The repository serves to store code for generating model results and figures in the TRR paper (TRR-S-19-07786): HOW DOES PUBLIC SUPPORT FOR SUSTAINABLE TRANSPORTATION POLICIES VARY ACROSS COUNTRIES?

The Mplus code folder contains Mplus input and output files for the model framework that includes 50 country binary variables.

The R code folder contains country-level estimated coefficients and R code files that generate relevant tables and figures in the paper.

As the world shapes a global agenda to mitigate climate change, national governments are looking to define and build support for sustainable development strategies for the transportation sector. In this international landscape, countries will look to learn from one another, but identifying peer countries for this learning can prove a challenge. In this study, we measure public support for transportation policies and use this measure of cultural distance to identify peer countries.

We modeled public support for 11 transportation policies in an international sample of 41,932 individuals in 51 countries/regions. Using a model that controls for individual effects, we measure pure “country-level” differences in public policy support. Measuring public support for different transportation policies can help policymakers understand how the public evaluates and envisions the role of government in shaping the current as well as future urban transport system, and to anticipate difficulties of implementing certain types of policies due to public resistance. In general, we find the highest public support for a given policy appears in countries that have not yet seen significant investment in the target infrastructure or service. We show that considering public support of transportation policies gives a different perspective than traditional indicators of economic development or motorization level, helping policymakers understand what the public wants and how they might build public support for new transportation policies. Finally, we present a clustering framework that goes beyond development status and geographical adjacency to help identify peer countries for policy learning.

Keywords: Public opinion, transportation policy support, international comparison

Xuenan Ni, Dr. Joanna Moody, Dr. Jinhua Zhao, M.I.T