What are tariffs?

Early Wednesday morning, major news networks reported that Donald Trump would win the 2024 presidential election. Now that the dust has settled, we can start to envision how the next four years might unfold.

Scioto Analysis usually focuses on state and local policy decisions. However, one significant national topic that will have an impact on pocketbooks across the country is President-Elect Trump’s proposal to raise tariffs.

Trump has called “tariff” the “most beautiful word in the dictionary,” while Vice President Harris has referred to his plan as the “Trump sales tax.” This discrepancy makes it easy to understand why many people are unclear about what this potential policy might mean.

A tariff is a tax on imported goods. Much of the debate in the media has focused on who ultimately pays this tax—whether it’s foreign nations or domestic importers (technically, importers pay the U.S. government). However, who writes the check is less important than who bears the actual increased cost.

In economics, we look at the tax burden to understand who ends up paying a tax. Even if importers pay the government directly, they can often raise prices to offset their costs. Fundamentally, a tax on producers and a tax on consumers are identical. 

The actual cost to either party is based on how willing and able they are to substitute their spending into other categories. Classical economic theory tells us that the degree to which a tax is passed to consumers depends on the elasticity of supply and demand. The elasticity of a good tells us how much supply and demand respond to changes in prices. Essentially, whichever side is less dependent on the taxed good or service bears less of the burden of the tax.

Consider President George H.W. Bush’s ill-fated yacht tax in the early 1990s. This tax on luxury yachts aimed to raise revenue from wealthy Americans. However, yacht buyers—who don’t “need” yachts—easily redirected their spending to other luxury items when prices rose. Yacht producers, however, had a harder time pivoting, so the tax burden fell heavily on luxury shipbuilders instead.

When evaluating new tariffs, we shouldn’t focus solely on who sends money to the Department of Treasury but rather on which goods are taxed. Ultimately, American consumers are likely to face higher prices on items that rely on foreign imports. But this doesn’t mean tariffs are always a poor policy choice.

Since tariffs increase the price of imported goods, they can make domestically-produced goods relatively cheaper, potentially boosting domestic industries and creating jobs locally. If producing something domestically has positive side effects (like reducing pollution or increasing wages), a tariff might be sound policy. These benefits could be offset, though, by lower spending domestically due to higher prices caused by tariffs.

A tariff is just another type of tax. Taxes generally create distortions for the economy, but they raise revenue that can fund important public services. If, for instance, tariff revenue were used to fund an expanded Child Tax Credit, the benefits might outweigh the added costs.

At this point, all we know is that President-Elect Trump intends to raise tariffs. Exactly what these tariffs will look like and how the revenue will be used will be crucial in determining their real impact on the American people.

What will the election really mean for inflation?

When voters cast their ballots for president next week, they will make a decision that will have a substantial impact on Ohio’s economy. According to the Pew Research Center, “the economy” is the top issue for voters this election, with 81% of registered voters saying it is very important to their vote in the presidential election this year. So let’s see what the implications of this election will be for the top economic issue for voters: inflation.

According to a late summer survey by the Pew Research Center, 74% of U.S. adults are very concerned about the price of food and consumer goods. The return of high levels of inflation for the first time in generations over the past few years has certainly had an impact on the public.

Vice President Harris has tried to blame rising prices on “price gouging” and corporate greed while Trump has focused on energy.

Harris’s proposals around a national ban on price gouging have caught skepticism from economists. A panel of preeminent economists recently rejected the assertion that price gouging was driving grocery prices.

The same panel also agreed tariffs, one of Donald Trump’s favorite policies, would increase consumer prices. The Peterson Institute for International Economics estimates Trump’s more aggressive tariff proposals would cost the average American household over $2,600 a year. Trump calls “tariff” “the most beautiful word in the dictionary. More beautiful than love, more beautiful than respect.” Your wallet disagrees.

Maybe the most important thing from the next president is what the chief executive will not do. Despite the rise in inflation to over 9% in the summer of 2022, action by the Federal Reserve pushed inflation down to 3% by the summer of 2023 and as of September of this year, it has dropped to 2.4%, its lowest rate in over three years.

Yes, tariffs will put upward pressure on inflation. But the difference between the presidential campaigns’ approach to the Federal Reserve might be even more important to the trajectory of prices. While Vice President Harris has made clear she supports continuing the tradition of independence of the Federal Reserve, Trump has repeatedly said he would want to exert power on the Federal Reserve as president.

While Trump was unable to use his political power to substantially threaten the political independence of the Federal Reserve in his first term, he was able to erode the political independence of and public confidence in a more central American institution: the U.S. Supreme Court. The Supreme Court bottomed out in 2022 at its lowest approval rating in generations partly because of its overtly political rulings, including rulings to shield the President from the reach of the law.

Turkey gives us a great example of what happens when politicians control monetary policy. President Recep Tayyip Erdogan has argued that low interest rates decrease inflation and put his hands on the levers of their national economy. This led to Turkish inflation reaching 85% in 2022, nearly 10 times as high as the U.S.’s generational peak that year. Inflation has only started to cool as Erdogan has taken his hands off the levers and allowed its central banks to increase interest rates.

If the U.S. has to contend with the twin problems of tariffs and loss of Federal Reserve independence, prices will increase again and could get worse than they were in 2022. Maybe it needs to get this bad for America to learn the dangers of authoritarian economic control. But while we learn that lesson, food will be harder to put on the table, rent will be more difficult to pay, and prices at the pump will increase. And state and local governments will be scrambling trying to figure out how to clean up the mess the federal government made.

How do basic income programs impact employment?

In recent years, many communities across the world have begun to test basic income programs, unconditional cash transfers to low income people. This type of assistance solves a problem that exists in other social safety net programs: in-kind transfers (such housing subsidies or food assistance) don’t offer much flexibility to the people that receive them.

A common criticism of basic income programs is that they might encourage people to exit the workforce. If people can get by without working, then what incentive do they have to keep working? This is just speculation right now, and there is some evidence to suggest that there aren’t negative labor market consequences to basic income programs. 

In a new working paper this month, there actually seems to be some evidence that at least one basic income has some positive impacts on the labor market. Researchers looked at a basic income program in Maricá, Brazil, a small city in Rio de Janeiro state. There, approximately 42,000 residents receive around $25 USD per month in the form of Mumbuca, a local currency. Recipients have the freedom to spend as they wish, and since Mumbuca is only accepted within the city, it ensures that the funds directly support the local economy.

The study found that Maricá’s basic income program positively impacted local employment rates. After the program's implementation, formal employment in Maricá was about 20% higher than in comparable municipalities without a similar program. The researchers offered three potential reasons why employment rates actually increased. 

1. Increased Local Consumption and Demand
   The unconditional income provided through the program strengthens the purchasing power of residents. With more reliable monthly income, recipients can spend more on goods and services locally. Since Mumbuca can only be used within Maricá, this spending stays local, boosting the revenues of city businesses. This increased demand requires businesses to expand, often by hiring more workers, which leads to job growth.

2. Reduced Financial Constraints for Job Seekers
   Basic income also reduces financial constraints for residents. With a steady income, they feel more secure financially, allowing them to engage in formal employment opportunities they might have avoided previously due to upfront costs like commuting or child care. Additionally, the program may encourage entrepreneurship, as recipients have the flexibility to use their funds to start small businesses. As these businesses grow, they add to the demand for labor, generating further employment opportunities.

3. Economic Spillover Effect of Local Currency
   The use of Mumbuca as a local currency amplifies the economic effects of the cash transfer. Since the currency cannot be used outside Maricá, it effectively locks the cash into the city’s economy. This restriction ensures that any funds spent by program recipients remain in Maricá, creating a higher local economic multiplier effect than if residents could spend outside the area. For businesses and employees, this local spending translates into stable, predictable demand, which further incentivizes hiring.

Maricá’s experience shows that basic income can potentially strengthen employment rather than hinder it, particularly in a tightly knit local economy. The boost to consumer spending and the spillover effects of the local currency help make the formal job market more vibrant and sustainable. While basic income programs are often viewed as a way to provide social safety nets, Maricá’s model suggests they may also stimulate local economic activity and job creation. 

The Maricá basic income program appears to have provided recipients with the flexibility to make different choices regarding their work. According to the study, labor income among recipients decreased by 17%, which researchers believe indicates that some participants may have transitioned to lower-paying but more personally fulfilling jobs. This trend suggests that the security provided by a basic income might enable individuals to pursue work that aligns better with their personal preferences or offers better work-life balance, especially important considerations during the pandemic.

This shift challenges the common assumption that basic income could reduce the incentive to work. Instead, it highlights how unconditional cash transfers can give individuals the freedom to choose jobs based on factors other than salary alone. This autonomy to pursue desirable work, even if it is lower-paying, underscores one of the potential benefits of basic income: it allows people to prioritize well-being and personal goals without the constant pressure to maximize earnings. For policymakers, this is a promising indication that basic income programs could contribute to a more adaptable, satisfied workforce.

We might worry that the unique nature of the basic income being paid in the form of a specific local currency might increase the potency of these positive effects, but this remains a positive sign for policymakers interested in exploring basic income programs for their own jurisdictions. Money gets multiplied as it moves through the economy. If well designed, basic income programs could make everyone better off. 

Ohio economists: “benefits cliff” creates barriers to career advancement

In a survey released this morning by Scioto Analysis, all 19 economists surveyed agreed that “benefits cliffs” caused by strict income requirements for public benefits create significant barriers to career advancement for low-income workers. The benefits cliff refers to the phenomenon where small increases in wage income can lead to large decreases in total income because people no longer qualify for benefits. For example, a low income worker might not want a raise or an increase in hours if those things would mean they no longer receive a valuable tax credit.

To address this problem, Ohio's Department of Job and Family Services announced earlier this month that they were introducing a new sliding scale for SNAP benefit levels in the state. ODJFS Director Matt Damschroder said "Fear of losing food benefits can be a deterrent to taking a new job, working more hours, or even accepting a promotion. Instead of an all-or-nothing approach, we are creating a sliding scale that encourages people to earn more by slowly reducing their benefits as  their income grows. This provides an incentive to accept promotions and pay raises knowing they won’t immediately lose benefits." 

When asked about this particular policy change, 13 economists agreed that the sliding scale will lower barriers to work for low-income people. The other six were either uncertain or had no opinion. As Curtis Reynolds from Kent State wrote “This should lower some barriers.  More importantly, however, it would likely help people retain some SNAP benefits.  Good research has shown that sharp work requirements lead some people to enter the labor market but cause a larger decrease in SNAP participation (see Harris, Timothy F. ‘Do SNAP Work Requirements Work?’)”

The Ohio Economic Experts Panel is a panel of over 40 Ohio Economists from over 30 Ohio higher educational institutions conducted by Scioto Analysis. The goal of the Ohio Economic Experts Panel is to promote better policy outcomes by providing policymakers, policy influencers, and the public with the informed opinions of Ohio’s leading economists. Individual responses to all surveys can be found here. 

How do you calculate the marginal excess burden of taxation?

Last week, I wrote about what the marginal excess burden of taxation is and why it’s important. The basics of that article are that usually, we don’t count transfers in cost-benefit analysis because what counts as a benefit to one person counts as an equal cost to another. The net cost to society comes from distortions the tax and transfer system makes to the economy: incentives or disincentives for work or consumption. This is because when the government has to raise taxes in order to initiate this transfer of dollars that creates a drag on the economy that we need to account for within a cost-benefit analysis.

Today, I want to talk about how we actually calculate the marginal excess burden of taxation. Below, I presenthat steps there are and what considerations need to be taken into account when estimating the marginal excess tax burden of a policy. 

Determine what indicators need to be included

In a cost-benefit analysis, it is not always obvious which indicators need to be viewed through the lens of marginal excess tax burden. In general, this should be anything that involves public dollars being spent, even in situations where a benefit or cost is not directly connected to a theoretical change in the tax code. This is because tax dollars ultimately are needed to finance these programs, and these taxes create distortions within markets.

This came up in a cost-benefit analysis we are currently working on. We are analyzing the impacts of a Universal Pre-K program in Ohio, and one of the benefits is the avoided spending on public schools as a result of fewer students having to repeat grades. 

Although this benefit is not directly associated with a change in marginal tax rates (this avoided spending could in theory just be redirected to some other public school program), because we are dealing with a reduced spending of tax dollars the benefit should be the loss of the theoretical drag on the economy. 

Choose a value for the marginal excess burden of taxation

Depending on what source you look at, the marginal excess burden of taxation could be as high as 75% or as low as 11%. Clearly, what value you choose can end up having a major impact on your final results. As James Hynes from the University of Michigan explains: 

“A major practical difficulty in measuring the excess burden of a single tax, or of a system of taxes, is that excess burden is a function of interactions that are potentially very difficult to measure. For example, a tax on labor income is expected to affect hours worked, but may also affect the accumulation of human capital, the intensity with which people work, the timing of retirement, and the extent to which compensation takes tax-favored (e.g., pensions, health insurance, and workplace amenities) in place of tax-disfavored (e.g., wage) form. In order to estimate the excess burden of a labor income tax, it is in principle necessary to estimate the effect of the tax on these and other decision margins.”

And that is just for the marginal excess burden of income tax. We know that there are different rates of excess tax burden for different types of taxes as well. 

If you know how a potential policy is going to be funded, then you should try and use an estimate for the marginal tax burden associated with the type of tax you expect to be levied. If it is unclear, then finding a median estimate is likely the best way to proceed. 

Multiply

The easiest step by far when determining the marginal excess burden of taxation is calculating it. If a program is going to cost $100 and you have determined that your marginal excess tax burden is 50%, then the social cost of your program is $50. 

Understanding and calculating the marginal excess burden of taxation is crucial in evaluating the true economic impact of public spending. By carefully selecting the appropriate indicators and using reliable estimates for the excess burden, we can more accurately assess the broader social costs of government programs.

Why carbon prices matter

Last week, New Republic Staff Writer Kate Aronoff penned a commentary arguing against approaches to climate action like carbon taxes and cap-and-trade programs. Her core argument in the commentary is that proper climate action is a question of trust and that public sector actors are more trustworthy than private actors when it comes to addressing climate change.

Aronoff makes some good points throughout her commentary. She hits on a core problem with climate change: left to their own devices, households have a strong incentive to emit carbon because their private benefits are much higher than their private costs. This is classic “tragedy of the commons” problem–a stable climate is a common resource. If no one is managing that resource, individuals will deplete it until it no longer exists.

This is a problem that was pioneered by Nobel Prize-Winning Economist Elinor Ostrom. Ostrom did groundbreaking work describing how common property can be successfully managed by groups that use it.

In an analysis Scioto Analysis conducted a few years ago, we looked at options for the state of Ohio to reduce carbon emissions. The tools we analyzed were a renewable portfolio standard (a mandate for utilities to generate a certain percentage of energy from carbon emissions), a cap-and-trade system (a limit to carbon emissions managed by the state), and a tax on carbon. Ultimately, when estimating the impact of each of these interventions, we found that any of these interventions would be highly preferable to the status quo, each with the ability to abate hundreds of billions of dollars worth of carbon emissions compared to the status quo.

So you have some policy analysts like us who have found compelling evidence that a cap-and-trade or carbon tax program would have a significant impact on carbon emissions in the state of Ohio. Why, then, does Aronoff say “[c]arbon pricing has thankfully fallen out of favor among wonks and lawmakers?”

There are two elements of Aronoff’s claim that are worth exploring. First, is the empirical claim that wonks and lawmakers do not favor carbon pricing.

It has been a few years since the IGM Forum has polled its national panel of economists on carbon pricing, but last time it did, the opinions were overwhelmingly positive. In a March 2021 survey, 91% of economists agreed increasing the price of carbon was sound policy, with 79% “strongly agreeing” and only 2% uncertain. No economists disagreed with the statement. In a November 2021 survey, 75% of economists agreed a global price floor on carbon emissions would be an effective tool for achieving sharp reductions in global carbon emissions. I am not aware of any evidence that this overwhelming economic consensus has deteriorated.

Meanwhile, 53 countries and 40 subnational jurisdictions have implemented some sort of carbon price. These range from 12 US states in the Northeast and West Coast to high-income countries like Canada, France, Germany, and the United Kingdom all the way to middle-income countries like China, Kazakhstan, Mexico, and South Africa.

What Aronoff may be referring to is some high-profile conflicts that have emerged over carbon pricing. Hedge Fund Executive Brian Heywood has been leading an effort in Washington State to repeal their cap-and-trade program through a ballot initiative. Canada’s Conservative Party has made their country’s carbon tax a rallying cry in their current effort to take back their government for the first time in a decade.

So yes, carbon pricing has its critics among lawmakers, though I don’t think Heywood and Canadian conservatives were ever particularly fans of carbon pricing mechanisms. But if we were in this universe where experts were fleeing from the consensus that carbon pricing is an effective tool to reduce emissions and lawmakers across the world were repealing these laws, why would we be thankful for this?

Aronoff’s argument against carbon pricing is that economics is wrong. The core argument she lands on at the end of her commentary is that “Only governments are equipped to make the kinds of plans that will keep people safe as temperatures rise.”

There is a bit of a conflation of two ideas here. Aronoff spills a lot of digital ink arguing against the idea of carbon pricing, which is a climate mitigation strategy, not adaptation strategy. In layman’s terms, this means carbon pricing is put in place to reduce the rise in temperatures. Adaptation strategies, like deciding where to live as climate changes, are strategies we deploy in light of temperatures rising.

What Aronoff claims throughout her commentary is that people are not capable of making decisions that are in line with the common good. She argues that key decisions are best left up to government because if people consume energy as they like or more to where they would like, it will lead to depletion of these common resources that we are talking about.

What she misses in this analysis is that government always relies on individuals to carry out its mandates. Tackling climate change is not something government can do on its own: it is going to take action by individuals to make sure that our stable climate resource is not depleted and that we take the necessary steps to manage infrastructure and our economy in the face of what climate change does occur.

On the other hand, individuals, left to their own devices, have little reason to act altruistically. Given the chance to help their family by purchasing electricity or have a marginal reduction in carbon emissions, by and large they will put their family first.

That is why carbon pricing matters. If people don’t see the cost of carbon on price tags, they will not change their consumption habits. The strange irony of arguing government needs to throw the kitchen sink at carbon emissions is that carbon pricing is the kitchen sink. It’s an impediment to actors throughout the economy contributing to a carbon-intensive economic system that will spur a host of economic adaptations that will reduce emissions.

So no, government can’t fight the climate on its own. And neither can markets. Only a market regulated by the public sector will be able to do that.

How to count non-human animals in cost-benefit analysis

Earlier this year, former OIRA Director and leading regulatory scholar Cass Sunstein published an article in the Journal of Benefit-Cost Analysis on why regulators should consider the impact of policy on non-human animals.

This is a topic we have written about at Scioto Analysis before. Non-human animals are often left out of cost-benefit analysis, with impacts of regulations on the lives of non-human animals getting a de facto value of zero in regulatory analysis.

Dave Weimer, a leading scholar of cost-benefit analysis, wrote a prominent article in 2019 on the “value of statistical dog life.” In this article, Weimer conducted a contingent valuation study where he surveyed dog owners on their willingness to pay for vaccines that would marginally decrease the mortality risk for their pets. Using this method, Weimer estimated a value of statistical dog life of $10,000.

While this is a step in the right direction for valuation of non-human animal life, this approach still derives the value from human markets using the value human beings place on non-human animal lives. This makes sense if human beings are the only people who participate in markets and economize their resources. And this is the general argument analysts make who exclude non-human animal costs and benefits from cost-benefit analysis: non-human animals do not take part in markets, so it makes little sense to designate market values to their welfare. Instead, the welfare of non-human animals should be treated as a consideration separate of cost-benefit analysis.

The problem with this reasoning is that non-human animals clearly manage scarce resources and engage in market-like behaviors with one another. Chimpanzees have been observed to engage in grooming and food sharing that mimics markets, with grooming serving as a form of currency. Capuchin monkeys have been able to intuit currency in laboratory settings, even demonstrating behaviors like price sensitivity and demand elasticity. A 2017 Bloomberg article detailed the many ways markets have arisen among non-human animals, ranging from wasps engaging in childcare markets to cleaner fish deciding who to eat dead skin and parasites off based on quality choices.

Sunstein says nonhuman animals pose an important challenge and problem for analysts conducting cost-benefit analysis. Last year, the Office of Management and Budget conducted the largest overhaul of Circular A-4, the federal regulatory guidance document for cost-benefit analysis, in a generation. Unfortunately, the question of how to incorporate benefits and costs of nonhuman animals into federal cost-benefit analysis did not receive any treatment in this revision. Sunstein calls this a “missed opportunity” and I am inclined to agree.

Sunstein goes back to the history of the value of statistical life to illustrate the complexity of valuing the benefits and costs of nonhuman animals. Value of statistical life began as a measurement used to estimate the cost of retraining bombers during the Korean War. Later iterations focused on future wages as a way to estimate the value of life. Most recently, value of statistical life is estimated by using labor market data. Economists are able to estimate the value people place on minute reductions in risk of death by seeing how different occupations at different skill levels are paid. This has led to a value of statistical life estimate that hovers around $10 million.

An analogue to the problem of estimating costs and benefits for non-human animals is the problem of estimating the value of statistical life for children. Children do not participate in the labor force, so we do not have the datasets we have to estimate the value of statistical life for children that we do for adults. This leaves us with options to either assume the value of statistical life for children is the same as it is for adults or find another way to estimate the value of statistical life for children. Often, researchers will use contingent valuation or revealed preference studies of parents to estimate the value they put on children to try to get at the value of statistical life for children as estimated by parents.

The problem with this approach is the assumption of perfect altruism, which we know is not the case with parents or pet owners. There also could be an opposite problem: pets or children could (in a theoretical perfectly rational state) value other things more than minute reductions in risk of death. In this case their guardians could overestimate the value of statistical life for their wards. There is a mismatch between the preferences of pets and children and their caretakers.

Putting aside these methodological problems, many laws have been put in place specifically to protect the welfare of non-human animals. Sunstein raises the examples of the Endangered Species Act, the Animal Welfare Act, and the Marine Mammal Protection Act as three laws that were specifically adopted to protect the welfare of non-human animals. Leaving their welfare out of the calculation of costs and benefits–especially in light of the information that nonhuman animals absolutely engage in market behavior–seems to be fundamentally missing the point of this legislation and leaving key information out of analysis that is supposed to guide policymakers in implementation of the legislation.

Sunstein says in his article that the problem with incorporating non-human animals into cost-benefit analysis is not a problem of quantification, but a problem of monetization. We can create estimates for how many non-human animals will be impacted by a regulation or other policy change. The problem is trying to figure out what the value of those benefits or costs are. Sunstein grapples with the same problems we lay out here. We can use stated preference or other strategies for estimating the value of impacts on non-human animals. Ultimately, though, these strategies depend on human assessment of the value of benefits and costs to non-human animals, not assessment by those who receive the benefits and costs themselves.

With these methodological problems in place, though, what can we do? Sunstein does not proffer much within his article: he mainly focuses on the problem rather than the solution. He does put forth one tool for consideration, though: break-even analysis. Basically, see what the value of non-human animal benefit or cost would need to be to tip the scales in the benefit-cost calculation. Then we can use our intuition to see if that is a reasonable value for the given benefit or cost and apply that reasoning to policymaking.

We consider break-even analysis to be a form of sensitivity analysis, and sensitivity analysis is an excellent tool in any benefit-cost analysis where we don’t know a key input. Maybe we don’t have the answers for the economic value of benefits and costs accrued by regulation to nonhuman animals. In the meantime, sensitivity analysis gives us a technique for incorporating consideration of non-human animals into benefit-cost analysis in light of a dearth of valuation information.

What is the Marginal Excess Burden of Taxation?

Next month is the presidential election, which means it is the time of year when everyone starts to have extremely strong opinions about taxes. Depending on who you talk to, taxes might be the backbone that keeps our country functioning or the heaviest weight preventing us from achieving our true potential as a society. 

From an economics perspective, taxes are a uniquely interesting way to move money from one household to another. When conducting a cost-benefit analysis, we are agnostic about transfers of money from one place to another. While there has been a recent push to pay more attention to the distributional effects of transferring money around, classical economic theory tells us there is no net economic benefit to moving money from one person to another.

If you give your neighbor $20, the economy hasn’t grown or shrunk, a small part of it has just changed hands. In terms of the value those $20 create, it is unlikely that your neighbor will use it in a dramatically more efficient way than you. $20 in your hands is equal value to $20 in anyone else’s hands.

This logic changes when we talk about transferring money to the government (i.e. taxes). There are two main reasons why:

1. People change their behavior in response to changes in their taxes.

2. The government can spend its money on providing public goods.

Say the government wants to fund an expanded Child Tax Credit and plans on raising income taxes to finance it. Individuals can see that their labor is relatively less valuable to them since more of the income will be paid in taxes. This gives them good reason to work fewer hours, instead spending time on other activities that have become relatively more valuable. 

This results in a distortion of the economy that economists call the “marginal excess burden of taxation.” When we do a cost-benefit analysis, this marginal excess tax burden is what we estimate as the social cost of raising taxes. Again, we are agnostic about transfers because a dollar in one person’s hands is no better than the dollar anywhere else. What we care about is how this policy change impacts the way people spend their time, which then changes the size of the economy. This distortion is also the justification for the “all taxes are bad” crowd. 

However, taxes don’t just sit in a vault somewhere, they often get used to fund important public programs. Public infrastructure, our social safety net, public schools, all of these need money to function. Additionally, because these are public goods they suffer from the free rider problem. Essentially they can’t be funded privately, because there are no incentives for people to pay for these goods. 

So, how can we tell if a tax policy change is worth it or not? We should figure out whether the dollars brought in by that tax are going to fund something that creates more economic value than the marginal excess burden of taxation we are incurring. 

There is another key tradeoff of public policy: equity vs. efficiency. Yes, in a vacuum taxes are an inefficient way to collect money because they create a drag on the economy. However, not collecting any taxes would lead to massive gaps in equity as people with fewer resources would not be able to access all sorts of things that are publicly provided by the government. 

We still have a month to go before the election is over, so we should expect the rhetoric about taxes to stay extremely polarized for the time being. Hopefully, once we know who the next president is we can begin to have more productive conversations about tax policy and its implications on the economy. 

Ohio tackles the “benefits cliff”

Earlier this month, the Ohio Department of Job and Family Services announced it was expanding eligibility for SNAP benefits, the program formerly known as “food stamps.”

This may come as a surprise to those who follow state politics in Ohio, which I assume most who read the Ohio Capital Journal do. But the expansion is aimed toward fixing a problem that people across the political spectrum are worried about: the “benefits cliff.”

The benefits cliff is the buzzword (“buzzphrase?”) used to describe a prevalent problem in policy design. A means-tested program focuses its funds on low-income households. This often means limiting eligibility based on income. For instance, a cash assistance program could limit eligibility to households with incomes under 150% of the federal poverty line.

The problem with a strict cutoff, however, is that it creates incentives on either side of the cutoff that can significantly impact work decisions. For instance, if your family gets $250 a month in means-tested cash assistance and you are offered a $100 raise that will make you ineligible for that assistance, you have a good reason to turn down that raise.

Similarly, if you earn income just over the eligibility threshold, this provides an incentive for you to cut hours to gain eligibility. If you are at the cliff, you don’t want to jump off. If you are at the bottom of the cliff, you want to get back on top.

When I was in graduate school, I did my capstone project on this problem. I recommended nonprofits aiming to ameliorate the problem of the benefits cliff provide cash to families that eases off as families make more income. Unfortunately, the now-closed research firm I worked with declined to share this information with the client it was prepared for, saying this analysis was not relevant to the client’s work.

Luckily, the Ohio Department of Job and Family Services is now proving them wrong. With their new expansion of the SNAP program, the Department is providing what they are calling a “sliding scale” of benefits that extend from the previous cliff of 130% of the federal poverty line to 200% of the federal poverty line. This means basically all low-income households will be eligible for SNAP benefits, with households closer to 200% of the federal poverty line receiving lower amounts than those at 130% of the federal poverty line and below.

The benefits cliff is a policy problem of our own making. Well-designed policies can eliminate cliffs. This does not eliminate incentives: households will still have some incentive to not take raises, promotions, or more hours due to lower benefits being provided as income increases. But eliminating the cliff will make the incentives much less drastic.

This is a great example of government working. People in the business community and poverty advocates both saw this as a problem with the system. Policymakers were willing to come to the plate and make the resources available to solve much of the problem. Ohio’s benefit system will be more efficient because of this. In a time when it is easy to be cynical about what government can do, let’s applaud a clear win when we have one.

This commentary first appeared in the Ohio Capital Journal.

Federal government takes the lead in removing lead pipes

On Monday, the Biden administration issued an updated Lead and Copper rule that requires drinking water systems across the country to identify and replace all lead service lines in the next 10 years. The rule also requires more rigorous testing of drinking water systems and increased communication about the risks associated with lead in drinking water.

I’ve written about the EPA’s lead and copper rule before, mostly focusing on this paper which talks about the immense benefits that this rule could create. That same paper recently influenced our own analysis of a proposal to replace lead service lines in Ohio. 

The biggest takeaway from both of these analyses is that removing lead service lines from our drinking water systems could be one of the most valuable ways to spend public dollars we have. The damage done by lead in our drinking water is immense, resulting in a wide range of economic and health problems for everyone exposed. Our analysis found that removing every lead pipe in Ohio could result in 650 fewer infant deaths and nearly 10,000 avoided deaths from heart disease in the first 15 years. 

Not only would replacing lead service lines prevent deaths, but it would also significantly improve the quality of life for Ohioans in many other ways. The analysis revealed that over 290,000 children in Ohio would avoid losing an average of 1.25 IQ points, a benefit that would lead to $8.4 billion in future earnings over the next 15 years. This is just one example of how the removal of lead service lines is an investment in Ohio’s future, an investment that pays dividends in better health, higher productivity, and stronger communities.

Our study also highlights the mental health benefits of replacing lead pipes, estimating that 3,800 fewer cases of depression and 520 fewer cases of dementia would occur over the 15-year period. We’d also see fewer cases of ADHD, anemia, and coronary heart disease that would result in substantial economic benefits in terms of medical costs and lost productivity.

From an environmental and economic perspective, the benefits are equally as striking. Replacing lead service lines would reduce water waste, with an estimated $82 billion saved over 15 years. Lead service lines, many of which are decades old, no longer function efficiently and contribute to unnecessary water loss. Updating this aging infrastructure is a key part of making Ohio’s water systems more sustainable and cost-effective in the long run.

This is especially important for Ohio, which faces a disproportionate burden when it comes to lead service lines. The state accounts for over 8% of the nation’s lead pipes despite making up only 3.6% of the U.S. population. This makes the issue even more pressing for Ohioans, and efforts to replace these pipes are extremely likely to be positive investments for the state.

Ultimately, the data from this cost-benefit analysis underscores that replacing lead service lines isn’t just about addressing a health crisis, it’s about making a smart financial investment in Ohio’s future.