We study possible worker-to-employer discrimination manifested via social preferences in an online labor market. Specifically, we ask, do workers exhibit positive social preferences for an out-race employer relative to an otherwise-identical, own-race one? We run a well-powered, model-based...

We conduct a unique, Amazon MTurk-based global experiment to investigate the importance of an exponential-growth prediction bias (EGPB) in understanding why the COVID-19 outbreak has exploded. The scientific basis for our inquiry is the received wisdom that infectious disease spread, especially...

We conduct a unique, Amazon MTurk-based global experiment to investigate the importance of an exponential-growth prediction bias (EGPB) in understanding why the COVID-19 outbreak has exploded. The scientific basis for our inquiry is the received wisdom that infectious disease spread, especially...

We study possible worker-to-employer discrimination manifested via social preferences in an online labor market. Specifically, we ask, do workers exhibit positive social preferences for an out-race employer relative to an otherwise-identical, own-race one? We run a well-powered, model-based...

We study possible worker-to-employer discrimination manifested via social preferences. We run a well-powered, model-based experiment, wherein we recruit 6,000 white American workers from Amazon's M- Turk platform for a real-effort task. We randomly (and unobtrusively) reveal the racial identity...

We conduct a unique, Amazon MTurk-based global experiment to investigate the importance of an exponential-growth prediction bias (EGPB) in understanding why the COVID-19 outbreak has exploded. The scientific basis for our inquiry is the received wisdom that infectious disease spread, especially...