Because our focus is at the intersection of data science and public policy. we have a diverse knowledge base across a host of policy-oriented domains.  When we analyze a given policy we do so with the following critieria in mind:

Is it economically efficient? If we’re going to spend taxpayer dollars on a new program will the benefits outweigh the costs?

Is it equitable? Will everyone benefit or just a disproportionate few?

It is politically feasible? Will it gain support from legislative officials and their constituents?

Are the motivations for the policy generalizable? How did we come up with this new strategy? Are we borrowing it from a place or context different from our own? What are the implications of this?

What are the unintended consequences? Will the behavior we are trying to incentivize lead to other negative outcomes?

Check out some of our policy analysis work here:

Chicago Tribune – Can Improvement Districts help save Chicago schools?
PlanPhilly – Why all affordable housing isn’t created equal
Planetizen: Lessons from West: Do Texas land use laws put residents at risk?