This paper establishes the relatively weak conditions under which causal inferences from a regression-discontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a discontinuity in any pre-determined (or "baseline") variables at the RD threshold. Specifically, consider a standard treatment evaluation problem in which treatment is assigned to an individual if and only if V > v0, but where v0 is a known threshold, and V is observable. V can depend on the individual's characteristics and choices, but there is also a random chance element: for each individual, there exists a well-defined probability distribution for V. The density function - allowed to differ arbitrarily across the population - is assumed to be continuous. It is formally established that treatment status here is as good as randomized in a local neighborhood of V = v0. These ideas are illustrated in an analysis of U.S. House elections, where the inherent uncertainty in the final vote count is plausible, which would imply that the party that wins is essentially randomized among elections decided by a narrow margin. The evidence is consistent with this prediction, which is then used to generate "near-experimental" causal estimates of the electoral advantage to incumbency.

The transition to kindergarten is a critical milestone for many children. Children who enter kindergarten ill-prepared may experience early academic and social difficulties that persist into their elementary school years. This dissertation examines the relationship between learning-related skills, executive functioning, and math achievement between the preschool grade and fifth grade. The purpose of this study is to identify the early executive functioning skills and classroom learning-related skills that predict academic success. I also examine the stability of one important executive functioning skill, sustained attention, between preschool and elementary school and the effects persistent problems with sustained attention through elementary school. Data were drawn from the National Institute of Child Health and Human Development (NICHD) Study of Early Childcare and Youth Development (SECCYD), a longitudinal dataset collected across the United States.

The results suggest that among three learning-related social skills, teacher ratings of attention problems in the classroom in first grade was the strongest predictor of concurrent and later math performance, even when controlling for individual executive functioning skills, gender, income, and maternal education. Next, sustained attention skills at 54 month - as measured by the Continuous Performance Task- was the strongest predictor, among the three executive functioning skills, of classroom attention problems and classroom work habits through elementary school.

This study also found that sustained attention skills relatively stable between 54 months and fourth grade. Analysis of trajectories suggests that students with persistently low attention control had weaker work habits and more attention problems as they progress through fifth grade. In fact, the gap in work habits skills between those with persistently low sustained attention skills and those with average attention skills increases between first and fifth grade. Finally, teacher-student relationship in kindergarten partially mediated the relationship between low sustained attention skills at 54 months and later attention problems in first and third grade. The significance of early skills, behaviors, and classroom experiences are highlighted in this study.

This paper provides a theoretical analysis of optimal minimum wage policy in a perfectly competitive labor market and obtains two key results. First, we show that a binding minimum wage { while leading to unemployment { is nevertheless desirable if the government values redistribution toward low wage workers and if unemployment induced by the minimum wage hits the lowest surplus workers first. Importantly, this result remains true in the presence of optimal nonlinear taxes and transfers. In that context, a binding minimum wage enhances the effectiveness of transfers to low-skilled workers as it prevents low-skilled wages from falling through incidence effects. Second, when labor supply re- sponses are along the extensive margin only, the co-existence of a minimum wage with a positive tax rate on low-skilled work is always (second-best) Pareto ineffcient. A Pareto improving policy consists of reducing the pre-tax minimum wage while keeping constant the post-tax minimum wage by increasing transfers to low-skilled workers, and financing this reform by increasing taxes on higher paid workers. Overall, our results imply that the minimum wage and subsidies for low-skilled workers are complementary policies. pa

Using administrative, longitudinal data on felony arrests in Florida, we exploit the discontinuous increase in the punitiveness of criminal sanctions at 18 to estimate the deterrence effect of incarceration. Our analysis suggests a 2 percent decline in the log-odds of offending at 18, with standard errors ruling out declines of 11 percent or more. We interpret these magnitudes using a stochastic dynamic extension of Becker's (1968) model of criminal behavior. Calibrating the model to match key empirical moments, we conclude that deterrence elasticities with respect to sentence lengths are no more negative than -0.13 for young offenders.

We estimate the effect of new unionization on firms’ equity value over the 1961-1999 period using a newly assembled sample of National Labor Relations Board (NLRB) representation elections matched to stock market data. Event-study estimates show an average union effect on the equity value of the firm equivalent to a cost of at least $40,500 per unionized worker. At the same time, point estimates from a regression-discontinuity design – comparing the stock market impact of close union election wins to close losses – are considerably maller and close to zero. We find a negative relationship between the cumulative abnormal returns and the vote share in support of the union, allowing us to reconcile these seemingly contradictory findings. Using the magnitudes from the analysis, we calibrate a structural “median voter” model of endogenous union determination in order to conduct counterfactual policy simulations of policies that would marginally increase the ease of unionization.

The growing role of technology in society has led to calls for more experiential, community-engaged learning to equip students with the skills and qualities needed for developing technology for the public interest. Yet, despite the growing number of initiatives that seek to provide such experiences, there is still limited research on the barriers that make it challenging to do so, particularly from the perspective of community members not currently engaged in campus partnerships, but interested in doing so. To better understand these challenges, we ran a matchmaking program to help community members connect with potential campus partners and conducted a series of interviews with 8 community stakeholders (nonprofits, government programs, and small tech consultancies) to understand potential project needs, expectations for collaboration, and views on connecting community needs to student learning. We analyzed these interviews to understand barriers and identified three themes around the central concept of misalignments: misalignments between the professional and non-profit world versus the educational system, misalignments between the goal of delivering project impact versus the goal of completing a course or developing a career, and misalignments between expectations of professionalism versus the reality of volunteers and learners. We conclude by reflecting on approaches to overcoming these misalignments and implications for designing computational ecosystems that support educational experiences more integrated with the community

Though social media platforms contain rich information and insights on professional life, encounters with this content are often fleeting and disconnected, raising questions about the extent social media content is valuable for career identity formation. This thesis reports on a research through design study that explores the potential of social media for supporting integrated learning experiences, through investigating and prototyping experiences around the use of TikTok #DayInTheLife videos for career exploration. We conducted semi-structured interviews of 10 college students to understand the value of social media content for career exploration and the feasibility of integrating such content towards reflective learning experiences. A qualitative analysis revealed that #DayInTheLife videos offer firsthand insights into professions, facilitating aspects of career identity formation, and have the potential to prompt and motivate further exploration. However, they are also limited due to their short-form, disconnected, entertainment-oriented nature, the distracting context in which they exist, and the potential lack of representation in recommended content. We also had the students participate in an experience prototype in which we used native social media interactions such as comments, mentions, and direct messages to integrate encounters of disparate posts towards holistic and reflective learning experiences. We found that integrating encounters can facilitate more intentional reflection, add interactivity, and provide a sense of agency. We also surfaced contextual risk factors and design factors for designing integrated learning experiences on social media. We build on our findings to introduce and discuss a concept we call SIMPLE apps (Social media Interactions Merged for Purposeful Learning Experiences) and to discuss broader design implications for better harnessing social media content towards purposeful integrated learning.