  Public Policy involves proposing changes to existing practices, alternatives,
new habits. Citizens and institutions react accordingly, accepting, refuting or
adapting. Agent-based modeling is a tool that can enrich the policy analysis
package explicitly considering dynamics, space and individual-level
interactions. This paper presents a modeling platform called PolicySpace that
models public policies within an empirical, spatial environment using data from
46 metropolitan regions in Brazil. We describe the basics of the model, its
agents and markets, the tax scheme, the parametrization, and how to run the
model. Finally, we validate the model and demonstrate an application of the
fiscal analysis. Besides providing the basics of the platform, our results
indicate the relevance of the rules of taxes transfer for cities' quality of
life.
