Chapter One: I contribute to the literature on the decline of the labor share in the United States by proposing a channel through which increasing household debt can lead to the decline of the labor share. Specifically, workers with lower net worth have lower reservation wages. Thus, workers in debt spend less time job-searching and accept lower-paying jobs. Focusing on the period between 1982 and 2016 - a time during which the labor share declined and household debt rose as a proportion of GDP - I describe a model which demonstrates that the lowering of household net worth may have caused a 12 percent decrease in mean wages, and caused the labor share to decline by 0.081 points. Since the labor share actually fell by 0.057 points in that period, the model ``over-explains'' the decline of the labor share. Chapter Two: What effect do labor-restricting policies have on how much people drive, and on carbon emissions? I model the effect of labor-restricting policies in the following way: I calibrate a model to match the United States in 2018, and also calibrate the model counterfactually to simulate what would have occurred had other policies been in effect. I compare the carbon emissions that result from the original calibration to the carbon emissions that result from the counterfactual-policy calibrations. The labor-restricting policies I consider are wage taxes, retirement mandates, and restrictions on time spent working. I find that, for all policies considered, reductions in work are associated with increases in driving but nonetheless lead to reductions in carbon emissions, due to overall declines in economic activity. Chapter Three: For the model introduced previously, I study transition paths for the following case: The model is originally in a steady-state and the agents expect the current policy regime to last forever; then they are surprised when the government announces and immediately enacts a policy change; they then expect the new policy regime to last forever. The policy changes I study are wage taxes and emissions taxes (either spent by the government or rebated). For each of these policy changes, the model economy begins in a baseline steady-state, then enters a transition lasting several periods, and eventually arrives at a new steady-state. During the transition, aggregate wealth gradually moves to its new steady-state value. Jump variables - such as aggregate consumption, driving, leisure, labor, and emissions - at first jump and then gradually move to their new steady-state values. Labor and emissions generally move in opposite directions, which apparently contradicts the idea that more work leads to more pollution. However, this contradiction is merely the temporary result of the fact that agents are spending down their aggregate wealth; thus they are consuming goods and services produced elsewhere, and are paying for labor to be done outside the model using wealth that was built up previously. / Economics

This dissertation consists of three chapters. First two chapters examines how nonprofit organizations (NPOs) react to the state level minimum wage increases, and the third chapter studies the effect of board interlock on the diffusion of innovation.In the first chapter, I investigate the impact of minimum wage increases on employment. I extend the literature by hypothesizing and showing a differential impact of state-level minimum wage increases on nonprofit organizations relative to for-profit organizations. While I find that increases in minimum wages reduce employment growth in both types of organizations, this decrease is substantially larger for nonprofit organizations. I also find that investment in automation, i.e., information technology, rises in nonprofits post minimum wage increase, consistent with the substitution of capital for labor. Minimum wage increases also increase the likelihood of nonprofit exit. In the second chapter, I investigate how CEO pay in nonprofit organizations responds to an exogeneous increase in labor cost resulting from state-level minimum wage hikes. I find that these increases in labor cost, which constrain budgets, are followed by declines in the total pay of NPO CEOs. In contrast, I do not find an impact on CEO pay in for-profit companies. I attribute the differential response between NPO and for-profit organizations to NPO CEOs acting as stewards of the NPO, whereby they are willing to take less to ensure the continued existence of the enterprise, as well as fulfillment of its mission. This phenomenon has previously been observed in the nonprofit sector and termed labor donation, whereby individuals who work for NPOs are intrinsically motivated and consequently, are willing to work for less money. Cross-sectionally I find the declines in compensation are larger in NPOs headquartered in smaller counties, in counties with higher levels of religiosity, and in counties with greater levels of social capital, and in NPOs that are run by their founders. In the last chapter, I propose that board interlocks can act as a channel of information transmission and social learning, hence enhancing the diffusion of innovation among firms. I find that a firm’s patents are more likely to be cited by patents from firms that have common directors (i.e., interlocked firm). The result is robust under a difference-in-differences setting, where the death or retirement of interlocking directors is used as an exogeneous shock to board interlock. The effect is more pronounced for interlocking directors who have longer experience in R&D-intensive industries, have a larger network, and have a higher compensation delta. While I find that board interlock enhances the diffusion of innovation across industries, it has no effect on within-industry knowledge diffusion. Finally, I document that board interlock enhances firms’ overall innovation output, measured by patent counts and citation counts per patent. The paper sheds light on an important role played by board of directors in promoting knowledge spillover and innovation. / Business Administration/Finance

With the ever-increasing availability of large, high-dimensional datasets, there is a growingneed for econometric methods that can handle such data. The last decade has seen the development of many such methods in computer science, but their applications to economic models have been limited. In this thesis, I investigate whether modern tools in (exact and approximate) Bayesian inference can be useful in economics. In the three chapters, my coauthors and I develop and estimate a variety of models applied to problems in organizational economics, health, and labor. In chapter one, joint with Andrew Olenski, we estimate a mortality-based Bayesian model of nursing home quality accounting for selection. We then conduct three exercises. First, we examine the correlates of quality, and find that public report cards have near-zero correlation. Second, we show that higher quality nursing homes fared better during the pandemic: a one standard deviation increase in quality corresponds to 2.5% fewer Covid-19 cases. Finally, we show that a 10% increase in the Medicaid reimbursement rate raises quality, leading to a 1.85 percentage point increase in 90-day survival. Such a reform would be cost-effective under conservative estimates of the quality-adjusted statistical value of life. In chapter two, joint with Laura Battaglia and Stephen Hansen, we demonstrate the effectiveness of Hamiltonian Monte Carlo (HMC) in analyzing high-dimensional data in a computationally efficient and methodologically sound manner. We propose a new model, called Supervised Topic Model with Covariates, that shows how modeling this type of data carefully can have significant implications on conclusions compared to a simpler yet methodologically problematic two-step approach. By conducting a simulation study and revisiting the study of executive time use by Bandiera, Prat, Hansen, and Sadun (2020), we demonstrate these results. This approach can accommodate thousands of parameters and doesn’t require custom algorithms specific to each model, making it more accessible for applied researchers. In chapter three, I propose a new way to estimate a two-way fixed effects model such as Abowd, Kramarz, and Margolis (1999) (AKM) that relaxes the stringent assumptions concerning the matching process. Through simulations, I demonstrate that this model performs well and provide an application to matched employer-employee data from Brazil. The results indicate that disregarding selection may result in a significant bias in the estimates of location fixed effects, and thus, can contribute to explaining recent discoveries about the relevance of locations in US labor markets. The three chapters demonstrate the usefulness of modern Bayesian methods for estimating models that would be otherwise infeasible, while remaining accessible enough for applied researchers. The importance of carefully modeling the data of interest instead of relying on ad-hoc solutions is also highlighted, as it has been shown to significantly impact the conclusions drawn across a variety of problems.

In this dissertation, I explore various fundamental challenges of inequality that developing countries continue to grapple with. The first chapter seeks to understand the role of social and cultural norms in explaining the persistent gender gaps in the labor markets. The second chapter studies how schooling decisions are made in the presence of liquidity constraints. Both the above questions are answered in the context of India. The third chapter adds to our understanding of the relationship between decision-making power within households and intimate partner violence in the context of Sub-Saharan Africa. Despite recent gains in women's educational attainment and reproductive agency, substantial gender gaps in the labor market still remain, particularly in developing countries. In my first chapter, I study the impact of culture and social norms in explaining this puzzle in the Indian setting. In particular, I examine the role of the male-breadwinner norm, which dictates that husbands should earn more than their wives. I first establish a sharp discontinuity in the distribution of the share of the wife's income at the point where the wife’s income exceeds the husband's income. I theoretically show that this pattern can be best explained by gender identity norms which make couples averse to a situation where the wife earns more than her husband. I also provide empirical evidence that this aversion has real implications for the labor market outcomes of the wife. First, the wife is less likely to participate in market activities if her potential income is likely to exceed her husband’s. Second, she earns less than her potential if she does work and can potentially out-earn her husband. Evidence from observing couples over time and bunching methods supplement these results. Moreover, these results are more pronounced in couples where the husband is making the labor market decisions of the wife and where other regressive gender norms are prevalent. My second chapter, co-authored with Dhruv Jain, studies the importance of liquidity constraints in determining the schooling decisions of households in developing countries. Evidence across developing countries suggests that parents are often credit-constrained when making schooling decisions for their children. But little is known about the severity of this constraint. In this chapter, we ask if temporary shocks to liquidity affect parents’ decisions regarding the schooling of their children. We use a shock to available cash in the economy induced by India’s 2016 demonetization to identify this effect. The policy made 86% of currency-in-circulation illegal overnight, and individuals could deposit old notes at the bank in exchange for new ones but with significant withdrawal limits. We identify the impacts of demonetization’s severity by leveraging discontinuities in banking access across Indian districts. Difference-in-discontinuity estimates show that districts that experienced more severe liquidity shock saw an increase in dropouts from private schools but no effect in free public schools, consistent with the presence of real credit constraints. Moreover, enrollments in future periods remained unchanged, suggesting a more permanent effect. The third chapter of my dissertation, co-authored with Aletheia Donald, Cheryl Doss and Markus Goldstein, studies the relationship between decision-making within households and its impact on intimate partner violence (IPV) in 12 Sub-Saharan African countries where 36% of women are affected by IPV. Using the wife’s responses to survey questions, we find that compared to joint decision-making, sole decision-making by the husband is associated with a 3.3 percentage point higher incidence of physical IPV in the last year, while sole decision-making by the wife is associated with a 10 percentage point higher incidence. Similar patterns hold for emotional and sexual violence. When we include the combined responses of the husband and wife about decision-making in the analysis, we identify joint decision-making as protective only when spouses agree that decisions are made jointly. Notably, agreement on joint decision-making is associated with lower IPV than agreement on decision-making by the husband. Constructs undergirding common IPV theories, namely attitudes towards violence, similarity of preferences, marital capital, and bargaining, do not explain the relationship. Our results are instead consistent with joint decision-making as a mechanism that allows spouses to share responsibility and mitigate conflict if the decision is later regretted.

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<p>My dissertation consists of three chapters in the field of labor and education economics. The first chapter studies the impact of early morning classes on students’ educational trajectories. The second chapter explores how college course shutouts affects students’ educational outcomes. The third chapter investigates the impact of kindness on wage returns.</p>

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