Replication data for: Default Tips
Principal Investigator(s): View help for Principal Investigator(s) Kareem Haggag; Giovanni Paci
Version: View help for Version V1
| Name | File Type | Size | Last Modified |
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| 20130098_code_data | 10/12/2019 05:18:PM | ||
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text/plain | 14.6 KB | 10/12/2019 01:18:PM |
Project Citation:
Haggag, Kareem, and Paci, Giovanni. Replication data for: Default Tips. Nashville, TN: American Economic Association [publisher], 2014. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E113897V1
Project Description
Summary:
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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.
Scope of Project
JEL Classification:
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D12 Consumer Economics: Empirical Analysis
L92 Railroads and Other Surface Transportation
D12 Consumer Economics: Empirical Analysis
L92 Railroads and Other Surface Transportation
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