Behavioral inference from non-stationary policies: Theory and application to ridehailing drivers during COVID-19 lockdowns
Description
In the aftermath of a disruptive event like the onset of the COVID-19 pandemic, it is important for policymakers to quickly understand how people are changing their behavior and their goals in response to the event. Choice modeling is often applied
