What is cost-effectiveness analysis?

When I was conducting my first true policy analysis in graduate school, I set out my policy analysis around three major criteria: effectiveness, efficiency, and political feasibility. I had seen from a recent report that Ohio’s worst indicator compared to other states was food insecurity, so I wanted to see what policy options could potentially turn Ohio’s bad problem with food insecurity around.

As I conducted this analysis, I found the most useful contribution I could make was around efficiency. Even more importantly, I defined efficiency in a specific way: how many dollars would it take to make someone no longer food insecure given a specific intervention? In the end, I found job creation programs pulled someone out of food insecurity for about $700,000 per person, cash transfers pulled people out at a cost of about $70,000 per person, and nutrition education pulled people out of food insecurity at a cost of about $700 per person.

This was my first time doing cost-effectiveness analysis.

Doing cost-effectiveness analysis is not rocket science, but before you dive into it, it is a good idea to get a good understanding of what you are doing. This starts with understanding what cost-effectiveness analysis is.

What is cost-effectiveness analysis?

At its heart, cost-effectiveness analysis is the question of how much bang for your buck you get for a given project. I have written before about how benefit-cost analysis contrasts with cost-effectiveness analysis but if you understand what benefit-cost analysis is, it is basically a type of cost-effectiveness analysis, but the variable of interest you are trying to maximize is how many dollars of social benefit you get compared to social costs.

The simplest equation you can use to calculate cost effectiveness is dollars divided by a given outcome. The cost of a program divided by the number of people it pulls out of poverty is a cost-effectiveness metric. In the example above, you can see how my study focused on dollars divided by people pulled out of food insecurity. You could imagine a range of different denominators that you could choose for a cost-effectiveness analysis.

How is cost-effectiveness analysis different from cost-benefit analysis?

If you want a full treatment of this question, you can refer to the blog post I mentioned above. But at its heart, cost-effectiveness analysis is a broader type of analysis that is answering a narrower question. Cost-effectiveness analysis tells you how many dollars a given approach costs. In a way, it is putting a valuation on an intervention, albeit a narrow one. It tells you how effective an intervention is at bringing about a specific outcome. Cost-benefit analysis, on the other hand, focuses on dollars in, dollars out.

A nice benefit of cost-effectiveness analysis is it gives a simpler scale for both analysts and policymakers. By focusing on one outcome, the impact identification phase of analysis is simplified greatly.

When should policymakers use cost-effectiveness analysis?

Cost-effectiveness analysis is a great tool when policymakers have a specific social goal they are trying to bring about when a policy is implemented. For instance, if policymakers are looking at different interventions to reduce chronic homelessness, having an idea of how much it costs under each intervention to pull a single person out of chronic homelessness helps policymakers compare alternative approaches against each other.

Cost-effectiveness analysis is also a powerful tool for helping policymakers deal with a neverending problem in public policy: budget constraints. Often, a policymaker who is working for an agency will be given a budget and a mandate and will have to figure out how to carry out that mandate with that budget. In this case, cost-effectiveness analysis is a powerful tool for figuring out how to help as many people as possible with a fixed budget.

Examples of cost-effectiveness analysis

We have already talked about a couple examples of cost-effectiveness analysis, but cost-effectiveness analysis has been used in real policy contexts to bring real improvements to lives.

The United Kingdom’s National Institute for Health and Care Excellence uses Quality Adjusted Life Years to recommend treatment options. Since the United Kingdom’s health care system is entirely run by the government, this helps the state get the most bang for its buck for interventions, maximizing the number of healthy years provided given the cost of health care in the country. The State of Oregon takes a similar approach with its Medicaid program, prioritizing cost-effective treatments that demonstrably improve health outcomes. The Centers for Disease Control and Prevention uses cost-effectiveness analysis around vaccine guidance, estimating the relative benefit of vaccines compared to alternate uses of resources.

Limitations of cost-effectiveness analysis

Cost-effectiveness analysis is not a panacea, of course. A huge problem with cost-effectiveness analysis is the problem of tunnel vision. For instance, while health impacts of Medicaid coverage have been mixed, the evidence around how Medicaid helps people with financial security is much stronger. After all, Medicaid is an insurance program. Focusing on the most cost-effective treatments may not be the best deployment of Medicaid resources. It may make more sense to go after the most costly programs, using the market power of the state to hold prices down and make these treatments more affordable for people.

Cost-effectiveness analysis can also lead policymakers into a McNamara fallacy of thinking that because they have outcomes quantified that they know how a policy will turn out. Proper sensitivity analysis has to be applied to cost-effectiveness analysis to make it a valuable exercise, and analysts must also disclose assumptions as much as possible so policymakers have an idea of what considerations are left off the table during an analysis like this.

Bottom line

Policymakers will not get an answer to every question about a given policy using cost-effectiveness analysis. But deployed correctly, cost-effectiveness analysis can tell a policymaker a crucial insight: how well does this policy fulfill a core goal of the intervention compared to other comparable policies? If a policymaker sets out to reduce homelessness and an alternate policy can do it at half the price per person, that alternate policy deserves consideration. And a policymaker deserves to have that analysis at her fingertips.

What happens if we suspend the gas tax?

If you’ve had to fill a car with gas recently or have been following the news at all over the past two months, you’ve certainly noticed how high the cost of gasoline has risen recently. The war in Iran has had a dramatic impact on the global supply of oil, and policymakers at the federal and state level are responding to this challenge with a sweeping proposal: suspend gas taxes as a way to provide consumers with short-term relief.

Tax burden vs. tax amount

One factor to consider is how much suspending the gas tax would actually lower costs for consumers. A common assumption is that if the federal  government suspends the 18.4 cent gas tax, consumers will automatically see prices fall by 18.4 cents per gallon. In reality, that isn’t how taxes work.

Economists distinguish between the legal burden of a tax and the economic burden of a tax. Just because one party has to actually pay the tax to the government does not mean that they are entirely responsible for the total cost of the tax. If a producer has to be the one to write the check, they can pass on a portion of tax amount to consumers in the form of higher prices. In general, they can't pass on the entire amount of the tax and the market will reach a new equilibrium price with both sides paying some percentage. In practice, that means that and 18-cent lower gas tax will lead to less than an 18-cent decrease in gas prices at the pump

Loss of gas tax revenue

Another issue with suspension of gas taxes is the loss of public revenue. Gas taxes are not just arbitrary charges added onto fuel purchases. In many cases, they are specifically designed as a user fee to fund transportation infrastructure such as highways, bridges, and road maintenance.

At the federal level, gas tax revenues flow primarily into the Highway Trust Fund. State governments often use their own gas taxes to support local transportation projects as well. Suspending these taxes, even temporarily, can create major budget shortfalls.

Those shortfalls do not simply disappear. Governments generally have three choices when revenue declines: reduce spending, raise taxes elsewhere, or borrow money. None of those options are free. Delaying road maintenance today can create much larger repair costs in the future, while shifting the tax burden elsewhere may simply redistribute the pain rather than eliminate it.

There is also a timing issue here. Infrastructure projects are often planned years in advance. Sudden revenue disruptions can make long-term transportation planning significantly more difficult for state and local governments.

Gas taxes curb externalities of gas consumption

Gasoline consumption also creates several negative externalities that gas taxes help reduce. An externality occurs when a market transaction imposes costs on people who are not directly involved in that transaction. In the case of gasoline, those costs include pollution, greenhouse gas emissions, traffic congestion, and road wear.

The gas tax helps correct this market failure by taking the external costs of consumption and adding them into the internal market price. Even though the war in Iran is an exogenous shock that has spiked the price, that shock only impacts the internal price. In order to avoid a market failure, policymakers still need to account for these externalities with a tax if they want to promote an efficient market in transportation fuels.

Why this might be a good policy

One thing that makes gas prices a strange policy tool is that individual elasticities for gasoline can be very different from person to person. I happen to live in a neighborhood where I have pretty easy walking access to a lot of my essentials. Add on top of that the fact that I work remotely and I only really ever have to get in a car if I want to go somewhere for fun. As gas prices have gone up and the weather has gotten nicer, I’ve been able to fairly easily substitute away from gas consumption to other forms of transportation.

Compare that to someone who needs to drive long distances for their work. Those people might have a nearly perfect inelastic demand for gas. These people are disproportionately impacted by higher gas prices, and they might need some targeted relief from the public sector to get through this difficult time. 

At the end of the day, suspending the gas tax is a tool that trades off future wellbeing for current wellbeing. The revenues created by the gas tax are an important funding stream for road infrastructure both the federal and state governments. Perhaps there could be some policy like a cash transfer that targets people who have to drive for work, funded via some broader base tax. This type of policy could still offer short-term support,  without distorting a specific market in the same way, but whether that additional complexity is worth it is for a policymaker to decide.

Original analysis: Scioto Analysis releases new study of inequality in Ohio

This morning, Scioto Analysis published a report on the current state of inequality in Ohio. This study serves as an update to a previous report on inequality released by Scioto Analysis in 2022.

The analysis finds that Ohio is currently less unequal than the United States as a whole. Ohio’s Gini Coefficient of 46.6 is two points lower than the national rate of 48.6. Geographically, this disparity is most concentrated in Ohio’s major urban centers and rural Appalachian counties. Inequality in Ohio is especially disparate for income distribution, homeownership rates, and housing cost burdens across race, age, and income level.

To demonstrate how policymakers can address inequality in Ohio, analysts evaluated the effects of several different policy options on inequality in Ohio.

• A negative income tax is the most effective intervention method that was analyzed. A -5% negative income tax would reduce the Gini Coefficient from 43.3 to 42.8, a -16% rate would reduce it to 42.1, and a -50% negative income tax rate would reduce the Gini Coefficient to 39.9, an impact comparable to the entire federal income tax system.

• Existing income taxes are effective at reducing inequality in Ohio. Current federal income taxes reduce the Gini Coefficient in Ohio from 46.6 to 43.7, and 2023 state income taxes reduce the Gini Coefficient even further to 43.3.

• The transition to a flat income tax structure is projected to worsen inequality, increasing the Gini Coefficient to 43.6, while reverting back to 2003 Ohio income tax rates would lower the Gini Coefficient to 43.0.

• Replacing property taxes with a progressive income tax would reduce the Gini Coefficient by 1 point, while replacing property taxes with sales taxes would have a negligible impact on inequality in Ohio.

• Adding a new higher income bracket to Ohio’s state income tax structure would reduce inequality in Ohio, decreasing the Gini Coefficient to 43.1

While inequality has been on the rise in Ohio since 2014, policymakers have several tested policy options to help reduce inequality across the state. The full report can be accessed here.

Market Failure: Rent Seeking

Rent seeking behavior is not in and of itself a market failure, but it is closely related. When a free market fails to allocate resources in a socially efficient manner, it is usually possible for the public sector to intervene with tools like taxes, license requirements, etc. and manipulate the market to get closer to the social optimum. 

However, these manipulations aren’t free to perform. Taxes can create drag on the economy, over complicated license requirements can create costly sludge that requires bureaucratic red tape. Because the regulatory framework is exceedingly complicated,  there are opportunities for some people to take advantage of these systems. 

What is rent seeking?

The term “rent seeking” was coined in 1974 by economist Anne Krueger, and it refers to the process of securing economic benefits without creating any additional economic value. In normal free market conditions, people only receive economic benefits when they produce something of value and trade it in some market. When a farmer grows crops and sells them to me at a farmers market for a profit, we are both better off than we were before.  I now have delicious produce that I can eat, and the farmer was able to sell their produce for more than it cost them to grow. 

When someone is rent seeking, their goal is to increase their own income not by creating new value, but by influencing the rules of the market in their favor. Instead of competing by making a better product or lowering prices, they may lobby for regulations that make it harder for competitors to enter the market, secure subsidies that transfer public money toward themselves, or obtain special legal protections that insulate them from competition.

A classic example is occupational licensing that goes far beyond what is necessary for public safety. Some professional licenses clearly provide value by ensuring minimum standards for doctors, pilots, or electricians. But in some cases, existing members of a profession may push for excessive training requirements or restrictive licensing rules primarily to reduce competition and keep wages artificially high. The people already inside the industry benefit, while consumers face higher prices and fewer choices.

Another example is tariffs and trade protections. A domestic industry may lobby the government to impose tariffs on foreign competitors, not because domestic firms have become more productive, but because the policy shields them from competition. While this benefits the protected firms, consumers often pay higher prices and resources remain tied up in less efficient industries.

Rent seeking can also be used to describe illegal activities. When someone breaks into a house and robs it, they are seizing some economic benefit for themselves without creating any value for society. In fact, this is a case where the rent seeking behavior leads to less overall economic wellbeing, since it forces people to spend on goods like home security systems that they otherwise would not.

Why rent seeking hurts the economy

Rent seeking is economically costly because resources are spent fighting over existing wealth rather than creating new wealth. Time, money, and labor that could have gone toward innovation, production, or investment instead get redirected into lobbying efforts, legal maneuvering, or regulatory gamesmanship.

This creates two layers of inefficiency. First, the policies themselves may distort the market by protecting inefficient firms or limiting competition. Second, society loses the productive resources that were spent securing those advantages in the first place.

For example, imagine several companies competing for a government subsidy worth millions of dollars. Instead of investing those resources into better technology or lower prices, they may spend heavily on lobbying, advertising campaigns, consultants, and legal teams to secure political influence. From society’s perspective, very little new value was created even though substantial resources were consumed.

What policymakers can do about rent seeking

One common approach to limiting rent seeking is simplifying regulations wherever possible. Complex systems with vague rules and numerous exemptions create more opportunities for firms to manipulate the process. Clearer and more transparent rules reduce the ability of special interests to secure narrow advantages.

Transparency measures are another important tool. Public disclosure requirements for lobbying activities, campaign financing, and government decision making can make it easier for voters and watchdog groups to identify situations where private interests may be shaping public policy for their own benefit.

Rent seeking can never be eliminated entirely because people will always have incentives to shape the rules of the economy in their favor. But well-designed regulatory structures can reduce the extent to which economic success depends on political influence instead of productive activity. When markets reward innovation, efficiency, and value creation rather than access and favoritism, the economy tends to produce stronger long-term outcomes for society as a whole.

Market failure: information asymmetry

In this post, I am going to explain the basics behind another common market failure, information asymmetry. If you would like a more broad overview of what a market failure is, I have a previous blog post on that topic. If you want more deep dives on market failures, check out my posts on the tragedy of the commons, externalities and natural monopolies. Additionally, I won’t be going into any of the math behind this concept. Instead, this will be a more intuitive discussion of how information asymmetries work and what their impact on markets is. 

What is information asymmetry?

Information asymmetry occurs when one person in a market transaction has some hidden information that impacts the transaction. In an ideal market, all the information would be public so that buyers and sellers can accurately judge the value of the goods they are trading. Information asymmetries distort markets by undermining this condition.

A classic example of information asymmetry is in the used car market, where sellers often have significantly more information about the condition of a car than buyers do. If a car has hidden mechanical issues, the seller is unlikely to volunteer that information, while the buyer has limited ability to detect those problems before purchasing. Because of this uncertainty, buyers may be unwilling to pay a high price, even for cars that are actually in good condition. This specific example was made famous by the economist George Akerlof in his paper “The Market for Lemons”.

Why is information asymmetry a market failure?

Information asymmetry leads to market failure because it prevents markets from reaching efficient outcomes. In a well-functioning market, prices reflect the true value of goods based on accurate information. When one side of a transaction has better information than the other, prices instead reflect uncertainty and risk.

This often results in two related problems: adverse selection and moral hazard. Adverse selection occurs before a transaction takes place, when hidden information causes one side of the market to disproportionately attract lower-quality participants. In the used car example, buyers anticipating hidden defects lower the price they are willing to pay, which pushes out sellers of high-quality cars and leaves behind mostly lower-quality options.

Moral hazard occurs after a transaction takes place, when one party changes their behavior because they are not fully exposed to the consequences of their actions. For example, an individual might begin to drive more recklessly knowing they have a comprehensive car insurance plan. The insurance company doesn’t know that this person is going to change their behavior after the contract is signed (that’s the asymmetry) so they can’t properly account for that risk in the market transaction.

How policymakers respond to information asymmetry

Because information asymmetry can undermine markets, both private institutions and public policy often step in to reduce its effects. One common approach is to increase transparency by requiring disclosure of relevant information. For example, sellers may be required to report known defects, and companies may need to provide standardized financial statements so investors can make informed decisions.

Another approach is signaling, where the better-informed party takes steps to demonstrate quality. Warranties, certifications, and professional licenses all serve as signals that help build trust between buyers and sellers. For instance, a warranty on a used car gives buyers confidence that the seller stands behind the product. 

Another example of signaling are reputation mechanisms like Uber’s rating system. Both drivers and passengers have their performance rated so both parties can get a better idea of how the transaction is going to go. These systems have been shown to be effective in reducing the impacts of information asymmetry.

Regulators can also play a role in setting minimum standards and protecting consumers. Laws around fraud, product safety, and truth in advertising all aim to reduce the most harmful effects of asymmetric information.

While information asymmetry cannot be eliminated entirely, these tools help markets function more effectively by narrowing the information gap. When buyers and sellers have better access to reliable information, they can make more informed decisions, leading to outcomes that are closer to what we would expect in an ideal market.

Will a new bill help bring Ohio’s public service delivery into the 21st century?

Last month, state Rep. David Thomas introduced Ohio House Bill 834, a bill designed to improve delivery of government services.

Ohio’s state government provides a range of services to its residents.

When people lose their jobs, the state provides unemployment insurance.  Ohio issues licenses to professionals, benefits to low-income families, permits for environmental and health clearance, and business registration.

How well the state provides these services can have an impact on the economy.

If you lose your job, not being able to get access to unemployment benefits can harm your ability to bounce back and get a new job or support your family in the meantime.

Occupational licensing is a notorious barrier to economic activity, making it more difficult for younger people and immigrants to break into an industry, especially if the licensing system is hard to navigate.

Cumbersome bureaucratic systems can be barriers to businesses trying to start new ventures and low-income households trying to get assistance to put food on the table.

Thomas’s plan is to build a structure run by the Ohio Department of Administrative Services to improve agency service delivery.

The Director of Administrative Services will appoint an executive to serve as a lead in improving service delivery, determine which services are “high-impact,” and prepare an annual report to the governor and legislative leaders on service delivery in Ohio.

This newly appointed lead would be in charge of developing service quality standards and collecting quantitative and qualitative data on service delivery.

Agencies would then each designate their own service delivery officials and develop implementation plans to meet the standards set by the service delivery lead.

On paper, this looks like a plan that could yield benefits for the state of Ohio.

The federal government passed a similar bill that was signed into law early last year, but it is still a bit too early to tell if this will end up yielding any service delivery benefits.

Some states have seen success with similar programs.

Utah’s “Citizen Feedback Program” was created in 2020. Recommendations that have come out of this program have shown that moving people from in-person, paper, and phone services to digital services can save the state tens of millions of dollars in administrative costs.

The New York Experience program launched by the State of New York reports its program has led to licensing wait times falling by 83%, its Division of Human Rights backlog declining by 44%, and its Higher Education Services Corporation eliminating its backlog of 8,000 unprocessed grants and scholarships for students in the state.

The Pennsylvania Governor’s Office reports its Commonwealth Office of Digital Experience has saved taxpayers $10 million by turning to digital services rather than vendors for service delivery.

Government efficiency will not solve all problems in the state. But promoting efficiency in service delivery is low-hanging fruit to help people in need, businesses, students, and workers get what they need from the state of Ohio without more friction and pain than is necessary.

A program like this has the potential for significant upside for the state of Ohio.

This commentary first appeared in the Ohio Capital Journal.

How did Ohio become a top 10 state for the price of gas?

Over the past several months, Americans across the country have been feeling the strain of rising gas prices. Living in Columbus, Ohio, I felt it firsthand last night when it cost me over $50 just to fill up my small sedan. With local prices sitting around $4.99 per gallon, this month is on track to be the second most expensive month for gas in Ohio history. The only other times we've seen prices get anywhere near this high were during the summer of 2022, where gas prices were priced similarly primarily due to Russia’s full scale invasion of Ukraine, and back during the 2008 recession. This raises the question– why are gas prices in Ohio starting to reach record high levels?

Why are gas prices rising?

Every year, gas prices tend to rise during the spring and early summer months. This is partially due to oil refineries switching from their winter-blend fuel to summer-blend fuel. Due to warmer weather, cars don’t need the fuel to evaporate as easily to start up. Instead, summer-blend fuel focuses on keeping emissions and smog low to meet various state and regional requirements. On top of that the demand for gas is higher during spring and early summer months, which can sometimes increase gas prices by 10 to 15 percent.

This spring, gas prices have been rising at unusually high rates. Over the past several weeks, the United States and Iran have been conducting naval blockades of the Strait of Hormuz related to their ongoing conflict. A quarter of the global seaborne oil supply passes through the strait, so blockades result in oil prices skyrocketing. Although the United States doesn’t import much oil from the Middle East, domestic prices for crude oil and gasoline are still reliant on global price trends since crude oil is traded at such high volumes in the global market. 

The conflict between the United States and Iran has now been happening for more than two months. Peace talks are underway, but it’s unclear whether or not the Strait of Hormuz opening back up this summer will significantly ease gas prices throughout the rest of the year.

How expensive are gas prices now?

As of May 3, 2026, the national average price for gas is about $4.45 per gallon. Average gas prices by state can be found in the table below.

Gas Prices by State
State	Gas Price
California	$6.10
Washington	$5.67
Hawaii	$5.63
Oregon	$5.25
Nevada	$5.17
Alaska	$5.04
Illinois	$4.93
Ohio	$4.89
Michigan	$4.87
Indiana	$4.83
Arizona	$4.74
Connecticut	$4.52
Pennsylvania	$4.52
District of Columbia	$4.48
Idaho	$4.46
New York	$4.45
Colorado	$4.44
New Jersey	$4.42
Vermont	$4.42
Maine	$4.40
Utah	$4.39
Rhode Island	$4.38
Wisconsin	$4.37
Florida	$4.34
New Hampshire	$4.34
Massachusetts	$4.34
Montana	$4.32
Wyoming	$4.30
West Virginia	$4.30
Maryland	$4.27
Kentucky	$4.22
Delaware	$4.21
Virginia	$4.17
New Mexico	$4.16
North Carolina	$4.08
South Dakota	$4.06
Minnesota	$4.05
South Carolina	$4.00
Tennessee	$3.99
North Dakota	$3.99
Missouri	$3.97
Kansas	$3.96
Alabama	$3.96
Nebraska	$3.96
Iowa	$3.95
Texas	$3.92
Louisiana	$3.90
Oklahoma	$3.89
Mississippi	$3.88
Arkansas	$3.88
Georgia	$3.85

Like always, gas prices are the highest on the West Coast, with California, Washington, Hawaii, Oregon, Nevada, and Alaska all above $5.00 per gallon. California tops this trend at a whopping $6.10 per gallon. Gas prices are often higher on the West Coast because states are farther away from suppliers. Additionally, California has especially strict regulations around the blend of gasoline permitted to be sold.

On the other hand, gas prices are currently lowest in the Deep South, with Georgia, Mississippi, and Arkansas having the three lowest prices per gallon. Southern states’ proximity to refineries along the Gulf Coast keep gas prices low alongside relatively lax state regulations around gasoline blend.

Normally, states in the Midwest face relatively low gas prices. However, following the top six most expensive states for gas which are all located in the West, Midwestern states fill the next four spots. Illinois, Ohio, Michigan, and Indiana all boast average gas prices upwards of $4.80 per gallon. On top of pre-existing global supply concerns for gasoline, Indiana and Missouri refineries are facing unexpected operational disruptions, which is driving midwest gas prices even higher.

How have gas prices changed?

Since January 20, the national average for gas prices has increased from $2.83 to $4.45 per gallon, a 57% increase. In the chart below, gas prices from January 20 until now are shown by state.

In January, 41 states had average gas prices below $2 per gallon. Now, just 13 states have average gas prices below $4 per gallon. Ohio has experienced the most dramatic increase in gas prices, a 79% increase from $2.74 per gallon in January to $4.89 per gallon now, while states like Hawaii which had already high gas prices are experiencing the lowest percent changes.

Across most states, gas prices were increasing steadily throughout February. In March, most states saw a huge jump, with gas prices leveling out the past couple weeks.

Ultimately, regional dynamics are the cause of Ohio’s gas price spike. This will likely lead to more pain for households, especially low-income and car-dependent households. This is an example of state economies being impacted by federal policy. Until the Strait of Hormuz is stabilized, states like Ohio will continue to suffer from high gas prices.

Survey: Economists agree that the costs of AI data centers exceed the benefits but don’t recommend a ban on construction

In a survey released this morning by Scioto Analysis, 10 of 14 economists agreed that tax incentives for data centers are not an efficient use of public funds to stimulate job growth in Ohio.

Petitioners in Ohio have started collecting signatures to get a proposed constitutional amendment to ban data centers on the November ballot. Ohio already has about 200 data centers, the fifth largest in the country. Proponents of data centers argue that they create jobs and stimulate the economy, while opponents argue they increase energy prices and use up otherwise valuable farmland.

Most respondents disagreed that tax incentives for data centers are an efficient use of funds, with 3 economists uncertain and 1 economist agreeing. Albert Summell of Youngstown State University explained “I can’t think of a worse use of public funds than to incentivize data centers. They are associated with very few permanent jobs and high external costs”. Other economists who were more uncertain expressed that whether or not tax incentives for data centers are an efficient use of funds depends on what economic activity occurs after construction commences.

8 of 14 economists disagreed that the economic benefits of new data centers in Ohio exceed the environmental and energy market externality costs associated with their construction. According to Charles Imboden of Bowling Green State University, “[Data centers] create very few jobs and destroy environmental conditions, for example by changing water temperatures [and] disrupting fish stocks”. Of the remaining economists, 2 agreed and 4 were uncertain. Among those who agreed, economists expressed that the environmental costs would be small, and the potential tax revenue could exceed such costs.

7 of 14 economists agreed that the economic costs of a statewide ban on new data centers in Ohio would outweigh the economic benefits. Michael Jones of the University of Cincinnati expressed, “It should be up to the market to pick winners and losers; and Ohio should not be targeting a particular industry. If there are concerns about energy use or land use, then data centers should internalize and pay the real costs of their deployment.” Of the remaining economists, 5 were uncertain and 2 disagreed. The economists who were uncertain recommended that data centers should be taxed according to their external costs or forced to cover the increased costs of electricity.

The Ohio Economic Experts Panel is a panel of over 30 Ohio Economists from over 30 Ohio higher educational institutions conducted by Scioto Analysis. The goal of the Ohio Economic Experts Panel is to promote better policy outcomes by providing policymakers, policy influencers, and the public with the informed opinions of Ohio’s leading economists. Individual responses to all surveys can be found here.

The coming Medicaid coverage cliff

In July 2025, President Trump signed the One Big Beautiful Bill Act into law. The legislation is a large budget reconciliation bill that mainly focuses on tax cuts and reduced social spending. One social program facing a substantial reduction in spending due to the bill is Medicaid, the largest single insurer in the United States.

There is a laundry list of changes coming to Medicaid in the next few years, but the ones affecting beneficiaries the most are new work requirements for Medicaid expansion coverage and more frequent eligibility checks.

New work requirements for Medicaid

By 2027, states must mandate that recipients engage in at least 80 hours per month of paid employment, job training, education, or community service to remain eligible for Medicaid coverage. Exceptions to this rule include parents with children ages 13 and younger and those who are medically frail. 

Currently, states are generally prohibited from making Medicaid eligibility contingent on work. During the first Trump presidency, 13 states received approval to implement work requirements through Section 1115 waivers, which allow states to experiment with Medicaid models that differ from federal statutes. All 13 of these states either had these waivers rescinded during the Biden presidency or withdrew them voluntarily. As of now, Georgia is the only state that maintains work requirements, also through a Section 1115 waiver.

Work requirements for Medicaid coverage are likely to result in fewer covered individuals due to procedural barriers such as submitting documentation to prove they have met the hourly quotas. This may disproportionately impact nontraditional workers such as those who rely on gig work. Recipients who meet an exception, such as those who are chronically ill, may also find it more challenging to navigate complex online portals or submit specific medical documentation.

More frequent eligibility checks for Medicaid

The One Big Beautiful Bill Act also requires states to check for eligibility for Medicaid more frequently. By 2028, states must verify whether Medicaid enrollees are still eligible for services at least every six months, with flexibility provided to states to check more often if they choose. Currently, states are only required to confirm Medicaid eligibility annually.

More frequent eligibility checks are expected to reduce Medicaid coverage due to procedural barriers such as address changes, missing notifications, and increased opportunities for administrative errors. It is also likely that more recipients will become temporarily disenrolled and then reenrolled, which only serves to increase the administrative burden for state and local governments.

Medicaid enrollment reductions due to the One Big Beautiful Bill Act

In total, between 4.9 and 10.1 million people will lose Medicaid coverage in 2028 due to work requirements and more frequent eligibility checks. Roughly 2 to 3.1 million of these recipients will lose coverage due to their eligibility being redetermined more frequently, and roughly 3 to 7 million will lose coverage specifically due to work requirements.

Because Medicaid is administered primarily at the state level, the impacts of these proposed changes will ripple through the states, with the individual effects varying widely by region. In the following table, we show the number of disenrollments expected from each state in 2028 based on analysis from the Robert Wood Johnson Foundation, ordered from highest to lowest percent change.

Medicaid Enrollment Reductions
State	Projected Coverage Loss	Percent Change
Massachusetts	−161,000	−54%
Connecticut	−155,000	−51%
Maryland	−172,000	−51%
Vermont	−20,000	−50%
Minnesota	−91,000	−49%
New York	−955,000	−48%
Virginia	−269,000	−47%
Missouri	−169,000	−47%
California	−1,995,000	−46%
Delaware	−28,000	−45%
New Jersey	−242,000	−44%
Arizona	−197,000	−44%
New Hampshire	−23,000	−44%
Illinois	−324,000	−44%
Rhode Island	−34,000	−43%
Colorado	−165,000	−43%
Hawaii	−57,000	−43%
Washington	−260,000	−43%
West Virginia	−61,000	−42%
Wisconsin	−70,000	−42%
Maine	−28,000	−41%
Kentucky	−166,000	−41%
Louisiana	−205,000	−41%
District of Columbia	−46,000	−41%
Ohio	−285,000	−40%
Iowa	−72,000	−40%
Michigan	−287,000	−40%
Utah	−33,000	−40%
Idaho	−30,000	−38%
Nevada	−113,000	−38%
Pennsylvania	−276,000	−37%
Oklahoma	−87,000	−37%
Montana	−28,000	−36%
Arkansas	−78,000	−36%
North Carolina	−249,000	−36%
Alaska	−23,000	−36%
New Mexico	−87,000	−36%
Nebraska	−25,000	−35%
Indiana	−201,000	−35%
Oregon	−185,000	−34%
South Dakota	−11,000	−34%
North Dakota	−8,000	−30%

Many of the states with the highest Medicaid enrollment rates are the states projected to be most affected by changes to Medicaid from the One Big Beautiful Bill Act, such as Massachusetts and Connecticut. Generally, states are expected to lose between 30% to 54% of their expansion populations due to eligibility changes.

How the One Big Beautiful Bill Act will change uninsured rates

While Medicaid is frequently considered a program intended solely to improve health outcomes, it effectively serves as a mechanism for fiscal relief for millions of American households. By ensuring access to low-cost health insurance, Medicaid frees up household budgets, providing recipients with more disposable income for necessities like housing and food, while reducing the likelihood of falling into medical debt. When people lose Medicaid coverage, especially lower-income populations, they face a tradeoff: pay out-of-pocket premiums for a private health insurance plan or forego coverage to save money for other immediate expenses.

To understand how changes to Medicaid from the One Big Beautiful Bill Act will affect uninsured populations, we compare current uninsured numbers to the potential increases expected from Medicaid recipients losing eligibility in 2028.

Impact on Uninsured Populations
State	Projected Coverage Loss	Current Uninsured	Projected Total Uninsured	Percent Change
New York	−955,000	973,715	1,928,715	98%
California	−1,995,000	2,314,464	4,309,464	86%
Oregon	−185,000	219,386	404,386	84%
Massachusetts	−161,000	198,589	359,589	81%
Connecticut	−155,000	211,726	366,726	73%
West Virginia	−61,000	100,543	161,543	61%
Louisiana	−205,000	348,045	553,045	59%
Michigan	−287,000	507,760	794,760	57%
Kentucky	−166,000	308,763	474,763	54%
Washington	−260,000	511,691	771,691	51%
Virginia	−269,000	595,595	864,595	45%
Maryland	−172,000	390,741	562,741	44%
Iowa	−72,000	174,113	246,113	41%
New Mexico	−87,000	211,289	298,289	41%
Indiana	−201,000	512,807	713,807	39%
Delaware	−28,000	71,608	99,608	39%
Illinois	−324,000	860,898	1,184,898	38%
Pennsylvania	−276,000	752,566	1,028,566	37%
Maine	−28,000	76,864	104,864	36%
Ohio	−285,000	782,626	1,067,626	36%
Missouri	−169,000	474,886	643,886	36%
Colorado	−165,000	463,722	628,722	36%
New Jersey	−242,000	727,278	969,278	33%
Minnesota	−91,000	290,828	381,828	31%
Nevada	−113,000	366,606	479,606	31%
Alaska	−23,000	77,532	100,532	30%
Montana	−28,000	98,102	126,102	29%
Arkansas	−78,000	284,915	362,915	27%
North Carolina	−249,000	927,893	1,176,893	27%
Arizona	−197,000	767,380	964,380	26%
Wisconsin	−70,000	310,536	380,536	23%
Oklahoma	−87,000	461,884	548,884	19%
Nebraska	−25,000	139,831	164,831	18%
Idaho	−30,000	181,552	211,552	17%
South Dakota	−11,000	73,403	84,403	15%
Utah	−33,000	288,681	321,681	11%

We project some of the most populated states to see the highest percent increases in the number of uninsured residents. We project New York, for instance, to see its uninsured population surge by over 98%, effectively doubling the number of uninsured residents. Similarly, California and Oregon face increases of 86% and 84% respectively, penalizing states with high populations and high Medicaid enrollment.

If those who lose Medicaid coverage remain uninsured, health systems in low-income communities which rely on Medicaid funds may become strained, worsening accessibility to medical facilities for low-income communities even more.

The Long-Term Outlook

The changes coming to Medicaid in the One Big Beautiful Bill Act will likely lead to millions of people losing coverage across the country. This change represents a shift in the priorities of Medicaid spending from promoting health insurance coverage for low-income households to reducing state and federal spending on Medicaid line items. While these changes may save taxpayers in the short run, they risk straining the administrative capacities of state and local governments and worsening healthcare options for low-income households across the nation.

Original Analysis: Oklahoma Wage Increase Would Lift 40,000 Oklahomans, including 16,000 Children, out of poverty

A new Scioto Analysis study examining the impact of Oklahoma’s upcoming minimum wage ballot measure estimates that raising the state’s minimum wage to $15 per hour will lift 40,000 residents, including 16,000 children, out of poverty. 

The report, written by Scioto Analysis on behalf of This Land Research and Communications Collaborative analyzes how increasing the minimum wage to $15 impacts poverty and the cost of living.

“Our analysis shows an increase in the minimum wage to $15 an hour will have a significant impact for Oklahoma families and the overall economy,” Rob Moore, Principal of Scioto Analysis and lead author of the report said, “Lifting 40,000 Oklahomans out of poverty, giving pay raises to the parents of more than 200,000 children will help more Oklahoma families keep up with rising costs and will make Oklahoma the most affordable state in the region for minimum wage workers.”

Oklahoma currently ranks as the eighth-poorest state in the nation, with one in seven residents living below the federal poverty line. The study found that rising costs following the COVID-19 pandemic have made Oklahoma increasingly expensive for working families.

In this study, we estimate a $15 minimum wage for the state would result in

• 40,000 fewer people in poverty

• 16,000 fewer children in poverty 

• ALICE “household survival budget” becoming affordable for single childless full time workers

 The research also examined the impact on working Oklahomans’ ability to afford basic living expenses. According to United Way estimates, a single adult in Oklahoma needs $2,315 per month to cover housing, food, transportation, healthcare, technology, and taxes. Under the current minimum wage, workers must work nearly 74 hours per week to afford these necessities. A $15 minimum wage would reduce that requirement to roughly 36 hours per week.

Additionally, the research suggests that a $15 minimum wage would make Oklahoma the most affordable state for minimum-wage earners in the region–improving the state’s competitiveness in attracting and retaining workers.

This study was the fifth in a series of Scioto Analysis studies on the minimum wage in Oklahoma. Past studies were on the minimum wage’s impact on housing affordability, public safety, health, and economic growth.