Goals averaged 3.74% of the value of contracts, with an observed average of 4.5 bidders per contract. <br></div><div>The research determined that 55% of observed states had a positive significant correlation with DBE Participation Goal and Bid Difference. This correlation translated to nearly $80 million in additional cost. In addition, the research determined that all 19 groups in this study had a negative significant correlation with the Number of Bidders. The correlation translated to a savings of nearly $500 million. <br></div>