As a policy analyst, I encounter a range of different types of policy studies. Different research questions demand different tools. For example, measuring the economic footprint of a cycling industry requires an entirely different approach than figuring out whether data centers create net value for society.
Getting useful answers to policy questions starts with identifying what kind of policy study is necessary to answer these questions. Today, I wanted to talk about four different types of policy studies that we frequently encounter at Scioto Analysis.
Economic Impact Analysis
Economic impact analysis can be used to estimate how increased spending or employment ripples through the economy of a defined area. This type of analysis looks at how economic activity in one industry affects spending in other parts of the economy. While not policy analysis on its own, economic impact analysis can be a helpful tool for understanding the scale of an industry or project compared to the overall economy.
Economic impact analysis works by taking a baseline spending figure and estimating how that spending ripples throughout a regional economy. We do this using economic multipliers. For example, if someone purchases bread at a bakery, the business uses that revenue to buy more flour and pay its employees. Those employees then spend their wages on rent, groceries, transportation, and more. The flour miller uses the money from the baker to buy more wheat and pay its employees, and so on.
To actually do the analysis, we collect or estimate spending data and use tools like RIMS II or IMPLAN to calculate how much a dollar spent in one industry spurs new activity in others. These multipliers break into three layers:
Direct Effects: initial spending and employment
Indirect Effects: business-to-business interactions along the supply chain
Induced Effects: household spending from workers after paying into taxes and savings
However, economic impact analysis has some limitations. For one, an economic impact analysis does not establish creation of new economic value. A new sports stadium could spur hundreds of millions of dollars of economic activity on restaurants, retail, and ticket sales, but that consumer spending could have existed regardless of the sports stadium existing–just in a different part of the economy. Economic impact analysis also does not account for social costs, so it does little to tell us the tradeoffs associated with a certain policy or economic activity.
In January 2025, we released a study about the economic and health impacts of bicycling and trails in Iowa. This study is a great example of when to use economic impact analysis: we used survey data from Iowa cyclists to determine what economic contributions cycling had in Iowa’s economy.
You should choose an economic impact analysis when you need to demonstrate the size, reach, and regional economic contribution of an existing sector, institution, or new facility to local stakeholders and legislators.
Cost-Benefit Analysis
While economic impact analysis measures benefits and costs in the formal economy, cost-benefit analysis measures costs and benefits in the broader economy. Cost-benefit analysis is the systematic inventorying of all benefits and costs of a public policy, expressed in monetary terms. The goal of cost-benefit analysis is to determine whether a certain policy creates more total value for society than it costs.
Instead of looking at spending flows, a cost-benefit analysis assesses allocative efficiency as a whole. This means that cost-benefit analysis assesses nonmarket outcomes using empirical studies and comparing real-world conditions, instead of just looking at formal economic activity.
To conduct a cost-benefit analysis, analysts follow a sequence of steps:
Establish a baseline: Costs and benefits should be measured against a counterfactual scenario, typically the status quo.
Determine policy options: Costs and benefits should be compared across multiple discrete alternatives.
Decide standing: It should be explicitly clear whose costs and benefits count in the analysis, which typically involves geography.
Identify impacts: The analyst should have a list of impacts to analyze in cost-benefit analysis that is based on current research and literature.
Quantify and monetize impacts: All impacts should be assigned numbers and monetary values.
Discount costs and benefits: All impacts should be discounted to account for current costs and benefits being valued more than future ones.
Conduct sensitivity analysis: Key assumptions should be tested to understand the certainty of results and the importance of different assumptions.
Tell your story: Results are communicated clearly in a report, press release, presentation, or something else entirely.
Scioto Analysis publishes the State Handbook of Cost Benefit Analysis as a toolkit for state and local analysts looking to conduct cost-benefit analysis.
We applied this framework in our cost-benefit analysis of congestion fees in New York City. We monetized impacts such as driver time savings, emissions, fuel waste, consumer spending, and implementation costs to understand the net social impact of congestion fees in New York City. We found that in 2025, congestion fees in New York City generated approximately $2 billion in net social benefits.
You should choose a cost-benefit analysis when you need to decide whether a proposed policy or public project creates more value for society than it costs, or when you are comparing different policy options to see which one delivers the highest net social return to the public.
Cost-Effectiveness Analysis
Cost-effectiveness analysis answers a straightforward question: how much bang do you get for your buck?
While cost-benefit analysis focuses on dollars in and dollars out across society, cost-effectiveness analysis is a broader framework that answers a narrower question. It calculates total program cost divided by a specific, non-monetized outcome, telling you how much a policy costs to deliver a physical result without trying to assign dollar values to social outcomes.
By focusing on a single metric, cost-effectiveness analysis simplifies impact identification and gives agencies working under strict budget caps an intuitive way to compare policy alternatives head-to-head. Instead of quantifying many different impacts, cost-effectiveness analysis focuses on a specific metric. Cost-effectiveness analysis is a great way to compare different policy options that are trying to achieve the same goal. The main limitation of cost-effectiveness analysis is that it is, by nature, tunnel vision. While it does a good job of comparing different policies against a singular goal, it doesn’t account for unexpected impacts or opportunity costs.
You should choose a cost-effectiveness analysis when you have an established goal or a fixed budget and need to identify the lowest-cost way to reach that target across competing policy options.
Program Evaluation
Program evaluation is the retrospective, data-driven assessment of an existing or completed policy to determine whether it actually achieved what it set out to do.
While forward-looking policy research projects what might happen under a pending proposal, program evaluation deals with the hard data generated during or after implementation. Program evaluation requires us to ask: did the program itself cause the observed changes, and how large was that impact?
To answer that question, evaluators rely on an econometric toolkit designed to isolate program effects. For example, if participants in a job training initiative see their incomes rise, that alone does not prove the program succeeded. Exogenous factors such as regional wage growth or inflation could lead to rising incomes, while the job training initiative might have done nothing. Because of this, evaluators often use causal methods like difference-in-differences and regression discontinuity to create a counterfactual, an analysis of what would have happened if the program didn’t exist.
Because of the emphasis on causality, internal validity is key to program evaluation. To properly evaluate the effects of a certain program, we should approach our analysis with an objective eye that is free from selection bias or confounding variables.
You should choose a program evaluation when you have already implemented a pilot or program and want empirical proof of its causal impacts.
There are more policy studies beyond these, but thinking about policy analysis with these four frameworks is a good place to start.
