“Default Tips”, 2014-07-01 ():
We examine the role of defaults in high-frequency, small-scale choices using unique data on over 13 million New York City taxi rides.
Using a regression discontinuity design, we show that default tip suggestions have a large impact on tip amounts. These results are supported by a secondary analysis that uses the quasi-random assignment of customers to different cars to examine default effects on a wider range of fares.
Finally, we highlight a potential cost of setting defaults too high, as a higher proportion of customers opt to leave no credit card tip when presented with the higher suggested amounts.
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