Chicago Taxi Trips (Tipping)

This dataset accompanies a paper examining how tipping practices changed during the pandemic. I download data on unique taxi rides taken in Chicago freely available from the Chicago data portal for Jan 2018-March 2021. The data include a number of variables for each taxi trip, including the fare amount, the tip amount, and the passenger's location. I merge in demographic data available from CMAP for the community area the passenger came from in Chicago as well as daily data on COVID-19 hospitalizations to enrich the analysis. I filter the dataset to taxi rides payed with credit card, and remove trips with exceptionally weird data (e.g. 0 second trip duration, fares greater than $1000). I use the dataset to estimate the effect of the pandemic on whether passengers tip and if so, the average percent tipped. I find that the likelihood that a passenger leaves a tip declines by roughly 5 percentage points during the pandemic but the average non-zero tip left increased by roughly 2 percentage points higher. I exploit geographic and temporal heterogeneity in the data to explore the possible mechanisms behind these patterns in tipping.