3 economics stories to watch out for in 2026

Happy New Year! Over the last couple of weeks, we’ve recapped Scioto Analysis’ past year, the general landscape of research, and I’ve reflected on my time so far with Scioto. Now, I want to take some time to look forward, and speculate a bit about what I think will be some of the biggest economic stories of 2026. 

What’s going to happen with SNAP benefits?

The way SNAP benefits are going to work in 2026 is going to change dramatically because of the One Big Beautiful Bill Act. Previously, the Federal Government funded SNAP and gave money to the states. Aside from some administrative costs, states were just getting money and distributing it.

However, now states are required to pay some of the benefit costs themselves. According to research done by the Georgetown Center on Poverty and Inequality, this is going to cause most states to start paying hundreds of millions of dollars. California and Florida are going to be on the hook for over $1 billion each.

This change may mean that states have to cut back their SNAP programs and limit participation. It’s difficult for states to raise that amount of money, especially because states (with a few exceptions) need to have balanced operating budgets. How this story plays out will have major ramifications for poverty and inequality across the country. 

What counts as a healthy economy?

Earlier this month, my colleague Rob wrote a blog post about the claim made by a financial advisor that the poverty line should be $140,000 instead of $32,000 for a family of four. This is based on the fact that spending habits have changed in the past 60 years since the poverty line was first introduced. 

When I read this article, my first thought was about how different people perceive the health of the economy. What does it mean for people or a whole nation to be doing well?

We at Scioto have calculated indicators such as the Genuine Progress Indicator to provide an alternative to Gross Domestic Product that tries to capture some other sentiments we have about what a healthy economy looks like. 

There are so many ways to try and pin down how people are doing. There are competing definitions of what it means to be middle class, there is the official poverty measure and the supplemental poverty measure, some groups prefer not using poverty measures and instead looking at the ALICE criteria. With diversion between unemployment rates, inflation rates, gross domestic product growth, and consumer sentiment as we enter the new year, which indicators rise to the top is a story to follow in 2026.

What will the Federal Reserve do with interest rates?

One of the biggest open questions going into 2026 is what will happen at the Federal Reserve once Jerome Powell’s term ends. In recent meetings, there has been uncharacteristic disagreement among Federal Reserve officials about rate cuts. At the heart of the debate is whether slow job growth or high inflation is a bigger threat.

President Trump has made it clear that he wishes the Fed had been more aggressive with cutting interest rates over the last year. It seems almost certain at this point that the next chair of the central bank will be an economist who believes inflation is largely under control, and that rate cuts are appropriate. Many people are worried that this could signal a weakening of the independence of the Federal Reserve, which would have negative ramifications across the economy. 

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2026 will have its fair share of economics stories to follow. State and local policymakers are going to have a whole set of new challenges and opportunities to work through in the new year.

Original Analysis: Home Visiting Programs Support Child Development

This morning, Scioto Analysis published a cost-benefit analysis about the impacts of Help Me Grow, a home visiting program in Ohio. Using analysis from the Washington State Institute for Public Policy, we estimate that Help Me Grow creates a net benefit of $112 million, with about $3.30 in benefits created for every $1.00 in costs.

Ohio is falling behind in kindergarten readiness scores while childcare subsidies remain low compared to other states. One solution to this problem is home visiting, which matches new and expecting mothers with a nurse, social worker, early childhood specialist, or paraprofessional who conducts home visits and provides assistance to families. Home visiting can help to reduce parental stress, increase access to childcare, and improve kindergarten readiness.

The Help Me Grow home visiting program in Ohio supports 13,000 families per year. The main contributing factors are $117 million in benefits from increased labor market earnings due to reduced child abuse and neglect, $17.7 million in benefits from less social spending due to reduced child abuse and neglect, and $12.1 million in benefits from less smoking later in life. Home visiting also creates benefits to employment, crime, and out-of-home placement.

We conducted 10,000 simulations of the current Help Me Grow home visiting program in Ohio with different variables and costs to test our model. We found that home visiting creates a positive net value for Ohio in 81% of trials, with the middle 90% of outcomes between -$97 million and $320 million in net social benefits.

For the 2026-2027 biennium, Ohio plans to expand the Help Me Grow home visiting by 23%. We estimate that this expanded program will produce a net benefit of $138 million, $26 million more benefits than the status quo. As Ohio expands Help Me Grow more, the number of families served increases, which increases the total benefit to Ohio.

Intergenerational poverty and goods we wish didn’t exist: Two economics papers I enjoyed in 2025

Every year, I like to look back at some of the academic research papers that I thought were impactful over the past year. Previously, I tried to do something akin to “The Important Papers of 202X,” but the truth is I could not possibly read enough to say with any certainty that the papers I came across were better than some that I missed. Additionally, academic papers take years to write, and I sometimes come across research that hasn’t been published yet, or I read something that has been in the works for years and only recently published. So, I’ve decided that this year I’m going to be a little more loose with my rules and just write about two papers I read this year that I found interesting. 

Intergenerational persistence of poverty in five high-income countries

This paper’s author Zach Parolin won the Association of Public Policy Analysis and Management’s David Kershaw award for his work studying how persistent poverty is in different countries. The idea behind this paper is fairly straightforward: If we assume that a country has perfect equality of opportunity, then whether or not you are in poverty as an adult should be independent of whether you experienced poverty as a child. 

So, using data from the United States, Australia, Germany, Denmark, and the United Kingdom, Parolin measured how much childhood poverty contributed to the likelihood of adult poverty, and explored the mechanisms that drove those disparities. He found that in the United States, intergenerational poverty effects were much stronger. In other words, Americans who experienced child poverty are significantly more likely to also experience adult poverty compared to children who experience poverty in those other countries.

The main driver of this effect he identified was a relatively weak tax and transfer system compared to those other countries. One of the key takeaways from this paper was if the United States had a tax and transfer system similar to that of the other study nations, we could cut the intergenerational persistence of poverty by one-third.

Goods that people buy but wish did not exist

The name of this paper by Cass Sunstein says it all. There exist goods that people spend money on (sometimes quite a lot) that they do not gain wellbeing from consuming. The main idea is that non-consumption creates worse negative effects compared to consumption, and so people choose to consume these goods anyways. 

Sunstein opens his paper by asking us to imagine that our friend is hosting a party we aren’t interested in going to. Because the party is happening, we feel pressured to go in order to avoid sending the signal to our friends that we don’t like parties, or perhaps we don’t care about them enough to show up. The best case scenario would be if the party was cancelled by the host, freeing us of the social need to attend. In this case, our preference ordering would be 1) nobody attends, 2) we attend along with everyone else, 3) we stay home while everyone else is at the party.

The key characteristic of the goods in question here are that many people would prefer they didn’t exist altogether, but because they do exist people feel compelled to consume them. This is different from something like a home security system that many people don’t get direct welfare from but often purchase anyway. Those goods are sometimes referred to as defensive expenditures, and they don’t quite fit this description because people don’t care about the existence of home security systems, they wish that crime didn’t exist. 

One major example Sunstein discusses is social media. If you ask someone how much they would need to be paid in order to stay off social media for a month, they will tell you that it would take quite a bit of money, around $50. This seems to suggest that people benefit from social media. 

However, you get a different answer if you flip the question on its head. People actually have a willingness to pay for eliminating social media altogether. Some people actually benefit from the existence of social media, but on average it appears that people wish it didn’t exist for everyone.

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These two papers exemplify what draws me to economics the most. The ability to take complicated topics like poverty or seemingly irrational decisionmaking and find a way to quantify it and model it. I’m looking forward to another year of learning in 2026, and I hope everyone has a pleasant end to their 2025.

Debunking the myth: suicide rates do not spike during the holidays

You ever have one of those moments where you realize something you’ve believed for years was completely false? That is something that happened to me last week.

The Planet Money newsletter this week was a round-up of great stories about the holidays. Topics covered included whether stock prices predictably increase during the holidays, why gas prices don’t increase with airline ticket prices during the holidays, and a classic paper by famous scrooge Joel Waldfogel arguing the inefficiency of gift giving.

But it wasn’t any of these that left me shocked. It was instead a two-paragraph story they had about how suicides don’t increase during the holidays.

Am I the only one who didn’t know this? Just last weekend, I was watching the 1984 comedy-horror classic Gremlins with my fiancée and one of the main characters was saying that suicide rates go up during the holidays. Neither of us batted an eye: it seemed to be an incontrovertible fact.

If you clicked the link above, you may be disappointed. The article defending the controversial claim is available for a cool $64 from BMJ journals. But have no fear! The NIH has made the scant review available for free. In this two page review of fifteen studies, six conducted between the mid 80s and early 2000s that were deemed high-quality, a consultant and a physician conclude “suicide and parasuicide rates go down around Christmas (emphasis added).”

Is this true? In recent data, this also seems to be the case. The Centers for Disease Control and Prevention makes fatal injury data available through its Web-based Injury Statistics Query and Reporting System. Using this data, you can see that suicide incidence per month is lower in December from 2021 to 2024 than every other month save one: February. Once you account for the fact that February has three fewer days than December, December is far lower than any other month, with average daily suicides anywhere from 4% (November) to 14% (August) higher in any other given month. Overall, the daily suicide rate is 7% lower in December than it is for the year as a whole. So from 2021 to 2024, suicide rates plunged to their lowest rates of the year in December. This trend has been so consistent over the past four years that December was the lowest daily suicide rate in 2022, 2023, and 2024. In 2021, January’s suicide rate was 0.2% lower than December and April’s was 1.3% lower.

So yes, suicide rates do go down in December.

So why does the myth persist?

One explanation is media. The University of Pennsylvania’s Annenberg School of Communication has been tracking media coverage of the “suicides increase during the holidays” myth for decades and finds dozens of stories nationwide every year perpetuating the myth. Last year was the lowest year in nearly two decades with 19 news reports reporting the myth. A typical year over the course of the study has over 50 news reports claiming suicides spike during the holidays.

I wonder if there is a connection here with the cultural exaggeration of Seasonal Affective Disorder. Despite widespread attention among the general population, studies of the disorder say that, at the high end, population prevalence is only 10% and is likely closer to 1-2%. A retrospective meta-analysis pegged the lifetime incidence of Seasonal Affective Disorder in the single-digits.

The mistaken association people have between the weather and well-being is well-documented. In a landmark study, Nobel-prize winning behavioral economist Dan Kahneman surveyed students at Ohio State University and the University of California, Los Angeles on perceptions of happiness. Both students in Ohio and southern California believed climate and weather was a strong predictor of happiness and both students in Ohio and southern California agreed that weather and climate was better in southern California than it is in Ohio. Despite this, students in California did not report being happier than students in Ohio.

Kahneman calls this mistake a “focusing illusion.” In Kahneman’s words, “nothing in life is as important as you think it is while you are thinking about it.” You see this all the time: students stressed out of their minds about an exam that they will not even remember in a few months, people excited about the prospects for a promotion to a job that will feel normal in a year. Weather is a particularly potent example of this.

No doubt the experience of walking across an academic quad or waiting at a bus stop is different on a 20-degree January morning in Ohio than it is on a 70-degree any-time-of-the-year day in Los Angeles. But what the best evidence shows is that this experience is fleeting. Eventually you get to class or on the bus, to work or home, and then things like whether you have close friends or a spouse, you are involved in your community, and you have a stable job and income impact happiness.

Maybe this is the missing piece of the puzzle around the “suicides go up during the holidays” myth. If well-being is more highly correlated with relationships, involvement, employment, and security than it is with weather, then we should not be surprised that suicides go down during the holidays. The holidays are a time when people spend time with family. If anything, people without connections are not more lonely as the pop culture parable goes. They are just as lonely as ever, while people who are living on the edge, who may usually feel lonely, find connection with others that they do not usually have.

So what can we do to reduce suicide risk in the face of this knowledge? The Annenberg School has collaborated with media organizations to develop a set of guidelines for reporting on suicide that reduce contagion. People should also be aware of 988, a crisis line that someone struggling with suicidal thoughts can dial to connect with someone. In addition to these tools, timing awareness campaigns around months that actually see higher suicide rates like in the summer can be more effective than focusing on the mythological winter rates.

You learn something new every day. Hopefully learning new things can help us make better decisions that will ultimately improve lives.

Three lessons from three years of policy analysis

I started working at Scioto Analysis in September of 2022, which means I am approaching the end of my third full year with the practice. When I started, I was fresh out of grad school and notably had never done any policy analysis before. As I’ve mentioned before, I graduated with a degree in statistics, from a program that had a pretty heavy academic lean to it. 

It was like going to school to learn all about the inner workings and uses of power tools, then getting a job as a carpenter. I had a deep understanding of the tools of policy analysis, but I didn’t yet know how to apply them. 

As the end of the year is approaching, I wanted to take some time to reflect on these first three years and some of the lessons I’ve learned about being a good policy analyst.

Policy analysis is about problem solving

In Eugene Bardach’s A Practical Guide to Policy Analysis, the first step on the eightfold path laid out by the author is problem definition. We start this way because we understand that the world is not currently perfect, and it is the role of the public sector to help us move towards a more perfect world. This is different from the outlook of people in my grad school program, who largely wanted to pursue statistics to further our collective understanding of the field. 

I want to be clear, I believe that what academics are doing is extremely important. We need people to push the frontiers of our knowledge and to try to improve our understanding of the world. 

However, the insights gained from academia need to be applied to the real world for them to improve outcomes for people, and that is a job not always well suited for academics themselves. When we as analysts begin with a problem that we need to solve, it gives us a different lens to approach the findings generated by academics. 

Policy analysis is client driven

An important memory I have from grad school was from a group project in my class called Statistical Consulting. Our goal was to do some analysis for a client that had a bunch of data and didn’t have the technical skills to analyze it. 

My group was a mix of masters and PhD students, and one PhD candidate was insistent that we include a plot in our presentation showing how we found the optimal penalty for our lasso regression. 

I suggested that we shouldn’t include this plot, because although it shows that our methods were valid, it didn’t mean anything to the client. I ended up being overruled by the group, and when we eventually gave our presentation we got the feedback that our presentation was too technical and we should have focused more on the results. 

That kind of information is better suited to an appendix. Those that want to replicate that work or anyone who wants to ensure that we are checking all the necessary technical boxes should have access to that, but the information that matters is what is going to help someone make a better decision, and super technical things don’t make the cut.

Policy analysis should be collaborative

One of the main reasons I was drawn to statistics in the first place was I could not make a decision about what interested me the most. I generally like learning about different topics, and I thought that statistics was broad enough that it could enable me to do research on all sorts of topics, from biology to political science. 

Policy analysis has a similar broad range of applications. My first ever project with Scioto Analysis looked at water quality in Ohio. The second project looked at the Genuine Progress Indicator, a broad economic replacement for Gross Domestic Product.

While this breadth of subject matter satisfies my desire to learn about different topics, it also largely means I’m not an expert in the thing I’m analyzing. I’m an expert in statistics and how to do policy analysis, but we often benefit from talking to people with more subject matter expertise. 

Fortunately for us at Scioto, many of our clients are subject matter experts who are looking for assistance with policy analysis and statistics. That naturally leads to a collaborative process which leads to a better final product. When this doesn’t happen though, it is often smart to seek out people with subject matter expertise to help provide context.

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It’s an exciting time in the world of policy analysis. The availability of good data and the abundance of statistical tools is making it more accessible than ever. The increased supply of analysis is being met with a rising demand, which is leading to better decisions being made by policymakers at all levels of government. At Scioto Analysis, we’re going to keep searching for ways to improve our analysis, as well as ways to get our information to policymakers more easily.

Survey: Majority of Ohio economists agree employment opportunities are driving Ohio’s population growth trend.

In a survey released this morning by Scioto Analysis, 20 of 23 economists agreed that employment opportunities are a major driver of Ohio's current population growth trend. 

The population growth rate in Ohio is currently declining. According to the Ohio Department of Development, the state is expected to lose more than 675,000 people by 2050. By 2030 alone, Ohio is expected to drop from the seventh most populous state to the ninth.

Respondents voiced opinions that employment opportunities affect net migration into Ohio and out of the state. As Kathryn Wilson of Kent State University noted, “Employment opportunities are a contributor on both sides of the ledger. Areas around Columbus that are seeing growth in population are also seeing job growth. Other areas of the state with less job growth are seeing a net migration out of people.”

A majority of economists agreed that state-level decisions on social policy issues are a major contributor to Ohio’s current population growth trend, with 14 of 23 economists agreeing. According to Will Georgic of Ohio Wesleyan University, “If you think of social policy issues as non-market amenities, and if you think that recent state-level decisions have worsened the quality of these non-market amenities, then following a Rosen-Roback type model could support the belief that these decisions are contributing to the State's current population trend.” David Brasington of the University of Cincinnati disagreed with this opinion about social policy issues, suggesting that “Not many people pick a place to live based on social policy. Jobs, climate, geography, quality of life all matter more.”

Opinions on if cost of living is a major contributor to Ohio's current population growth trend were more mixed across economists. Eight economists agreed that cost of living is a major contributor to Ohio’s current population growth trend, eleven economists disagreed, and three economists were uncertain. Multiple economists agree that the relationship between cost of living and Ohio’s current population growth trend may run the other direction. Curtis Reynolds of Kent State University writes, “Cost of living is quite low in most parts of Ohio compared to many other areas of the country but that is partly driven by lack of pressure on the demand side due to declining population.”

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.

What we learned in 2025: 12 Scioto Analysis studies that changed how we think about public policy

2025 is almost in the books! This was Scioto Analysis’s busiest year yet. We released twelve studies to the public this year and we’re very close to releasing a thirteenth before the year ends. Let’s take a look at these twelve studies and what we learned throughout the year.

In January, Scioto Analysis released its first study of the year, a qualitative study of economic barriers faced by immigrants and new Americans in central Ohio. In this study, we interviewed nearly 50 people in central Ohio who are either immigrants or who support immigrants in the region. This was timely due to the election that was occurring while we were doing these interviews and how immigration took center stage as a policy issue. One of the biggest things I learned from this study was the importance of language learning. Person after person told us that immigrants wanted to learn English and were looking for more opportunities to learn it because the resources in central Ohio for learning English do not meet the demand for language learning.

Later that month, we released a study we conducted on the economic impact of cycling and trails in Iowa. In this study, we surveyed over 2,500 cyclists across the state and used those surveys along with data from People for Bikes, the Census Bureau, and the Centers for Disease Control and Prevention to estimate how cycling impacts the state economy and health of Iowans. We found that cycling contributes about $1.4 billion to the state economy every year, saves millions of dollars in health care costs, and prevents hundreds of tons of carbon emissions every year.

In March, we released a cost-benefit analysis conducted by then intern Jacob Strang on wildlife crossings. Wildlife crossings are bridges or underpasses built to help wildlife cross busy road corridors and to reduce collisions with vehicles. I can honestly say that to date, this was the most impressive cost-benefit analysis Scioto Analysis had done, with Jacob monetizing impacts that ranged from construction and maintenance costs to vehicle damage and value of lives saved to ecosystem services and the value of deer, elk, and moose lives.

Later that month, we released a cost-benefit analysis on Minnesota’s child tax credit conducted by policy analyst Michael Hartnett. Minnesota has one of the most generous and progressive child tax credits in the country so we took the model researchers at Columbia University used to win the Society for Benefit-Cost Analysis’s Best Journal Article of the Year Award to analyze the Minnesota child tax credit. We found investment in child tax credits will lead to hundreds of millions of dollars in higher labor market earnings and lower crime costs due to children having more household resources that put them on a better lifetime trajectory.

In April, we released a cost-benefit analysis on universal prekindergarten conducted by intern Omar Rangel. States like Georgia, Oklahoma, and West Virginia all have universal prekindergarten programs, so in this study, Omar analyzed what a universal prekindergarten program would look like in Ohio. He estimated a universal prekindergarten would lead to thousands more children enrolled in prekindergarten programs, which would lead to higher labor market earnings for these children down the road.

In May, we released the first of a series of studies we are doing on Oklahoma’s minimum wage, this one focused on housing affordability. In June of 2026, Oklahoma voters will cast their ballots to decide whether to raise their state minimum wage from the federal minimum wage of $7.25 to $15. In this analysis, we simulated wages at the household level to estimate that the change could pull as many as 40,000 Oklahoma households above the level of being housing cost burdened.

In September, we released the next report in that series, this time on public safety and the minimum wage. Poverty and crime are connected to each other, so policies that can reduce income stress on households can lead to lower crime rates. Using evidence of interaction between minimum wage changes and crime we estimated a $15 minimum wage in Oklahoma would lead to 7,000 fewer crimes per year, including 55 fewer homicides.

Later that month, we released a cost-benefit analysis by our intern Van Woodcock on the Move to Prosper program. This is a program that provides rental assistance and counseling support to move people from low-mobility into high-mobility neighborhoods. We estimated expanding the program would lead to over $100 million in increased future earnings for young children in households involved with the program.

In October, we released a cost-benefit analysis on another universal program: school meals. During the COVID-19 pandemic, the United States Department of Agriculture made the national school lunch program universal for all schools across the country. Since that national program expired, a number of states adopted state universal school meal programs. Our policy analyst Emily Cantrell estimated a universal school meal program for Ohio would lead to hundreds of millions of dollars in increased future earnings at the same time that it reduced health care costs due to obesity and saved parents time preparing meals for their children.

In December, we released a rash of studies. First came the third in our series of studies on the minimum wage in Oklahoma, this time on health. Families with higher incomes have more access to health resources and the health outcomes that come with that. Using our microsimulation model, we estimated a higher minimum wage for Oklahoma would save about 400 lives every year, including 240 infants.

Next came our cost-benefit analysis on a cigarette tax for Ohio by our intern Seneca Baldi. In January, Governor Mike DeWine proposed an increase in Ohio’s per-pack cigarette tax, a proposal that the Ohio House cut out of the state budget. Using the best available data of the impact of price on teenage consumption, Seneca estimated the cigarette tax would be effective at reducing teenage smoking initiation, leading to billions of dollars in benefits to teenagers who never begin smoking.

Our most recent study was a study we released with the Ohio Chamber of Commerce Research Foundation on energy permitting in Ohio. While energy permitting processes allow for community input into energy projects, they sometimes are used by competitors of an energy project to slow or even prevent energy projects from being approved. We found projects pulled from the energy production queue cost Ohio 9,000 megawatts of energy production, $440 million in capital investment, thousands of jobs, and millions of dollars in tax revenue each year.

Before the year ends, we plan to publish a report on home visiting in Ohio. It has been a great year and I’m looking forward to an even better year in 2026!

What is stopping development of solar and wind energy in Ohio?

Last year, I was called to testify at a hearing of the Ohio Power Siting Board on a plan to develop a large solar farm in Knox County.

My firm Scioto Analysis was asked to make some estimates about the cost of climate change for local governments in Knox County and how the solar project could help make up for these costs in the long run.

I was surprised to see the level of scrutiny this project was undergoing.

Installation of a large, clean power project that will bring plentiful, low-cost energy is not something that I would generally expect to be controversial.

But grassroots groups had organized against the project, making dubious claims about environmental impacts and arguing that the project would be “unsightly.”

It has always seemed strange to me that neighbors can have so much of a say in what people do with their land.

If a farmer finds it is more profitable to install solar panels than to use land for soybeans, why can their neighbors go to state boards and argue against that use of their land?

The fundamental argument for this sort of community input in these sorts of projects is that energy developments can have external impacts on community members.

If you build a coal-fire power plant next door and upwind of an elementary school, you expose children on the playground to PM2.5 and NOx emissions, which can cause breathing problems and in extreme cases, death.

Community input helps alert policymakers to these sorts of problems and improve energy projects for the community they are located in.

On the other hand, there is such thing as “too much community input.”

If bad actors abuse the system, the community input system ends up being a tool for slowing or even killing projects.

The Icebreaker Wind offshore wind project in Lake Erie is one example of this. It has dealt with years of delays, mainly at the behest of people who have aesthetic opposition to wind turbines.

This past week, Scioto Analysis released a report with the Ohio Chamber of Commerce Research Foundation on energy permitting in Ohio.

In the face of growing interest in Ohio as a data center hub, many people are worried about Ohio’s ability to keep up with the energy needs associated with these projects.

An efficient energy permitting process is a key to making sure enough energy is available to continue to have these sorts of centers in the state without subjecting the state to soaring energy costs.

Using data from Lawrence Berkeley Laboratories on energy projects in the development queue, we estimated that the state of Ohio loses out on 9,000 megawatts of energy projects per year due to developers withdrawing their projects.

This amounts to about $440 million in lost investment every year, 5,400 fewer jobs, and millions of dollars in lost tax revenue.

There needs to be space for community input. But if the state of Ohio is going to keep up with energy needs and keep energy prices from skyrocketing, it means balancing those needs with the need for energy supply.

Making sure the process serves the needs of ratepayers as much as it serves the needs of residents who find solar panels and wind turbines “unsightly” is paramount to an effective system.

This commentary first appeared in the Ohio Capital Journal.

The importance of the Census Bureau’s race data

At the beginning of this year, I wrote a blog post talking about the changes that the Trump Administration was making to publicly available data. Going back and reading this blog, it’s interesting to see which of my fears were warranted and in what cases I was being reactionary to what was a very uncertain time where data was being removed seemingly at random. 

The good news is that we still have access to a lot of data. The 2024 Behavioral Risk Factor Surveillance System is available for download thanks to a court order, the Census Bureau has released 2024 American Community Survey Data and there is a scheduled release date for the 5-year estimates. Additionally, the team over at IPUMS is working to get the individual microdata ready for release!

Not everything has been smooth however. We asked our Ohio Economic Experts Panel about the firing of Erika McEntarfer, the former Bureau of Labor Statistics commissioner and they agreed that reduced trust in that organization would hurt Ohio’s economy. However, because of the government shutdown, the BLS has said they won’t be releasing some employment data from October. While these events might not be related, this does mean that we don’t have all of the federal data we are used to having.

Near the end of my blog post about public data, I mentioned that in 2024 the Census Bureau was going to be changing the way they collect race data by adding categories for Middle Eastern/North African, as well as adding Hispanic as a race instead of asking a separate ethnicity question. 

Recently, NPR reported that the current Census Bureau is reviewing those changes, opening the door for them to be reversed. While this doesn't necessarily mean that these standards will be undone, it seems likely based on the administration's past track record with data pertaining to race, gender, etc. that it will.

I want to note here that how we collect race data is not an easy decision. Any time we try to categorize people into neat boxes we invariably have to make assumptions and decisions that harm the overall quality of the data. However, some options are better than others. 

The old way the Census collected race data was worse than the 2024 standard. The only argument that I can think of against it is that changing that question makes comparisons to past years of data more difficult, but I think the improved understanding of the present and future far outweighs those costs. 

I don't even think it would be too difficult to compare to previous years if you take the time to look at the microdata. WIth a couple of assumptions about how people would be classified under the old system, you could seemingly reconstruct those estimates and get those backward comparisons. It wouldn’t be perfect, but I bet that if dedicated researchers took their time they could produce fairly accurate estimates. 

While I don’t expect this to happen, it has crossed my mind that a review of the race standard might mean some other change as opposed to a revision back to the previous rule. The worst-case scenario would be if the Census Bureau decided to not ask a question about race and ethnicity at all. As I said before, there is no “right” way to collect race data. However, we would all be worse off if a change diminished our understanding of race in this country. 

The 2030 census is still a long way away. However, projects that big and ambitious require immense amounts of planning and preparation. Decisions made now about the survey will have major ramifications that we will feel for a very long time. I hope that the Census Bureau’s review doesn’t undo this particular change. It might not be perfect, but it’s better than what we had before.

Original Analysis: Energy Permitting in Ohio

This week, the Ohio Chamber of Commerce Research Foundation released an analysis conducted by Scioto Analysis on Ohio’s energy permitting process. This analysis focused on the impacts of the energy permitting process on energy supply, economic growth, and development of Ohio’s energy infrastructure.

Key findings from the report include the following: 

• $440 million in capital investment is lost every year due to energy projects withdrawing from the queue.

• This leads to 5,400 fewer jobs in Ohio every year, including 2,600 high-paying construction roles.

• 9,000 Megawatts of potential power generation have been withdrawn each year since 2016.

• $3.2 - $4.3 Million in state income tax revenue are lost annually due to withdrawn projects.

“When permitting is an excessive burden to developers, Ohio loses solar, wind, and other energy projects to other states,” said Scioto Analysis Principal Rob Moore, “this leads to less energy supply and higher energy costs for Ohio ratepayers.”

The report also includes several recommendations for improving the permitting process in Ohio, including enforcing statutory timelines, expanding accelerated reviews, and modernizing community engagement.

“Energy permitting in Ohio is not perfect, but with some changes, the system could be improved, more projects could get online faster, and Ohio can avoid the energy crunch that other parts of the country are already seeing,” said Moore.