Unfair treatment is common in the workplace, where it may manifest through channels such as unequal wage compensation, task misallocation, or overt discrimination. This paper provides causal evidence that perceived unfairness reduces attention, impairing performance on workplace-relevant tasks. Using a large-scale online experiment with over 3,300 participants, I find that unfair treatment significantly reduces attention scores by roughly 7%, with especially pronounced effects when unfairness is attributed to discrimination. These results highlight the cognitive costs of unfairness, with implications for productivity and workplace design.

with O. Giuntella & J. Costa-Font

We study the effect of the 1998 UK Working Time Regulation (WTR 98) on the use of time and the well-being of employees. Using data from the British Household Panel Survey and an event-study analysis approach, we compare trends in the outcomes of workers exposed to the regulation before and after the reform. We find that workers working long hours before the reform reduced their hours and reallocated time towards sleep, leisure, and related personal care activities. Exposed workers were less likely to report dissatisfaction with their jobs, and we find some evidence of an increase in happiness and in the likelihood of reporting no anxiety or depression among women. We do not observe any significant income change or a notable impact on satisfaction with earnings. Instead, there is evidence of an increase in the employment and earnings of the partners of exposed workers, driven by women.

with V. Burdea & J. Woon (Submitted)

We investigate how different belief elicitation methods influence reported prior beliefs about induced (objectively described) probabilities in the online environment. We compare two incentive compatible methods, the binarized scoring rule (BSR) and the stochastic Becker-deGroot-Marschak mechanism (BDM), with unincentivized introspection (INTRO). We find that subjects perceive the incentive compatible methods as significantly more difficult. Moreover, the error in priors is significantly higher for the incentivized methods than for INTRO. Lower perceived difficulty and higher probabilistic skills do not reduce the error in priors between the incentive compatible methods and INTRO. With learning, however, both the BSR and BDM methods lead to higher errors in priors. Higher numeracy significantly and almost perfectly compensates for the increased error (reducing the error by an approximately equal amount) in the BDM condition, but not in the BSR condition.

In this chapter, we review the evidence on the effects of the COVID-19 pandemic on health behaviors and explore observational data on mental health, anxiety medications, and time use. We focus on the most vulnerable populations: young adults, parents and children, essential workers, and minorities. First, we explore the heterogeneity in the impact of COVID-19 on mental health, and then examine more closely the impact on time use with a specific focus on health behaviors (exercise, sleeping, eating habits) and personal care.

In Philadelphia, an estimated 1 billion single-use disposable plastic bags are used annually, contributing to carbon emissions, plastic waste, and litter. In response to these environmental impacts, the Philadelphia City Council passed Bill 190610 in 2019, which banned retail establishments from distributing single-use plastic bags and paper bags not made of at least 40% recycled material. To assess the effectiveness of the ban, the research team compared plastic bag usage in grocery stores in Philadelphia (“Philadelphia” sample) with usage in surrounding suburbs (“Suburbs” sample). The results of the study showed a significant decrease in plastic bag usage in the city after the ban was implemented. Extrapolating the results from our sample, we estimate that the ban led to the elimination of over 200 million plastic bags in the city. This is roughly equivalent to filling Philadelphia City Hall with plastic bags every eight months.

Behavioral economics is an increasingly influential field across the social sciences, including public administration. But while some behavioral economics ideas have spread rapidly in public administration research, we argue that a broader range of behavioral economics concepts can and should be applied. We begin by outlining some central models and concepts from behavioral economics to fix ideas, including the rational model and the “behavioral” response. We then discuss how a variety of heretofore underutilized behavioral economics concepts can be applied to a specific area of work in public administration – bureaucratic decision making. Our aim in doing so is two-fold. First, we hope to provide fresh food for thought for researchers and practitioners working in the broader behavioral public administration space. Second, we hope to demonstrate that there is substantial scope for expanding behavioral economics’ influence on public administration research.

According to the World Health Organization (WHO, 2022), the COVID-19 pandemic triggered a 25% increase in the prevalence of anxiety and depression worldwide. Social isolation, loneliness, fear of infection, bereavement and financial concerns have contributed to the observed rise in anxiety and depression. The pandemic, the necessary public health interventions, and the negative impact on economic activity had long-lasting effects on people’s mental health. This chapter reviews the literature on COVID-19 and mental wellbeing. It first examines the role of public health measures, school lockdowns, economic uncertainty, and changes in working arrangements, as well as the effects of vaccine rollout. The second part of the chapter explores the heterogeneity of the COVID-19 impact in the population, documenting alarming tends in the mental health of the most vulnerable populations such as young adults, women, families with children, minorities, and essential workers.

Little is known about the extent to which financial institutions furnish information on natural disaster assistance or how furnishing may vary by industry and consumer type. This report documents the prevalence of natural disaster comment codes in credit records to shed light on current practices for natural disaster reporting. It also documents how this reporting may vary based on account characteristics and consumer credit score.

This paper explores the relationship between sleep, productivity, and weather and climate conditions and identifies sleep aids which mitigate these effects. I utilize a combination of data scraped from Weather Underground and RCT data available from Bessone et al. (2021) to answer these questions. I first match the panel data set of actigraphs from the RCT study to city-level atmospheric and weather data between 2017 and 2019. Then I examine the extent to which temperature and climate contribute to the nightly sleep deprivations observed in the sleep data, and finally estimate how this effect on sleep and productivity is mitigated by sleep aids in the study. I find that certain sleep aids are significantly effective at mitigating the negative impact of temperature on sleep and productivity, but do not amplify the positive effects of rainfall on sleep.