Using Uber's H3 tool, the tool maps geographic data into a hexagonal grid over Los Angeles County to provide a more granular look at the effects of policy changes.
The tool combines population statistics such as age, gender, racial composition, and education from the 5-year American Community Survey with LA County tax assessor, crime, and transportation data to model the effects of policies across multiple dimensions.
We model using Markov Chain Monte Carlo simulations to simulate how policy changes will affect vulnerable populations 5, 10, or 15 years into the future.
For more information about our methodologyClick Here
We are a team of graduate Data Science students from UC Berkeley