Tippers and stiffers: An analysis of tipping behavior in taxi trips

Elliott, David; Tomasini, Marcello; Oliveira, Marcos; Menezes, Ronaldo

doi:10.1109/uic-atc.2017.8397523

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…3 , where I plot monthly averages for each outcome of interest by income tercile. Panel A demonstrates that passengers from the lowest-income tercile were less likely to leave a tip prior to the pandemic, which is consistent with recent research on stiffing rates among NYC taxi passengers ( Elliott et al, 2017 ). The declaration of a national emergency in March 2020 led to a drop in Tip?…”

Section: Resultssupporting

confidence: 84%

“…1 . Evidently, 20% is still the most common value of Tip % in the sample, which aligns with previous research on taxi tip rates in NYC ( Elliott et al, 2017 ). The distribution is skewed to the right, with most passengers tipping more than 20%, while roughly 5% of passengers did not tip at all.…”

Section: Methodssupporting

confidence: 89%

“…For example, Lynn, 2009 , Lynn, 2015b finds a positive correlation between consumer income and their reported likelihood of tipping in occupations that are routinely tipped. Similarly, in an analysis of 13 million taxi trips taken in NYC, Elliott et al (2017) demonstrate that passengers originating in locations with lower average income per capita are consistently more likely to stiff.…”

Section: Background and Literature Reviewmentioning

confidence: 93%

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Tipping in crises: Evidence from Chicago taxi passengers during COVID-19

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2022

Journal of Economic Psychology

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In early 2020, the novel coronavirus (COVID-19) spread to the United States and upended normal life. Using trip-level data on over 17 million taxi rides taken in Chicago from 2018–2021, I document how tipping behavior changed during the COVID-19 pandemic. I find that the average non-zero tip as a percent of the taxi fare increased 2 percentage points, or roughly 10%. Meanwhile, the likelihood that a passenger left a tip at all declined by roughly 5 percentage points, down from a pre-pandemic likelihood of 95%. My preferred specification suggests that the effect on the intensive margin dominates that in the extensive margin, leading to an aggregate increase in tipping generosity during the pandemic. I leverage granularity in the data to explore the mechanisms behind these trends and offer two explanations consistent with the data. First, passengers responded to the two economic shocks of the pandemic – unemployment and savings overhangs – by varying their tipping rates accordingly. Second, passengers internalized the increased risk of COVID-19 infection as an additional cost for taxi drivers and increased their tips as compensation. My analysis testifies to the sustainability of tipping in times of crises and offers theoretical insight into what drives tipping behavior.

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