Economics Insights @ CBS

Making good health insurance decisions is important for health outcomes and longevity, but consumers’ errors are well documented. The authors examine whether targeted choice architecture interventions can reduce these mistakes. The article examines the interaction of two choice architecture tools on improved consumer insurance decisions in online health care exchanges: (1) ordering the options from best to worst based on a high-quality user model and (2) partitioning the total set of options.

‘Moral hazard’ links geoengineering to mitigation via the fear that either solar geoengineering (solar radiation management, SRM) or carbon dioxide removal (CDR) might crowd out the desire to cut emissions. Fear of this crowding-out effect ranks among the most frequently cited risks of (solar) geoengineering. We here test moral hazard versus its inverse in a large-scale, revealed-preference experiment (n~340,000) on Facebook and find little to no support for either outcome. For the most part, talking about SRM or CDR does not motivate our study population to support a large U.S.

Although organizations increasingly seek to communicate allyship with the Black community, their ally statements can receive vastly different responses from Black observers. We develop and test a theoretical model outlining key drivers of allyship evaluations among these perceivers. Drawing from signaling theory and integrating insights from the literature on identity safety, we reveal the costliness and consistency of ally statements as critical determinants of Black perceivers’ evaluations of organizations as allies.

Big data technologies change the way in which data and human labor combine to create knowledge. Is this a modest technological advance or a data revolution? Using hiring and wage data, we show how to estimate firms' data stocks and the shape of their knowledge production functions. Knowing how much production functions have changed informs us about the likely long-run changes in output, in factor shares, and in the distribution of income, due to the new, big data technologies.

Due to the Covid-19 pandemic, many employees have spent a considerable amount of time being forced to work from home (WFH). We draw on the Job Demands-Resources (JD-R) model and self-affirmation theory to study how the anticipation of returning to the physical workplace affects work engagement and burnout. We assumed that employees are conflicted about returning to work (RTW). Whereas they may look forward to RTW they also appreciate aspects of WFH which would have to be foregone.