What makes policy analysis credible?

Earlier this month, I wrote a blog post reflecting on Eugene Bardach’s A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving. I wrote about the “Grandma Bessie Test,” a strategy Bardach recommends to make sure we understand the conclusions from our work well. To conduct the “Grandma Bessie Test,” we try to explain our data, findings, and conclusions to an intelligent but non-expert audience (like our Grandma Bessie) in about one minute.

Bardach’s eightfold path is a book that we reference a lot at Scioto Analysis. In some ways, it’s the very bread and butter of our work as policy analysts. The eightfold path is an eight-step framework to help us understand public policy and conduct policy analysis more effectively. The eight steps in the framework are as follows:

1. Define the Problem

2. Assemble Some Evidence

3. Construct the Alternatives

4. Select the Criteria

5. Project the Outcomes

6. Confront the Trade-Offs

7. Decide!

8. Tell Your Story

As Bardach develops these eight steps throughout his book, an important theme of credibility emerges repeatedly. Today, I want to focus on an important theme that Bardach references throughout his book: what makes an analysis credible, and what makes one not credible?

What makes policy analysis credible?

When we’re doing policy analysis, we should be thinking about credibility multiple times throughout the analysis. Credibility means selecting trusted sources, creating well-researched methodologies, and fact-checking our analysis at the end. The following considerations can help ensure our work is credible.

Defending against Politically Inspired Criticism

Defending against politically inspired criticism is the first strategy Bardach recommends to protect credibility. If we think there might be parties who will oppose or attempt to undermine our work, then we should touch base with them before publishing our analysis. 

We can do this by having conversations or conducting interviews with parties who might be opposed. To bolster our analysis, we can include quotes from opposing parties. In addition, we should always be thorough with our analysis: we shouldn’t conduct analysis that heavily favors one side without considering the other.

Ultimately, conducting evidence-based analysis with data and statistics may be the best way to defend against politically inspired criticism. If our findings are grounded in data and statistics, then critics cannot so easily sweep these findings aside as mere personal bias.

Preparing for Premature Exposure

The second strategy Bardach recommends to protect credibility is to prepare for premature exposure. Research and policy analysis can be a slow process. Throughout our analysis, we should be prepared for unexpected deadlines or sudden windows of opportunity. For example, reporters might reach out suddenly looking for a quote on a certain policy. Alternatively, an event might pop up that our analysis would be useful for.

To help prepare for these opportunities without sacrificing credibility, Bardach recommends that we spend time early in our analysis figuring out the answers to the most basic, crude questions that people are bound to ask. That way, if opportunities pop up throughout our analysis, we can share information without overstating our analysis.

Sensitivity Analysis

One of my favorite parts of performing policy analysis is sensitivity analysis. Sensitivity analysis is the process of estimating how assumptions included in an analysis impact the uncertainty around the findings of the analysis. Conducting sensitivity analysis is an exercise in testing the precision of our results. 

Bardach recommends we ask ourselves the question, “how big a mistake can I afford in this assumption before this analysis is in really big trouble?” Sensitivity analysis helps answer that question by forcing us to look at our assumptions and determine where results might be vulnerable. By conducting sensitivity analysis, we can prove that our results aren’t just based on a couple of key assumptions.

What makes policy analysis not credible?

Understanding how to produce credible analysis is important, but so is recognizing the pitfalls that can undermine its credibility. Bardach points out that some of the biggest problems with a project’s credibility come from carelessness and letting our own opinions get in the way of the data.

The quickest way to destroy our credibility is by allowing our preferred solution to interfere with how we define the problem. For instance, if we define a problem as “there is too little funding for this program”, we have already assumed the answer to the problem before doing any research. To ensure credibility, we should leave the door open for all potential solutions.

We can also kill our credibility by letting optimism get in the way of our analysis. Bardach warns us not to count on one of our alternatives working out just because we expect it to. Instead of assuming results, we should rely on data to show us what the truth of a certain policy really is.

How do analysts decide what not to count in a cost-benefit analysis?

An underrated skill policy analysts need to have is understanding when something should not be included in an analysis. It often feels safer to always want to include more, but managing the balancing act of deciding when enough is enough can lead to better results.

How standing can limit results

One reason an analyst might choose to exclude something from their analysis is because they decide that it doesn’t have standing. Standing is the principle that a cost or benefit should only be included if it accrues to the group whose welfare is being evaluated. While this sounds straightforward, it can dramatically change the scope of an analysis. 

Suppose a state government is evaluating a transportation project using a state-level cost-benefit analysis. The primary question is whether the project makes the residents of that state better off. If the project causes travelers from another state to save time, those benefits are certainly real, but they are not benefits to the population being evaluated. Likewise, if a policy simply shifts economic activity from one state to another, the gains in one jurisdiction are offset by losses in another and may not represent a net benefit from the perspective of the analysis. 

For more information about standing, check out our State Handbook of Cost-Benefit Analysis.

When further analysis costs too much

Another reason an analyst might decide not to include something is because the marginal benefit of more research doesn’t meet the marginal cost. As with any project, there comes a point where additional effort produces very little additional value. Good policy analysis is not about measuring every conceivable impact, but about measuring the impacts that matter most. 

Analysts can hone their intuition when it comes to prioritizing which inputs to measure. For example, it is probably always worth exploring a mortality impact if the policy you are analyzing might have one since reductions in mortality are often extremely valuable. Conversely, if you think that an impact is probably not very valuable, then it’s worth using your limited time and resources to explore other impacts first.

If the data isn’t good enough

One final reason you might want to exclude something from an analysis is if the quality of the data isn’t good enough to support something quantitatively. Nearly every policy has effects that are difficult to measure, and there is often a temptation to assign numbers to those impacts simply because they seem important. Unfortunately, a quantitative estimate built on weak evidence can be more misleading than acknowledging that the effect cannot yet be measured. 

That does not mean these impacts should be ignored entirely. In many cases, the appropriate approach is to discuss them qualitatively while being transparent about the limitations of the available evidence. This allows decision-makers to consider potentially important effects without giving a false sense of precision. 

Note that poor data quality and high variance estimates are not the same thing. At the start of this year, the Trump administration stopped counting the health benefits of environmental policies, claiming that the monetization step was too uncertain. What they should have done if they were concerned was spend more time unpacking how that uncertainty might affect results through sensitivity analysis.

Ultimately, deciding what to leave out is just as important as deciding what to include. Every policy analysis involves limited time, limited data, and limited resources. The best analysts recognize these constraints and focus their efforts where they can provide the greatest insight. By carefully considering standing, weighing the costs and benefits of additional research, and being honest about the quality of the available evidence, analysts can produce work that is not only more efficient, but also more credible.

What is “social welfare?”

At Scioto Analysis, we perform policy analysis through an economic lens. While that is a true statement, it doesn’t do a great job of actually describing our work. You could use that exact sentence to describe what organizations like the World Bank or the Federal Reserve do in their research. I bring this up because I wanted to describe in more detail what it is we actually do at Scioto Analysis and what some of the theoretical underpinnings are.

A better description of our work would be something like this: we perform policy analysis at the state and local level using microeconomic tools rooted in the ideas of welfare economics. Policy analysis at the state and local level is fairly self explanatory, that is just an issue of scope. The more interesting part to discuss and what I want to explain in more detail today is what welfare economics is and why it has the tools that we like to use when it comes to policy analysis.

What is welfare economics?

Welfare economics is a branch of microeconomics that focuses on measuring how a society as a whole allocates its resources and how well-off that makes its local residents. Microeconomics gives us the toolbox to evaluate individual decision making, and welfare economics provides the framework to make assessments about how those individual decisions impact society as a whole.

One of the challenges in welfare economics is that there is no objective way to measure or compare one person's wellbeing against another's. There is the field of subjective wellbeing research and that data could be an extremely valuable input into a welfare calculation, but we’d need more and better data to really dig much deeper.

 Because of this, welfare economics relies on assumptions about how individual wellbeing should be aggregated into a measure of society's overall wellbeing. Different assumptions lead to different conclusions about which policies are desirable, which is why economists have developed a variety of social welfare functions that reflect different views about fairness, efficiency, and the tradeoffs between them. 

Types of social welfare functions

While you could technically have any social welfare function you wanted, in order to be useful it should probably use the individual welfare functions of everyone in a society as an input. Most commonly, we use some form of a utilitarian social welfare function as our starting point.

Under a simple utilitarian social welfare function, the total wellbeing of a society is calculated as the sum of all individual welfare functions. This has some useful features that lend themselves to cost-benefit analysis. If we are agnostic about who in society is benefiting from a change, then it makes sense that we’d prefer policy options so long as the net change in individual wellbeing is positive. 

A natural extension of the utilitarian model is to account for diminishing marginal returns of income. In other words, $100 given to a millionaire doesn’t increase their wellbeing by very much at all, while that same $100 given to a person in poverty could significantly improve their wellbeing. The end result is that taking $100 from a super wealthy person and giving it to a poor person increases total social welfare.

One of the most important contrasts to utilitarian social welfare is the Rawlsian social welfare function. This concept is based on the ideas of philosopher John Rawls whose work centered around ideas of social justice. The economic framework named after him is that a society is only as well off as its least well off member. Mathematically, this is represented as Social Utility = min(U1 ,  … , Un). Under this framework, a policy change would only be worth it if it benefits the least well off person.

Having a well defined social welfare function is an essential part of policy analysis. It is the heart of how we assess the tradeoffs of a policy. This is not to say that this is the only approach for policy analysts to use. Some evaluations might not explicitly rely on welfare economics, and reasonable people can disagree about which social welfare function best reflects society's values. At Scioto Analysis, however, welfare economics provides the foundation for much of our work because it offers a consistent framework for comparing the costs and benefits of different policy options and making those tradeoffs explicit.

Which states have the highest pre-k enrollment?

Last year, we released a cost-benefit analysis about universal prekindergarten in Ohio. We found that universal prekindergarten in Ohio could lead to between 9,300 and 29,000 new children enrolled in prekindergarten and between $220 million to $750 million in net economic returns. These benefits include increased lifetime earnings, reductions in criminal justice costs, and savings in special education.

Universal prekindergarten means that all families have the option of enrolling their children into a universal prekindergarten program that is publicly funded and accessible to all. Usually, universal prekindergarten is limited to four-year olds and sometimes three-year-olds. As of now, only four states (Colorado, Florida, Oklahoma, and Vermont) and Washington D.C. have universal prekindergarten. Another eight have universal eligibility programs that do not necessarily provide prekindergarten to every eligible child. Today, I want to look at prekindergarten enrollment by state as reported in the American Community Survey to see if they align with the states that offer universal prekindergarten programs.

Pre-K Enrollment Across the United States

The following table shows the number of children enrolled in prekindergarten by state. The table is ordered by the percentage of children enrolled in prekindergarten in each state.

Pre-K Enrollment by State
State	Number of Children Enrolled in Pre-K	Total Children Aged 3-4	Percentage of Children Enrolled in Pre-K
Vermont	8,646	12,164	71.08%
New Jersey	150,741	220,240	68.44%
New York	278,601	436,513	63.82%
Connecticut	45,537	72,133	63.13%
Mississippi	37,847	64,986	58.24%
Massachusetts	85,351	148,874	57.33%
New Hampshire	15,923	28,253	56.36%
Illinois	148,149	269,663	54.94%
Wyoming	6,232	11,382	54.75%
Colorado	65,653	122,308	53.68%
Louisiana	61,553	114,828	53.60%
Florida	254,189	493,696	51.49%
Kansas	34,515	67,543	51.10%
California	430,286	853,418	50.42%
Pennsylvania	139,085	277,992	50.03%
Rhode Island	12,039	24,217	49.71%
Maryland	69,906	143,001	48.88%
Michigan	107,189	220,343	48.65%
Georgia	121,366	249,671	48.61%
Virginia	96,086	197,701	48.60%
South Carolina	55,752	115,622	48.22%
Maine	12,350	25,669	48.11%
Texas	386,523	808,459	47.81%
Minnesota	61,667	129,083	47.77%
New Mexico	19,092	40,582	47.05%
Washington	78,144	167,498	46.65%
Delaware	10,018	21,504	46.59%
Oregon	37,732	82,534	45.72%
Missouri	64,800	141,853	45.68%
Alabama	51,516	114,660	44.93%
Iowa	34,497	77,108	44.74%
Arkansas	31,442	70,715	44.46%
Wisconsin	57,890	131,336	44.08%
Ohio	122,176	281,087	43.47%
Utah	42,343	97,649	43.36%
North Carolina	103,385	238,779	43.30%
Nebraska	21,386	49,735	43.00%
Montana	9,475	22,284	42.52%
Tennessee	68,684	168,220	40.83%
Hawaii	12,701	31,275	40.61%
Oklahoma	39,248	99,149	39.58%
Indiana	66,128	169,134	39.10%
Nevada	28,342	72,874	38.89%
Alaska	7,735	20,325	38.06%
Arizona	61,233	161,159	38.00%
Kentucky	41,187	108,996	37.79%
South Dakota	8,248	21,921	37.63%
West Virginia	13,611	36,536	37.25%
Idaho	17,215	46,570	36.97%
North Dakota	6,582	18,345	35.88%

The American Community Survey asks families if their children attended school at all in the last three months, so this data likely overestimates actual prekindergarten enrollment rates. The top five states for prekindergarten enrollment are Vermont, New Jersey, New York, Connecticut, and Mississippi, ranging from 58% to 71% prekindergarten enrollment. This means that only one state with universal prekindergarten, Vermont, ranks in the top five states for prekindergarten enrollment. The other three states with universal prekindergarten, Colorado, Florida, and Oklahoma, rank 10th (54% enrollment), 12th (51% enrollment), and 41st (40% enrollment) respectively. 

Colorado and Florida still rank relatively high for prekindergarten enrollment, while Oklahoma is in the bottom 20% of states. One reason could be that Oklahoma’s universal prekindergarten program is only for four-year olds, so prekindergarten enrollment for three-year olds is likely much lower than for four-year olds.

What about the top five states for prekindergarten enrollment? What are the factors driving enrollment among these states?

Vermont

About 8,600 of 12,100 children aged 3-4 years old in Vermont are enrolled in school, accounting for about 71% of the population. Vermont’s universal prekindergarten program requires at least 10 hours of prekindergarten to be available for all children aged 3 to 5 years old in Vermont for 35 weeks in a school year.

Vermont is also the second smallest state by population and the sixth smallest state by land area, so administering universal prekindergarten and boosting enrollment is more seamless than for larger states. Vermont’s high prekindergarten participation rate may contribute to future educational attainment as well, as Vermont is the third-highest state for bachelor’s degree attainment with a bachelor’s degree attainment rate of 45.1%, only ranking behind Massachusetts and Colorado.

New Jersey

About 151,000 of 220,000 children aged 3-4 years old in Vermont are enrolled in school, accounting for about 68% of the population. New Jersey does not have universal prekindergarten, but they have an expansive prekindergarten program available for vulnerable populations. New Jersey also heavily invests into prekindergarten programs. The state spends nearly $19,000 per child on preschool education, ranking second in the nation, only behind Washington, D.C. Alongside New York and California, New Jersey is just one of three states that spends more than $1 billion on preschool annually.

Similar to Vermont, New Jersey is the fourth-smallest state in terms of land area, but they are the eleventh largest state in terms of population. In fact, New Jersey is the most densely populated state in the nation. A denser population historically results in higher participation in public programs, which may partially explain why New Jersey’s prekindergarten participation rate is so high.

New York

About 279,000 of 437,000 children aged 3-4 years old in New York are enrolled in school, accounting for about 64% of the population. In New York City, which accounts for close to half of the entire state’s population, all four-year olds already have access to prekindergarten. Prekindergarten access and New York City’s dense population are both key reasons for its high prekindergarten enrollment rate.

Earlier this year, New York Governor Kathy Hochul announced that by the 2028-2029 school year, New York will begin offering full universal prekindergarten for all children under 5 years old. This policy change is likely to increase New York’s prekindergarten enrollment rates even higher.

Connecticut

About 46,000 of 72,000 children aged 3-4 years old are enrolled in school in Connecticut, or about 63% of the population. Connecticut joins the first three states as another state located in the Northeast with high prekindergarten enrollment. Similar to Vermont and New Jersey, Connecticut is the third smallest state in terms of land area with a medium-sized population. Connecticut’s small size might make it easier for families to enroll in prekindergarten. 

Connecticut doesn’t currently offer universal prekindergarten. However, Connecticut has recently been making strides to make prekindergarten more accessible for vulnerable populations, and some legislators have proposed plans for universal prekindergarten within the next several years. Connecticut also ranks ninth in median household income in the country at about $99,240. With more income, Connecticut households may be able to enroll their children in prekindergarten at higher rates.

Mississippi

About 38,000 of 65,000 children aged 3-4 years old in Mississippi are enrolled in school, accounting for about 58% of the population. Being located in the South, Mississippi is a deviation from the Northeast trend of the rest of the highest ranking states for prekindergarten enrollment. 

According to the National Institute for Early Education Research, Mississippi is one of six states in the country to meet 10 of 10 benchmarks for preschool quality. Mississippi doesn’t have universal prekindergarten, and state spending on prekindergarten is only $4,832 per child, ranking 35th in the nation. So, why does Mississippi have such high prekindergarten enrollment rates?

Prekindergarten in Mississippi is mostly administered through Early Learning Collaboratives. Early Learning Collaboratives are state-funded pre-K programs which include school districts, Head Starts, and licensed childcare providers. Communities can receive state funding for Early Learning Collaboratives by forming collaborative partnerships between school districts and childcare providers. This means that many prekindergarten programs in Mississippi are offered through a partnership between public school districts and private childcare providers. Mississippi also offers a 1:1 state tax credit for individuals or corporations who donate funds to Early Learning Collaborates for up to $1 million, which encourages private entities to increase access and quality for prekindergarten in their communities.

The future of pre-K in the states

As time passes, more states are beginning to offer universal or subsidized prekindergarten programs. Universal prekindergarten can increase prekindergarten participation rates and create future financial savings for the state and households alike. However, as Mississippi has shown, universal prekindergarten might not be the only answer for states and communities to improve prekindergarten quality and access.

Federal bill would open the door for Ohio housing reform

Last week, U.S. Congress sent the 21st Century ROAD to Housing Act to the White House for signature, the most significant piece of bipartisan legislation of President Trump’s second presidency and the largest housing affordability measure in a generation, though Trump is refusing to sign it.

The bill makes a number of policy changes to increase home supply like streamlining federal regulations, restricting institutional investors, and incentivizing local governments to lower housing barriers.

This follows an unprecedented rise in housing costs fueled by antiquated construction rules, underbuilding during the Great Recession, and rising inflation.

Though Ohio has enjoyed a relatively affordable cost of living for decades, the state has not been immune to these national housing trends.

The average Ohio house cost 65% more in January 2026 than it did in January 2020.

Without enough homes to meet the country’s growing demand, prices are going up and, with them, the median age of first-time homebuyers which now tops 40 years old. 

But Ohio doesn’t just have a housing supply issue. It also has a housing choice issue.

Increasingly, buyers do not have the freedom to choose the type of home that best fits their family’s unique wants and needs, constrained by local zoning regulations that often ban historic housing styles. 

In Ohio, only 3% of all homes are duplexes which Dr. Jason Reece, professor of City and Regional Planning at the Ohio State University, has called America’s “original workforce housing” because of their natural affordability and power to build family wealth through sweat equity. 

These so-called “missing middle” homes — duplexes, triplexes, and small townhomes — previously played a crucial role in expanding homeownership opportunities to middle-income families.

In the past, a young family that purchased a duplex could use their spare unit to generate extra rental income. They could also offer decent housing to family members at the start of their career or in their twilight years. This not only kept expenses low but also made family caregiving easier.

In theory, this path to the middle class is still possible.

In a recent analysis my firm Scioto Analysis conducted with the Affordable Housing Alliance of Central Ohio, we estimated a typical family can now earn or save nearly $1.3 million over a lifetime through duplex homeownership. And that doesn’t include the value fo the equity that the home itself builds over time. 

But Ohio families can only benefit from a duplex if they can find one.

We also mapped the zoning code rules in all eleven of central Ohio’s counties and estimated that duplexes were prohibited on 79% of all parcels.

In some communities, including those facing intense job growth pressures, they’re banned entirely. 

This isn’t just a problem in Ohio.

Across the country, duplexes and other traditional styles have gradually been removed from the marketplace.

Consumers have more freedom than ever to choose the kinds of food they eat or the places where they get their news, but they have fewer housing choices than their grandparents. 

From Maine to Montana to Arizona, and many places in between, cities and states are confronting this challenge with laws aimed at re-legalizing the duplex and restoring that tradition of choice. 

The 21st Century ROAD to Housing Act offers Ohio an opportunity to join them.

In particular, local communities will soon be able to learn zoning and land-use “best practices” from national research and case studies, compete for planning grants to localize these strategies, and seek a share of more than $200 million in competitive innovation funds to make these plans a reality. 

The state can accelerate this work, too, with its own reforms and supports, many of which were already laid out in the Ohio Senate Select Committee’s “Housing Reimagined” report and the Home Matters to Ohio plan.  

Each of these tools would make building housing in Ohio easier, which will improve prices and quality while expanding meaningful resident choice. And that will benefit everyone.

This commentary first appeared in the Ohio Capital Journal.

How can local governments impact affordability?

Over the weekend, I saw my first political ad of the midterm cycle. Current U.S. representative Angie Craig was playing softball as a metaphor for how she's ready to step up to the plate in her bid for the open Senate seat. 

If you happen to live in a state that is more open politically than Minnesota, I suspect you’ve been seeing ads and yard signs for quite some time now. With election month only four months away now, I wanted to talk about one of the topics that has been dominating the political conversation for over a year now, affordability. 

Earlier this year, we released a study looking at how Franklin County compared to its peers in terms of cost of living. Over the course of this research, we learned a lot about the conditions of state and local governments that can influence cost of living. 

From a state and local perspective, cost of living is not something that policymakers can fully control. The levers needed to meaningfully influence the price of gasoline or food are only really available at the federal level. Despite this, we know from our study that there are differences in cost of living observable at the county level, even within states. 

Tax policy’s impact on affordability

Taxes are a difficult part of the cost of living discussion because in order to fully understand their impact we need to take into account both how much they cost residents and what their tax dollars are being spent on. If the public sector is providing services that people want and would otherwise spend their own money on, then it might make a place feel more affordable even though people technically have less discretionary spending power.

We found in our study that property taxes had the biggest impact on cost of living when compared to income and sales taxes. This is probably part of the reason why recently in Ohio eliminating property taxes has been a major policy discussion.  

Housing policy’s impact on affordability

One of the key findings from our study was that local differences in housing costs were a significant driver in the cost of living index. There are two main reasons for this: housing is a good that is strongly influenced by local policy conditions and housing is often one of the single largest expenses people have. 

One way policymakers can make housing more or less affordable is through their local zoning laws. More relaxed zoning laws provide developers and builders more options for where to build new housing. More options in turn should lead to lower costs overall. Another common policy employed in some places is rent control. I’ve talked before about why most economists don’t like rent control, but in short it benefits current renters and hurts future renters.

In general, local housing policy can determine whether new housing is easy or difficult to build. Some municipalities might not want new housing for some policy reason. Recently, the city of Lakeville Minnesota stopped building new housing since they felt their other infrastructure wasn’t able to keep up with the rapid population growth. 

As these elections get closer, consider what your local elected officials are planning to do when it comes to affordability. They might have less broad economic influence than the federal government, but the policy decisions they make can still have a noticeable impact on local economic conditions.

The economic impact of rolling back cap-and-invest

One of the biggest stories of the last four months has been the high cost of crude oil due to the U.S. war with Iran and its impact on the cost of gasoline. We know that rising gas prices hurt low-income and rural consumers disproportionately because they have a less elastic demand for gasoline. When prices go up, they still need to fill up their tanks just as frequently. 

This has led to states suggesting policy changes in order to help out these people. One such proposal was to suspend gas taxes, which I’ve already written about. More recently, California and New York have suggested rollbacks of their cap-and-invest programs.

Fundamentally, cap-and-invest and the gas tax are attempting to do the same thing: address externalities associated with the consumption of gasoline. The mechanisms are different, but they both raise the price of gasoline in order to get the market to account for costs that would otherwise be imposed on society. By increasing the price of activities that generate pollution, these policies encourage consumers and businesses to reduce emissions where doing so is less costly than continuing to pollute.

What is wrong with rolling back cap-and-invest?

The core issue with these policies is that they are introducing deadweight loss into these markets and making them less efficient. The cap-and-invest program is designed to provide markets a way to interact with the cost of their carbon dioxide emissions. As long as you accept that carbon dioxide emissions have a social cost, then it is non-controversial that markets which create carbon dioxide emissions should account for that cost.

Changing these policies doesn’t do anything to change the market price of gasoline. That is largely outside the control of these governments. Suspending cap-and-invest may lead to a reduction in the price of gasoline at the pump, but it does so at the cost of higher than optimal negative externalities.

It may be the case that the goal of easing financial burdens for these affected communities is worth the cost of introducing these additional externalities, but policymakers should recognize that this is a tradeoff rather than a free source of relief. Lowering the price consumers pay by weakening environmental policy reduces the incentive to conserve fuel and increases emissions. If the objective is simply to help households cope with higher prices, there are often more targeted ways to accomplish that goal. 

An alternative solution: improving access to gasoline substitutes

This is a vague suggestion because how people substitute away from gasoline consumption might look very different across the country (and it may be impossible for some), but a natural suggestion to ease the burden of rising costs is to help people increase their elasticity of demand. 

In urban areas, this could be achieved by expanding public transportation services or reducing the cost of using it. Having free buses that run more frequently might encourage people to find a bus route to work instead of driving themselves. Similarly, investments in safe bicycle infrastructure or commuter rail can provide additional options that reduce dependence on gasoline over time. 

In more rural communities, the available substitutes to gasoline use are more limited. Expanding vanpool programs, supporting employer-sponsored transportation, or encouraging greater access to remote work can all reduce the amount of driving households are required to do. If policymakers want to take a more long-term view of the problem, tax incentives for people to purchase EV’s could reduce the specific demand for gasoline. None of these policies eliminate the need for gasoline entirely, but they make consumers less vulnerable when prices inevitably rise.

Another option is to provide direct financial assistance to households rather than lowering the price of gasoline for everyone. Targeted tax credits or cash assistance preserve the price signal created by gas taxes or cap-and-invest programs while still helping families afford higher transportation costs. Instead of making gasoline artificially cheaper—and encouraging greater consumption—these policies allow consumers to make their own decisions about how best to use the additional income.

High gasoline prices create real hardships, particularly for households that have few alternatives to driving. But that does not necessarily mean environmental pricing policies are the wrong target. If the goal is to reduce financial burdens without sacrificing the benefits of pricing pollution, policymakers should focus on making consumers more resilient to price increases rather than ignoring the costs of externalities.

Making policy analysis make sense: The “Grandma Bessie Test”

Over the past month, I’ve been reading through Eugene Bardach’s A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving. I’ve been with Scioto Analysis for just about a year and a half now, and when I came on as a full-time policy analyst in May, it was due time I made my way through Bardach’s eightfold path for policy analysis.

Eugene Bardach passed away earlier this year, and the Goldman School of Public Policy, where Bardach was an esteemed faculty member, wrote a great article in May to honor Bardach and to remember his legacy. A large part of Bardach’s legacy is his contribution to the policy analysis field, as policy analysts, we follow the guidance from Bardach’s eightfold path closely in much of our work.

My colleague Rob has written extensively about Bardach’s eightfold path. In late 2022, Rob closed out a series of blog posts he was writing about each step of the eightfold path and practical applications of them. The eightfold path is an eight-step framework to help us understand public policy and conduct policy analysis more effectively. The eight steps in the framework are as follows:

1. Define the Problem

2. Assemble Some Evidence

3. Construct the Alternatives

4. Select the Criteria

5. Project the Outcomes

6. Confront the Trade-Offs

7. Decide!

8. Tell Your Story

Today, I want to focus on the eighth step of Bardach’s eightfold path: “Tell Your Story”.

How can we tell stories as policy analysts?

One of my biggest takeaways from Bardach’s eightfold path is the importance of conveying results and information to stakeholders and interested parties. In policy analysis, your relevant audience can range from policymakers to reporters to everyday constituents. The audience of policy analysis might be friendly, and they might be hostile. 

Bardach emphasizes the importance of choosing an appropriate medium, creating a well-structured narrative flow, maintaining credibility, and most importantly, explaining findings simply and clearly. Before even presenting our findings at all, Bardach recommends we apply the “Grandma Bessie Test”. This is an exercise where we aim to explain our work and conclusions in about one minute to our Grandma Bessie, our intelligent but not politically sophisticated grandma.

The purpose of this test is to give us a reality check–do we actually understand the conclusions from our work well enough to explain them clearly and succinctly? If we find ourselves struggling to explain our work to other people, then perhaps we don’t understand the findings well enough to make reasonable conclusions, let alone well to present to others.

How do I perform on the Grandma Bessie Test?

To determine if I’ve been following Bardach’s eightfold path well myself, I want to apply the “Grandma Bessie Test” to a few of the analyses I’ve worked on while at Scioto Analysis. For each project, I’ll aim to explain the goals, methods, and findings in just a couple of sentences,

Wildlife Crossings

In spring of 2025, we released a cost-benefit analysis about wildlife crossings. Wildlife crossings are bridges, culverts, underpasses, or other structures intended to direct animals across roadways to safely navigate through their habitat. To conduct our analysis, we pulled data from various departments of transportation and other state agencies to calculate how many wildlife-vehicle collisions can be prevented from each structure. 

By preventing collisions, we can save lives, avoid damage to vehicles and infrastructure, and restore ecosystem connectivity. Ultimately, we found that over a 70 year lifespan, one wildlife crossing can prevent 1,400 collisions, decrease at least one fatality, reduce 60 injuries, and create over $14 million in net present value to society.

Energy Permitting

In December of 2025, we released a study analyzing the energy permitting process in Ohio in partnership with the Ohio Chamber of Commerce Research Foundation. This refers to the process of applying for and getting approved for a permit to build an energy permitting facility in Ohio. The energy permitting process is lengthy and methodical: there are many built-in opportunities for community input and legal review. These steps are important because they ensure that both community and legislative priorities are taken into consideration, but they come with a steep tradeoff. 

To conduct our analysis, we reviewed the entire energy permitting process according to the Ohio Revised and Administrative Codes, and we collected data on energy permitting timelines from projects across the past several years. We found that the average timeline for receiving an energy permit is 540 days, nearly one year longer than the statutory goal. Per year, these delays result in $440 million in lost investment, 5,400 fewer jobs, 9,000 megawatts of lost energy capacity, and $4.3 million in lost state tax revenue.

Affordability in Franklin County

In February, we released a study on affordability in Franklin County. Our goal was to replicate the regional price parity but at the county level. The regional price parity is an affordability measure created by the Bureau of Economic Analysis. The measure consolidates relative prices from housing and essential goods and services into one index that can be used to compare prices across different states. In our analysis, we wanted to create a county price parity measure to compare prices in Franklin County to other, similar counties around the country.

We used consumer price index data from the Bureau of Labor Statistics, total spending data from the Bureau of Economic Analysis, and household income and expenditure data from the American Community Survey. We found that despite a high tax burden, the cost of living in Franklin County is relatively low compared to similar counties. For instance, prices in Franklin County are about 18.5% lower than in Tampa’s Hillsborough County and 11.8% lower than in Atlanta’s Fulton County, mainly due to relatively affordable housing, electricity, and groceries.

How do you think I did? If Grandma Bessie can’t understand these, then at least some policymakers are struggling with it, too. This test is a great tool for making policy analysis accessible to the people who are supposed to use it.

TIFs: When Future Tax Dollars are Already Spoken For

I graduated from the University of Oklahoma this May. Around campus, I heard a lot about the planned Rock Creek Entertainment District. The development will be anchored by a new arena for the university’s basketball and gymnastics teams, which will be surrounded by other event venues, hotels, and restaurants. 

Because I don’t watch sports, this was initially a mundane piece of news for me. The topic became more interesting when I observed how many of my fellow Sooners took issue with the plan.

Some felt the new arena will be too far from campus and downtown Norman, Oklahoma. It will sit miles to the north and just off of Interstate 35. The location is sure to be convenient for visitors, but it may lead them to get back onto the interstate quickly once an event ends rather than sticking around Norman and spending money which would generate tax revenues for the city.

Another critique owes to the funding plan attached to the arena. This month, Oklahomans for Responsible Economic Development sued a slew of parties involved in the project’s development to stop it on these grounds. The group argues that the two tax increment financing districts Norman created for the project are illegal under Oklahoma’s constitution, among other complaints. The same group previously raised a petition for a public vote on the tax increment financing plan which garnered over 11,000 signatures. That effort failed after Oklahoma’s supreme court rejected it.

What is TIF?

A TIF district, or tax increment financing district, reallocates future tax dollars raised in an area to fund a project’s development costs. Essentially, a local government wagers that once the project is complete, it will generate new tax dollars in the form of sales taxes, property taxes, hotel taxes, or other levies. The local government borrows money today, and the loan is later repaid via tax dollars the project creates once finished. Separate tax increment financing districts can be created for the same project to commit tax revenue from different sources to this purpose.

The taxes used to repay the loan generally only include new revenues generated, which will ensure that the local governments can continue to fund services as they did before the tax increment financing district was created if this money were not to be raised otherwise. This arrangement is attractive to local governments who want to invest in large development projects without the appearance of giving over large quantities of public dollars to developers instead of investing them into services which more directly benefit the public welfare.

Why is Norman’s TIF Controversial?

The Rock Creek plan is not one tax increment financing district; it is two. A first controversy is the scale of the public commitment. The total authorized public financing across the two districts is up to $600 million. Some doubt that the Rock Creek District can generate enough new tax growth to justify authorizing that much money over the plans’ 25 year lifetimes. Beyond concerns about the price tag, each of the districts carries its own controversy.

The Property Tax Increment Financing District

This tax increment financing district captures growth in taxable property value above the existing base. In theory, a property tax increment financing district doesn’t take money away from existing public services. If $10 million in annual revenue is currently generated, and later the area generates $30 million in property taxes, the original $10 million continues being collected as it always has, and the added $20 million is used to pay for the project.

The Rock Creek tax increment financing plan depends on the claim that the entertainment district will create property tax growth that would not otherwise exist. If the arena and its nearby hotels, restaurants, and retail developments generate new, taxable activity, the city can argue that the project is partially paying for itself. 

But what if, in the absence of the district, there would have been property tax growth anyway? In that case, the city’s future tax revenues would suffer. Without tax increment financing, that new tax revenue would have supported city services, schools, and other public needs. With tax increment financing, the growth is instead redirected to a development tied closely to college athletics.

The Sales Tax Increment Financing District

This tax increment financing scheme captures a portion of the city’s sales tax revenue generated inside the district. Specifically, the sales tax increment is drawn from Norman’s non-dedicated and capital improvements sales taxes, which together equal 3% of gross taxable sales inside the district. Those revenues would otherwise flow into Norman’s General Fund or Capital Improvements Fund.

The logic here is that the project will generate sales that would not otherwise occur in Norman. Developers argue the city is not giving up existing revenue as much as they are dedicating a portion of the new sales tax created within the district to pay for the development that made it possible. If the district succeeds, the project helps finance itself.

This argument depends on a key assumption: that the sales generated by the project would not happen without the project. If visitors come from out of town and spend money in Norman that they otherwise would have spent in another city, Norman may come out ahead. But if they just choose a restaurant or hotel inside the entertainment district instead of one elsewhere in Norman, the city has not gained new economic activity. Instead, local spending was redirected into a district where the project, rather than the city budget, gets to claim some of the tax receipts.

Why Tax Increment Financing Matters Beyond Norman

The Rock Creek fight is local to Norman; tax increment financing is not. The tool has become a common way for local governments to finance economic development. Tax increment financing is authorized in nearly every state, and some states use them extensively. In Wisconsin, there were 1,400 active tax increment districts in 2024. Minnesota had 1,657 in 2024, and Illinois had 1,488 in 2025.

These thousands of tax increment financing plans don’t generate many news stories because they tend to be used for lower-profile projects than Norman’s Rock Creek District. They often support development in underused or “blighted” areas by financing roads, utilities, brownfield cleanup, or other infrastructure needed to make land more developable. Using tax increment financing that way does not usually produce high-profile public conflicts like Norman’s arena district has.

Tax increment financing may be so common because its appeal to cities is obvious. Local governments are often asked to produce economic growth without raising taxes, and tax increment financing offers a way to promise development today using revenue the project is expected to create tomorrow. Structuring investments this way can make public financing feel less costly than other methods might.

But tax increment financing does not create money out of nothing. Future revenue is still public money, and giving one development first claim on those dollars means the money cannot be spent on anything else. If growth would have happened without tax increment financing, or if spending shifts from elsewhere in the city to the new development, then the city may just lose access to future tax revenue it otherwise would have received.

Using tax increment financing for arena or stadium districts is especially noteworthy because stadiums and arenas have a weak record as economic development investments. The economic literature consistently finds that these facilities tend to produce modest and sometimes negative effects on local economies. Norman’s Rock Creek District may prove to outperform the average arena project. Still, the poor track record of stadium-centered economic development investments should be considered. The more uncertain the payoff, the more important the tax dollar tradeoff becomes. 

Despite this, Norman will not be the first place to use tax increment financing this way. Washington D.C. used tax increment financing to fund improvements to Capital One Arena. Louisville and Port St. Lucie, Florida used tax increment financing for soccer stadium developments. These examples suggest that tax increment financing may be becoming a route for local governments to finance sports and entertainment projects while describing the public’s contribution as self-financing.

Research on tax increment financing gives reason for caution about that claim. In a 1999 study on northeastern Illinois municipalities, researchers found evidence that tax increment financing may stimulate growth inside of the designated district while slowing growth elsewhere in the same city. More recent reviews find that though tax increment financing remains popular, it often falls short of their promise to reinvigorate struggling areas, especially when cities do not rigorously examine whether development would have happened without granting tax increment financing.

That is why the Rock Creek Entertainment District fight has relevance far removed from Oklahoma college sports. It makes plain the question which every tax increment financing plan should have to answer, whether used to finance a sporting arena or a more mundane development. Is the project creating enough new public value to justify the future tax revenue it receives? If the answer is yes, the claim on tomorrow’s taxes may be worth granting. If property tax growth would have happened anyway, or if spending is merely shifted around town, tax increment financing may not actually pay for itself.

What is regulatory capture?

In past blogs, I’ve written about lots of different market failures. If you want to learn more about public goods, the tragedy of the commons, information asymmetry, natural monopolies, or externalities, check out the relevant links. 

Today I wanted to talk about another problem that occurs in markets, but one that is not technically a market failure (some people use the term “government failure”): regulatory capture. 

What is “regulatory capture?”

In classical microeconomic theory, firms are profit-maximizing entities. In competitive markets where prices are determined by market forces, it follows that for a firm to increase their profits they need to lower their costs.* This system is designed to drive innovation, pushing firms to improve their processes and products in order to get a competitive advantage in the marketplace. That’s the goal of the competitive market: firms that innovate more successfully get a competitive advantage and enjoy higher profits.

However, perfect competition is a theoretical ideal. In the real world, there is all sorts of noise that muddies the water. These are the market failures that we’ve spent so much time going over, and the end result is that markets often need some kind of intervention from the public sector in order to operate more efficiently. Regulatory capture occurs when the presence of regulations gives firms an incentive to use political capital to improve their standing in a market instead of relying on a competitive advantage. 

One example would be a company lobbying policymakers for more strict licensing requirements in order to keep new competitors out of the market. If regulators adopt those rules primarily because of pressure from existing firms rather than because the rules benefit the public, this would be an example of regulatory capture. They haven’t invested in improving their service, but by pushing for more stringent regulations they can artificially inflate their presence in the market. 

Another example would be when public officials rely on expertise from industry representatives to help form regulations. This can happen anywhere, but it is especially prevalent in highly technical industries such as information technology and energy. 

The challenge with these industries is that policymakers don’t have the expertise required to make sensible regulations. The industries are just too complicated. So, they must rely on advice from members of the industry who have a vested interest in making sure the regulations suit their needs rather than overall social wellbeing. 

What can policymakers do about regulatory capture?

The short answer is deregulation. Of course, there are many markets where the threat of regulatory capture is not as important as solving a market failure, so the decision whether to regulate or not is entirely dependent on the specific circumstances of a particular market. Policymakers could try and implement a regulatory budget to try and balance these competing interests. 

In cases where regulators must rely on firms for specialized information, the ideal would be to have more subject matter experts working in the public sector. While governments may never have the same level of expertise as the industries they regulate, building independent expertise and seeking input from a broad range of stakeholders can make regulatory capture less likely and help ensure that regulations are designed to benefit the public rather than a handful of firms.

* Firms could also charge more for a higher-quality product, but it generally is easier to think of goods in markets as being homogenous and that producers can generate more or less surplus based on what kind of competitive advantage they have during production.