Research Papers

We estimated the elasticity of consumption with respect to typical labor income shocks using firm-wide changes in monthly pay, and analyzed how this elasticity varies by wealth and race, using administrative bank account data.

We sought to understand the consumption responses to typical income fluctuations and explore how wealth and racial disparities affect consumption smoothing, addressing an open question about heterogeneity in consumption responses.

Our findings reveal significant racial disparities in consumption smoothing, with black and Hispanic households experiencing higher welfare costs from income volatility than white households, primarily due to differences in liquid wealth, offering insights into economic inequality and its impact on welfare.

We conducted a 2-year randomized clinical trial involving 4834 employees at the University of Illinois at Urbana-Champaign to evaluate the effects of a comprehensive workplace wellness program on health, health beliefs, and medical use.

We aimed to determine whether such programs improve employee health and reduce medical costs, as randomized evaluations of workplace wellness program efficacy are rare.

Our study provides evidence that while the program did not significantly impact clinical health outcomes or medical use, it positively influenced health beliefs and increased the number of employees reporting having a primary care physician, offering insights for employers considering similar initiatives.

We developed a new method for estimating randomized intervention analogues to the natural direct effect (rNDE) and the natural indirect effect (rNIE) in the presence of treatment-induced confounders.

We aimed to address the challenge of estimating mediation effects when treatment-induced confounders complicate the mediator-outcome relationship. Existing methods require cumbersome weighting procedures, making them difficult to use. Our method provides a more practical and accessible approach for researchers by utilizing simpler regression-based techniques.

Our approach allows researchers to estimate mediation effects more efficiently and accurately, even when treatment-induced confounders are present. By simplifying the estimation process, this method makes causal mediation analysis more accessible and robust.

We introduced “residual balancing” as an alternative method for constructing weights in marginal structural models (MSMs) to estimate time-varying treatment effects, aiming to address issues inherent in inverse probability weighting (IPW).

We sought to overcome limitations of IPW, such as inefficiency, sensitivity to model misspecification, and difficulty with continuous treatments.

Residual balancing improves the efficiency and robustness of estimating marginal treatment effects in the presence of time-varying confounders. By offering a more reliable and user-friendly alternative to IPW, it enhances causal inference accuracy in observational studies.

We investigated the impact of the Social Security Annual Earnings Test (AET) on employment decisions of older Americans using a differences-in-differences design.

We aimed to understand how the AET, which reduces benefits for earnings above a certain amount, affects employment rates among older Americans nearing retirement age.

Our findings indicate that the AET significantly decreases employment rates among those aged 63-64, providing critical insights for policymakers on the labor market effects of Social Security policies.

We introduced a method to estimate the cost of adjusting earnings and the earnings elasticity with respect to the net-of-tax share, using bunching in the earnings distribution at convex budget set kinks before and after policy changes.

We sought to explore the relationship between tax policy changes and earnings adjustments, specifically focusing on the Social Security Earnings Test, to provide a clearer understanding of the behavioral responses to tax rate changes.

Our results highlight that adjustment costs can significantly dampen the short-run effects of changes in effective marginal tax rates, offering crucial insights for policymakers on the efficiency and impact of tax policy adjustments.

We designed and implemented a comprehensive workplace wellness program for a large employer with over 12,000 employees, randomly assigning program eligibility and financial incentives at the individual level.

We sought to determine whether workplace wellness programs effectively reduce medical spending, boost productivity, and improve employee well-being, addressing the gap in evidence supporting these claims.

Our results indicate that while these programs may not directly reduce costs or enhance productivity, they could still benefit employers by attracting and retaining healthier, lower-cost employees, potentially leading to net savings.

We evaluated hypotheses about education’s impact on beliefs about racial inequality using cross-sectional, sibling, and panel models. Analyzing data from the General Social Survey (GSS), the 1994 Study of American Families, and the 2006–2010 GSS panels, we assessed whether education promotes structural explanations for racial disparities or if observed effects are superficial and influenced by unobserved factors.

We aimed to clarify conflicting perspectives on education’s influence on racial attitudes: whether it genuinely fosters more enlightened views or if associations are superficial and due to unobserved biases. By employing different models and datasets, we sought to disentangle these complexities and provide a nuanced understanding of education’s role in shaping beliefs about racial inequality.

Our findings suggest that while cross-sectional analyses indicate education promotes structural explanations for racial inequality, sibling and fixed-effects models suggest these effects may be superficial and inflated by unobserved factors. This challenges simplistic interpretations and underscores the need for careful methodological considerations in studying the relationship between education and racial attitudes.

We employed a novel rank-based index of stratification to measure how occupational classes occupy distinct, non-overlapping, hierarchical layers in the US income distribution from 1980 to 2016.

We aimed to address the gap in empirical studies that focus on inequality rather than stratification. By developing a rank-based stratification index, we sought to accurately capture class stratification and provide insights into the structural dynamics of the US income distribution over time, enhancing the understanding of class structure and social stratification.

Our findings show a substantial increase in class stratification in the US from 1980 to 2016, driven by factors like income returns to education, deunionization, and deindustrialization. These results highlight growing economic divides based on occupational class, informing theories of class structure and guiding policies to reduce economic stratification and promote social mobility.

We developed a method to estimate the effect of kinked or notched budget sets on workers’ employment decisions and applied it to the Social Security Old-Age and Survivors Insurance (OASI) Annual Earnings Test (AET).

We aimed to understand how the AET, which reduces OASI benefits based on earnings, influences employment rates, using a Regression Kink Design and Social Security Administration data.

Our findings show that the AET significantly reduces employment, providing valuable insights for policymakers on the labor market effects of benefit reduction policies.