Earlier this month, Scioto Analysis released an analysis we did in partnership with the Center for Climate Integrity on the cost of climate change in Pennsylvania.
In this study, we built on the work we did on our Ohio cost of climate change report to estimate how climate change will impact different types of communities.
A lot of lip service is paid to “equity” in public policy analysis these days. Equity is one of the “big three” criteria for analyzing public policy along with effectiveness and efficiency. But unlike effectiveness analysis, which has tools like randomized controlled trials and quasi experimental methods, and efficiency analysis, which has cost-benefit analysis, equity analysis has no go-to methodology for its conduct.
So how do we conduct equity analysis? The steps we took ended up looking a lot like a broader policy analysis. While you could go through the steps of the Eightfold Path to conduct an equity analysis, our approach in this study boiled down to three major steps.
Step 1: Define Criteria
One of the major reasons equity analysis is not as standardized as effectiveness or efficiency analysis is because of the many dimensions equity can be analyzed on. Race, income, sex, rurality, age, education, sexual orientation, geography, employment, immigrant status, language spoken at home, and housing are just a handful of different examples of dimensions of equity.
Criteria should be defined based on (a) what is informative to your client, (b) what you have reliable data on, and (c) what is relevant to the content of the study.
The former consideration is always paramount in public policy analysis: what will people listen to? When speaking truth to power, an analyst needs to be aware of what her client is interested in and what she will listen to if policy analysis is to be useful.
Also important is whether data is available. A client might be eminently interested in how their policy impacts high-IQ students, but if the data is not available on how those students are impacted by the policy, an analyst is not very useful.
Step 2: Calculate Impacts
This is the “technical” part of the analysis. This phase of equity analysis consists of gathering data and estimating what the range of impacts are for different groups.
For our Pennsylvania analysis, we had defined municipalities as municipalities of interest based on them having larger racial minority, impoverished, rural, non-English-speaking, or foreign-born populations. We then calculated what these communities’ per-capita costs were compared to the per-capita costs of the average municipality statewide.
Step 3: Communicate Results
Policy analysis requires good communication, and equity is no exception to this. Communication of equity results can demand extra care because of the sensitive political dynamics associated with communities of interest defined by equity categories. Knowing the right language to use around race, income, and gender is tantamount, especially when making sure a client will take this analysis seriously.
Also important is making sure that results are communicated in a way that transparently and clearly shows the differences between equity categories. In our results, we showed the dollar figure difference between communities. This showed how much different communities would have to pay based on the type of community they were.
When all was said and done with this study, we found that high-poverty and rural municipalities would pay more per-capita than the average Pennsylvania municipality. This was a useful insight: it told us something about who will shoulder the burdens of the cost of climate change. And this is just the sort of insight that helps us understand who will benefit from policy interventions.