Asking for Too Much? Evidence from the NYC Taxi Cab Industry
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Presenter
Research Fellow at University of Michigan - School of Information
Abstract
This paper explores how setting default options above the social norm influences consumer behavior in a setting where consumers can use a suggested default or manually enter a tip amount. To identify the impact increasing the suggested tip levels have on behavior, I take advantage of the variation of credit payment vendors within the New York City taxi industry. Using both timing of the payment screen installations and variation across taxis in the technology vendor, I identify how a five percentage point increase in the default tip percentages influence consumer tipping behavior. I find that higher tip suggestions result in an increase in tip amounts of approximately $0.57 per fare which translates to an increase in a cab drivers hourly wage by 5.35 percent. I discuss the policy implications of these results and how they are particularly relevant for low-wage workers in economies increasingly dominated by the service industry.