What is “economic growth?”

When I started Scioto Analysis in 2018, the first thing I did was conduct a study on economic growth. Even before I registered with the Secretary of State’s office, created a website, or even told most people I was starting this practice, I was working to investigate what economic growth looks like in the United States.

In January, I wrote a blog post about what defines “the economy.” The definition I put forth is the following:

“The Economy” = Formal Market Activity + Informal Market activity + Nonmarket Activity + External Costs and Benefits of Market Activity

Overall, when we talk about “the economy,” we are talking about the sum of all the stuff (tangible and intangible) in society and the intensity of people’s desires for that stuff. We measure the sum of stuff by counting it and we measure the intensity of people’s desires for stuff by estimating their “willingness to pay” for it.

The core measure we use at Scioto Analysis to estimate the size of the economy is the Genuine Progress Indicator, a “GDP+” measure that estimates the economic value of environmental and social indicators next to traditional economic indicators.

The value of the Genuine Progress Indicator is that it gives us a holistic picture of the economy, correcting for problems in Gross Domestic Product like valuing environmental damage cleanup and excluding economic activity like caring for children at home. Another value of the Genuine Progress Indicator is that it gives us an idea of how the economy has changed over time.

A chart that usually comes with a Genuine Progress Indicator study is a line chart comparing growth of the economy as measured by the Genuine Progress Indicator compared to the growth of the economy as measured by Gross Domestic Project. The figure below is from our 2023 study comparing the two measures and their relative growth over time. The trend is usually the same in Genuine Progress Indicator studies: once you factor in the adjustments for environmental damage, social value, and economic growth that the Genuine Progress Indicator makes, economic growth is not as robust as it is under Gross Domestic Product.

So how do we know if a public policy will grow or shrink the economy? That is the task of cost-benefit analysis.

Cost-benefit analysis has at times been described as “applied welfare economics.” When we say “welfare,” we’re not referring to the shorthand for social programs that give assistance to low-income people. We’re talking about welfare in the sense that it was used in the preamble to the United States Constitution, when one of the aims of the document was to “promote the general welfare.” 

More specifically, when we say “welfare,” we’re talking about it in the sense of Arthur Pigou in his foundational text in welfare economics, The Economics of Welfare.

Basically, “welfare” defined in this sense is the same definition we have for “the economy”: it is the sum of all the tangible and intangible stuff people have a willingness to pay for minus the sum of all the tangible and intangible stuff you would have to pay people to have. So a society that has more stuff people want is a society with a larger economy (higher “welfare”) than a society with less of that stuff.

Cost-benefit analysis is the systematic analysis of a public policy to see if it grows the economy (increases welfare) or shrinks it (decreases welfare). Whenever we are conducting a cost-benefit analysis, that is the project we are undertaking.

This is admittedly an opinionated take on the definition of “the economy.” Many people will claim that “the economy” should be restricted to activity conducted in formal markets to limit confusion. The line grays here, though, with informal markets where dollars change hands and taxes are not paid. Or with nonmarket activity like spending your time caring for children at home while not being paid for it. Or external costs and benefits. While there is certainly value in analyzing the formal market, drawing the line of consideration of public policy at its boundaries leaves a lot out, even when just trying to answer this admittedly narrow question of how we maximize the amount of stuff people want in a society.

Another objection to this line of thinking comes from an environmental sustainability angle. There are a lot of thinkers in the environmental economics world who are skeptical of the idea of growth due to concepts of planetary limits. This has led many to be drawn to ideas like Kate Raworth’s Donut Economics. But “maximizing the stuff people want in society” does not mean “maximizing material goods.” A full conception of the “economy” acknowledges that allowing wild land to not be used and developed is a type of “stuff” that we can elicit willingness to pay for with survey research. The same goes for the value of basic research, time spent with family and resting, reductions in risk of death, and even the value that people in the future place on ecological stability. If anything, this conception of “the economy” is better at promoting ecological stability than either a narrow conception of the economy focused on formal economic activity or the faint sketch of a framework laid out in books like Donut Economics.

An objection someone may have to the value of economic growth can come from another angle, and I’ll call this the “Buddhist Objection.” The objection is this: why should strength of preference matter? If an advertiser is able to convince someone to the point where their willingness to pay for a pair of jeans rises from $40 to $400, does value really increase tenfold? Conversely, if someone learns to live more simply, desiring less, should we consider that a loss to society as a whole?

I think this last critique of economic growth is a deeper one, and gets at something more fundamental than these other critiques. What I think makes it a valuable critique is that it gets at something we also focus on at Scioto Analysis: the essential pluralism of public policy analysis.

No one framework will be able to tell us with certainty what makes good public policy. The policy with the highest net present value, which means it grows the economy and general welfare the most, is not always the “best” public policy. Neither is the policy that reduces poverty and inequality the most, that improves health and education the most, or that improves subjective well-being the most. Each of these frameworks is just one way for us to understand a deep question that people have debated for millennia: what makes a good society?

My most truthful answer to this question is “I don’t know.” My most practical answer to this question is that a society where more people have more of what they want, where poverty and inequality is lower, where the population is healthy and educated, and where people evaluate their lives positively is a probably better society than one where people have less of what they want, where poverty and inequality is high, where people are unhealthy and lack education, and where people believe their lives are not going well. And we as analysts have precisely the tools to help us evaluate which of those worlds we live in and how to get closer to one than the other.

What do people do if they aren’t working?

The American Time Use Survey is one of the most fascinating publicly-available data sets. The concept is deceptively simple: the Bureau of Labor Statistics takes a nationally representative sample of Americans and surveys them on how and with whom they spend their time. The insights we glean from them tell us so much about how America uses its most precious resource.

Just last month, the 2024 data was released. This gives us the opportunity to once again dive into this dataset and see what sort of insights we can uncover.

Figure 1: People without jobs spend more time on leisure and household activities

The biggest difference between people who work full time and people without jobs is naturally the time spent working. On an average day, someone who is employed full-time spends about 6 hours working, compared to only about 5 minutes for people without jobs. While these people may not directly be engaged with the labor market, this creates an opportunity for them to engage in other valuable activities. 

The category that people without jobs spend the most time on relative to people with full time jobs is “leisure and sports.” On average, someone without a job will spend an additional 2.7 hours on leisure activities (6.7 hours compared to 4.0). This makes up about 28% of the total day for someone without a job. 

A few years ago, my colleague Rob Moore wrote about leisure time and how it is an important part of a well functioning economy. People find relaxation and fun valuable, and so time spent on those activities is a benefit to the economy even if it doesn’t grow GDP. 

The category that non-workers see the second largest increase in time spent on is “household activities.” This is a category of time spent that is much more understandably productive, even though it still is not captured by our mainstream definitions of the economy. People without jobs on average spend an additional hour per day on household activities (2.6 compared to 1.6). 

The next biggest difference between workers and non-workers is the amount of sleep each group gets on average. People without jobs spend about 45 extra minutes per day on “personal care, including sleep” when compared to non-workers. Fortunately, both groups spend more than eight hours on this category on average (10.2 compared to 9.5)

The last category where there is a difference of more than 30 minutes is the time spent on “educational activities.” The average person without a job spends about 45 minutes on educational activities every day compared to only 5 minutes for people who work full time. 

There are few things we can learn from this. One is that when people aren’t working, they tend to substitute about half of those hours with added leisure time. This is an important reminder that leisure is extremely valuable, and people tend to prioritize it.

Another important takeaway is that there is a lot of non-market productivity that happens outside of working hours. Both people with jobs and those without spend considerable portions of their day taking care of household chores and other family members. 

Notably, people without a job are not caring for family members any more than people with full-time employment. This means people who are not working are not using this freed up time to care for children or elderly family members.

The American Time Use Survey will continue to provide countless insights for policy makers. Understanding how people spend their time and how these trends change in response to policy decisions can be an important tool in ensuring the economy succeeds in getting people the things they want.

Were the Texas flood deaths a policy failure?

On Friday, July 4th, disaster struck when torrential rain poured into southern Texas near the Guadalupe River, one of the top three most dangerous regions in the country for flash floods. In just 45 minutes, the river rose 26 feet, the second-highest rise on record. Rainfall rates ranged from two to four inches per hour, creating up to 18 inches of water in some areas. 

Flash flood warnings began to be released at 1:14am local time, three hours before catastrophic flooding began. However, flash flood warnings provided by local weather channels have become so common for the region that many could not anticipate the true severity of the flood. The flooding that ensued was devastating, and as of Thursday evening, at least 120 people had been found dead in the state, with hundreds more still missing. Numerous FEMA and DHS officials and resources have been sent to the state to assist with rescue and recovery efforts. On Thursday morning, more than 2,100 personnel were on the ground helping to recuperate families after devastation.

While it can be difficult to attribute a single weather event to climate change, intense rainfall and flooding are happening with increasing frequency in Texas and across the rest of the United States. Many are referring to the disaster in Texas as a “perfect storm”: the distribution of rainfall was one of the worst possible patterns for the region, concentrating rainfall in an area with steep terrain; southern Texas itself had been experiencing a severe drought, leaving behind compacted soil that decreased water infiltration and increased runoff; and the Gulf of Mexico (or “Gulf of America” depending on which shore you stand on) has had warmer-than-average temperatures, leading to higher water content in the air near Texas. 

As the disaster settles, concerns continue to grow that local jurisdictions may not be adequately prepared for such flooding events. Even more so, uncertainty around the future of federal funding toward disaster prevention, particularly with agencies such as FEMA, make local disaster management shortcomings even scarier.

Whether the flooding in Texas was due to growing concerns of climate change, unlucky weather patterns, lack of local preparedness, or something else entirely, the increasing prevalence of heavy rainfall and flooding calls for the discussion of more disaster prevention infrastructure and policymaking.

One tool that we employ a lot at Scioto Analysis is cost-benefit analysis, and it can be a great way to evaluate and show the effectiveness of flooding mitigation infrastructure and other disaster prevention projects.

While early cost-benefit analysis has been traced back to French public works projects in the seventeenth century, cost-benefit analysis in the United States is typically believed to have started with water resource and flood control projects in the nineteenth and twentieth centuries. In the nineteenth century, water resource development was gaining momentum in the United States, and while proponents justified these projects with talks of economic development, political unity, and national defense needs, it was difficult to show clear, immediate benefits for the public that were worth such a high price tag.

In 1936, the Flood Control Act was passed as part of the New Deal, which marks what most believe to be the official start of cost-benefit analysis in the United States. Some of the most relevant language in the legislation includes, “if the benefits to whomsoever they may accrue are in excess of the estimated costs”.

An earlier report from the National Resources Board has an even clearer objective: “to achieve rational planning and in particular to achieve equitable allocations of benefits and contributions to cost in public works programs.” Both the Flood Control Act and guidance from the National Resources Board meant that there was now a cost-benefit analysis rule written into U.S. law. If Congress wanted to authorize a new public works project, it needed to be extensively studied, analyzed, and approved. 

More recently, there have been executive orders and additional federal guidance that require cost-benefit analyses to be completed for all major regulations. The importance of this level of analysis cannot be overstated, especially when it comes to estimating the costs of human life.

We have written about the value of a statistical life at Scioto Analysis extensively in the past. In policy analysis, the value of a statistical life is the amount that individuals are willing to pay to reduce the risk of death, determined using labor market data around pay premiums for more hazardous occupations. It is important to make sure human life is taken into account in economic policymaking, especially when evaluating public works projects such as flooding mitigation or other disaster prevention that can have a major impact on human life. In 2025, current estimates of the value of a statistical life are in the $13 million range. This means that beyond the inherent value in saving lives, an infrastructure project saving just one–or a fraction of– human life can yield immense economic value to society. 

Public policy decisions ultimately lead to loss of life in Texas. On July 4th, peak flooding levels in Texas of 34.3 feet were recorded at 6:45am. As early as 4:22am, when flooding levels were already reaching nearly 20 feet, a volunteer firefighter asked Kerr County, a county within the area of the flooding, to release alerts to the county with their emergency mass notification system. However, reports from numerous residents indicate that these text-message style alerts did not arrive on people’s phones until 10-11am, after some of the worst flooding had already passed. Additionally, the county did not issue its own Amber Alert style warning until two days after the deadliest day of flooding.

Could this have been prevented? In 2016, Kerr County put together a proposal to fund a flood warning system that would have added flood alert sirens to the area. Ultimately, the sirens were cut from the proposal due to cost and the risk of them accidentally going off at night. In total, the proposal was estimated to cost $1 million. If the warning system was installed and saved even one of the lives lost in Texas this past weekend, there would have been a net economic value of more than $10 million. This means even from a cold economic perspective, a poor decision was made.

As more time passes, the risk of flooding is only worsening. Some of the most severe floods are five times more likely to happen each year now than they were just a few years ago. As we conduct cost-benefit analysis about these kinds of infrastructure projects, it is easy to get lost in the weeds of analysis. But, it is important to remember cases such as southern Texas, where rigorous cost-benefit analysis can help convince policymakers of the ever-growing importance of planning for disaster and saving lives. 

‘Big Beautiful Bill’ makes Medicaid a big ugly mess, in Ohio and across America

In 2019, I attended my first meeting of the Society for Benefit-Cost Analysis in Washington, D.C. The keynote speaker was Cass Sunstein, one of the most prominent public advocates for the use of benefit-cost analysis and former administrator for the Office of Information and Regulatory Affairs under President Obama.

His keynote was on a phenomenon he called “sludge.” This was the phenomenon of how much time costs are exacted by the government on individuals through paperwork.

His idea was that time that people spent on filling out government paperwork is time they could be spending working, resting, with their families, or any of the other ways people spend their time. Therefore, we should consider the time people spend on regulatory compliance as a cost to society.

As policymakers at the federal level passed the “Big Beautiful Bill,” they ushered in a new moment in the history of sludge: the moment sludge was used to try to discourage people from getting health insurance.

According to the Kaiser Family Foundation, the Big Beautiful Bill creates new requirements for verifying addresses, cross-checking eligibility and data against other sources, and reduces retroactive coverage from three months to one month. It also imposes work requirements, puts penalties in place for covering immigrants, and makes renewing Medicaid more time-consuming and onerous.

The goal of these changes is to reduce enrollment in Medicaid.

In Ohio, the Center for Community Solutions said in an analysis that enrollment loss could be as high as 450,000 people.

The federal government is not alone in working to create sludge in the Medicaid program. For years, policymakers have been working to exact work requirements on Medicaid recipients.

The problem with this approach is that work requirements don’t work.

When work requirements for Medicaid enrollment were put in place in Arkansas during the first Trump Administration, most of the people who lost their health insurance were people who were working but did not know how to comply with the new requirements for reporting that had been put in place.

When policymakers at the federal level were working to reform the welfare state, they reduced spending by turning entitlement programs into block grant programs, allocating only a certain amount of money to each state and requiring them to manage that money.

While many would argue this was not good policy (it certainly turned America’s most important cash assistance program into a shell of itself), it was at least not so cynical of a policy as to throw sand into the cogs of the state then complain about it not working.

Part of the reason for the different strategy is because Medicaid is popular. Of the 50 states, 40 have adopted Medicaid expansion. A majority of the states that have adopted Medicaid expansion voted for Trump in 2024.

Out-and-out cutting Medicaid would be unpopular among the constituents of legislators. So instead, they turned to rules that seem reasonable on their face — like eligibility verification and work requirements — that in reality just make the system more complicated and push people off health insurance.

Policymaking predicated on deceiving the public is cynical.

Creating red tape on programs you don’t like removes any moral high ground you have to complain about government inefficiency.

If you don’t believe in government working, I don’t really know why you want to spend your career working in it.

This commentary first appeared in the Ohio Capital Journal.

Can we do budgeting differently?

Over the last few months, all of the most important public policy stories had one thing in common: they were tied to budgets. We’ve talked about topics like the proposed child tax credit, funding for state parks, child care, and even federal budget topics such as Medicaid cuts.

It can feel like the budget season is the only time policymakers make meaningful decisions, and there is a good reason for this. Public policy is somewhat of a blunt instrument. Policymakers have some capacity to change incentives, but changing the way people interact with each other is extremely hard. 

The best tool policymakers have at their disposal is their ability to move resources around the economy. Their ability to raise and lower taxes and determine what programs do or do not receive those tax dollars is unbelievably powerful and has a huge impact on the way people live their lives. 

As an analyst, this creates a disconnect. In most cases, our policy analyses are based around the concept of an “average” outcome. For example, if you increase taxes on cigarettes, then people will on average smoke less. 

When we simplify this in our models to determine how much less people smoke, we usually assume that all smokers will experience a very slight decrease in smoking. What happens in practice is that a few individuals will likely have large changes to their behavior, while most will just face the higher prices. The overall impact is the same, so this isn’t an issue for an analyst.

However, this is a major issue for policymakers. A policymaker doesn’t deal with an “average” constituent. They represent real people who have preferences that differ from the averages.

This means that when policymakers cast their votes, they are not necessarily making a decision based on what is good for the most people, they are making a decision based on what is good for the people they represent. 

Ideally, this should still lead to overall positive results for society. This assumes that representatives are a weighted average of the people they represent. However, in a world of increasingly polarized party politics, this is less likely to happen.

Because of the importance the budget has in shaping public policy, policymakers are incentivised to get as much done as possible to advance their agendas. When one party has a majority, they essentially have the power to ignore the preferences of those who did not vote for them.

From an economic perspective, this creates a social inefficiency because decisions are being made not to maximize everyone’s well-being, but only that of a select group of voters. In a mathematical sense, this is equivalent to using an incorrect willingness to pay figure. 

One way policymakers could try to avoid this pitfall is by adopting consensus budgeting as the main way budgets are created. Consensus budgeting a way of adopting budgets where the goal is not for policymakers to try and advance their own agendas as much as possible, but rather to submit a budget that attempts to maximize compromise, preferring average outcomes that leave the fewest people dissatisfied over majority opinions that some people strongly prefer and others strongly dislike.

If stakeholders from different corners of society are worked into the budgeting process, then we should expect the final decision to much more closely reflect the desires of the whole society rather than just those who support the party in power. 

To better align public spending with the diverse needs of society, policymakers can change the way budgets are negotiated and approved. Policy analysts can sometimes get too wrapped up in the world of averages the fact that real people have preferences different from the averages. Still, we may all be better off if policymakers made more efforts to realize that their constituents only represent a part of a larger community, and that people have other priorities that should be taken into consideration.

Ohio economists say state parks bolster Ohio economy

In a survey released this morning by Scioto Analysis, all 19 economists surveyed agreed that public spending on state parks is an efficient strategy for producing goods for Ohio residents like recreation, environmental quality, and health. This comes as fracking revenue was reallocated from park improvement to park operating expenses in the most recent state budget.

As Kevin Egan from the University of Toledo said in his comments, “Ohio only has 0.77% of its land as state park and ranks 34th in the nation for federal or state lands. The worst part is possibly reducing funding due to taxing fracking less. It is efficient to tax activities that cause pollution more and then using those tax dollars for public parks is a ‘double dividend’.”

Despite the general consensus, many respondents noted that while public spending on outdoor recreation is in many cases an efficient use of resources, there is a point where there are diminishing marginal returns to higher levels of spending. As Will Georgic from Ohio Weselyan wrote “There is an efficient level of public spending on state parks that is certainly greater than zero, so I strongly agree with this statement as written. However, there is some optimal level of spending on state parks beyond which further spending would be inefficient.”

Additionally, 14 out of 19 economists agreed that reducing funding for state parks will lead to long-term deterioration of natural assets that will reduce the future economic potential of those areas. 

Rachel Wilson noted that these decreases may lead to decreases in tourism, writing “I think it can also attract out of state visitors which is where the real economic boom comes from as it introduces new spending into the economy rather than re-allocating current residents' recreational money.”

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.

Gov. DeWine issues vetoes that will impact Ohio’s economy for decades to come

Last week, Gov. Mike DeWine signed Ohio’s two-year budget into law. Before doing this, he issued 67 vetoes, significantly reshaping the budget that was sent to him by the General Assembly. While he made many changes to the budget, the following three stood out to me as potentially having a significant effect on Ohio’s economy.

Tightening fiscal policy for public schools

Ohio lawmakers have been looking for ways to reduce the impact of property taxes on property owners and renters for a couple of years now. One of their solutions was to impose new rules on school districts that limited the amount of cash they could hold from year to year, mandating property tax decreases to make up for cash not being spent.

The perverse incentives in this policy should be clear to a reader. While it could lead to lower property taxes, it could also lead to school principals making mass purchases of unneeded equipment at the end of the year rather than saving funds for more useful purchases the year after.

Ensuring public school districts aren’t dealing with arbitrary limits on their reserve funds will allow for fiscal flexibility that will benefit public schools making tough decisions around long-term financial planning.

Reduction of Medicaid coverage for children under age four

Medicaid is another category of state spending that legislators have been eyeing. Medicaid is the top insurer of Ohioans and even though the federal government picks up a large portion of the tab for Medicaid, the state still spends billions of dollars on it per year. One way legislators were planning to reduce state spending on Medicaid was to require families with young children to do more paperwork, increasing the chance they will miss a deadline and lose their health coverage. 

While this is a way to save money, it would also lead to lower health insurance coverage rates and more fiscal instability for families with young children. This also would happen at a crucial moment in child development. This veto has the potential to keep coverage for more households with young children, getting them off to a good start with health and family resources.

Limiting voters’ ability to fund local services

Another strategy state lawmakers have adopted to reduce property taxes is to empower county lawmakers to reduce local property taxes at will, even overturning levies passed by voters. This would allow county leaders to reduce property taxes, lowering rates for property owners and renters, but also reducing resources for local schools and human services. If this provision was left in the budget, it could have led to lowered property tax rates across the state and less resources for local governments that rely on these property taxes.

Ohio’s state budget is a long, labyrinthine document. It also is the main tool policymakers use to set public policy in the state. The decisions in this document have wide-reaching implications that impact the future of our economy, poverty, inequality, education, health, and well-being of Ohio and its residents. Now the ball is in the court of the General Assembly to see how many of these 67 vetoes will stand.

How child care subsidies could reduce child care deserts

In the newly-passed Ohio state budget, one of the major new provisions is the Child Care Choice Voucher program. Much like school vouchers, a topic we’ve covered before, child care vouchers provide subsidies to families in order to pay for some pre-approved child care options. 

Unlike school vouchers, the Child Care Choice Voucher Program is not targeted towards low-income families. This is because of the Publicly Funded Child Care program, which covers child care costs for low-income families. Instead, this new voucher program is specifically targeted towards families between 145% and 200% of the federal poverty line.

My colleague Rob Moore has written about the impact of child care quality before, and it would seem on its surface that these types of vouchers help address this problem. If you give parents the resources to identify a child care opportunity that they think will work well for their child, then it should be the case that more children end up in beneficial situations.

However, this ignores a major issue in the child care space: the supply of child care is largely insufficient in many communities.

Areas without an adequate supply of child care are often called child care deserts, and they are common all across the country. According to the think tank The Center for American Progress, nearly 40% of Ohioans live in child care deserts. 

From an economic perspective, these vouchers could lead to fewer child care deserts in the long run. If the state is putting more money into these markets than there otherwise would be, then they would create an incentive for new child care providers to enter the market and offer services in places that might not currently have them. However, there are some hurdles that need to be overcome in order to ensure this ends up actually benefitting families.

One issue these vouchers might face is an uptake problem. People need to claim the vouchers and increase demand to encourage suppliers to enter the market. Families where a parent acts as a full-time caregiver or those who rely on relatives for child care might prefer those options and choose not to utilize the vouchers. 

Another issue that might minimize the effectiveness of these vouchers is inframarginality. Essentially, if these families are already spending money on child care, then the vouchers aren’t actually adding any money into the child care market. It essentially acts as a cash transfer, and families who receive vouchers would just be able to increase their spending elsewhere. It is probably unlikely that the low-income families that don’t quite qualify for public child care would experience this like a cash transfer, but it is an important consideration. 

While the Child Care Choice Voucher Program has the potential to increase access and flexibility for low-income families, its ultimate effectiveness will depend on how it interacts with the broader child care market. Without addressing the underlying supply shortages and ensuring families actually use the vouchers, the program may fall short of its goal to meaningfully expand child care access. Hopefully, this program can encourage more people to provide child care and help eliminate some of the deserts that exist across the state.

How do climate models work?

In policy analysis, we are almost always trying to quantify what might happen in a future scenario where a particular policy is enacted. A lot of the time, we are focused on short time frames, like what will happen in the next five or ten years after a policy is enacted.

However, sometimes we need to look much further ahead. There has been a recent push to study the impact today’s economic policies have on future generations in fields like poverty and education, but most research still focuses on the impacts people alive today will experience. 

One area of policy analysis that is almost exclusively forward-looking is climate policy. With climate policy, policymakers today need to consider not only their short term needs, but the needs of people far into the future.

This presents a major challenge for analysts because our forecasting tools are largely designed for short-term thinking. We can’t just use the same tools to model the global climate into the future that we use for other questions. 

So, let’s talk about climate models, and what sets them apart from the type of models you may be more familiar with.

When we talk about any type of forecasting model, one of the first things we need to understand is whether a model is fixed or random. The technical terms for this is whether a model is deterministic or stochastic. 

In deterministic models, the same inputs will always return the same output. If you plug in X, you will always end up with Y. The downside of these models is that they usually require stricter assumptions and a better understanding of the underlying systems at work, but their advantage is that they enable you to look significantly farther out into the future. 

With stochastic models, the same set of inputs doesn’t always yield the same output. These types of models allow analysts to account for some variability and uncertainty in their assumptions which can be useful in situations where we might be missing some information about what influences the underlying systems. 

Models don’t have to be entirely stochastic or deterministic. A lot of the time, it is beneficial to include both types of elements. That way, analysts can take advantage of specific deterministic knowledge they do have, while accounting for some of the variability that exists in some of the less understood processes. 

One example of a simple climate model comes from the University Corporation for Atmospheric Research. This is a deterministic model that just only takes into account the amount of carbon in the atmosphere. They use an established link between the amount of carbon and temperature to estimate what the global climate will look like in the future.
This model highlights another key characteristic of climate models, their resolution. 

The University Corporation for Atmospheric Research model makes global climate predictions. If you were interested in understanding what might happen in your city, state, country, or even hemisphere, this model can’t help you. 

Instead, you might be interested in the Representative Concentration Pathways, sometimes called “RCPs.” This set of models separates the globe up into over 500,000 grid cells, each with their own emissions data. This enables researchers to study how local changes can impact global climate change. 

There are multiple different Representative Concentration Pathways that each come with a slightly different set of assumptions about what the world is going to look like in the future. Using a scenario analysis like this is one way that modelers can capture some of the stochastic uncertainty without specifically defining a variable process. You can just test what happens with a different set of assumptions. 

One challenge that all predictive models face is that they are using past data to predict the future. This assumes that the underlying processes the these models are based on aren’t going to fundamentally change anytime soon. 

Climate models push the boundaries of traditional forecasting by demanding models that account for both immense complexity and long-term uncertainty. As we confront the realities of climate change, improving our models and adapting our analytical tools will be essential. Good models give us good information, and good information is the key to good policy decisions.

How would proposed Medicaid and SNAP cuts affect Ohio?

The “Big Beautiful Bill” currently under consideration in Congress proposes substantial changes to Medicaid and the Supplemental Nutrition Assistance Program (SNAP, formerly “food stamps”). Below, I take a closer look at these proposed changes and examine their implications for Ohio, including both direct impacts and spillovers into the broader economy. The numbers cited here reflect the House version of the bill; some changes occurred in the Senate version.

The bill proposes a range of provisions to limit Medicaid and SNAP spending. Some of these provisions would directly cut spending through decreased program participation, while others would likely prompt states to scale back eligibility and benefits. The Medicaid provisions include new work requirements, additional out-of-pocket costs for recipients, reductions in funding for states that serve unauthorized immigrants, a cap on Medicaid provider taxes, and limits on Medicaid state-directed payments, among others. The SNAP provisions include state matching requirements and an expansion of work requirements, among others.      

To understand how these federal changes might affect Ohio, I examine projections for state and congressional district-level impacts. According to an analysis from George Washington University, the combined impact of the provisions mentioned above would reduce Ohio’s annual Medicaid funding by $3.4 billion (a 12% reduction) once the changes have been fully phased in in 2029, and would reduce Ohio’s annual SNAP funding by $1 billion (a 30% reduction) by 2029. 

The nonpartisan research organization KFF estimates that the proposed Medicaid cuts would cause 270,000 Ohioans to lose their health insurance, while the Center on Budget and Policy Priorities estimates that the proposed SNAP cuts put 316,000 Ohioans at risk of losing some or all of their current food assistance benefits. Figures 1 and 2 show the estimated number of Ohioans at risk of losing health insurance and SNAP benefits by congressional district.

Figure 1: Ohio Residents Who Would Lose Health Insurance Due to Medicaid Cuts Proposed in the “Big Beautiful Bill,” by Congressional District: Link to interactive map

Map generated with data from Seeberger, Colin, Andrea Ducas, Lily Roberts, Shannon Baker-Branstetter, Kennedy Andara, and Kyle Ross. 2025. The Devastating Harms of House Republicans’ Big, ‘Beautiful’ Bill by State and Congressional District. Center for American Progress.

Figure 2: Ohio Residents at Risk of Losing SNAP Benefits due to Cuts Proposed in the “Big Beautiful Bill,” by Congressional District: Link to interactive map

Map generated with data from the Center on Budget and Policy Priorities. Estimated number of SNAP participants in households at risk from two provisions of Johnson proposal.

Beyond the individuals directly affected, reductions in Medicaid and SNAP spending may have broader economic impacts through spillovers into other parts of Ohio’s economy. Funding from these programs flows into local economies through healthcare facilities, grocery stores, and other retailers. If the benefits are reduced, those local businesses would lose revenue, which may lead to job losses and further spillovers. The report from George Washington University estimates that across all states, the proposed cuts to Medicaid and SNAP would reduce states’ GDP by $154 billion in 2029 when the cuts have been fully phased in, which is more than the $131 billion the cuts would save in federal spending. The loss to Ohio’s GDP would be $5.2 billion. Furthermore, the report estimates that the cuts would cause 44,700 lost jobs in Ohio (0.8% of Ohio’s employment), and a $366 million reduction in Ohio’s annual state and local tax revenue.   

An analysis by the Washington Center for Equitable Growth underscores the impact of Medicaid and SNAP on state and local economies. The analysis finds that income transfers from Medicaid (measured as Medicaid payments to medical care providers) and SNAP jointly make up 5.6% of Ohioans’ personal incomes. Figure 3 shows the percent of residents’ personal income that comes from Medicaid and SNAP, by congressional district.

Figure 3: Medicaid and SNAP as a Percent of Personal Income, by Congressional District: Link to interactive map

Map generated with data from Manduca, Robert. 2025. Medicaid and SNAP cuts in congressional Republicans’ budget bill will negatively impact local economies. Washington Center for Equitable Growth.

Studies also suggest that spending on social safety net programs like Medicaid and SNAP for families with children has economic impacts decades into the future, because childhood poverty is associated with worsened long-term health outcomes and reduced future earnings. A cost-benefit analysis by Columbia University’s Center on Poverty and Social Policy found that for every $1 in cuts to SNAP for families with children, there is a $14 to $20 economic loss to society in the long term. 

Medicaid and SNAP play an important role in Ohio’s health, food security, and economy. Changes to these programs would affect not only their recipients, but also the healthcare and retail sectors, with ripple effects into other parts of the state’s economy. Similar impacts are projected for other states. As policymakers consider reducing spending on these programs to shrink the federal deficit, it is important to consider not only the effects on public health, but also the broader economic implications.

For more on Medicaid and SNAP, see our articles on Medicaid work requirements, Medicaid expansion, Medicaid’s impact on poverty, SNAP benefits in Ohio, the SNAP benefits cliff, Ohio’s safety net, and ending hunger in America.