Quantifying causal effects of road network capacity expansions on traffic volume and density via a mixed model propensity score estimator

摘要: Road network capacity expansions are frequently proposed as solutions to urban traffic congestion but controversial because it is thought that they can directly “induce” growth in volumes. This article quantifies causal effects of road on aggregate volume and density U.S. cities using a mixed model propensity score (PS) estimator. The motivation for this approach we seek estimate dose-response relationship between suspect confounding from both observed unobserved characteristics. Analytical results simulations show longitudinal PS be used adjust effectively time-invariant via random (RE). Our empirical indicate cause substantial increases volumes such even major actually lead little or no reduction densities. re...