Have you ever been at a restaurant and suddenly noticed a service fee on your bill that wasn’t there before? It is a charge you did not really do anything to cause, but now you are expected to pay it anyway. Right at the end, you are still asked to tip on top of everything. It makes you think about how people respond to tipping when prices change in ways that feel unexpected or out of their control.
Beginning in February 2019, New York City imposed a congestion surcharge on taxi and for-hire vehicle trips traveling in Manhattan below 96th Street. Yellow taxi passengers were charged an additional $2.50 per trip, while green taxi and ride-hailing passengers paid $2.75. The surcharge is paid by passengers and cannot be deducted from driver earnings. Importantly, the surcharge was highly visible. The congestion surcharge, along with other fees, was laid out individually on the payment screen. Passengers could see a detailed fare summary before selecting a tip amount.
Economists have long studied tipping behavior and found that tips are often influenced less by service quality than by social norms. People do not always tip based on rational calculations. Instead, they respond to social expectations, suggested defaults, and how prices are presented. The congestion surcharge, therefore, created a great research question: Would passengers reduce tipping because rides became more expensive overall? Or would they increase tipping because they felt sympathy for drivers dealing with traffic congestion and higher costs?
To answer this question, I used detailed trip-level data from NYC Open Data for both yellow and green taxis between 2018 and 2019. The dataset contains millions of trips and includes information such as fare amount, trip distance, pickup and drop off locations, payment type, and tip amount. Using a Difference-in-Differences method, I compared trips affected by the congestion zone with trips outside the zone before and after the surcharge was introduced. This approach allows me to isolate how tipping behavior changed specifically due to the policy.
Overall, passengers actually increased tipping after the congestion surcharge was implemented. For yellow taxis, tip percentages increased by 2.7 percentage points. Green taxi trips showed similar positive effects in most specifications.
The surcharge made congestion more visible to passengers, potentially increasing awareness of the difficulties drivers face in heavy Manhattan traffic. Riders may have viewed drivers as working under more stressful conditions and responded with higher gratuities. Additionally, passengers may separate the congestion surcharge from the tip itself in their mind, viewing the surcharge as a government fee rather than part of the driver’s earnings. As a result, some passengers may have responded by tipping more out of fairness or sympathy.
However, the results become more complicated when looking across different types of trips. The strongest negative tipping responses occurred among cheaper rides. When the congestion surcharge represented a relatively large share of the total cost, passengers felt the extra charge more strongly and often reduced tipping substantially. Green taxis showed especially large declines, with around 11 percentage point reductions.
In contrast, expensive trips displayed much smaller negative effects and eventually positive effects in the highest fare ranges. When fares are already large, a $2.50 ($2.75) surcharge becomes less noticeable relative to the total bill.
The goal of this policy is to reduce congestion, travel times, and emissions. But this research suggests that consumers also adjust social behaviors, like tipping, when prices become more visible and salient. Future research could examine the new 2025 NYC congestion pricing policy in Manhattan’s CBD area below 60th Street and see whether this new policy creates similar behavioral effects.
Hayou (Leonard) Wang is a PhD Student in the Department of Economics at West Virginia University. To learn more about his research, his website is https://sites.google.com/view/haoyuleonardwang/home/