Default Tip Suggestions in NYC Taxi Cabs

This paper explores how changes in default options can influence consumer behavior in a setting where consumers can use a suggested default or manually enter a tip amount. To identify the impact that different defaults have on behavior, I take advantage of variation within the New York City taxi industry, whereby credit payment vendors were randomly distributed across taxis. Using both timing of the payment screen installations and variation across taxis in the credit vendor, I identify how changes in the default tip percentages influence consumer tipping behavior. I find that higher tip suggestions result in an increase in tip amounts. The estimates suggest that during a single shift, cab drivers wages increase by 27.43 percent