What is a negative income tax?

Recently, we released a study on inequality in Ohio and some of the policy options that impact it. One topic was the Negative Income Tax, an idea first proposed by Milton Friedman as an alternative to the in-kind transfers we typically associate with the social safety net. 

How does a negative income tax work?

To understand how a negative income tax works, it is helpful to first consider how a regular income tax works. Above a certain threshold, the government collects a percentage of your income. If the tax rate was 10% for income above $10,000, then someone making $20,000 has to pay $1,000 in taxes. Negative income taxes work in reverse. Instead of paying a percentage of your income above a threshold, someone receives a match for the percentage of their income that falls below some threshold.

For example, let's say that below $10,000 there is a negative tax rate of 50%. Someone with no income at all would receive $5,000 from the government, and someone earning $5,000 would receive $2,500. Once a person’s income rises above the threshold, the subsidy disappears and the ordinary tax system takes over.

One of the main goals of a negative income tax is to create a smoother transition between receiving assistance and earning additional income. Many traditional welfare systems phase out benefits abruptly as income rises, which can create situations where earning an extra dollar leaves someone little better off or even worse off overall. This phenomenon is called the benefits cliff, and it is a major policy issue. Because the negative income tax phases out gradually, individuals continue to gain financially from working more and earning higher wages.

Why do economists like negative income taxes?

One of the most clear benefits of the negative income tax is its simplicity. Rather than operating dozens of separate programs with different eligibility rules, benefit formulas, and administrative requirements, a negative income tax consolidates assistance into a single cash transfer system tied directly to income. It would take little additional work from the IRS, and everyone who files their taxes would automatically be enrolled.

Supporters also argue that cash transfers give households more flexibility than in-kind benefits. Instead of policymakers deciding exactly how assistance must be used, recipients can allocate resources according to their own needs. One household may prioritize rent, another childcare or transportation costs. Economists generally believe people managing resources at the household often have better information about their own needs than centralized benefit administrators or legislators do.

Costs of a negative income tax

Like any large transfer program, a negative income tax could be expensive. The total cost depends on how generous the benefits are, where the income threshold is set, and how quickly payments phase out as earnings rise. The good thing is that policymakers could easily control how much this costs since they have historic tax data to look at, but it is likely that this would be a big line item in any public budget.

One option to finance a negative income tax would be higher taxes elsewhere. That could mean raising income taxes, consumption taxes, or corporate taxes depending on how policymakers chose to structure the system. While this would allow the program to exist alongside much of the current safety net, higher taxes also create their own economic costs.

Another option would be replacing existing welfare programs with a negative income tax. This was closer to Milton Friedman’s original vision. Instead of operating many separate assistance programs, the government could consolidate portions of the social safety net into one direct cash transfer system. This could potentially reduce administrative complexity and give recipients more flexibility in how they spend assistance.

However, replacing existing programs also creates tradeoffs. Some households may benefit more from direct cash transfers, while others may rely heavily on targeted programs like housing assistance, Medicaid, or food assistance. A single cash-based system may be simpler, but it may also provide less support for people with unusually high medical expenses, disabilities, or other specialized needs.

Ultimately, a negative income tax is another option policymakers have for reducing inequality. Like most economic policy questions, there is no solution without costs. Policymakers must decide which tradeoffs they are most willing to accept and which goals they want the system to prioritize.

Why is SNAP enrollment falling?

Earlier this year, we wrote about some of the federal changes arriving to SNAP between 2025 and 2027. Prior to this year, states covered half the administrative costs associated with SNAP and none of the benefit costs. With the passing of the One Big Beautiful Bill Act, however, states are now required to pay 75% of administrative costs and a portion of benefit costs. According to the Georgetown Center on Poverty and Inequality, state budgets for SNAP are more than doubling due to changes from the One Big Beautiful Bill Act. 

At the start of this year, my colleague Michael predicted that changes to SNAP benefits would be one of the biggest economic stories of 2026, and we’re now seeing these changes take effect. Between the July 2025 passing of the One Big Beautiful Bill Act and the start of the year, the use of federal food assistance is down in every state and Washington, D.C. Overall, nearly 3.5 million people have lost access to SNAP benefits. 

The states that have been hit the hardest by changes to SNAP are Georgia, Arizona, Florida, California and Texas. All five of these states are among the top fifteen most populous states in the country. This means that proportionally, it makes sense for these states to have lost the most SNAP enrollees. However, at Scioto Analysis, we’re most interested in state and local policymaking. Today, I looked into each of these five states to try to understand the key driving factors in SNAP reduction for each state.

Georgia

Between July 2025 and January 2026, more than 460,000 residents in Georgia have lost access to SNAP. Even after this reduction, roughly one in six Georgia residents (~1.4 million people) receive SNAP benefits each month, slotting Georgia in as the sixth-highest state in the nation for SNAP participation.

In addition, Georgia lawmakers have proposed stricter legislation that would require citizenship verification, annual recertification, and heavier limitations on which items Georgia SNAP recipients can buy at the grocery store. These new restrictions could result in even fewer Georgia residents maintaining access to SNAP benefits due to administrative churn or stigma.

Arizona

Between July 2025 and January 2026, the number of SNAP recipients in Arizona plummeted by about 42%, from nearly about 880,000 to just 510,000. As of April, that number dropped to a meager 235,000 recipients. Across nine months, around nine percent of the total population in Arizona lost access to SNAP.

Since last year, Arizona has been struggling with a massive backlog of SNAP applications, with some families still waiting for updates after initially applying in August. Arizona was a state that moved quickly to overhaul their SNAP application process, meaning that other states may start to experience similar backlogs. The Arizona Department of Economic Security attributes the backlog to a new program that complies with new payment error rate requirements.

The combination of stricter SNAP regulations and rising grocery prices have stretched family budgets across the state. Some food banks in Arizona have reported a 17% increase in traffic compared to this time last year.

Florida

In Florida, about 270,000 have lost access to SNAP benefits between July 2025 and January 2026. SNAP recipients temporarily faced weeks of SNAP benefit suspension due to the government shutdown last fall. Florida residents briefly saw their full benefits reinstated in mid-November before facing Florida’s implementation of new federal SNAP requirements at the start of December. The groups most impacted by the volatile SNAP eligibility in Florida are seniors and veterans.

Florida also faces one of the highest payment error rates in the country, at around 15%. This error payment rate exceeds the new federal requirement to keep payment error rates below 6% to avoid harsh financial penalties. To help reduce payment errors, Florida legislators have proposed funding a new artificial intelligence system designed to reduce payments made in error. The proposal would include $4 million to implement machine learning techniques aimed at identifying root causes of incorrect SNAP eligibility determinations and recommending improvements to solve such problems. 

If implemented correctly, artificial intelligence solutions to incorrect eligibility determinations could save Florida millions of dollars in funding in the long-run. However, there are many risks associated with the increased use of artificial intelligence in benefits programs, such as reinforcing inequities related to race, gender, immigration status, or other demographic categories.

California

From July 2025 to January 2026, 260,000 SNAP recipients lost their benefits in California. One policy change unique to California from the One Big Beautiful Bill Act that may have contributed to this initial drop is a utility-related loophole that the act closed at the start of November. In the past, California gave families a tiny annual energy payment which triggered a special utility deduction that lowered their counted income and boosted their monthly food assistance. Now, households without a senior or a person with a disability can no longer use this workaround, which has shrunk monthly benefits and removed thousands of people from the program due to new paperwork hurdles.

One of the provisions in the One Big Beautiful Bill Act limits SNAP eligibility to U.S. citizens and lawful permanent residents. California has the largest unauthorized immigrant population in the country at about 2.9 million people, accounting for about 20% of the nation’s total unauthorized immigrant population, and the second-largest refugee population in the United States. This means that changes to SNAP eligibility for immigrant populations disproportionately impacts California residents. The immigrant related eligibility changes went into effect in California at the start of April, and a total of 72,000 humanitarian immigrants are expected to lose SNAP coverage in addition to the 260,000 residents who already lost coverage.

Texas

From July 2025 to January 2026, around 250,000 SNAP recipients lost coverage in Texas. More recent state data shows that around 500,000 fewer residents are eligible for SNAP in Texas between April 2025 and May 2026. Many residents who lost SNAP benefits lost coverage due to stricter work requirements.

However, a more unique issue that Texas residents are facing regarding SNAP benefits relates to harsher immigration crackdowns over the past year. Similar to California, Texas has much higher immigrant populations than the rest of the country. Many Texas households include undocumented immigrants who were already ineligible for SNAP benefits but had children or family members in the household who could claim SNAP benefits. Texas is one of at least 27 states who forwarded SNAP information to the Department of Homeland Security. Because of this, many children or family members of undocumented immigrants have foregone federal assistance to mitigate risks of deportation.

Looking Ahead

Moving forward, many states plan to introduce the stricter SNAP regulations outlined in the One Big Beautiful Bill Act starting in June and for the rest of 2026. As state and local governments continue to implement these regulations, SNAP coverage is likely to worsen across the country even more.

Do school cell phone bans work?

Last summer, Governor Mike DeWine signed the Ohio state budget into law. The budget made Ohio’s income tax flat, made a number of changes to the state property tax system, included provisions to decrease state Medicaid support if the federal government reduced its support, and put $600 million toward a new Cleveland Browns stadium. But probably most important to Ohio’s 1.8 million school-age children was that this bill banned cell phones in schools.

Cell phone use in general and social media use in particular has come under scrutiny by people in the public health field, especially those focused on mental health. Researchers argue there is a relationship between heavy social media use and depression, anxiety, loneliness, and suicidal ideation. A survey released last year by the National Center for Education Statistics reported that most of the public school leaders they surveyed believed cell phone use was hurting student academic performance.

These opinions have led to policy adoption in states across the country. According to a Newsweek report in January, over half of U.S. states have enacted statewide school cell phone bans. These bans occur in states across the country, with states in the Northeast, Midwest, South, and West enacting bans, though bans are most prominent in the South, with every Southern state besides Mississippi enacting a statewide ban.

In my daily life, I hear about this ban. My fiancée is a high school geometry teacher at Columbus City Schools, and she has to enforce this ban day to day. It has been a challenge to say the least.

Since some of these bans have been in place for a few years now, we are starting to get some evidence back about their effectiveness. 

I was interested in this topic after I saw a recent National Bureau of Economic Research working paper on the topic. This change studied a 2023 policy in Rio de Janeiro that banned cell phone use in schools. The researchers compared the test scores of students in schools that adopted the policy before and after the district-wide change to test score changes among students in schools that already had a no cell phone policy before the districtwide policy was put in place. The researchers estimated the cell phone ban caused a 0.06 standard deviation increase in test scores, an increase comparable to small-group math instruction programs studied in Norway and free school meal programs in New York City.

These results reflect a study on English cell phone bans a decade earlier that compared schools that enacted bans versus schools that did not, finding a 0.07 standard deviation increase in test scores among schools that enacted bans compared to schools that did not.

A study by Swedish researchers on data from Swedish schools in 2020 gave more pessimistic results. They used the same approach researchers used in the study on English schools but found no effect. This may have been due to more strict environments in place in Swedish schools already: a schoolwide ban is unlikely to have an impact if teachers are already effectively banning cell phone use at the classroom level. A 2024 study of an Australian cell phone ban also was unable to find any academic or social results from cell phone bans.

A 2024 study out of the Norwegian Institute of Public Health found social and academic benefits from cell phone bans in Norway, particularly for girls. The researcher found smart phone bans led to less health care take-up for psychological symptoms and disease, less bullying, higher GPAs, and more likelihood to enroll in high school among girls. She also found less bullying among boys caused by the bans.

The first prominent study on U.S. cell phone bans focused on a cell phone ban in Florida. Researchers found a significant increase in suspensions among students right after bans were put in place and that these were higher among Black students. They also found that this suspension spike dissipated after a year, suggesting there was an adjustment period associated with the new policy. They found test scores increased in the second year after buildings adopted the policy and that attendance also improved in those schools. The researchers suggested this may be a mechanism for increases in test scores: less cell phone use in school leads to high attendance, which then increases test scores for students.

Last month, a nationwide study of U.S. cell phone ban data compared students in schools across the country that banned cell phones versus schools that did not. The results were not particularly rosy. In the first year of adoption of a cell phone ban, student discipline rates increased and well-being fell. While these bans led to less cell phone use, the researchers did not find increases in test scores, attendance, or attention in class. There was some silver lining to the study, though: by year three, the disciplinary spike had dissipated, and student well-being rebounded and ended up even better than it had been before the cell phone ban.

There are few things I take away from these studies. One is that while test score increases have not been observed in all contexts where bans were put in place, there are a number of contexts where test scores did improve after cell phone bans. This does seem to suggest that cell phone bans can be a tool for increasing student academic performance, though not a perfect one.

Another takeaway I have is that transitions matter. Some interventions might be needed in the first year of a cell phone ban to ensure that disciplinary incidents do not rise too quickly. But on the other side of a first year of implementation, cell phone bans can lead to better attendance and better academic performance for students.

If there is anything that makes me most encouraged as a policy analyst around cell phone bans, it is that the truly negative impacts of cell phone bans, disciplinary increases, are temporary, while the benefits have seemed to last. This suggests that if schools are willing to deal with some short-term disruptions, cell phone bans could be an effective tool at increasing student academic performance and well-being.

Ohio economists: gas tax holiday costs outweigh benefits

In a survey released this morning by Scioto Analysis, 11 of 19 economists indicated that a three-month gas tax suspension would not provide meaningful financial relief to Ohio residents.

Since January, Ohio has experienced the most dramatic increase in gas prices out of all fifty states. In response, members of the Ohio House of Representatives have been considering a potential three-month suspension of the state’s motor fuel tax. The tax is $.385 per gallon for gasoline and $.47 per gallon for diesel. Tax revenue from Ohio’s fuel tax most commonly goes toward funding state infrastructure.

Most respondents disagreed that a gas tax suspension would provide meaningful financial relief to Ohio residents, with 2 economists uncertain and 6 economists agreeing. Bob Gitter of Ohio Wesleyan University explained, “If you buy a tank of gas every week you would save $6. Over a three month period that would be about $80. Low-income people could use a break but $80 would not, in my view, by meaningful financial relief.” Among those who agreed, economists expressed that while a gas tax suspension may provide financial relief, the policy would likely hurt Ohio’s economy in the long-run.

15 of 19 economists disagreed that the long-term economic benefits of a three-month gas tax suspension would outweigh the long-term economic costs of reduced state infrastructure funding. According to David Brasington of the University of Cincinnati, “Gas tax holidays usually end up causing deferred maintenance, which makes roads more expensive to repair than if normal maintenance had been done. It's like skipping a few dentist visits: it will save you some money upfront, but the resulting cavities will be more expensive to repair.” Of the remaining economists, 1 economist agreed and 3 were uncertain.

9 of 19 economists agreed that more of the benefits of a three-month gas tax suspension would accrue to consumers than fuel retailers. Curtis Reynolds of Kent State University expressed, “There is some research showing that gasoline taxes at the state level have high incidence to consumers (price increases almost one-for-one with the tax) so most of the benefits should accrue to customers in the form of lower prices.” Of the remaining economists, 5 were uncertain and 5 disagreed. These economists expressed uncertainty over whether fuel retailers would pass on the entire tax reduction onto consumers under a short-term gas tax suspension.

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.

Ohio has more money than expected. Should it save it or spend it?

Last week, it was reported that Ohio collected $1.2 billion in taxes more than it expected. More revenue means more flexibility for policymakers, more resources for public services, and potentially more room for tax relief. There will inevitably be debate about what the best way to use this extra revenue is, so I wanted to briefly talk about some of the potential options. 

Why do we save money?

This is a rhetorical question, but I want to take a second to spell it out formally because it highlights an important economic concept. Consumption smoothing is the idea that people have a tendency to consume fairly consistently, even though incomes may be inconsistent. 

A very simple example of this is that we need to eat every day, even though most people don’t get paid every day. Humans aren’t able to consume two weeks worth of calories at once and internally dole out that energy over time. We need to spread out our consumption over different periods than our incomes because even if we can predict both accurately, they almost always operate on different time frames. 

On a longer time horizon, saving for long-term expenses like retirement allows us to smooth consumption over the course of our lives. Most people earn the majority of their income during a few decades of working age adulthood, but they still need to consume before entering the workforce and after leaving it. Saving allows us to transfer purchasing power from periods where our income is high to periods where our income is low. In many ways, government budgeting works similarly. Tax revenues can fluctuate significantly from year to year depending on economic conditions, while the demand for public services tends to remain relatively stable.

That creates a challenge for states. During economic booms, tax revenues can increase unexpectedly. Similarly, revenues can fall during recessions which happen to coincide with a higher demand for services. If governments dramatically expand spending during good years and then suddenly cut programs during downturns, residents experience the same instability that individuals try to avoid in their own lives. Saving during prosperous years can help smooth that cycle out. 

So, what should Ohio do?

Impacts of spending this extra revenue

The value of the state spending money is entirely dependent on what they choose to spend it on. Some forms of spending create lasting economic benefits while others primarily provide short-term political rewards. Investments in infrastructure, education, or maintenance can potentially raise future productivity and improve quality of life for years after the money is spent. In those cases, spending today may generate returns that exceed the benefits of simply holding onto the cash.

There is also an argument that taxpayers themselves may be better positioned to decide how to use the money. If the surplus exists because taxes collected exceeded what was necessary to fund government services, then returning some of that money through tax relief could allow households and businesses to make spending and investment decisions based on their own priorities rather than political ones.

At the same time, temporary revenue spikes can create long-term obligations if states use them to fund permanent spending increases. Hiring large numbers of new employees or creating ongoing programs with one-time revenue sources can leave governments vulnerable when revenues eventually return to normal levels.

Impacts of saving this extra revenue

One of the biggest drawbacks of saving this revenue is that people have a preference for things today over things in the future. Saving is really just deferring our consumption to a later date, so it seems on its surface that it would be better to get the consumption out of the way and see if it can lead to long-term benefits. Using this lens, it becomes clear that saving this money would be a better decision if there were something in the future it could be spent on that would be even more valuable than anything we could spend it on today.

The state could put this surplus into its rainy day fund which functions similarly to an emergency savings account for households. Recessions, natural disasters, or unexpected budget shortfalls are inevitable at some point, even if their timing is uncertain. Building reserves during strong economic periods gives policymakers flexibility when conditions worsen. It can also reduce the need for abrupt tax increases or spending cuts during downturns, both of which can intensify economic pain.

According to research by Pew, Ohio’s rainy day fund could currently finance the state’s obligations for 47.4 days, putting it basically right at the national average. This extra cushion has become more important as a result of unreliable funding at the federal level. The pendulum swings between administrations make it much more difficult for states to predict how much money they might be able to expect for certain programs. Big changes to SNAP and Medicaid are two prominent examples that state governments might want to have extra reserves to help cover.

Ultimately, the best use of a surplus depends less on whether the money is spent or saved and more on whether policymakers understand the tradeoffs involved. A surplus is not free money. It represents resources that can either improve current consumption or provide stability and flexibility in the future. The difficult part is deciding which of those goals matters more today.

Who is moving out of California?

A few months ago, I wrote a blog post about who is moving in and out of Ohio. The results were mostly a story about age and income: older and younger Ohio residents move out of Ohio most frequently, presumably for either job opportunities or retirement. This kind of analysis is easy to do using data from the American Community Survey, which asks respondents about their current state of residence and their state of residence in the previous year. With this information, we can look at the demographics of who is moving in and out of different states.

I first looked at Ohio because that’s where a lot of our analysis is focused on at Scioto Analysis (and I live in Ohio myself). Another state that is equally interesting is California. It’s the most populated state in the country, and California is vastly different from Ohio. Additionally, between 2020 and 2024, the population in California decreased, just one of seven states that experienced a population decline across the United States.

Where are California residents moving?

According to American Community Survey data, around 315,000 households moved out of California between 2023 and 2024. Among these movers, the most common destinations were Texas, Arizona, Washington, Nevada, and New York.

The average age of residents moving out of California among the top ten destinations is between 31 and 47, with the youngest movers going to New York and the oldest moving to Nevada. The average age of California residents who remain in the state is about 40, meaning that the age of residents leaving California is not substantially different from those who are staying.

The average income of California residents who move out of the state is between $43,000 and $93,000 among the top ten state destinations. The states with the lowest average incomes for California emigrants are Oregon, Idaho, Arizona, and Nevada, with incomes ranging between $43,000 and $59,000. Three of these states border California, with Idaho only two states away. This trend might imply that lower earners who cannot keep up with the high cost-of-living in California choose to move out of the state to lower cost-of-living areas. Such residents who choose to relocate might be choosing nearby states to keep relocation costs low or stay relatively close to home.

On the other hand, the highest earners are moving to Florida, New York, and Washington, with average incomes ranging from $80,000 to $93,000. New York and Florida are both common states for workers to move to, and it’s likely that mid- or late-career professionals are moving for better job opportunities or retirement prospects. 

The trend of California emigrants moving to Washington, however, is more unique, and it is most likely explained by the significant tech hub located in both states. Over the past several years, it has become common for tech workers, especially from Los Angeles or the Bay Area, to move to Washington. This is primarily because tech workers from California can earn similar wages in Washington without paying state income taxes. California has the highest individual state income tax in the country, while Washington has zero state income taxes.

Who is moving into California?

According to the American Community Survey, around 184,000 households moved into California between 2023 and 2024. Among these movers, the most common destinations are Texas, New York, Arizona, and Washington.

The average age of movers to California among the top ten states is between 32 and 46, with the youngest movers coming from New York and the oldest movers coming from Oregon. Similar to migrants out of California, individuals moving into California do not have drastically different ages than pre-existing California residents.

The state with the lowest average income, by a wide margin, is Oregon, with an average income of about $43,000 for individuals moving from Oregon into California. This trend is most likely due to Oregon’s proximity to California. However, Oregon also had the highest average age of movers into California. This seems counterintuitive; I would expect most older individuals to be older professionals moving for job opportunities or retirement. However, the relatively low income of individuals from Oregon moving to California might imply that many of these movers are relocating for personal or family reasons.

Movers to California from Illinois and Virginia boast the highest average incomes, with both states exceeding $100,000. This trend is likely explained by these states’ proximity to major cities. Chicago’s location in Illinois and Washington D.C.’s proximity to Virginia could mean that movers out of these states are high-earners in lucrative industries. These movers could be looking for better job opportunities or similar job opportunities with better weather in California.

One distinct difference between individuals who move to a state like Ohio and individuals who move to California is income. Movers to California have incomes nearly double that of movers to Ohio. Regardless of who is moving to California, they must have incomes high enough to keep up with the high cost of living in the state.

Can we make Ohio’s homes more healthy?

A good friend of mine has owned his home for over a decade now.

A few years ago, he had a son, and it wasn’t soon after that when he found out he had dangerous levels of radon in his basement.

He quickly moved to remedy the problem.

According to the Centers for Disease Control and Prevention, radon exposure can be a cause of lung cancer.

Even if he was to keep his son out of the basement (a tall order for a three-year-old), being down there himself would expose him to risk that could then put his son’s father in jeopardy. He quickly invested in fan systems that remove radon from his basement.

Radon is just one example of home hazards that can lead to long-term harms for families. Peeling paint in homes built in the 1970s and earlier can lead to lead poisoning for children. Secondhand smoke can lead to asthma, respiratory problems, sudden infant death syndrome, lung cancer, and accidental fires.

Lack of precautions like smoke alarms can lead to fire injuries and deaths. Moistures and molds can cause asthma and respiratory problems. Pesticide use can be the cause of acute poisonings and even chronic conditions such as cancer, low birth weights, and premature births.

Some of these problems can be solved with better information. My friend just needed to know this was a problem and he was ready to invest in remediation. He is surely not the only person in the state of Ohio who just needed a little bit of information to take action.

A new bipartisan bill introduced in the Ohio House last week aims to provide that information.

The “Healthy Homes Program Act” would instruct the state health director to create an information and awareness program around mold, lead, radon, and carbon monoxide to help members of the public understand the threat of these hazards and proper remediation of them.

The bill as it stands is just a mandate without a line item.

This means the health director would have to find ways to administer this program within his current budget.

The Mid-Ohio Regional Planning Commission received a $2 million grant to support a Healthy Homes program in Central Ohio over the three years. The public information on the program emphasizes public information, home inspections, and assessments.

A well-financed state program would probably have to be funded more than this regional program to be effective at its goal.

Public information can only take you so far, however.

A special consideration here is children.

While we often assume parents will be perfect stewards of their children’ s health, we often find that parents underinvest in their children’s future, especially when they are dealing with tight budget constraints at home.

Subsidies for remediation targeted at low-income households with children would be a common-sense intervention for dealing with this mismatch between parental resources and children’s futures.

A well-funded information program with resources for needy households with children would help fight poverty and support economic growth in Ohio’s future.

Giving households tools to fight hazards in the homes can support health, educational outcomes, economic mobility, and equity for households in Ohio.

This commentary first appeared in the Ohio Capital Journal.

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.