Calibrated block-group level coefficients for NYS mode choice

Calibrated block-group level coefficients for New York State mode choice. The coefficients are calibrated by a group-level agent-based mixed logit (GLAM logit) model using Replica's synthetic datasets. This .csv file contains 120,740 rows. Each row contains a set of mode choice coefficients for each block-group OD pair and each population segment (we call this an agent). The empirical distribution of agent-level coefficients is neither Gumbel nor Gaussian, which reveals a regional divergence of the value of time and mode preference, indicating potential inequity issues in the transportation system. This is infeasible for conventional discrete choice models (DCMs) to capture.