How would Ohio’s child tax credit impact typical Ohio families?

Since Governor DeWine made his budget recommendations earlier this month, we have been talking nonstop about the potential Child Tax Credit he proposed. Earlier this week, we even released a brief memo where we fed this proposal into our cost-benefit analysis model to see what some of the impacts might be.

From a broad economic perspective, this proposal seems like it could dramatically improve people's lives in Ohio. However, people’s day-to-day experiences do not always reflect the broader economic perspective. For some people, this credit won’t dramatically change their outcomes. 

So, we wanted to help answer the question about what this might actually look like for types of families. To do this, we created a few example families. Using wage data from the Bureau of Labor Statistics, we figured out how much these hypothetical families would receive from this proposal and what that would actually mean for their income. 

Columbus: Married couple with two children

Our first hypothetical family is married with two qualifying children living in the capital city. One parent works full time as a construction laborer, making the median hourly wage of $18.62 per hour. The other parent spends most of their time taking care of their two kids, but manages to find time to pick up a few shifts at the grocery store every week to help make ends meet.

Combined, they bring home a total of just under $46,000 per year. This puts their household income just under the 40th percentile for the city and below 150% of the federal poverty line, fitting into what many people would define as lower-income. 

Because they file their taxes jointly and their income is between $22,500 and $75,000, they are eligible to receive the full amount of the credit. That means they get $2,000 back on their taxes, which can be thought of as a 4% increase in their annual household income. 

Assuming this family approximately follows the Department of Agriculture’s moderate food cost plan, this would be about enough money to pay for two months of groceries.

Youngstown: Single parent with one child

Our second hypothetical family is a low-income single parent raising their child in Youngstown, located in the Appalachian region of the state. This parent is able to almost work full time as a fast food cook, but one day each week their sister is unable to provide childcare, so our parent has to stay home. 

Because they are unable to work full time, this parent makes just under $19,000 per year.  This means that under this proposal, they do not qualify for the full amount of the credit. Instead, when tax season rolls around they should expect to get a little over $800.

Even after this credit, this family is only at 93% of the poverty line. Like the married family from Columbus, this additional $800 represents about a 4% increase in this parent’s annual income. Additionally, if we assume this family follows a low food cost plan, this would also be about 2 months worth of groceries. 

Dayton: Single parent with two children

Our final hypothetical family is made up of a single parent who works full time as a licensed nurse and their two children. As a nurse, they make $28.04 per hour which adds up to a yearly income of a little over $58,000.

Because this person is filing by themselves, they fall above the threshold where the benefit starts to phase out. At their specific income, this parent would only qualify for about $560 per child. Because they have two qualifying children, their expected credit would be $1,124. 

This is not quite enough money to pay for two months' groceries assuming a moderate food cost plan, but it is a little more than what the fair market rent for a 2-bedroom apartment in the Dayton Metropolitan Statistical Area is according to the Department of Housing and Urban Development.

Marietta: Married family with three children

The final hypothetical family lives in Marietta on the West Virginia border. Both parents work, one as a restaurant server, the other in retail, and they have had three children born in the past five years. They both make the median hourly wage for their jobs, $13.41 and $12.75 respectively. They both took a little time off from work recently after their third child was born, but now they are both back to working full time.

This family's total income is a little over $54,000, just a hair under 150% of the federal poverty line. This means that they qualify for the full amount of the credit, and will get an additional $3,000 to supplement their income.

It is often the case with living expenses that there are economies of scale. In other words, while going from two to three people in a household is a 50% increase in the number of people, the resources needed to maintain the same standard of living needs to increase by less than 50%.

Because of this, our hypothetical Marietta family experiences some of the biggest returns from this credit. Using a moderate food cost plan, they could afford groceries for almost three months with this credit.

Akron, single parent with one child:

This hypothetical parent works as a preschool teacher in Akron. Fortunately, their child gets to attend the preschool with them, so they can still work full time. They earn the median hourly wage of $14.20 per hour.

This means that our hypothetical parent earns $29,536, putting them a little under 150% of the federal poverty line. Because of their income, this qualifies for the full amount of the Child Tax Credit.

The extra $1,000 is roughly the same as receiving a 4% raise. Assuming this family follows a low food cost plan, this is almost enough money to cover three months of groceries. Alternatively, this is a little more than the fair market rent for a 2-bedroom apartment in their neighborhood just West of downtown

Akron, married couple with one child: 

Our second hypothetical family from Akron is married and just had their first child earlier this month. One parent is staying home with the newborn full time, while the other is working two jobs to try and make ends meet.

Their first job is part time at a coffee shop, where they work 20 hours a week at the median salary of $11.47 per hour. This parent just got their hours cut at their second job where they work at a fast food restaurant. Now they only get 10 hours per week at $11.09 per hour.

Added together, this family’s household income is $17,696, only 66% of the federal poverty line. Because they don’t earn at least $22,500, they only qualify for about $760 from the Child Tax Credit. Still, this represents about a 4% increase in their income. 

Assuming this family is following a low food cost plan, this amount will cover a little over one month’s worth of groceries. Alternatively, this is about one month’s worth of fair market rent for their one-bedroom apartment Northwest of downtown.

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I hope these examples help conceptualize what the impact of this child tax credit might feel like for some of the people who receive it. It’s certainly not a silver bullet by any means, but it does put a lot of money in the pockets of Ohioans.

Scioto Analysis estimates proposed child tax credit would grow Ohio’s economy by $740 million

This morning, Scioto Analysis released a memo presenting an analysis of the impact of the child tax credit in Ohio’s proposed FY 2026-2027 budget. As currently constructed, we estimate the Child Tax Credit would provide nearly $450 million in direct benefits to Ohio families. These direct benefits primarily accrue in low- and middle-income families, but the indirect impacts this may have on Ohio’s economy would be beneficial to nonrecipients as well. 

“There is a robust body of research that shows how investments made in early childhood are beneficial both to the families who receive them and the broader community” said Scioto Analysis Principal Rob Moore. “Children who grow up with access to more resources have an easier time in the short term, which often translates to better wage, health, and criminal justice system involvement outcomes later in life.”

Children who have more resources in formative years tend to have higher wages, better health, and less criminal justice system involvement. Using previous literature on the relationship between tax credits and outcomes for households, we estimate the current proposal will lead to the following annual impacts:

• $740 million in net benefits for the Ohio economy

• $450 million in direct credits to qualifying Ohio families.

• $500 million in higher future earnings for children receiving the credit

• $190 million in reduced costs associated with future crime 

The report draws from research conducted by the Columbia University Center on Poverty and Social Policy, indicating that financial support for families with children leads to better health outcomes, higher educational attainment, and lower crime rates. This study was awarded the 2023 award for “Best Original Article” in the Journal of Benefit-Cost Analysis due to its methodological rigor and policy relevance.

While raising revenue to fund this credit will exact a cost on the economy due to foregone tax revenue, the potential long-term gains for Ohio’s economy and communities are substantial. After running 10,000 simulations of the proposed child tax credit under different circumstances, we found the benefits of the child tax credit outweigh its costs in 90% of those simulations. 

“Investing in Ohio children is a good bet for growing Ohio’s economy in the long run,” said Scioto Analysis Principal Rob Moore.

Where does the term “Caucasian” come from?

Still in the first 100 days of the second Trump presidency, we have seen a lot of changes, particularly around data availability and collection of data related to diversity.

As my colleague Michael Harnett wrote about before, lack of collection of data on a population can severely hamper our ability to understand the population in question. Many are worried that changes in the federal administration will lead to reduced collection of demographic data that will then make it harder for researchers and analysts to understand demographic trends among the public.

The Biden Administration had even improved some demographic collection practice for the Census Bureau, greenlighting “Middle Eastern or North African” and “Latino” as options for future censuses. This was a change a decade in the making.

But just as the federal government was beginning to modernize demographic categories—finally recognizing groups like Middle Eastern or North African as a distinct racial identity and using a phrase like “Latino” that is more commonly used among people from that racial group—current decisions by the new federal administration could potentially unravel the existing demographic collection infrastructure. Instead of refining how surveyors collect data to better understand the demographics of the U.S. population, they are now facing a chance that demographic data could be obscured or never collected in the first place.

This threat isn’t just about which categories appear on a form. It’s about how researchers, analysts, policymakers, and the public think about identity, and whether the categories we do reflect the reality of identity in the United States today or reinforce other incorrect classifications.

One example of a term that lingers in public discourse is “Caucasian.” In 1977, the Carter Administration’s Office of Management and Budget Directive 15 established “white” as the official racial designation throughout the federal government, endorsing it over its rival “Caucasian.” It is a sign of our times that this original directive is not available for public viewing as of February 2025, though it was publicly available as recently as December 2024 according to the Wayback Machine.

Even though the federal government has endorsed the use of “white” over “Caucasian” for nearly half a century now, the word still appears in legal documents, medical research, and everyday conversation. Where did this phrase come from and why is it still so persistent today despite falling out of official favor five decades ago?

The term “Caucasian” used to refer to how we refer to people who are ethnically “white” dates back to the late 18th century, when a German historical school with a special focus on race was trying out different classifications of human races. An especially popular classification was to split humanity into three major races: “Caucasian”, “Mongoloid,” and “Negroid”, roughly corresponding to what our Census Bureau would term “White,” “Asian or Pacific Islander,” and “Black.”

But why “Caucasian?” The term comes from an association with the Caucasus Mountains, a range that defines the northern borders of modern-day Georgia and Azerbaijan with Russia between the Black and Caspian seas. What does this area have to do with white people?

This goes back to a historical theory that is very different from the present-day consensus. The prevalent view among European scholars in the 19th century was that the human species began in the Caucasus Mountains. This was based partially on Caucasus being the purported landing place for Noah’s Ark.

“Caucasian” was first applied to a broad swath of humanity by German historian Christoph Meiners in his 1785 book The Outline of History of Mankind. In this book, Meiners grouped Europeans, Middle Easterners, North Africans, and Indians into one racial group, arguing its main characteristic was beauty driven by virtue. In his words, “the more intelligent and noble people are by nature, the more adaptable, sensitive, delicate, and soft is their body.”

Ten years later, German Anthropologist Johann Friedrich Blumenbach popularized the term in his studies of human craniology. He categorized human “varieties” into five categories: Caucasian, Mongolian, Malayan, Ethiopian, and American. Despite creating these categories, he acknowledged the capriciousness of this approach to categorization, saying “All national differences in the form and colour of the human body...run so insensibly, by so many shades and transitions one into the other, that it is impossible to separate them by any but very arbitrary limits.”

While many of Blumenbach’s views would not be seen as correct today, he was considered an anti-racist in his time, opposed slavery as a practice when it was still in legally sanctioned in nearly every country across the world, and argued against common claims of his day that certain races were imbued with an “inherent savagery.”

Despite these views, Blumenbach made the phrase “Caucasian” popular and much of his work was later co-opted by scientific racists who told a very different story about mankind than Blumenbach did.

Meanwhile, in the new United States of America, the terminology of “white” was a big part of the early law of the country. The designation was one of the original categories of self-reporting in the decennial census of the fledgling nation. Naturalization was limited in the Naturalization Act of 1790 to “free white persons.”

The term “Caucasian” became a lynchpin for citizenship debate in the 1920s, with immigrants from Japan and India losing Supreme Court cases where they tried to argue they should be considered “caucasian” under current immigration law. The U.S. draft for World War II often designated enlistees as “Caucasian” and legal briefs and arguments around the case of Brown v. Board of Education in the 1960s often used the phrase. Even the Equal Employment Opportunity Commission, formed by the 1964 Civil Rights Act, used the phrase “Caucasian” in demographic reporting.

It was not until the Carter Administration designated “white” as the preferred term in 1977 that the federal government officially moved away from the phrase “Caucasian.” But we still see it in use today, especially in medical research contexts.

I actually remember first hearing the phrase, and I remember the allure of it. Today’s understanding of race is so messy: a social phenomenon roughly associated with phenotypic characteristics. There was a certain allure to this new word I heard: this feeling of scientific precision that race doesn’t give us. I don’t think I am alone in feeling this draw.

But it’s a falsehood. “Caucasian” is a phrase that misplaces current social phenomena in an 18th Century German story about a sparsely-populated mountain range in central Asia. Correct understanding of social phenomena means understanding the true roots of these categories. So just use “white.” It’s easier, everyone knows what you’re talking about, and you’re not rooting your language in a veneer of scientific accuracy that is built on a shaky pseudoscientific foundation.

Which states rely the most on federal funds?

Currently, the Trump Administration is in a battle with the courts to freeze federal spending of billions of dollars.

Acting Office of Management and Budget Director Matt Vaeth said the goal of the freeze is to reduce waste by reducing use of “Federal resources to advance Marxist equity, transgenderism, and green new deal social engineering policies.” Programs targeted by the freeze include foreign aid, grants to non-governmental organizations, diversity, equity, and inclusion (DEI) initiatives, and environmental programs. Groups that have been hit swiftly by the funding freeze are farmers and rural businesses invested in renewable energy projects and global humanitarian efforts.

Another constituency at risk with federal spending in turmoil is state and local government. In our federal system, state and local governments rely on the federal government for a large proportion of their funding. This amount ranges, though, according to the Census Bureau. For instance, North Dakota receives less than 20% of their state revenue from the federal government. On the opposite side of the spectrum, Alaska receives nearly 40% of their revenue from the federal government.

State	Total State Revenue	Revenue from Federal Government	Percentage Federal
Alaska	$ 15,667,334.00	$    6,160,971.00	39%
Kentucky	$ 57,911,686.00	$    22,085,818.00	38%
Vermont	$ 11,232,873.00	$    4,237,732.00	38%
West Virginia	$ 22,420,270.00	$    8,389,354.00	37%
District of Columbia	$ 20,055,882.00	$    7,464,202.00	37%
Arkansas	$ 37,010,485.00	$    13,633,748.00	37%
Louisiana	$ 59,715,604.00	$    21,879,544.00	37%
Arizona	$ 89,076,443.00	$    32,415,044.00	36%
South Dakota	$ 10,549,378.00	$    3,771,835.00	36%
Rhode Island	$ 16,093,147.00	$    5,573,332.00	35%
Mississippi	$ 35,802,048.00	$    12,256,551.00	34%
Montana	$ 13,725,435.00	$    4,657,041.00	34%
Missouri	$ 68,260,987.00	$    21,715,343.00	32%
New Mexico	$ 42,233,407.00	$    13,421,271.00	32%
Oklahoma	$ 48,271,122.00	$    15,307,503.00	32%
Alabama	$ 64,777,600.00	$    20,229,466.00	31%
Maine	$ 18,317,563.00	$    5,666,935.00	31%
Michigan	$ 122,032,979.00	$    37,439,964.00	31%
Indiana	$ 85,344,253.00	$    25,378,951.00	30%
Pennsylvania	$ 171,577,131.00	$    50,519,392.00	29%
Ohio	$ 148,265,683.00	$    43,575,300.00	29%
Oregon	$ 68,290,949.00	$    19,908,513.00	29%
Nevada	$ 37,682,330.00	$    10,825,535.00	29%
Maryland	$ 89,612,692.00	$    25,199,517.00	28%
North Carolina	$ 129,216,170.00	$    36,222,639.00	28%
Idaho	$ 20,594,801.00	$    5,656,225.00	27%
South Carolina	$ 68,387,664.00	$    18,443,484.00	27%
Delaware	$ 15,569,155.00	$    4,166,816.00	27%
Illinois	$ 182,611,763.00	$    48,785,747.00	27%
New York	$ 442,057,068.00	$    117,525,817.00	27%
Florida	$ 242,920,560.00	$    63,400,621.00	26%
Massachusetts	$ 115,529,854.00	$    30,043,910.00	26%
New Hampshire	$ 15,874,696.00	$    4,112,203.00	26%
Texas	$ 346,395,677.00	$    88,920,949.00	26%
Minnesota	$ 85,328,127.00	$    21,901,865.00	26%
Tennessee	$ 76,677,348.00	$    19,651,768.00	26%
Wisconsin	$ 69,139,173.00	$    17,456,814.00	25%
Iowa	$ 46,012,142.00	$    11,209,676.00	24%
Washington	$ 120,010,103.00	$    28,146,897.00	23%
Georgia	$ 112,024,120.00	$    26,207,436.00	23%
Connecticut	$ 53,800,618.00	$    12,192,573.00	23%
Hawaii	$ 24,781,244.00	$    5,585,436.00	23%
Kansas	$ 39,440,642.00	$    8,795,251.00	22%
Colorado	$ 83,113,844.00	$    18,380,857.00	22%
Nebraska	$ 30,506,889.00	$    6,704,898.00	22%
California	$ 739,308,929.00	$    161,662,728.00	22%
New Jersey	$ 140,427,448.00	$    30,659,868.00	22%
Utah	$ 46,530,335.00	$    10,138,408.00	22%
Virginia	$ 111,838,708.00	$    23,433,620.00	21%
North Dakota	$ 14,589,875.00	$    2,818,355.00	19%

From this table, you can get an idea of which states rely the most on federal funding. For instance, let’s consider Alaska. Between national parks, conservation land, and military bases, 60% of Alaska’s land is federally owned. This not only requires federal funds to maintain this land, it also limits Alaska’s state and local governments’ ability to raise revenue through property taxation, which nationally makes up 27% of total state and local tax revenue.

Alaska also requires more federal investment due to its small population of less than a million people flung over the area of the country’s largest state. This requires high per-capita infrastructure costs on roads, utilities, and airports. On a recent project I did where I had to dig through a list of each airport in the United States, I recall seeing line after line of Alaska airports. This is because flying is often the most economical mode of travel due to the size of the state. And airports usually require federal funding to operate. The low population density also requires the federal government to invest in transportation, broadband, and other rural infrastructure.

Alaska also has a unique revenue structure compared to other states. Due to its vast oil resources, the state relies heavily on oil revenues, to the point that they share with New Hampshire the distinction of being one of two U.S. states without either a state income tax nor a state sales tax. The volatility of oil revenues and their lack of other state taxes make Alaska especially reliant on federal revenues for state budget stabilization.

Alaska is unique in the number of communities they have that are not connected to the rest of the continent by roads. Being off the road system requires goods be shipped in via air or water transportation, which drives up the cost of goods and services. This increases the state’s demand for federal health care, food assistance, and energy programs. In the event that Greenland became a part of the United States, it would suffer from similar problems.

Alaska relies on federal programs due to unique elements of its economy. Native American and Alaska Native programs bring federal dollars into the state. Alaska’s strategic Arctic location makes it a hub for military bases like Anchorage’s Joint Base Elmendorf-Richardson (JBER), Fort Wainwright in Fairbanks, and Fort Greely near Delta Junction. Its large coastline gives it a large Coast Guard and fishery management system and its high healthcare costs lead to high spending on Medicaid and health care subsidies.

Alaska experiences severe weather and earthquakes, making it a receipt of federal disaster assistance. Coastal communities are dealing with climate change, which makes the state a recipient of support for climate adaptation and relocation.

All of these above factors make Alaska one of the top states per capita for federal spending.

The two states that come after Alaska are two other rural states that are very different from it: Kentucky and Vermont.

Kentucky is a rural state with high poverty rates and a relatively low median income. This leads to higher reliance in Kentucky on programs like Medicaid, SNAP, and TANF. It also has a large population requiring medical assistance, which contributes to federal spending on Medicaid. Kentucky also receives educational support from the federal government in low-income areas.

Both Vermont and Kentucky, as rural states, deal with a lot of the same dynamics as Alaska. They have small populations per capita, giving them smaller tax bases and large areas to maintain services across. Roads, healthcare, and infrastructure cost more to provision per capita in rural areas than in urban areas. 

Vermont has some health care dynamics that lead to higher federal costs. One-third of the state’s population is enrolled in Medicaid and Vermont has one of the oldest populations in the United States, leading to higher medical costs. The state receives rural assistance in the form of transportation and infrastructure investment, agricultural subsidies, and energy efficiency projects.

Vermont has budget focuses that bring in federal dollars. Its investment in education, social services, and sustainability and conservation programs bring in federal dollars to help support them in those efforts. Vermont was a large recipient of COVID-19 relief funds. Funds supporting public health, hospitals, and economic recovery helped bolster Vermont’s economy during those years.

What does this tell us about states that rely on federal funds? Well for one, they are rural. Vermont, Kentucky, West Virginia, and Arkansas are all in the top 5 for highest percentage of revenue coming from federal sources and are also in the top 10 for most rural states. They also tend to be high-poverty: Kentucky, West Virginia, Arkansas, and Louisiana are in the top 10 states for reliance on federal funds and for poverty rates.

In an era of uncertainty around federal funding what we do know is this: different states will be impacted by uncertainty more than others depending on their reliance on federal funds.

A defense of "sin taxes"

Ohio Gov. Mike DeWine’s final two-year budget proposal, released earlier this month, has caused quite a stir.

The headline many have seen about it over and over again is the changes the budget recommends to taxes — namely proposed increases to taxes on cannabis, cigarettes, and sports betting.

These taxes are often given the pejorative label of “sin taxes” because they cover “vices” that are potentially more palatable to tax than say…income or general sales. 

The phrase “sin tax” smells a lot like the rebranding of the “estate tax” as a “death tax.” It’s a way to get at our gut and rankle that libertarian impulse that we as Americans almost all have whether we like it or not. Who is to say what constitutes a “sin” or not? Certainly not the government. Don’t tread on my Marlboros!

The problem with this framing is that it obscures a valuable tool of taxation: to correct social problems.

The typical function that we ascribe to taxes is to raise revenue for operations of government. If that were the only way we could use taxes to a good end, the answer for how to raise taxes is pretty straightforward: cover as many different economic transactions as possible to make taxes as efficient as possible then rebate either cash or services back to low-income households to offset the regression of the system.

The problem with this line of thinking about taxes is that it is both excessively narrow-minded and a century behind the times.

When Teddy Roosevelt instituted the national estate tax, he saw it as a way to promote equality of opportunity. Why should your wealth be a function of your parents’ wealth? An estate tax reduced how much wealth you could receive from your parents, which had an impact on inequality.

At the same time, Economist Arthur Pigou was promoting what later became known as “Pigouvian taxation,” the idea that we can tax economic transactions that lead to “externalities,” or social spillovers that cause harm to others.

This became the theoretical basis for carbon taxes. If we want to reduce the release of carbon into the air, we need to bring the private cost of carbon pollution into line with the social cost of carbon pollution.

This is how taxes on cannabis, cigarettes, and sports gambling work.

A study released by the Federal Reserve Bank of Kansas City last year found state cannabis legalization caused double-digit increases in substance use disorder, chronic homelessness, and criminal justice involvement. Cigarette smoking leads to hundreds of millions of dollars in health care spending and productivity losses every year. Sports betting is causing household fiscal instability and fueling addiction.

Yes, increasing taxes on cannabis, cigarettes, and sports betting does raise some equity concerns. The amazing thing about Pigouvian taxation, though, is that by using the revenue raised you can promote efficiency and equity at the same time by funding programs that support low-income people like child tax credits…just like this current budget does.

You cannot build a state budget on a foundation of Pigouvian taxes — these three taxes will only raise 4% of total tax revenue in DeWine’s FY 2026-2027 budget. But if we can curb social problems and fund programs at the same time, why wouldn’t we?

This commentary originally appeared in the Ohio Capital Journal.

COVID's lasting impact on learning

Five years ago, I was a senior at Bates College spending almost all of my free time trying to finish up my economics thesis. My concerns at that time were 1: Graduating, 2: Thinking about grad school, and nothing else. Less than a month later, I had flown back to Minnesota and the only thing I was worried about was COVID-19. 

I did still end up finishing my thesis and going to grad school, but like so many other things during those early years of the pandemic, I had to be entirely remote while they happened. 

I’m someone who works well independently and is extremely comfortable with computers, so this adjustment was not as hard for me as I’m sure it was for others. Despite this, I struggled mightily in that first semester of grad school. I had to completely overhaul all of the systems I was familiar with to make my education successful. I would say that switching to remote education had an impact on the quality of my learning.

For many students, the shock of the pandemic was much more difficult to adapt to. Some students might not have had the high-speed internet access needed to participate in a remote classroom. Some students might not have had computers at all. 

Add on to that the missing social element of schools and the general stress and anxiety caused by the worst global pandemic in over a century and it should not be surprising that there was a significant decrease in standardized test scores across the country. 

Researchers Tom Kane and Sean Reardon started the Education Recovery Scorecard to track these learning losses. They found that between 2019 and 2022, the average third through eighth grader lost roughly half of a grade level of math achievement and one third of a grade level of reading achievement. These losses were more pronounced in lower-income and urban school districts. 

This is something Scioto Analysis has covered in the past. Our 2020 cost-benefit analysis on the subject found that the risk of death reduction from school closures was less valuable than the damage done to students’ academic performance (and we even got some attention for this study in the Wall Street Journal).

Unfortunately, conditions have not been improving. In their most recent report, they found that the average student is even farther behind in reading than they were in 2022, now about half a grade level behind. 

As was the case in 2022, these results are not uniform. Some school districts have recovered to pre-pandemic levels of achievement. Districts in the highest income decile were four times as likely to have recovered as districts in the bottom income decile, again highlighting how important income is to school achievement. 

One problem preventing recovery efforts is chronic absenteeism. Although data on absenteeism is not super robust, researchers have found that absenteeism rates are higher post-pandemic than they were pre-pandemic. Absenteeism rates can exacerbate disparities as well: lower income school districts have higher rates of absenteeism compared to high income districts. 

These researchers also explain how federal relief dollars have impacted education recovery efforts. Districts that spent more money on academic catch-up programs (e.g. tutoring, summer school, etc.) have seen faster recovery rates compared to districts that spent less. 

Kane and Reardon make a point to highlight the policy implications of their research. They’ve identified a problem: student achievement has not recovered from the pandemic, and they are looking at some of the reasons why so we can start to address them. 

They mention on their website that despite the evidence that the average student is not achieving at what we expect for their grade level, 90% of parents think their child is at or above grade level. Policymakers and analysts need research like this to understand why students are underperforming, and to find solutions to help get children back on track.

Ohio Gov. DeWine’s budget proposal could transform state poverty and public health landscape

I will have to admit: I’m kind of stunned.

This week, Ohio Gov. Mike DeWine proposed a policy that would both reduce child poverty and save lives. His final biennial budget proposal includes a $1,000 child tax credit for low-income and middle-class families with young children, paid for by a tobacco tax increase that would nearly double the state’s cigarette tax.

This policy couples a proven poverty-fighting tool with a tax that discourages smoking, the leading preventable cause of death in Ohio. I am not exaggerating when I say this could be one of the most consequential anti-poverty and public health measures in recent memory all wrapped up in one policy change.

As a policy analyst who focuses on taxes, poverty, and public health, I think a lot about these two policies, and there are few policies I think could be more transformative on their respective fronts than child tax credits and tobacco taxes.

Child tax credits are incredibly effective tools to tackle poverty head-on. They’re so effective that during last fall’s presidential election both campaigns embraced the idea.

From an economic standpoint, child tax credits are effectively giving cash to families who are supporting children. In 2019, a consensus group of economists from across the political spectrum released a report commissioned by Congress on how to reduce child poverty. Child allowances like child tax credits were their top recommendation.

At the time it seemed like a “maybe someday” sort of policy, but with the COVID-19 pandemic, a policy window opened. Congress passed the American Rescue Plan, which nearly doubled the federal child tax credit for young children and increased the child tax credit for other children by 50%. This policy pushed poverty rates down to their lowest rates on record and nearly cut the U.S. child poverty rate in half.

Due to Joe Manchin’s unwillingness to extend the credit beyond 2021, however, the expansion expired in 2022 and poverty rates rebounded that year.

Since then, states have embraced child tax credits as tools to support families with children. A total of 16 states have their own child tax credits, including states like Arizona, Idaho, Oklahoma, and Utah.

From a public health perspective, tobacco is one of Ohio’s worst problems. Tobacco kills three times as many Ohioans per year as drug overdoses and Ohio is in the top five states in the country for tobacco use prevalence.

Tobacco use also has economic consequences, costing our state health care system billions of dollars a year and hampering statewide productivity by billions of additional dollars each year.

Tobacco taxation is well-established as the most effective and efficient way to reduce tobacco consumption, particularly among youth. So for those of us who care about fewer people dying prematurely in Ohio, we tend to get excited about any talk of tobacco taxes.

Ohio has a chance to take a bite out of poverty and finance it with a tax that will save lives. Now we have to wait to see if the General Assembly likes this idea as much as the governor, and poverty and public health researchers do.

Federal data is vital to good policy analysis

Last week, Robert Santos decided to step down as the director of Census Bureau. This decision comes at a time when the Trump administration is making a concerted effort to remove public data from government websites due to a perceived connection to diversity, equity, and inclusion. 

The Trump administration’s war on DEI practices has escalated. It is no longer about stopping workplace sensitivity trainings or changing hiring practices, it is instead focused on changing the way people in this country understand people that are different from them. 

Things are changing quickly, and it’s difficult to predict what the extent of these data removals will be. For example, the Center for Disease Control’s Behavioral Risk Factor Surveillance System (one of the best publicly available health databases) was temporarily taken down. As I’m writing this on Wednesday, February 5, parts of it are back online. 

I imagine that most people who read blog posts on sciotoanalysis.com understand the importance of this kind of data, but the severity of this situation is worth repeating. Policymakers, non-profit organizations, academic researchers, and others rely on the availability of high-quality public data. 

Fortunately, researchers have been working  to download as much data as possible in the event things do start to get taken offline. We won’t completely lose the data that already exists, even if we might not be able to use new data going forward. 

That being said, it is hard to imagine that over the next four years, the newly collected public data is going to be of the same quality. If I had to guess, I would say that we probably aren’t going to have nearly as precise data on things like gender, race, sexuality, etc.

It might be the case that those questions are removed entirely from government-run surveys like the American Community Survey. I am optimistic that those surveys won’t entirely disappear. Much of this optimism comes from the fact that I can’t even begin to imagine how damaging it would be to have the decennial census be the only piece of publicly collected national data.

Still, a lot of harm will come from failing to collect adequate data. One example that comes to mind is thinking about how the Census Bureau records race data. Currently, there are only six race categories: White, Black, Native American, Asian, Pacific Islander, and Other. This does not do a good job of capturing the different racial identities people in the United States have. 

The Census Bureau decided in 2024 that it would add North African/Middle Eastern as a racial category, an important change that would have helped improve our understanding of racial dynamics. I don’t know if the current version of the American Community Survey is already in progress with this updated race question, but I would be very surprised if this data ever became public. 

As a researcher, it’s hard not to be discouraged by the thought of losing so much data over the next four years. But I want to end on a slightly more optimistic note. 

Yesterday, I was talking with a community group of data scientists. Near the end of our chat, this topic came up. While people were still extremely nervous about whether or not we would continue to have access to high quality data, the people in that meeting were still very optimistic. People were sharing the data repositories they knew about that wouldn’t be taken down and talking about how we might address these shortcomings going forward. 

Right now, we don’t know to what extent we are going to lose data. As statisticians, it is our job to ensure that going forward, we don’t leave groups behind just because we are losing data about them. We likely won’t be able to rely on the Census Bureau as much in the short-term, but we can still explore effectiveness, efficiency, and most importantly right now, equity.

Ohio economists: school funding cuts could increase inequality

In a survey released this morning by Scioto Analysis, 13 of 16 economists surveyed agreed that cutting school funding in Ohio would significantly increase inequality in Ohio. Over the last four years, Ohio's public schools have relied on the Cupp-Patterson Fair School Spending Plan to provide over $300 million in funds per year. This bill was initially supposed to provide funding through 2027, but the new Speaker of the House has indicated that he would like to cut this funding. If these funds are cut, it would reduce spending on public schools by about $650 million over the next two years.

As Kathryn Wilson from Kent State points out “The purpose of the funding was to have less reliance on local property taxes. There are large differences in per-student-spending across districts within Ohio. Reducing this funding will increase those gaps and increase inequality.”

Additionally, 13 of 16 economists agreed that these spending cuts would significantly reduce Ohio’s future economic output. Bill LaFayette wrote in his comment “School spending is not an expenditure, it is an investment in our future workforce. If we don't have the revenue to support our schools, colleges, and universities adequately, perhaps we should rethink some of those tax cuts.”

The Ohio Economic Experts Panel is a panel of over 40 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.

What can we learn from airport data?

We are currently working on a project at Scioto Analysis where we are using data on the number of people traveling through airports to make some tax revenue estimates. That project is interesting for a whole host of reasons, but one especially fun part has just been poring over this airport data.

We compiled data from Ohio and North Carolina on the monthly passengers flying into every airport in the state from 2002 to 2024. Since these numbers are a little difficult to pull out and use, we thought it would be valuable to share some of the observations we had about this dataset.

The COVID-19 impact has faded

The lockdowns that happened in 2020 as a response to the COVID-19 pandemic had a major impact on all forms of travel. For most airports, this meant a drop in the total number of passengers arriving by 60% - 70% in 2020 compared to 2019. 

In recent years, most airports have returned to their pre-pandemic levels of visitor traffic. For most airports, they achieved this in 2023. During 2024, we saw some of the regular growth that more closely follows the trends before the pandemic. 

This will be an interesting statistic to track going forward. We can learn a lot by understanding how people move around. 

Cincinnati was a major airport in the early 2000s

In 2004, Cincinnati had multiple months where over 1 million people passed through the airport there. By 2010, monthly visitors were down to under 400 thousand. The Cincinnati airport has hovered around this same number of monthly visitors since then, keeping it in line with the airports in Cleveland and Columbus. 

The main reason for this change was the merger between Delta and Northwest airlines in 2008. After the merger, Delta cut flights to Cincinnati. This had such a significant impact on the airport that it closed one of its terminals in 2009.

What drives airport traffic?

In our analysis, we are specifically comparing air travel between Ohio and North Carolina. Looking at these states, you see that North Carolina has had over double the total number of air passengers landing in their airports compared to Ohio over the past couple of decades. Most of this is driven by the airport in Charlotte, which by itself nearly matches the combined monthly passengers landing in Cincinnati, Cleveland, and Columbus. The Raleigh-Durham airport also has about 50% more traffic than any of the large airports in Ohio.

So, why is it that two states that have very similar populations have such different air traffic numbers?

One thought I had was that North Carolina might have more tourists than Ohio. The intuition behind this is that tourists often travel further distances to get to where they are trying to go, and as such may be more likely to travel by plane. The issue with this is that according to the Ohio Department of Development and the North Carolina Department of Commerce, Ohio has more tourism spending than North Carolina!

This doesn’t mean that tourism is not part of the reason why North Carolina has more air traffic than Ohio, but it probably means it’s not the main explanation. 

One thing that could be driving this is people flying to Charlotte to get to destinations in South Carolina. This is purely speculation on my part, but there must be some reason why there are so many more people flying to North Carolina than Ohio.