Behavioral Responses to Congestion Pricing in New York City: Mode Shift, Preference Change, and Effect Persistence

This thesis examines the behavioral impacts of New York City’s congestion pricing policy on weekday peak-hour travel into the pricing zone. Using a two-stage Bayesian Multinomial Logit framework applied to monthly aggregate mobility data, the study disentangles underlying preference shifts from observed mode share changes in response to the toll. Stage 1 estimates population-level travel sensitivities to cost and time, while Stage 2 uses a hierarchical structure to capture heterogeneity across demographic segments defined by income, age, and gender. The analysis spans January–June 2025 and compares results to the same months in 2024 as a counterfactual scenario without pricing. Findings show that while the policy generated a sustained mode shift away from private automobiles toward public transit, preference adaptation varied by demographic group and evolved over time. Some cohorts reinforced the intended policy effects through reduced transit travel time sensitivity, while others exhibited partial reversal as cost sensitivity shifted. These dynamic patterns underscore the importance of evaluating both immediate and evolving behavioral responses when designing congestion pricing strategies and highlight the value of aggregate behavioral modeling for timely, data-driven policy assessment.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Urban Studies and Planning

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Shen, ChenAn

Advisors dc:contributor.advisor

• Zhao, Jinhua
• Aloisi, Jim

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/164581

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/164581