Scioto Analysis releases 2026 State Handbook of Cost-Benefit Analysis

This morning, Scioto Analysis released the 2026 edition of the State Handbook of Cost-Benefit Analysis. The State Handbook of Cost-Benefit Analysis is a handbook for state analysts interested in adding cost-benefit analysis to their analytical toolkit.

Cost-benefit analysis is a tool to evaluate the social costs and benefits of public policy through an economic lens. The 2026 edition provides analysts with the history and theory behind cost-benefit analysis and it provides comprehensive guidance and examples for conducting cost-benefit analysis. Designed for administrators, policymakers, and engaged citizens, the Handbook walks through how to establish a baseline, construct alternatives, establish a standing, complete quantification and monetization, categorize costs and benefits, discount impacts appropriately, conduct sensitivity analysis, and communicate findings. 

The 2026 edition focuses on the analytical process of conducting cost-benefit analysis and expands upon quantification, monetization, and communicating results. Cost-benefit analysis is a useful tool, even for administrators, policymakers, or citizens with limited analytical resources. 

Cost-benefit analysis is used commonly at the federal level but is still underutilized at the state level. Analysts who are interested in promoting evidence-based decision making among policymakers and administrators should consider using the State Handbook of Cost-Benefit Analysis to adopt cost-benefit analysis in their analysis.

Economic development and the “winner’s curse”

I feel like I’m a broken record sometimes talking about how much Planet Money sparks ideas for me to write about public policy. But, they’ve done it again. And this time it is around a concept called the “Winner’s Curse.”

Planet Money’s recent story was focused on the re-release of Richard Thaler’s The Winner’s Curse, a 1991 book on a concept he had pieced together in his work pioneering the field of behavioral economics. Since this book was published, Thaler has won the Nobel Prize in Economic Sciences and the field of behavioral economics has gone from fringe to mainstream.

Thaler’s central concept in “The Winner’s Curse” is that there are certain times that bidding wars can push people into irrational behavior. Theoretically, each person should have a specific willingness to pay for a good in a bidding war. Theoretically, a bidding system creates an efficient system of allocation where people increase their bids until their willingness to pay, then do not bid anymore. This means that the person with the highest willingness to pay will then stop on their last bid, receiving the good at the lowest price possible according to the market.

So let’s say you have a “priceless” Dalí painting. Adam really wants it and is willing to pay $3.5 million. Beth wants to buy it as well and is willing to pay $2.9 million. Adam initially bids $2 million. Beth increases the bid to $2.5 million. Adam increases it to $3 million. Beth does not bid any longer, since the price has exceeded her willingness to pay. So Adam buys it at $3 million, receiving $0.5 million in consumer surplus since he would have paid up to $3.5 million.

A problem with this model is the following: why do sellers put their goods up to auction? Ideally, a seller wants to get the most producer surplus possible, which means pushing the buyer as close to her willingness to pay as possible. What benefits does an auction bestow the seller?

Well one problem is an information problem. You will notice that many auctions are for goods with indeterminate value. There is no market for rare Dalí paintings, so we can’t determine what the market value is. So having buyers go to auction over it helps solve that problem.

Another explanation, though, is that auctions may do a different service for the seller. It may induce the buyer to act irrationally.

What if Beth doesn’t stop at $3 million, but instead jumps to $3.5 million to top Adam? Then Adam jumps to $4 million to top her? Suddenly, each of the bidders are above their willingness to pay. Suddenly, the person who wins will end up with the curse of negative consumer surplus from something they will buy and the seller will run away with a bigger payment than they ever could have got without the auction.

This is the curse: how auctions can lead us to act irrationally by playing on our competitive spirits. The win is fleeting: ultimately, the prize is not worth what we pay for it.

What this reminded me of was economic development.

We’ve all heard about it: the exorbitant packages that are given away in tax incentives to lure businesses across borders. When Amazon announced its “HQ2” project, it became the ultimate prize for economic development professionals. Local governments across the country scrambled to offer whatever they could to get into the running, with the winners ultimately stuck with the tab.

The leading national researchers on economic development incentives have concluded that somewhere between 75% and 98% of projects would have been sited in the same place they ended up going to without economic development incentives. That means that in somewhere between three-quarters to nearly all projects, the market clearing price for incentives is zero. All that money that is being spent by most economic development projects is pure producer surplus for the people selling their new development.

Why do cities keep suffering the winner’s curse? A few reasons.

The game is set as a competitive game for economic development professionals. Economic development professionals don’t get rewarded for passing up projects that get too expensive, they only get rewarded when they land projects. This creates an incentive for them to overpay for projects and promise more in the form of deferred tax revenue than the community’s willingness to pay for the project.

A reason this materializes is due to lack of transparency in projects. Often, in the name of securing a “competitive edge,” economic developers who are in charge of creating incentive packages are shielded from the public. This allows them to privilege their own interests over the interests of the public. They will not ultimately pay for giving away too much in deferred taxes: the public will. They will pay, though, if they do not win the development project. This worsens the principal-agent problem between economic development professionals and the public and makes it more likely for developers to fall into the winner’s curse.

This insulation from the public also worsens another problem: a lack of clear, stated goals. If you go into an auction and do not know what your willingness to pay for that Dalí is, you become a sucker for the winner’s curse. You will make “winning” the goal instead of maximizing consumer surplus. Often, economic developers do not have a walk away price or a goal other than to win the economic development project. This predictably leads to them becoming victims to the winner’s curse.

Economic development is not about “winning,” but by pitting different sites within different communities against each other, corporations are able to utilize auction dynamics that ultimately get communities to jack up their offer prices to the point where they exceed the point of marginal social benefits. In the economic development world, the winner’s curse is real. Only by rooting economic development incentives in a framework of social value will economic developers be able to sidestep the winner’s curse and focus on projects that maximize social value. Until then, the economic development world will continue to bear the curse.

Does forecasting actually work?

Most of policy analysis and indeed most of the work we do at Scioto Analysis is forward-looking. We sometimes look back at policies that have been put into place to determine what effects they had (which is sometimes called “evaluation” and sometimes called “ex post analysis”), but in order to help policymakers make better decisions, we need to be able to give them information about what will happen if they choose to enact a given policy.

We call this “forecasting,” but if you want to be less technical, we’re trying to predict the future. We have tools that give us confidence that our predictions are better on average than just randomly guessing about the future, but at the end of the day we are making a claim about something that has not happened yet. 

One question you might have about forecasting is straightforward: does it work? If people are making so many predictions, why don’t we just do some evaluation and see if they are accurate or not?

A new working paper from the National Bureau of Economic Research tries to answer this question. 

In this study, economists looked at 100 social science projects which made tens of thousands of forecasts between 2020 and 2024. They wanted to find out whether or not these forecasts were successful at predicting what would happen in the future, and if they were able to identify any characteristics that made people better or worse at forecasting. 

The good news is that, in general, the forecasts they looked at had predictive value. There was a tendency for forecasts to overestimate the treatment effect, but in general, a forecast was able to provide meaningful insight about the future. 

This study also supported the “wisdom of the crowd” hypothesis. When the researchers found multiple forecasts about the same topic, then the average of those forecasts would be a better predictor than any one by itself. 

When looking at the quality of predictors, the researchers found that academics (professors and top-ranking PhD students) performed better than non-academics. Since results tend to be overestimated, this generally means that these academics are finding smaller effect sizes, which might explain why they have the perception of being cautious. In a similar vein, the researchers found out that people who were more confident in their estimates tended to perform worse than people who were less confident. 

Overall, I think this is a success story for forecasters. When I think about the information a policymaker tends to want, the first thing we need to do is make sure our effect direction is correct. If we say a policy is going to grow the economy, then it better not shrink it. 

Of course, we want to be as accurate as possible and any good policy analysis should be rigorous, but getting the direction correct already gives policymakers information to make their decisions with. 

At the end of the day, the goal of analysis is to inform better decision making. This paper suggests that in general, social scientists are doing a good job at getting the main idea right. We should probably be skeptical about the magnitude of some effects, but overall, research helps us understand what the future might hold.

What would a measles outbreak do to your community?

Last week, the Centers for Disease Control and Prevention released new information on its website reviving a widely-debunked claim that vaccines could be linked to autism. U.S. Department of Health and Human Services Secretary Robert Kennedy subsequently took responsibility for the website change change.

From a public health standpoint, the danger of misinformation around vaccination comes from the possibility that vaccination rates will fall. Vaccination is one of the best tools the public has to prevent the incidence of life-threatening diseases and reduced rates of vaccination can lead to diseases being reintroduced into local populations.

Despite the Centers for Disease Control and Prevention’s new website information, the site still hosts an useful tool for answering questions around vaccination and one major disease–measles. The Centers’ Measles Outbreak Simulator lets anyone simulate a measles outbreak in a community and what different vaccination rate and policy interventions would do to stymie the spread of the disease in the public.

Let’s look at a community of 100,000 people to see what the simulator tells us.

First, let’s look at the best-case scenario. Currently, West Virginia’s measles vaccination rate is over 98%, the highest in the United States. If a community of 100,000 with 98% vaccination rate has a measles case, the simulator expects only one measles case will occur and no one will be hospitalized. Widespread vaccination works. If we drop this number to a 95% vaccination rate, the goal rate for vaccination and the rate we see in Tennessee, we only get one additional case and a single hospitalization.

Most states are below this rate, though. The median U.S. state, South Carolina, is at 92% measles vaccination. The introduction of a single measles case in a 92% vaccinated community, though, would only lead to a total of five measles cases in our simulation community, and only a single hospitalization.

Things start to pick up once you drop below this median number, however. The 25th percentile of states (states like Arizona and Hawaii) are vaccinated at under 90%. A single measles case introduced in a community of 100,000 with 90% vaccination coverage would blossom into a total of 5,800 cases and about 860 hospitalizations. If the death rate mirrors 2025 U.S. death rates, an outbreak like that would lead to about 10 deaths.

Things get even more dangerous once you drop below 80%, which only the state of Idaho has done so far. A community of 100,000 with 80% vaccination rates would see over one in five people infected with measles, about 21,000 cases and 3,100 hospitalizations. At current U.S. measles death rates, this would also lead to about three dozen deaths.

Okay, so let’s say we get to this disaster scenario and a community at 80% vaccination rate has a measles case introduced. What can they do? Well, the simulator from the Centers for Disease Control and Prevention also lets us test different interventions.

One intervention is to catch up with vaccinations. If the community starts a vaccination campaign a few days after the first case is caught and gets 75% of unvaccinated people vaccinated over the course of a few weeks, total measles spread will drop to 16, a 99% reduction and three dozen lives saved. Even vaccinating half the unvaccinated population would lead to a 57% reduction in measles cases and save 21 lives. A more conservative campaign that only gets 20% of the unvaccinated population vaccinated would cut infection rates by 21% and save seven lives. 

Less aggressive vaccination campaigns that vaccinate people more slowly or begin later are also effective at reducing measles spread. Even a five-month vaccination campaign started at the beginning of infections and reaching a total of 20% unvaccinated population vaccination rate would have similar results to stymie the spread. Similarly, a vaccination campaign that begins a few months after the first measles case is similarly effective to one that starts a few days after the first measles case. This means that the public health response should not feel like they “missed the boat” if they did not respond right away: widespread vaccination can still make a difference as long as it is implemented within a few months of the first recorded cases.

What if a community isn’t willing to turn to widespread vaccination? Another option is isolation of measles cases. The problem with this intervention is how quickly measles spreads. If 50% of people who contract measles isolate for a whole year each, only 9% of measles cases would be prevented. These durations of isolation are likely unachievable, making this an unviable strategy for making strong gains against measles.

Another option is quarantine. A communitywide quarantine would have to last more than a month and achieve 50% adherence to significantly reduce measles rates. A community of 100,000 would have to work very hard to achieve these adherence rates for this duration to stop the spread of measles in their community.

What I learned from this simulator is this: vaccination is still king when it comes to measles. As much as a barrier vaccine hesitancy is, isolating people who contract the disease from the public for a year or shutting down a community for over a month are each less practical and more disruptive than community-wide vaccination campaigns.

Which brings us back to the public policy issue at hand. The Centers for Disease Control shares in their own simulations that vaccination is the best way to prevent spread of dangerous communicable diseases. Scaled up to a state like Ohio, vaccination rates dropping from its current 89% to 80% could mean thousands of measles deaths per year. State health departments have a strong interest in combatting sources of misinformation that lead to vaccine hesitancy among the general public. If people skip out on vaccination, it puts them in harm’s way, and it also endangers their neighbors. Preventing states from backsliding on vaccinations means saving lives, preserving individual choice, and keeping the economy on its rails at the same time.

Survey: Majority of Ohio economists agree new Ohio affordable childcare program will improve educational outcomes for children.

In a survey released this morning by Scioto Analysis, 13 of 19 economists agreed that the new Child Care Cred affordability program announced by Ohio Governor DeWine in September 2025 will improve educational outcomes for children in Ohio. The Child Care Cred affordability program will allow families whose incomes are between 200% to 400% of the federal poverty line to share childcare costs with their employers and the state. Through the program, employees will cover 40%, employers will cover 40%, and the state will cover the remaining 20% of childcare costs.

Respondents voiced opinions that subsidized childcare can improve educational performance later in life, free up money for parents to spend on other resources for their children, and help improve social mobility among low-income children and families. As Jonathan Andreas of Bluffton University commented, “Most children in America have gotten an educational boost by going to professional childcare centers because the average American kid grows up [in a] low-income, low-education household where they get less mental stimulation than they would get in a professional childcare center”. 

Michael Jones of the University of Cincinnati disagreed with the consensus, suggesting that if the Child Care Cred affordability program pushes mothers back to work more quickly, child educational outcomes may suffer. He notes, “A growing body of research shows that mothers who spend more time at home with their young children, rather than rushing back to work, see better outcomes for both themselves and their children. [...] In addition, children who spend more time with a parent in their early years (rather than in institutional care) can realize increased cognitive skills and stronger emotional development”. 

While most economists agreed that the Child Care Cred affordability program would improve educational outcomes for children, they had mixed opinions on how work requirements for public childcare programs would impact economic outcomes like unemployment rates. In Ohio, parents must now work at least 33 hours per week to qualify for full-time publicly funded childcare benefits. Three economists agreed that work requirements for publicly funded childcare will reduce unemployment rates, nine economists disagreed, and nine economists were uncertain. David Brasington of the University of Cincinnati disagreed that work requirements for publicly funded childcare will reduce unemployment rates, explaining that, “Almost all daycare subsidy recipients use the daycare money to free up time to engage in market work already”.

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 information do policymakers use to make decisions?

Last week, I was at the Association for Public Policy Analysis and Management’s annual research conference. In past years at this conference, I’ve spent most of my time at sessions talking about specific areas of policy research. This year however, I got to go to more sessions looking more generally about the tools of policy analysis. 

One of these sessions had a presentation by someone from The People Lab at Harvard. This was not necessarily a presentation about methods like some of the more technical presenters, but rather it was what information researchers include in their papers compared to what information policymakers use to select policies. 

To do this, the researchers are surveying as many local government employees as they possibly can. In the survey, government employees are shown two randomly generated policies and some key characteristics about them. For example, they might be shown two policies to address housing in a hypothetical city. Policy A has a large effect size but is high cost, Policy B has a smaller effect but a lower cost.

On each policy, the respondent is shown information about the experimental design (e.g. is it a randomized control trial or an observational study, etc), the policy’s general effects (e.g. effect size, variance, costs, etc), and some other contextual factors (e.g. political feasibility, would it require hiring new staff, etc).

Based on their preliminary results,* the researchers were able to determine which factors were most important in the decision making process for government officials. The five most important things that drove decision making were:

1. Short-term outcomes

2. Political context

3. Long-term outcomes

4. Study year

5. Whether a study had been replicated

The second part of this research project was to scrape data from research journals and see how often these different topics were brought up in academic research papers. Looking at the same list again, the reported percentage is the share of academic papers that include some mention of each of these categories. 

1. Short-term outcomes - 95%

2. Political context - 5% 

3. Long-term outcomes - 57%

4. Study year - 98%

5. Whether a study had been replicated - 9%

Compare this to the categories that policymakers cared the least about and we can clearly see that challenges that communicators of research need to overcome: 

     10. Sample size - 94%

     11. Statistical significance - 93%

     12. Evaluation method - 100%

Policymakers do not care as much about some of the things that researchers spend the most time thinking about. Those bottom three categories are three of the most important things I look for when trying to determine the relative quality of a research study. In an ideal world, policymakers would care more about these too since they are good indicators of the chances that a policy studied elsewhere will have similar results in their jurisdiction. 

However, I don’t just think that policymakers need to care more about variance. This list also clearly shows academics some ways they can make their research more relevant. Take the relative importance of long-term outcomes. Only a little of half the studies these researchers looked at measured long-term outcomes, despite the fact that it is something policymakers care a lot about. 

Additionally, policymakers care a lot about whether a study has been replicated. If an academic is only replicating a past paper, then they aren’t contributing nearly as much new information to the field. Replication studies are still extremely important for increasing our understanding of a topic, but there exists a bias against such studies.** 

The final and largest gap between academics and policymakers is the discussion of the political context. While it may not be appropriate for an academic paper to take a political stance, it would be beneficial to policymakers if there was some information about the political context in which a program was studied. 

There is a lot we can take away from these early survey results. We know this gap between academics and policymakers exists, and we at Scioto Analysis try to bridge that as best we can. Still, we’d be better off if policymakers and academics were more aligned on the things that matter most. 

* This was presented as a work in progress. The researchers were receiving their first wave of survey results the week leading up to this conference, and they expect these results to change somewhat by the end of the project.

** Replication studies that find different effects than the original are actually preferred, but if a researcher thought a study was well done and that they would find similar results then they would be disincentivized to try and replicate it.

Should Ohio inmates be allowed to work remotely?

With October finally coming to an end, last week I changed out my rotation of vampire books on tape for my old favorite podcast: Planet Money.

Each time I spend an extended amount of time away from this podcast, I return wondering why I had. This time was no exception.

The episode I returned to was focused on a new class of remote workers, this time operating from prisons in Maine.

During the COVID-19 recession, the rise of remote work led to new opportunities for inmates to take classes and work toward getting high school and college degrees.

Naturally, the rise in remote opportunities and connections made through education also led to interest in having inmates engage in remote work.

Administrators saw remote work as an opportunity to reduce recidivism by helping reintegrate inmates easier and they also saw it as an opportunity for inmates to make money to pay court fees and restitution to victims and their families.

I should make clear: these are not prison workers making nominal amounts in order to qualify their work as employment. These are inmates making market-clearing wages.

The compensation was so good that both the inmates asked in the story declined to say how much they made, though one software developer confirmed he was making upwards of $100,000.

These wages go toward taxes, court-ordered restitution, child support, room and board, and what is left after that can be kept by the inmate.

In an era when employers are wringing their hands about talent, Ohio’s incarcerated population is a group of people who do not currently have access to many employment opportunities.

According to the state of Ohio, nearly 46,000 people are currently incarcerated in Ohio prisons, which equals nearly the entire population of Mansfield.

Of those 46,000 inmates, nearly three-quarters are in minimum- or medium-security prisons.

But most do not have access to opportunities to work for market wages.

Standard inmate wages as laid out in the Ohio Administrative Code cap at $24 per month.

About 1,200 inmates (less than 3% of the total prison population) take part in the Ohio Penal Industries program, which is authorized to pay above the $24 per month limit for employment for workers.

Of these, it is likely only a few hundred took part in the Prison Industry Enhancement Certification Program, which pays market wages, and none took part in remote work.

A report from earlier this year says 40 Maine inmates took part in their Resident Remote Work program.

That is a little over 2% of Maine’s 1,800 inmates. If a program in Ohio had a similar uptake, that would mean about 1,000 Ohio inmates would be taking part in remote work from prison.

Yes, there are some risks associated with remote work.

But overall, this program has given an opportunity for inmates in Maine to contribute, develop their human capital, escape the recidivism cycle, at the same time that they earn resources that help pay child support, restitution, court fees and taxes, and for investments in the future and provide support for employers who need them.

Why shouldn’t Ohio have this opportunity, too?

This commentary first appeared in the Ohio Capital Journal.

What Drives Energy Prices?

Recently at Scioto Analysis, we’ve been talking about energy. We just asked our Ohio Economic Experts Panel about the potential impacts of nuclear energy, and we’ve been working on projects behind the scenes looking at funding energy projects as well as energy regulations in Ohio. In the past, we’ve also worked on a project that mapped out how the energy storage industry could grow throughout Appalachia.

The reason energy is such a pressing public policy topic is because our energy demands are quickly changing. Data centers, electric vehicles, heat pumps – electrification is coming and that means our demand is increasing. 

In a vacuum, higher demand means higher energy prices. However, markets rarely work exactly like they do in a high school economics textbook, and the energy market is certainly no exception. 

To better understand what actually drives energy prices, we can look to a technical report published by the National Renewable Energy Lab. In this report, researchers explain what factors led to an increase in energy utility prices between 2019 and 2023. Today, I wanted to go over some of these reasons and explain how policymakers might use some of this information. 

First, a question: If people consume more energy, do you think utility costs would increase or decrease? If you realized that this is a trick question and guessed they decrease, you’re right!

The reason more consumption can lead to lower utility rates is because energy utilities have massive upfront costs that they need to finance by selling electricity. In other words, when you plug your phone charger into an outlet in your home, you aren’t just paying for the electricity that you are consuming, you are also paying for a portion of the massive capital expenditures that utility companies incur each year. 

When more people consume electricity, the laws of supply and demand tell us that the cost of that electricity should increase. However, when that also means everyone gets a smaller slice of the fixed costs pie, they find that the unit cost of electricity decreases.

Another reason that increased consumption might not always mean increased costs is because the cost of fuel for electricity generation is extremely variable. According to the report, about 40% of electricity generation in the country is fueled by natural gas. The price of natural gas can vary a lot from the supply side, meaning that only focusing on the demand for electricity doesn’t give us the full picture of prices.

Diversifying the means by which we generate electricity will make the price of electricity more consistent from the supply side. As renewable energy generation becomes more common over time, we should expect the demand side effects to have relatively larger impacts on the utility cost of electricity. 

For policymakers concerned with rising costs, understanding the drivers of utility costs is extremely important. One takeaway from this report is that capital expenditures are a huge factor driving utility costs, and data centers are going to change the energy landscape. These facilities require enormous amounts of reliable electricity which means utilities must build out new transmission lines and reinforce existing infrastructure to handle the load.

For policymakers, this shift underscores the need to plan ahead. Unlike fuel costs, which fluctuate with markets, transmission and distribution investments are long-term commitments that lock in expenses for decades. If regulators and legislators fail to anticipate these needs, communities may face sudden rate hikes as utilities scramble to recover costs. Careful oversight of utility capital projects can spread costs more evenly and ensure that economic development tied to data centers and electrification does not come at the expense of affordability.

What can Ohio lawmakers do in the face of SNAP cuts?

In part of its tug-of-war game with Congress, the Trump Administration announced last week they would be cutting payments to Supplemental Nutrition Assistance Program (SNAP, formerly known as “food stamp”) families as a way to pressure Congress to end the federal government shutdown.

This means 1.4 million Ohioans will have benefits reduced this month. Since the average per-person benefit is $186, that means Ohio will lose about $130 million in food support in November if the administration goes through with this threat.

While the SNAP program is ostensibly about food assistance, the program has a range of impacts.

According to at least some research, SNAP is an effective food insecurity program. Urban Institute researchers estimate SNAP recipiency reduces the chance of being food insecure by 30%.

Researchers at the Center for Science in the Public Interest followed families that newly received SNAP, finding their food insecurity rates dropped by 11% six months into the program.

SNAP is also an income support and antipoverty program. Since families still usually spend more of their income on food than their SNAP benefits cover (try feeding even your most peckish family member for a month on $186), SNAP benefits effectively free up resources for households to make other purchases.

Urban Institute researchers found that the 2021 update to the Thrift Food Plan used to set SNAP benefits kept 2.9 million Americans out of poverty.

On top of being a food insecurity and antipoverty program, SNAP is also an economic stimulus program.

When low-income people receive payments, they tend to spend them, which then puts money in the pockets of workers at grocery stores, who use it to pay rent, buy their own groceries, and purchase other necessities.

The United States Department of Agriculture estimates that every $1 spent on SNAP leads to $1.54 in increased Gross Domestic Product.

This can be especially important during economic downturns, when SNAP acts countercyclically to pump more money into the economy when the country needs spending the most.

So if Ohio’s federal support for fighting food insecurity, poverty, and stimulating the economy is going away, are there things the state can do to pick up the slack?

One option the state of Ohio has is funding nutrition education.

Initiatives like the SNAP-Ed program are effective tools for helping families meal plan and spend money strategically, showing in randomized controlled trials in other states to reduce food insecurity by as much as a third. 

This can be a strategy the state can use to reduce food insecurity even in the face of SNAP cuts.

To fight poverty, Ohio lawmakers can use tax credits like the earned income tax credit or the child tax credit.

These sorts of programs put cash in the pockets of low-income workers while helping children get off on the right foot, supporting their health and income in the long-run.

To stimulate the state economy, one of the most powerful tools lawmakers have is state education spending, particularly early education spending.

Expanded access to high-quality prekindergarten education is a tool that can be as effective as well-designed economic development incentives at increasing local incomes in the long-run.

Ohio lawmakers can only do so much to control federal politics.

But if lawmakers want their constituents to be food secure, free from poverty, and to have economic opportunities in a thriving economy, they have options to let them do that.

This commentary first appeared in the Ohio Capital Journal.

What can Colorado expect from universal free school lunch?

This week, voters across the country went to the polls to vote on a bevy of state and local candidates and issues. You would be forgiven for thinking that because it is not a federal election year, there were only votes being cast in New York City, Virginia and New Jersey, but I promise there were elections across the country. 

In my hometown of Saint Paul, we just elected a new mayor, voted to increase property taxes, and voted to allow administrative citations for certain violations of city ordinances. Today though, I wanted to talk about one election result that may have flown under some people’s radar.

Colorado’s Propositions LL and MM passed on Tuesday, which are both related to funding the school’s universal free school breakfast and lunch program. The specific mechanisms between the two propositions are different, but in essence they both asked voters to decide if they wanted to allow the state to collect additional tax revenue to fund this program.

The reason Colorado had to ask voters to collect additional revenue is because they underestimated how popular the program would be, and they did not allocate enough money at the outset. Minnesota faced similar challenges when we rolled out our free school meal program, with uptake being higher than expected. 

At Scioto Analysis, our most recent cost-benefit analysis was about the impact that universal free school meals would have in Ohio. We found that despite the fact that many students already qualify for free meals, making the program universal would still create large positive impacts for the state.

In a blog post I wrote on that paper, I talked about some of the reasons that making a program universal could have some inherent benefits, even if the benefits are accruing to people who might not have difficulty accessing something on their own. However, in the specific context of universal free school meals, we find that big benefits accrue to families that don’t otherwise struggle with food security. 

One major benefit that accrues to parents is the time saved that they otherwise would have to spend preparing and packing lunches for their children. In Ohio, we estimated that time spent not packing lunches could be worth $15 million to parents of children over the course of a year. I would argue the fact that Colorado and Minnesota both had more people take advantage of the free meals being provided is evidence that parents do have high values for this time. 

The unexpectedly high uptake of universal free school meal programs in states like Colorado and Minnesota suggests that their appeal extends beyond families facing food insecurity. For these families, the value lies less in the meals themselves and more in the convenience and time savings. Preparing and packing lunches every day represents a real cost in terms of time spent, and when presented with an appealing alternative, parents respond accordingly. 

Our research suggests that the benefits of providing free school meals outweigh the costs. Colorado voters seem to agree with that assessment. We’ll have to wait and see how today's students benefit in the long run from this policy, but we can be certain that many parents are getting some of their precious time back.