Developing country megacities suffer from severe road traffic congestion. However, this fact is not directly informative about the magnitude of equilibrium inefficiency due to congestion externalities. I study the peak-hour traffic congestion equilibrium in Bangalore, India. To measure travel preferences, I use a model of departure time choice to design a field experiment with congestion pricing policies and implement it using precise GPS driving behavior data. Commuter responses in the experiment reveal moderate schedule flexibility and a high value of time. I then show that in Bangalore, traffic volume has a moderate and linear impact on trip duration. Peak-hour traffic equilibrium simulations with endogenous congestion reveal small travel time benefits and negligible commuter welfare gains from optimal congestion charges. This result is driven by the shape of the externality. Overall, these results suggest limited commuter welfare benefits from peak-spreading traffic policies in cities like Bangalore. https://github.com/Gkreindler/personal-website/blob/master/paper-cp-bangalore/Kreindler%20(2020)%20Congestion%20Pricing%20Bangalore%2005-02.pdf
Gabriel Kreindler studies transportation, urban and spatial economics topics in developing countries, with a focus on equilibrium traffic congestion and public transportation design. In his research, he uses quantitative and computational models, randomized and natural experiments, and big mobility data. He received his Ph.D. in Economics from MIT in 2018, was a Saieh Family Fellow at the University of Chicago in 2018-19 and a Prize Fellow in History, Politics and Economics in 2019-20. Since 2019 he has been an Assistant Professor in the Economics department at Harvard University.