How do you value public goods?

I just got back from a vacation in Hawaii where I got to go see Volcanoes National Park, the site of the actively erupting Kilauea shield volcano and one of the most unique landscapes you can find on earth. While I was there, I picked up my America the Beautiful Pass, an annual pass that provides unlimited entrances to all of the areas managed by the national park service that require fees to enter. 

This is a great example of the government stepping in to try to prevent a tragedy of the commons, but I wanted to talk about a different angle about what this entrance fee might tell us. Particularly, how much value do people get out of national parks?

Why do we need to know willingness to pay?

In cost-benefit analysis, “willingness to pay” is the essential piece of information that allows us to compare wildly different impacts in a single coherent way. It is what allows us to say things like “X reduction in the crime rate is equivalent to Y energy savings annually.” A cost-benefit analysis is not complete without the monetization step, and when we are measuring something that doesn’t have a price because it isn’t traded in some market then we need some estimate for what that price would be if a market existed.

So, in the example of the national park, is it fair to say that my willingness to pay was $80? One flaw right away is that I purchased an annual pass, and since purchasing it I’ve used it three times already. Does that mean my willingness to pay is $80 divided by the number of visits I make in a year? 

Clearly the entrance fee is not a good estimate for willingness to pay. We might be clued into that realization from the fact that these entrance fees aren’t market prices, they are a policy intervention to limit overuse. Again, natural resources are often common goods and can’t easily be traded in a fair market. One approach that economists use is the travel cost method, looking at the cumulative travel costs that go into a trip to determine the total willingness to pay.

Using travel costs to estimate willingness to pay

I’ve written before more generally about how economists go about calculating willingness to pay, and using travel costs certainly falls under the umbrella of a revealed preferences approach. The basic idea is this: when a natural area has a primary function of outdoor recreation,* then how far people are willing to travel gives us some idea of how valuable that particular area might be to the people who visit it.

For example, imagine that your neighborhood has two parks. One you can quickly walk to that doesn’t have many amenities, and another that you’d have to drive to but has newer facilities. If you consistently choose to drive to the second park, you are revealing something about your preferences. The extra time, gas, and effort involved in getting there are costs that you are voluntarily choosing to incur because you believe the experience is worth it.

The logical conclusion is that because you are willing to spend more to travel to the nicer park, those amenities must be more valuable than the additional costs. Collecting this information from multiple sources over a wide range of costs and amenities can give us enough to calculate willingness to pay.

The travel cost method is one way economists can get better estimates for how much people value all sorts of things. It’s mainly used to help value ecosystem services, but there might be other scenarios where this method might be helpful. 

* The literature surrounding the value of ecosystem services is broad and reaches far beyond the direct willingness to pay people have for recreation opportunities. A full deep-dive into all the ways natural areas provide value to humans is beyond the scope of this blog.

Who Pays if Ohio Eliminates Property Taxes?

Earlier this month, county finance directors breathed a collective sigh of relief as outlets reported the statewide effort to abolish property taxes had not collected enough signatures to make it onto the fall ballot.

Organizers announced they were not going to give up the fight yet, vowing to continue collecting signatures with the goal of putting the initiative on the ballot in November 2027. Ohio will likely continue talking about property tax abolition for the next year and a half, if not longer.

Why do people want to abolish property taxes?

Affordability debates often focus on housing, grocery, and transportation costs, but local tax policy matters too. Tax burdens, housing costs, wages, and local services all shape how attractive Ohio is to current and potential residents.

Property taxes have catapulted themselves into the center of the state public policy conversation in Ohio over the past few years, but they have always been something that homeowners have paid attention to. Property taxes are visible. Unlike sales taxes, which are often hidden in prices of goods bought at retail, and income taxes, whose sting is reduced through withholding, homeowners see property tax bills, and feel them when they go up during increases in housing prices. In the past five years, Ohio’s housing prices have grown at the fastest rate on record. Since property taxes are based on assessed housing values, homeowners are feeling these price increases as large, automatic tax increases.

These increases are especially difficult for retirees and other people on fixed incomes like people with long-term disability. Their incomes usually do not rise with the costs of housing, so their discretionary income falls with increases in housing prices. It can also be a challenge for people dealing with low incomes and weak labor markets.

Though property taxes burden homeowners and renters, they have a major benefit: funding public services. Though the connection between public services and taxes can be difficult to see, property taxes are one of the most important tools for financing local government in Ohio.

What do property taxes pay for in Ohio?

A September 2025 memo by the Ohio Legislative Service Commission lays out the uses of property taxes in the state.

The majority of property taxes in Ohio go to school districts. The Ohio Legislative Service Commission estimates property taxes will pay for $15 billion in school district funds in Fiscal Year 2027, which represents nearly two-thirds of all property taxes collected in the state. A few years ago, we conducted a study on school spending which found spending on schools pays off in future labor market earnings for students.

The Ohio Legislative Service Commission projects another $3.8 billion to go to county governments, which provide human services (including administration of safety net programs like SNAP), courts, jails, and public health services.

The remaining $4.6 billion is split between townships, municipalities, and special taxing districts, which finance fire, police, roads, libraries, parks, senior, child, and developmental services, and a range of other public services.

How much money is at stake if property taxes were repealed in Ohio?

All in all, the Ohio Legislative Service Commission estimates local governments will collect over $23 billion in property taxes in Fiscal Year 2027. The Commission estimates that a full repeal would lead to a shift of about $2.6 billion in taxes to fixed-sum levies which would not be covered by the repeal, meaning that the full repeal would amount to a total of $21 billion in property tax repeals.

What could replace property taxes in Ohio?

Property tax repeal would leave a multibillion dollar gap in Ohio’s local government budget. Policymakers will have to find some way to adjust to this policy change if it happens.

One option would be to increase state income or sales taxes. Ohio has been taking steps to decrease its income tax rate over the years, so this would be a reversal of state policy on this front. Ohio increased its sales tax in 2013 as part of a move to shift its taxes from income taxes to sales taxes. Ohio has lower sales taxes than all neighboring states, so it has some room to increase sales taxes without exceeding rates seen nearby.

Another would be to increase local income or sales taxes. The state of Ohio gives pretty wide latitude for local voters to approve new income taxes for municipalities and school districts. Abolition of property taxes across the state would likely lead to a wave of new local income tax levies to replace lost funding. Counties also have some ability to levy sales taxes, but state caps on county sales tax rates would have to be lifted for these to be able to meaningfully replace property taxes.

Lastly, local governments could cut budgets. This strategy is unlikely to close the gap on its own given the tens of billions of dollars that would be lost, mostly from schools, but it would likely be a part of any post-repeal fiscal environment.

Why is replacing property taxes difficult?

While repeal would happen in one fell swoop, replacement would be a piecemeal process. The most viable options for replacing property taxes would come with a required vote at the ballot, which would introduce both delays and uncertainty to the public finance system and would be accompanied with public campaigns before they could be adopted. This would also make things difficult for townships, which have fewer options for authorizing new local taxes than school districts, counties, municipalities, and special districts.

A big question mark for local governments would be whether the state would step in to help fill the budget gap at all. Given that the state has decreased support for local governments over the years and that a statewide anti-tax vote would signal hostility to new taxes, the state would face a lot of headwinds to helping local governments adjust to the new fiscal environment.

How should we evaluate property tax reform in Ohio?

Ultimately, the public and state and local policymakers will have to answer the questions they always should be answering around public policy changes: are they effective, efficient, and equitable?

While property tax reform will reduce tax burdens for some, it will come at the expense of higher taxes in other places, service cuts, or some combination of the two. Local policymakers will need to balance tax increases and benefit cuts adeptly for property tax reform to effectively ease burdens and increase incomes for residents.

Property taxes are not a particularly efficient form of taxation and their repeal could lead to efficiency gains, especially if the state replaced them with land value taxes. On the other hand, deep cuts to education will cripple Ohio’s economy in the long-run.

Property tax repeal could be a huge shift in fiscal equity in Ohio. Likely the largest distributional shift that would come from property tax repeal would be generational. Older Ohio residents who own more property and live in larger houses are likely to benefit at the expense of today and tomorrow’s schoolchildren and current wage and salaried workers.

Property tax reforms may improve Ohio’s tax system. In the short-term, however, full repeal will leave the state, its schools, and local governments with serious fiscal decisions to make.

Introducing Policy Analyst Jacob Strang

Today marks one month since I started as a full-time policy analyst at Scioto Analysis. I originally started at Scioto Analysis as an intern in January of last year. Then, I returned as a research assistant last summer, and I came on permanently as a policy analyst in May. Today, I wanted to take some time to reflect on my path to Scioto Analysis, my time at Scioto Analysis so far, and look to the future.

What was my path to becoming a policy analyst?

I graduated from The Ohio State University last month with a Bachelor of Science in Economics and Political Science. I grew up in a household where resources were tight, so when I got to college, I was always passionate about economics and policymaking. Growing up, I got to experience some economic policies that work very well and some that work very poorly. This is a big part of the reason I’m excited to join Scioto Analysis as a policy analyst: I get to help provide evidence-based analysis for policymakers and organizations to inform decision making around these very policies I experienced myself.

During college, I realized that to contribute most effectively to economic policy, I should focus on the analytical side of policymaking. I found myself especially excelling in my math, economics, statistics, and programming coursework. I earned a minor in Computer Science, and I took as many econometric and political analysis courses that my majors allowed for.

Outside of Scioto Analysis, I also completed an internship with the Ohio Auditor of State, which helped to further develop my analytical skills. I received training in Microsoft Excel, and I assisted with various state projects to test out different analytical techniques. I became a stronger and more organized analyst, which helped me move into a more significant role as research assistant at Scioto Analysis during my final year of college.

How has my time been spent at Scioto Analysis?

During my internship at Scioto Analysis, I conducted a cost-benefit analysis about wildlife crossings. The internship was one of the most valuable learning experiences I completed during college.

Throughout each twelve-week internship, interns conduct a cost-benefit analysis mostly independently with a lot of guidance and review from the rest of the team. Our internship is great for people who find experiential learning most effective–it requires a deep dive into a specific subject material and a high level of discipline to stay on track.

The cost-benefit analysis has since gotten fairly consistent coverage by various organizations and news outlets. Earlier this year, the analysis was cited by the Pew Research Center in a fact sheet about wildlife crossings. Just last week, Treelines cited the cost-benefit analysis in an article discussing new wildlife crossings structures across the country. 

I also got to present on the study at the 2025 Ohio Health Policy Summit and the 2026 annual conference for the Society of Benefit-Cost Analysis. The Society of Benefit-Cost Analysis hosts an annual conference in Washington D.C. to share current studies and findings in the cost-benefit analysis field. 

I had the incredible opportunity as a research assistant to join the team and present on the report while also learning about other cutting edge research in the cost-benefit analysis space. My personal favorite presentation during the conference was a study presented by Solomon Hsiang from Stanford University on quantifying and monetizing global climate loss and damage, which you can read more about here.

In June of last year, I returned to Scioto Analysis as a research assistant. Almost immediately, I had the opportunity to play a major role in a variety of projects. Some of my favorite projects were as follows:

• A process analysis of the energy permitting process in Ohio, where I did a deep dive into the Ohio legislative code to map out the legislative process surrounding energy permitting in Ohio

• A county price parity analysis of affordability in Franklin County, where my colleague Micheal and I replicated the Bureau of Economic Analysis’s regional price parity at the county level

• A refresh study of the state of inequality in Ohio, where I simulated what inequality in Ohio would look like under different tax scenarios

All of these projects helped develop a unique set of skills and knowledge that I will continue to use moving forward, including the ability to research, write, analyze data, program, and more.

Looking Ahead

Joining Scioto Analyst as a policy analyst is a very exciting step in my career–I’ve wanted to get involved with this kind of impactful policy work since my early days in high school debate. As a full-time analyst, I’m looking forward to the opportunity to collaborate on more economic analyses, learn more about state policymaking by writing more frequent blog posts, and become more connected in the state policymaking space.

If you have any advice as I continue on this new path as a policy analyst, or if you want to chat about any of the work I’ve done or new prospects, feel free to reach out at jacob@sciotoanalysis.com. Looking forward to many more blog posts!

How will Ohio pay for federal SNAP policy changes?

Last week, the Ohio Senate unanimously passed Senate Bill 315, a bill to increase cybersecurity for Ohio’s Supplemental Nutrition Assistance Program (SNAP), formerly known as “food stamps.”

The Supplemental Nutrition Assistance Program has come under scrutiny recently due to changes passed at the federal level as part of House Resolution 1, known to many as the “One Big Beautiful Bill Act.” Due to changes placed in this bill, state lawmakers have been rushing to tighten their state food assistance programs, hoping to avoid penalties associated with improper payments. This is likely to have a big impact in many states and could especially hit Ohio hard.

What is changing in SNAP?

The federal government is mandating a range of changes to state nutrition assistance programs through House Resolution 1. These changes focus on shifting more responsibility from the federal government to state governments and beneficiaries.

First, House Resolution 1 shifts administrative costs to states. Before House Resolution 1, states were on the hook for 50% of administrative costs. The new bill increases that cost to 75%, meaning states will need to take on more of the cost of administering SNAP programs.

The federal government is also requiring states to pick up more of the tab for benefits. The scale that the federal government has mandated is that the federal government will cover the cost of 100% of benefits for states with less than six percent error rates, but that coverage rate will shrink to 85% for states with error rates of 10 percent or higher.

Finally, the federal government is expanding work requirements for food assistance eligibility. The new law mandates new work requirements for parents of teenagers, veterans, homeless individuals, former foster youth, and people living in places of high unemployment.

Why do changes to SNAP matter for Ohio?

Ohio is a major state for food assistance benefits. 1.3 million Ohio residents received Supplemental Nutrition Assistance Program benefits in February 2026 according to the United States Department of Agriculture, about 11% of the state’s population. That amounts to about 700,000 households and $250 million in spending. Since Ohio spent about $50 billion on groceries in 2024, that means about 6% of all grocery spending in the state of Ohio comes from federal food assistance benefits.

All in all, about 1 in 17 grocery dollars in Ohio come from SNAP and about 1 in 9 Ohio residents benefitted from those dollars directly in February of 2019.

What SNAP costs could HR1 shift to Ohio?

The two largest cost categories Ohio policymakers are having to look at in the face of these new changes are administrative costs and benefit sharing. Analysts at Georgetown Law’s Center on Poverty and Inequality estimate Ohio’s Supplemental Nutrition Assistance Program spending will nearly quadruple under the new law, with the state’s $150 million Supplemental Nutrition Assistance Program obligation ballooning to nearly $540 million.

Some of this cost will come from higher administrative costs falling on the state. According to the Georgetown Law Center, Ohio currently splits a $290 million administrative obligation with the federal government, each paying half. Ohio’s share would increase from $150 million to $220 million under baseline. The remaining $320 million of new obligations would come from cost share determined by Ohio’s error rate.

How do counties fit into the SNAP cost shift?

According to the National Association of Counties, Ohio is one of ten states that delegate the obligation to administer Supplemental Nutrition Assistance Program to its counties. Among those ten, Ohio is one of six states that splits the state obligation for administering Supplemental Nutrition Assistance Program between state and county government budgets.

The County Commissioners Association of Ohio reports that the state of Ohio has appropriated $44 million for Supplemental Nutrition Assistance Program administration and requires counties to cover $41 million. They estimate that the changes in House Resolution 1 will lead to an additional $47 million in new administrative costs which the state has not determined plans for yet. Note these costs are low compared to the estimates made by the Georgetown Law Center, so these costs could end up being higher.

What can Ohio do about HR1’s new SNAP rules?

Ohio will have some decisions to make in the face of these new changes. In a best-case scenario, the state will be on the hook for tens of millions of dollars, though it seems like it will be on the hook for hundreds of millions of dollars more. The state will have four main options for dealing with this change.

Absorb the costs at the state level. This would mean either raising revenue through new state taxes or fees or cutting spending elsewhere.

Shift costs to counties. This would require counties to find ways to pay for these new costs through new revenue streams or cuts to other programs.

Reduce enrollment through administrative rules. This would mean making it harder for people to claim food assistance, which would impact food insecurity and family budgets for low-income families.

Reduce error rates through investment in administrative capacity. This is certainly one of the goals of the federal legislation: to reduce moral hazard for states by giving them incentives to reduce error rates.

What do Ohio policymakers need to watch out for as SNAP changes to HR1 are implemented?

As Ohio policymakers enter this brave new world of Supplemental Nutrition Assistance Program regulation, their eyes need to be on certain targets. The most important is error rates. Different tiers of error rates will mean swings of hundreds of millions of dollars of state obligations.

At the same time, these new obligations will mean new costs for counties, households, and local safety net systems. Policymakers will need to keep an eye on county administrative burden to see how this obligation is shared between state and local government in Ohio. Families will be impacted by benefit access, food insecurity, and churn. And in the broader support community, local food bank demand may be impacted by changes in benefits.

Changes to the Supplemental Nutrition Assistance Program do not eliminate costs for the federal government, they just move them. Decisions made by state policymakers will decide to what degree these costs will be further shifted to county governments, and county decisions will decide to what degree they are shifted to families and private food assistance networks. No matter what decisions are made, someone will still pay.

Should Ohio take a closer look at what fracking does to drinking water?

Carbon emissions in Ohio have fallen by about a third over the past twenty years according to data from the Energy Information Administration.

Americans don’t necessarily think about Ohio as a leading state in the move toward decarbonization of our energy system, but Ohio emitted 86 million fewer metric tons of carbon in 2023 than in 2003.

How did the state’s energy system do this?

The answer is largely a story about a see-saw in energy consumption in Ohio from coal to natural gas.

Coal consumption in Ohio fell by 71% from 2003 to 2023 while natural gas consumption increased by 65%.

While natural gas is not carbon-free, its 30 million additional metric tons of carbon emissions over the past two decades was far outbalanced by the 100 million fewer metric tons emitted by Ohio’s abandoning of coal as an energy source over that time period.

The balance of the carbon emission reductions came from reductions in use of petroleum for energy generation.

Ohio’s natural gas boom has also come with concerns about local extraction of natural gas.

The reason Ohio has adopted natural gas so rapidly is because of a well-documented boom in natural gas drilling driven by “fracking” technology deployed in Ohio’s eastern Appalachian region.

This has led to frequent clashes between environmental advocates who worry about the broader environmental and health impacts of natural gas drilling and companies looking to tap into this natural resource.

According to the United States Environmental Protection Agency, nearly 1,200 different chemicals have been used for hydraulic fracking.

The United States Department of Energy maintains a database of wells across the United States and disclosed chemicals used within these wells.

A 2016 United States Environmental Protection Agency report found that issues such as water withdrawals, spills, poor well integrity, direct injection into groundwater, inadequate wastewater treatment, and unlined pits can lead to drinking water impacts, potentially causing public health hazards for residents local to drilling projects.

Earlier this month, Northeast Ohio state Reps. Derrick Hall and Sean Brennan introduced legislation to beef up oversight of the chemicals used in oil and gas wells.

Ohio House Bill 958 would require more detailed chemical reporting by well owners, add disclosure for chemicals used to stimulate wells, create a state-level chemical disclosure database, and ensure the accuracy of chemical disclosures with random wastewater testing across the state.

This new oversight regime would move past the current level of reporting in the Department of Energy database by providing information about chemical use throughout the drilling process.

It would also create a testing regime and impose penalties for inaccurate disclosure, ensuring the fidelity of chemical use disclosure.

It would also allow medical professionals access to exact chemical compositions when exposures occur, allowing for better treatment and potentially better health outcomes for people exposed to chemicals.

Functioning energy markets, like any other market, are based on proper disclosure and flow of information.

This matters for consumers of energy, but also to third parties such as people whose drinking water may be contaminated by oil and gas extraction.

As long as disclosure requirements are not designed to be so onerous that they impede development of safe wells, requirements like this can be an effective tool for making energy markets more efficient and safeguarding environmental and public health.

This commentary first appeared in the Ohio Capital Journal.

What’s the matter with data centers?

In the past year, data center development in the United States has transformed from a topic of excitement among economic development enthusiasts to a widespread issue of concern among regular members of the public.

Honestly, I can’t go half a day without someone bringing up data centers. A phrase that seems wonky and technical has captured public imagination in a surprising way in 2026.

This isn’t just my experience, either. Google Trends data shows the exponential growth in the search term “data centers” in Ohio over the past year. Ohio residents googled the term “data centers” 10 times more in May 2026 than they did a year earlier.

What is driving this rising interest in data centers in Ohio and beyond?

One explanation is environmental impact. Many are concerned about the impact of data centers on local water supply, a concern that has made a lot of headway in social media circles.

Another is electricity prices. Many fear the increased demand for electricity to power data centers will lead to higher prices for consumers. In an era of fears of growing problems with affordability and an economy that is still living in the shadow of 9% inflation in 2022, anything that could lead to higher prices still poses an area of concern for consumers.

Members of the public are also concerned about public investment in data centers. Ohio created a framework for economic development incentives for data centers over a decade ago in the Kasich administration’s first budget bill. Two years later, the incentive was expanded to more data centers. A recent story by Signal Ohio reported Ohio’s sales tax exemption for data centers ballooned from a projected $136 million in deferred sales taxes to $555 million in 2024 and $1.6 billion in 2025. A recent poll of Ohio economists conducted by my firm Scioto Analysis found only one of 14 economists believing tax incentives for data centers were an efficient strategy for job creation.

Another factor driving public interest in data centers is community change. Many of these arguments sound a lot like community opposition to solar panels or wind turbines, with people saying they are ugly or change the character or tenor of a neighborhood. For people who see a number of data centers crop up in their neighborhood in a short period of time, this sort of change can be shocking.

A final reason people are worried about the proliferation of data centers comes from a broader concern: social change. I was on a panel with social critic Michael Clune and tech consultant Nicole Jackson hosted by workforce strategy organization ASPYR last month. One thing that stuck with me that Clune said was that polling around adoption of the internet when it appeared in the 1990s was optimistic, even as few people were using it. This trend has been reversed with artificial intelligence: the technology is seeing rapid adoption, and the public is generally pessimistic about it. A viral speech from a Ravenna City Council meeting given against approval of a data center by a former programmer captures this sentiment well.

The truth is that each of these areas of concern for the public have shades of grey. Data centers impact the environment, but not nearly as much as agriculture or transportation. They impact energy prices, though these impacts can be mitigated by construction of new power generation projects to support them. Data centers and AI will change our communities and our society, but our communities and society are changing with these particular changes or without them.

But Ohio lawmakers can decide whether they want to spend billions of dollars on projects that are likely to happen without those incentives. Last week, Representative Tristan Rader and ten other members of the Ohio House of Representatives introduced legislation to phase out the data center subsidy starting later this year, leaving new data centers to the whims of market forces. While this change would not curtail all concerns with data center development in the state, it would at the very least give a chance for data center development to come a little closer to what an efficient market would provide.

This commentary first appeared in the Ohio Capital Journal.

The Policy Problem Lurking in Our Sewage

Have you ever stopped to wonder what ultimately happens to things you flush down the toilet? If you are like me, probably not. Or, to the degree you have ever paid any mind to the fate of your waste, you probably know that it ends up at a wastewater treatment facility. But what happens after it has been treated there? The answer, in many places around the U.S., is that it gets renamed and spread onto farmland.

For decades, this practice has been widespread across the U.S. Recently, though, this once-obscure corner of waste management practice has become a live issue for state legislatures and environmental agencies across the country. As concerns about contaminants in processed sewage waste have grown, states have begun taking a much closer look at what exactly is being spread onto their land and what should be done about it.

What are Biosolids, and Where and Why Do We Use Them?

Biosolids are the official term for what remains of waste after it has been processed and treated at a wastewater treatment plant. The liquid components of sewage are separated from the solids, then the solids are treated physically and chemically, resulting in biosolids. Biosolids are also commonly referred to as sewage sludge. 

Under Environmental Protection Agency rules, biosolids may be used on forests, parks, golf courses, rangelands and more; however, it is most commonly applied to agricultural land. 

Biosolids can improve the soil, making farms more productive while costing farmers very little, since the biosolids are generally provided by waste systems for free. The practice also comes with environmental benefits. Applying biosolids sequesters carbon in soil and reduces demand for phosphorus-based fertilizer, which is non-renewable but necessary for crops.

Moreover, biosolid waste has to be disposed of somehow. Recycling waste by applying it to land generates fewer greenhouse gas emissions than other options, such as burning the waste or dumping it in landfills would. It also saves public dollars which would otherwise need to be spent on these forms of disposal.

States vary in how much biosolids they apply to agricultural land. 

Comparison: What Percentage of Biosolids are Applied to Agricultural Land by State?

Chart Data: National Biosolids Data Project

Per- and Polyfluoroalkyl Substances (PFAS) in Biosolids

Since 1993, the Environmental Protection Agency has required biosolids applied to land to be processed under standards which includes requirements on sanitizing the waste for pathogens and sets maximum levels for metal contamination. In a September 2000 report, the Environmental Protection Agency cited the main issue of public concern over the practice as being the unpleasant smells people believe biosolid application will produce in their neighborhoods.

In the decades since, however, more substantial concerns have emerged. A 2013 study tested biosolid waste nationwide and found widespread contamination of chemicals known as “PFAS.” Subsequent research found similar results. 

What is “PFAS?”

PFAS is an umbrella term for thousands of related chemicals which have been widely used in industrial processes and consumer products since the 1950s. All PFAS have a carbon-fluorine bond in their chemical makeup. This type of bond is particularly strong, and that property means these chemicals do not break down easily. This trait is what earned them the nickname “forever chemicals,” as it gives them their tendency to persist in the environment.

PFAS’ presence in biosolids used for land application constitutes a public health concern because PFAS exposure has been linked to increased risks of kidney, prostate, and testicular cancers, increased cholesterol, low birth weight, accelerated puberty in children, and other negative health outcomes.

Policy Responses to Biosolid Contamination Problems

The Environmental Protection Agency states that due to these risks, it is taking steps to research and remediate biosolids PFAS contamination. The agency recommends that states monitor their own biosolids for PFAS in the meantime and work to identify industrial sources of the problem. 

States across the U.S. have responded to this guidance from the Environmental Protection Agency in different ways, with some moving beyond monitoring and source identification.

Testing and Threshold Approaches

States in this category are closest to the Environmental Protection Agency’s recommendation for policy to minimize the harms of PFAS in biosolid re-use. They are testing biosolids for PFAS, and in many cases certain levels of contamination trigger source identification efforts. Some states go further, forbidding or limiting the amount of biosolids which can be applied to land if PFAS is detected above a certain threshold. 

Colorado

In 2023, Colorado’s Department of Public Health and Environment began requiring biosolids preparers to monitor for PFAS contamination. If the level of perfluorooctanesulfonic acid (one specific type of PFAS, which Colorado uses as an indicator of more general PFAS contamination) detected exceeds 50 parts per billion, preparers are required to contact Colorado’s Department of Public Health and Environment and conduct an investigation into the contamination source.

Maryland

In 2024, Maryland’s Department of the Environment began requiring wastewater treatment plants to test for PFAS contamination. If the level found exceeds 100 parts per billion, the waste is prohibited from land application. If PFAS concentrations are 20-99 parts per billion, there are limits on how much biosolid may be applied per acre of land.

In 2026, Maryland updated these rules with the passage of Senate Bill 719. The new law restricts PFAS concentrations in biosolids used for land application to 25 parts per billion. Treatment facilities are required to develop mitigation and monitoring plans if their biosolids are found to have PFAS concentrations over 50 parts per billion. The new law will take effect in 2028.

Michigan

Michigan began a policy of testing biosolids for PFAS in 2021 and amended their approach in 2022 and 2024. Biosolids with PFAS contamination above 100 parts per billion are currently prohibited from land application use. Levels between 20-99 parts per billion trigger a source investigation and limits on how much biosolid can be applied per acre of land.

Minnesota

In 2025, Minnesota’s Pollution Control Agency released a strategy requiring wastewater treatment facilities which intend to apply biosolids to land to test for PFAS. If contamination greater than 125 parts per billion is detected, land application is not allowed and the source of the contamination must be investigated. Samples with 20-124 parts per billion may still be applied, with limits on how much can be used per acre of land. These samples also require a contamination source investigation.

Rhode Island

Rhode Island has an existing permitting process for anyone wishing to apply biosolids to land. In 2025, the state enacted a law requiring PFAS test results on the biosolids be included as part of the permit application. Those holding permits will also be required to furnish test results quarterly. No specific contamination threshold for rejection was outlined in the law.

Virginia

In 2026, Virginia passed a bill which will phase in testing for PFAS in biosolids. Wastewater treatment facilities will be required to test for PFAS, and if concentrations are found to be greater than 50 parts per billion, biosolids may not be used for land application.

Wisconsin

In 2024, Wisconsin’s Department of Natural Resources issued an interim strategy which requires biosolids to be tested for PFAS. If concentrations above 150 parts per billion are found, land application is not allowed and an investigation into the source of the contamination is required. If values are between 20-149 parts per billion, an investigation into the source should be performed, but application is still allowed, with limits on how much biosolid may be applied per acre. 

Differing Thresholds by State

Bans on Biosolid Application

These states have banned the practice of biosolid land application through new state laws.

Connecticut

In 2024, Connecticut passed PA 24-59, which banned the use and sale of biosolids for land use. The state had already prohibited direct land application of biosolids, so the new law primarily addressed commercial biosolid fertilizers and soil amendments which the earlier ban did not cover. 

Maine

In 2022, Maine became the first state to ban biosolid land application entirely.

Legislation to Study Contamination

This policy choice commits states to studying the levels of PFAS contamination for a period of time before moving forward with any future potential actions.

Washington

In 2025, the State of Washington enacted a law which requires facilities to test biosolids for PFAS between January 2027 and July 1, 2028, and supply results to the state. The law requires that the data be used to produce a report to the state legislature which will include recommendations on future legislative action.

Pending Legislation

Several states have introduced legislation which could alter their policy regarding biosolid land application. Some legislatures are working to introduce moratoria on biosolids land application, while others are attempting to establish PFAS monitoring practices.

Florida

During the 2026 legislative session, Florida’s legislature approved a bill which would require wastewater treatment facilities to test for PFAS quarterly and submit results to the Florida Department of Environmental Protection. If signed into law, this bill will take effect on July 1, 2026.

Illinois

Illinois’ Senate Bill 3917 would introduce monitoring requirements for PFAS in biosolids. The bill passed both the Illinois House and Senate and is currently awaiting the Governor’s signature.

New Hampshire

New Hampshire’s House Bill 1275 would impose a 5-year moratorium on the application of biosolids for agricultural use if passed into law.

New York

Senate Bill S9115A was introduced in the New York State Senate in 2026. This bill would establish a five-year moratorium on biosolid land application and require PFAS testing and reporting for biosolids. It is currently scheduled for a vote on the New York State Senate floor.

New York’s Department of Environmental Conservation already requires sampling of all biosolid sources and sets thresholds for acceptable concentrations. If levels above 20 parts per billion are not brought to less than 20 within one year of detection, biosolid use from that source is prohibited.

Where State Policies May Go Next

In the absence of a uniform federal standard, states are likely to continue developing their own approaches tailored to their local political environments, degree of local PFAS contamination concerns, and competing waste management and agricultural priorities. The result is a rapidly evolving policy patchwork across the U.S.

A core concern for those choosing to ban or heavily restrict biosolids application is what to do with all the biosolids waste otherwise. In Texas, House Bill 1674 was introduced in 2025. The bill would have regulated the use of biosolids as land fertilizer, but it ultimately failed in part due to opponents’ concerns about how much other disposal methods would cost wastewater utilities. Maine’s experience has proven those concerns are not unfounded. Since their outright ban of biosolid land application in 2022, nearly all biosolid sludge in the state now goes to one landfill. The landfill has applied for an expansion to accommodate the influx, but the process has been stalled by an appeal from a conservation organization concerned about the waste’s PFAS concentration polluting a nearby river.

Owing to these concerns, source control efforts may become more important to regulatory responses in the coming years. Michigan, Minnesota, Colorado, and Wisconsin all have policies which focus on identifying the sources of the PFAS contamination. If these states are successful at reducing PFAS in waste before it reaches wastewater treatment plants, they may be able to mitigate the public health risk without banning land application of biosolids, and other states may be able to follow suit in setting their own policies.

What is the difference between descriptive and inferential statistics?

Policy analysis is a data-driven field, but in this work we come into contact with a large number of people that don’t have as much experience working rigorously with data. Lobbyists, advocates, communications professionals and many more all play a role in the cadre of people who are involved in getting our policymakers the necessary information to make better informed decisions.

I wanted to take a moment today to talk to some of my colleagues who are working towards the same goal of evidence-based policymaking, but don’t necessarily have the formal background in statistics and explain one of the most common challenges that data analysts face.

Descriptive vs. inferential statistics

When most people hear the word “statistics,” they think of the specific numbers that we use to describe things in the world. However, I want to talk about statistics as a particular type of mathematics: the practice of doing statistical analysis. When we do statistics, it is almost always in one of two major categories of analysis: descriptive or inferential.

Descriptive statistics are used to summarize and describe data that we already have. If I tell you the average income in a county, the unemployment rate in a state, or the percentage of students who passed an exam, I am describing observed information. These statistics help us understand what happened, but they do not necessarily tell us why it happened or whether the same thing would happen somewhere else.

Inferential statistics go a step further. They use data from a sample to draw conclusions about a larger population. This is important because collecting information from every person, business, or household is often impossible. Instead, we gather information from a smaller group and use statistical methods to estimate what is likely true for the broader population.

How samples help us understand populations

Suppose you wanted to know the average height of every adult in Ohio. Measuring all 9 million adults would be extraordinarily expensive and time consuming. Instead, you might randomly select a few thousand people and measure them.

If the sample is chosen properly, the average height in the sample will probably be very close to the average height in the full population. It will not be exactly correct, but it will usually be close enough to answer most practical questions.

The same principle applies throughout policy analysis. Pollsters survey a few thousand voters to estimate public opinion. Economists analyze a subset of households to estimate poverty rates. Researchers study a group of patients to learn about the effectiveness of medical treatments.

The key idea is that we are rarely interested in the sample alone. We use the sample because we want to learn something about a much larger population. 

Notice how quickly the lines between descriptive and inferential statistics can get blurred. Calculating the average height of a group is a descriptive task, but intentionally calculating the height of a representative sample is inferential. This might seem a bit pedantic, like arguing about whether we should be saying this data or these data, but I would argue that this distinction is essential to understand.

The challenge of generalization

One of the most common mistakes people make when interpreting research is assuming that a finding from one population will automatically apply to another. This works when we’re careful about how we set up our analysis, but it can quickly fall apart and lead to incorrect analyses when we interpret results too broadly.

Imagine a workforce development program that increases employment among participants in one city. That result tells us something useful about that specific program in that specific location. However, it does not necessarily tell us what would happen if the exact same program were implemented somewhere else.

The local economy may be different. Participants may have different educational backgrounds. Employers may have different hiring practices. Transportation systems, housing costs, and labor market conditions may all vary. Even when the underlying program is identical, the environment surrounding it may not be.

This problem appears constantly in policy research. A tax policy that works well in one state may produce different outcomes in another. An educational intervention that improves test scores in one district may have little effect elsewhere. Researchers often refer to this issue as external validity. In other words, how well do we think results from one study can be generalized beyond the group that was originally examined.

This doesn’t mean that we can’t learn anything from past studies or programs that have been implemented in other locations. Often in policy analysis this is the only kind of data we have access to. What it does mean is we need to think about what the unique factors are that might influence these outcomes, and we need to do sensitivity analysis to try and figure out what might happen if some of our assumptions don’t hold.

Understanding the difference between descriptive and inferential statistics is important for anyone who works with data regularly. It is essential to be able to identify whether a piece of information is a simple statement of the way things are, or if it has been carefully constructed to enable us to make generalizations about some population.

What are the top anti-poverty programs in the United States?

Each September, the United States Census Bureau publishes a “Poverty in the United States” report on the current status of poverty across the country. In the report, the Census Bureau reports both the Official and Supplemental Poverty Measures across all fifty states. 

We’ve written about the difference between the official poverty measure and the supplemental poverty measure many times in the past at Scioto Analysis. The Official Poverty Measure estimates poverty rates using pre-tax income and family composition. The Official Poverty Measure can be somewhat limited in its scope since it doesn’t make any adjustments to income other than for inflation, though it does provide a consistent definition of poverty over time. 

The Supplemental Poverty Measure expands the definition of poverty to include noncash benefits, account for taxes and necessary expenses, and consider geographic cost-of-living differences. The Supplemental Poverty Measure presents a more comprehensive view of poverty and economic well-being across the country than the official poverty measure by adjusting for fiscal and geographic impacts on household resources and needs. Because it accounts for pre-tax income and noncash benefits, the Supplemental Poverty Measure is also useful for evaluating the effectiveness of anti-poverty programs in the United States.

The Census Bureau’s poverty report makes evaluating the effects of anti-poverty programs straightforward. Each year, they report on the change in the number of people in poverty after including each anti-poverty program in the Supplemental Poverty Measure’s calculation. In 2024, these programs resulted in at least 29 million people lifted out of poverty, 8-9% of the total U.S. population.

I decided to look into which anti-programs are the most effective tools at reducing poverty across the country. According to the Census Bureau, the top five most effective programs in reducing poverty in 2024 were Social Security, refundable tax credits, SNAP, Supplemental Security Income, and housing subsidies.

Social Security lifts 29 million Americans out of poverty

According to the Census Bureau, Social Security was responsible for lifting 28.7 million people out of poverty in 2024. This makes Social Security by far the most impactful anti-poverty program in the country by sheer magnitude. The most significant proportion of Social Security recipients are retirees– about 20.1 out of the 28.7 million people who were moved out of supplemental poverty are aged 65 years or older.

In 2024, the U.S. federal government spent about $1.5 trillion on Social Security, accounting for 15.9% of total federal spending. Despite the success of Social Security in providing supplemental income to retirees and disabled persons and reducing poverty, the program continues to grow more expensive each year. 

The Social Security Administration projects that by 2035, federal taxes will only be able to fund about 75% of the cost of Social Security. Given how many people the program affects, it’s no surprise that worries about the long-term feasibility of Social Security have grown more serious over the past several years.

Refundable tax credits lift 6.8 million Americans out of poverty

In 2024, the Census Bureau reports that refundable tax credits lifted about 6.8 million people out of poverty in the United States. Refundable tax credits include the Earned Income Tax Credit and the refundable portion of the Child Tax Credit. 

In a blog post I wrote earlier this year, I discussed the difference between grants and tax breaks in fighting poverty. I found that tax breaks are often much more efficient than grant-based anti-poverty programs. The administrative burden for tax-based anti-poverty programs is lower than other anti-poverty programs, as administering funds through the tax code is less costly than funding state and local welfare programs through grants.

Another reason refundable tax credits are so good at moving people out of poverty is that they allow households to spend money how they see fit instead of requiring the government to understand the individual needs of different households to achieve economic security. This is a similarity that refundable tax credits have to Social Security: these programs provide direct cash assistance to households, which allows them to use the money as they see fit.

SNAP lifts 3.6 million Americans out of poverty

The third most effective anti-poverty program according to the Census Bureau is SNAP. If you don’t know, SNAP stands for the Supplemental Nutrition Assistance Program, and it provides monthly funds for low-income households to purchase food. In 2024, SNAP was responsible for lifting about 3.6 million people out of poverty.

SNAP is different from Social Security or refundable tax credits because it provides in-kind benefits, which are non-cash benefits that are provided to meet specific needs (in this case, food). However, in many ways, SNAP functions similarly to cash-based anti-poverty programs by freeing up a significant portion of monthly income for other household expenses.

According to the ALICE survival budget for Ohio, the state where I live, a single adult’s monthly survival cost for food is $443, nearly 20% of their total monthly budget. The average SNAP benefit for a family in 2023 was about $332, relieving a significant portion of food spending for other household expenses.

Supplemental Security Income lifts 2.5 million Americans out of poverty

According to the Census Bureau, Supplemental Security Income is responsible for lifting about 2.5 million people out of poverty in 2024. Supplemental Security Income provides monthly cash payments to low-income older adults and people with disabilities.

Despite the program’s effectiveness in reducing poverty, The Brookings Institution estimates that just 50% of people who are eligible for Supplemental Security Income receive benefits. This may be partially due to the program’s complicated application and approval process. In particular, Supplemental Security Income has extremely strict limitations on assets. To qualify for Supplemental Security Income, countable resources may not exceed $2,000 for an individual or $3,000 for a couple, a metric that has not been updated since 1989.

Housing subsidies lift 2.1 million Americans out of poverty

According to the Census Bureau, housing subsidies are the fifth most effective anti-poverty program in the United States, lifting about 2.5 million people out of poverty in 2024. Housing subsidies in the United States generally fall into three main categories: rental housing assistance, assistance to state and local governments, and assistance for homeowners. To reduce poverty, the main goal of housing subsidies is to make housing affordable for low-income households. Two of the major forms of housing subsidies for low-income households are section 8 vouchers and public housing. 

Section 8 vouchers are rental subsidies which allow renters to pay a lower, more affordable monthly rent payment to private landlords. Renters typically pay about 30% of their gross monthly income on rent, and the government pays the difference between the amount charged by the landlord and the amount paid by the renter. Public housing refers to subsidized residential properties that are owned by the government to provide more affordable places for low-income households to live.

Housing subsidies can be a great way to reduce poverty since they focus on the most significant portion of most households’ monthly budgets. However, the shortage of affordable housing continues to grow across the country, and most housing subsidies are associated with long waiting lists and stigma.

What is a negative income tax?

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

How does a negative income tax work?

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

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

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

Why do economists like negative income taxes?

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

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

Costs of a negative income tax

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

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

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

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

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