Meet Our New Data Science Intern, Noah Stein!

Last week, analyst Noah Stein started as a data science intern for Scioto Analysis.

Noah is currently an undergraduate at Denison University, majoring in Data Analytics with a concentration in economic theory. Previously, Noah has performed consumer research and analysis for on-site restaurant company Bon Appetit to inform spending decisions around local food sourcing. Noah has also done operations analysis for the Canadian National Women’s rugby team.

At Scioto Analysis, Noah will be producing hard-hitting analysis on the COVID-19 crisis including a cost-benefit analysis of Ohio’s state social distancing measures. In the summer, Noah will be playing a big part in the creation of a new Ohio poverty measure designed to capture geographic differences in cost of living and the impact of the state social safety net.

“I look forward to being able to provide analysis of key issues during this important time for global health,” said Noah.

Join us in welcoming Noah!

How many lives will Ohio save with social distancing?

In the past week, the state of Ohio unveiled Ohio State University modeling of projected daily cases of COVID-19 through the end of May. This forecast suggests that social distancing measures have pushed the peak of the epidemic back by a month and reduced peak daily infections from 60,000 new infections down to less than 10,000.

Data from the Ohio Department of Health.

Many who have advocated for flattening the curve say that the reduction of the strain on the health care system—the justification for social distancing policies—would save lives even if the long-term infection rate was the same by making sure everyone who needs treatment has access to it. The OSU modeling, though, suggests the total number of Ohioans infected from the beginning of March through the end of May will be nearly halved from 450,000 to 230,000 through adoption of strict social distancing measures.

So how many fatalities should we expect over that time period? The most straightforward way to estimate this number would be to assume the current fatality rate of 2.6% stays constant. This is close to the US fatality rate of 2.4% (derived from Johns Hopkins University Center for Systems Science and Engineering numbers) so this seems like a reasonable assumption. In this scenario, we would expect to see about 6,000 fatalities from COVID-19 over the next three months. If Ohio’s leading causes of death are similar to what they were in 2017, this would make COVID-19 the sixth leading cause of death in the state, between stroke and Alzheimer’s disease.

A more optimistic scenario would be if Ohio’s social distancing could reduce its fatality rate to that of South Korea (1.7%), the country that has had the lowest fatality rates and has been seen as an international leader in COVID-19 response. In this case, Ohio would lose about 4,000 lives, dropping COVID-19 below Alzheimer’s to be the seventh leading cause of death.

Social distancing measures are designed to reduce hospital overuse and thus depress the fatality rate. We can use alternate fatality rates along with the OSU data to estimate how many people would die without social distancing. If the fatality rate did not change, a best-case scenario, 11,000 Ohioans would die, making COVID-19 the third-largest cause of death after heart disease and cancer. If fatality rates hit Italian levels, a worst-case scenario, 53,000 Ohioans would die of COVID-19, almost twice as many as died of cancer in 2017, making it by far the largest killer of Ohioans.

Data from Ohio Department of Health and Johns Hopkins University Center for Systems Science and Engineering

This means that in a conservative scenario where social distancing does nothing to suppress the fatality rate, about five thousand lives would be saved over the next three months just by reducing the infection rate, about the same as died of Alzheimer’s disease in Ohio throughout all of 2017. If hospital capacity constraints would exacerbate the fatality rate even moderately, bringing Ohio’s fatality rate to the global fatality rate of 5%, social distancing could save almost 17,000 lives over the next three months and if social distancing would prevent Italian-level fatality rates, social distancing could save nearly 50,000 lives. In short, Ohio State’s data suggests social distancing will save a lot of lives.

State social distancing measures don't correspond to local outbreaks

Last weekend, the Cleveland Plain Dealer released a 50-state survey of state responses to the COVID-19 pandemic. State policy is rapidly changing and by the time this blog post is published many of these state policies will have changed, but in the meantime this is an interesting snapshot of the US’s patchwork quilt of social distancing measures enforced at the state level.

From a qualitative standpoint, it’s easy to make conclusions from this map. Liberal California and New York anchor the hotspots of state response to the pandemic. It is telling that New York, California, and Illinois, home to the country’s three largest metropolitan areas (New York, Los Angeles, and Chicago) and controlled by Democrats, also have adopted the highest level of restriction at this point. Also notable is the fact that Texas, home to the next two largest metropolitan areas (Dallas and Houston) and controlled by Republicans, has less restrictions.

Something that interested me, though, was whether these restrictions were related to the incidence of disease in a given state. Theoretically, a function of federalism is to allow different jurisdictions to react to local conditions. Therefore, we should expect to see states that have larger outbreaks adopt stricter measures and states with smaller outbreaks to adopt laxer measures.

Using data from the Johns Hopkins Center for Systems Science and Engineering, we can compare the cases identified in a state to the level of restrictions imposed by the state. In the chart below, higher restriction levels correspond to more restrictions as reported by the Cleveland Plain Dealer.

Data from Johns Hopkins Center for Systems Science and Engineering and Cleveland Plain Dealer. New York excluded as a high-case outlier.

Overall, I find that there is a very weak relationship between the number of cases in the state on the day the Cleveland Plain Dealer article was published and the restrictions they have in place. The number of cases in a given state only explain 7.5% of the variation between states. Adjusting for per-capita case rates only improve this number slightly and using older data to account for a lag only weakens the relationship. Note that Washington state, the original epicenter of the coronavirus outbreak in the U.S., has relatively weak restrictions in place despite a large number of cases.

Another approach I was interested in taking was to compare death rates to restrictions. If policymakers weren’t responding to cases of coronavirus, maybe they were responding to loss of life associated with the disease.

Data from Johns Hopkins Center for Systems Science and Engineering and Cleveland Plain Dealer. New York and Washington excluded as high-case outliers.

The relationship here is nonexistent, with only 0.3% of the variation in restrictions explained by death cases in the states. Like the relationship between restrictions and cases, the relationship gets slightly stronger if deaths are measured on a per capita basis and slightly weaker if lagged, but neither of these changes are enough to significantly strengthen the relationship. With this chart we can even see the variation among higher-death states, with California adopting strong restrictions, Hawaii and New Mexico adopting laxer restrictions, and Maine and Georgia acting even more lax.

Overall, what the relationship between outbreak data and state restriction data says is that state decisions are not being driven by conditions on the ground, but by other factors. While often federalism allows for state-by-state specialization and adaptation to local conditions, a quickly-moving global threat like COVID-19 can make patchwork policy less effective and even creates the potential to undermine efforts from state to state.

Moore Talks Economic Fallout of Coronavirus on Prognosis Ohio

Scioto Analysis Principal Rob Moore appeared on Ohio University Health Policy Professor Dan Skinner’s WCBE podcast Prognosis Ohio this week to talk about the economic fallout of coronavirus in Ohio.

In the episode, Skinner and Moore talk about the immediate economic fallout associated with the virus and social distancing measures, policy options to address the fallout at the state level, and how COVID-19 will impact public problems ranging from the upcoming redistricting cycle to individual well-being.

“More and more people are going to be losing their jobs, but also shift[s] from unemployed to underemployed is something we need to worry about,” said Moore.

One of the themes of the interview was that state governments have the power to close sections of the economy to slow the spread of the virus but don’t have the power to provide economic relief to those sectors to offset the economic impact of these closures.

“Right now the state has the…police power to…close businesses…but the state doesn’t have a lot of economic power because we have a balanced budget requirement and we can’t just inject a bunch of money into the economy without help from the federal government,” said Moore.

Prognosis Ohio is an Ohio health policy and politics report hosted by Dan Skinner addressing all facets of health care, health policy, and health politics in Ohio.

The coronavirus response among Ohio’s neighbors

Ohio Gov. Mike DeWine’s leadership during the coronavirus pandemic has garnered national attention, particularly in contrast to President Donald Trump’s mixed messages and slow response as the pandemic has unfurled nationally. 

DeWine has taken swift action to close schools, ban large gatherings, close businesses, and even this week to go as far as to defy a court order to keep voting locations open for this week’s scheduled election.

Ohio isn’t alone in enacting serious measures to slow the spread and combat the effects of coronavirus. Ohio’s neighboring states have been at work on similar measures, enacting a host of policies in this time of national crisis.

Closing Schools

All of Ohio’s neighboring states have closed K-12 schools, mostly for about two weeks each. Major universities in Ohio and all of its neighboring states have suspended in-person classes in March, opting for to be determined virtual alternatives in the short term.

Banning Large Gatherings

Michigan has banned gatherings of over 50 people, the most restrictive large gathering ban in the region. On Monday, Ohio matched that number and Indiana has banned gatherings of over 250. Pennsylvania’s governor has discouraged large gatherings of 250 or more without going as far as a ban.

Kentucky’s governor has not banned large gatherings but has indicated he may soon if citizens do not avoid them on their own. West Virginia’s governor has been least aggressive on this issue, discouraging large gatherings in public remarks but taking little steps at this point to enforce a ban.

Closing Businesses

When DeWine ordered the closing of dine-in and bar services throughout the state on Sunday, Ohio led the region in closing of businesses. On Monday, Kentucky, Indiana and Michigan followed in Ohio’s footsteps, and West Virginia followed on Tuesday. 

Pennsylvania has banned business through another means, by blanket banning all “non-essential business” that doesn’t cover key categories and Ohio banned a number of recreational centers on Monday as well. As the week has gone on, states have closed more and more categories of businesses.

Providing Relief

Michigan Gov. Gretchen Whitmer has expanded eligibility for unemployment benefits as a way to support people hit by the economic consequences of the epidemic.

Price Controls

Michigan’s governor also enacted price controls in order to keep prices at non-emergency levels. While this may be popular with the public, it is likely to have the unintended consequence of further exacerbating the problem of shortages of supplies in demand during this time.

Postponing Elections

In what was a near stumble for DeWine, the governor ordered a postponement of the scheduled March 17 election then was overruled by a Common Pleas Judge. DeWine then defied the judge’s order, ordering polls to close anyway. 

Michigan went ahead with its election last week and Pennsylvania, Indiana, West Virginia, and Kentucky can put off its decisions until late April to mid May when their primaries are scheduled, though may see Ohio’s battle between the branches as reason to think ahead as the epidemic is projected to be at its height in the region during those scheduled elections.

Currently, this is a moment of unprecedented exercise of modern power for Governors in the Midwest and across the country. Governors are balancing the traditional dual goals of security and liberty, a balancing act often reserved for textbooks. 

The lives of the elderly and immunocompromised, the livelihood of service workers, the right to assemble, and the functioning of our elections are competing interests balanced by these crucial policymakers in this moment. I don’t envy the decisions they have to make.

This commentary first appeared in the Ohio Capital Journal.

The Economics of Social Distancing

By now I’m sure you know that the phrase of the week is “social distancing”—the act of maintaining distance from others in order to slow spread of disease. Social distancing can mean anything from cancelling of public events to workplace interventions to self-quarantine measures, all with the goal of reducing contact between people to reduce the number of new infections.

Social distancing measures have benefits. The benefit getting the most attention recently is the reduction of strain on the health care system. An epidemic can put strain on capacity of hospitals and clinics, making it harder for the system to prioritize harsher cases and potentially increasing the fatality rate of a disease. The goal of social distancing on this front is to “flatten the curve” of disease outbreak by slowing the spread of disease and spreading new cases out over a longer period of time so the health care system can better manage new cases.

Social distancing can also strategically protect more vulnerable populations and can potentially buy more time for development of treatments and prevention methods.

At the same time, social distancing has costs. Cancelled events means lost experience for attendees and revenues for hosts. Closed workplaces can mean less work for employees and less value for employers. Closed schools and conferences mean reduction in human capital development and exchange of ideas.

In a way, social distancing is different from a lot of interventions analysts study because the benefits are easier to measure than the costs: less people die when social distancing is implemented. That being said, every good analyst needs to ask the question of how much life is preserved through measures as opposed to how much life experience is destroyed through social distancing. After all, social interaction is a cornerstone of much of the theoretical and empirical evidence we have around well-being.

One way to estimate the tradeoffs individuals face when deciding whether to engage in social distancing is to see how individuals mitigate risks to life in other areas. In formal cost-benefit analysis, this is referred to as the “value of a statistical life”, or how willing people are to trade off fatality risks for monetary compensation. The current best practice for determining what people are willing to trade for fatality risk is by comparing compensation of more- and less-risky jobs and how willing people are to take on higher wages for accompanying higher fatality risk in the workplace. Using this technique, the current estimate of how much people value their lives in the workplace is $11 million.

Using this number, we can conduct some conservative individual-level cost-benefit analysis to estimate how people trade off coronavirus infection risk with the costs of social distancing techniques. For instance, if the median household income in Ohio is roughly $55,000, this means two weeks off work unpaid costs the average family about $2,100. Under the most conservative of scenarios using the low fatality rate in South Korea of 0.8%, that means an averted case of coronavirus would be worth about $92,000 to the average household using the standard value of a statistical life. This includes only fatality risk and not other medical costs that are more common with coronavirus, so this should be considered a low-end estimate of the cost to a household associated with coronavirus infection. With fatality rates ranging from 0.8% in South Korea to 6.6% in Italy, the fatality risk reduction value of avoiding a coronavirus infection at the household level could be as high as over $700,000.

Fatality rates as of 6:00am Thursday morning.

Under the conservative relatively low-risk 0.8% fatality rate scenario, if a family thinks taking two weeks off of work unpaid would allow a family member to avoid a 2.3% chance of contracting coronavirus, it makes economic sense for the household to do so on avoidance of fatality risk alone. With as much as one percent of the Ohio population assumed to be infected and coronavirus’s high infection rate, this does not seem to be a ridiculous assumption to make. In the opposite extreme case of an Italian-level 6.6% fatality rate, even avoiding a 0.3% chance of infection is worth the cost of two weeks’ wages.

It also should be noted that a two-week unpaid quarantine is an extreme measure. There may be lower-cost interventions for families such as telecommuting, avoiding mass gathering, and simple sanitary activities that could yield huge savings for households in reduced fatality and medical risks.

That being said, this analysis applies to the average household. Lower-income households might have less ability to mitigate risks and less flexibility in the workplace. Nonetheless, actors like state and local departments of health and broader state and local government want to encourage social distancing in these populations as well. This is where interventions like sick leave funds and even cash transfers could encourage workers to stay home and mitigate the spread of this disease.

Ultimately, social distancing will pay off for households, but public sector actors have tools to create stronger encouragement by reducing the cost of social distancing. Paying attention to both sides of the ledger for households will make interventions to promote social distancing more effective than they would be otherwise.

What Ohio can do to fight coronavirus

Last week, Nancy Messonnier, Director of the Centers for Disease Control and Prevention’s National Center for Immunization and Respiratory Diseases, released a statement on coronavirus’s likely spread to the United States, saying that “It’s not a question of ‘if,’ but rather a question of ‘when’ and how many people in this country will have severe illness.”

Coronavirus is coming to Ohio. The question is what we will do about it as a state. 

While the federal government has done a commendable job of chipping in to fund programs to reduce opioid overdoses as a part of what many are calling the worst drug epidemic in U.S. history, many public health officials have had trouble figuring out how to effectively spend money to reduce deaths.

For infectious disease, though, we have a playbook. Below are four tools policymakers have for reducing the impacts of infectious diseases, roughly in order of cost-effectiveness.

Vaccination

We’ve all heard it: vaccination is the best way to protect yourself and others from infectious disease. The problem we currently have with the coronavirus is that a vaccine will not be created at least for a few months and will not be widely available for as many as a few years. 

When this vaccine is made available, vaccination campaigns and interventions to make them available and cheap will be a cornerstone of the response, but vaccines will be little help to battle the disease in the short term.

Screenings

Screening for illness is an important practice for all kinds of disease, ranging from substance abuse to genetic disease to infectious disease. Screenings can take place during routine or other examinations or can be administered as a standalone service as is commonplace with sexually transmitted infections. 

Ohio Department of Health programs that support targeted screenings, especially in elderly population centers since coronavirus is especially deadly for people older than age 65, could help identify cases early and provide targeted treatment to help the person infected and appropriate social distancing to reduce spread of the disease.

Social distancing

Social distancing interventions such as isolation of suspected cases, school closures, travel restrictions, and cancellation of public events are a quite extreme and costly way to reduce spread of disease. 

While voluntary quarantines can be effective in some cases, it is unlikely a highly communicable disease such as coronavirus that spreads faster than influenza can be stemmed by targeted quarantine. 

That being said, Department of Health officials promoting limited social distancing methods in locations like long-term care facilities could be an effective way to protect the most vulnerable populations from infection.

Treatment

Currently, the CDC recommends no specific antiviral treatment for coronavirus. Doctors can do their best to relieve symptoms and in the most severe cases support vital organ functions. Besides promoting seeking treatment, the state has little it can do on this front compared to a disease like opioid use disorder where interventions like medication-assisted treatment have been shown to be much more effective than alternatives.

All in all, it seems that public information campaigns and building infrastructure for screenings are the top tools the state currently has to fight coronavirus. 

Future medical science progress may lead to effective vaccination and treatment interventions, but social distancing interventions need to be taken lightly, since the personal liberty and economic consequences of such interventions can be severe. 

Like any new disease, the role of the state is to provide support without overshooting the mark and doing harm through its interventions.

This commentary first appeared in the Ohio Capital Journal.

Saving Lake Erie from farm fertilizer runoff: Ohio’s options

Last week, the Ohio Environmental Protection Agency announced via its draft 2020 water quality report that it will be developing a limit on the amount of phosphorus that can be dumped into the Lake Erie watershed.

This was a big announcement for Lake Erie. Four years ago, Ohio signed a pact with Ontario and Michigan to reduce phosphorus runoff into Lake Erie feeding the lake’s toxic algae blooms that are decimating both its ecosystem and its tourism industry. To this point, though, the state has leaned on cleanup dollars and tech incentives to reduce phosphorus runoff, leaving the state well short of the 40% phosphorus reduction goal in the 2016 agreement.

This element of the water quality report signals the state’s first willingness to tackle algae blooms directly. But what options does the state have to finally choke off the flow of fertilizer running into Ohio’s most notable natural resource?

Phosphorus Caps

The most straightforward way to reduce phosphorus runoff would be to enforce a 40% reduction in phosphorus runoff distributed between Ohio’s farms. This approach would mean apportioning limits to phosphorus-based fertilizer to all the farms in the state and enforcing these limits through fines if farms exceed their limit.

While this approach would certainly achieve the goal of reducing phosphorus runoff by 40%, it would also come with two challenges. First would be enforcement. Monitoring and levying penalties cost resources and those would have to be expended in order to give the caps teeth. This would likely be a more cost-effective strategy than current education and cleanup strategies, but could still be costly.

A bigger issue is the economic cost of phosphorus caps. Presumably, larger farms could absorb the costs associated with more expensive or less use of fertilizer more than smaller farms, so caps might need to be set lower for larger farms and higher for smaller farms. It will be hard for the state to equitably and efficiently set caps in light of these complications.

Tradable limits

Enter limit trading. One way to get the benefits of phosphorus reductions at a lower cost than state-mandated caps is to set caps but then allow farms to trade allowances for phosphorus runoff with one another. This will allow less fertilizer-intensive, smaller, and more innovative farms to sell their allowances to more fertilizer-intensive, larger, and less efficient farms, providing incentives for innovation and reductions in pollution while apportioning limits more efficiently. 

While some may balk at allowing a market in pollution, this is the strategy the state of California has taken to reducing carbon emissions and allows regulators to balance the benefits of runoff reduction with the benefits of farm innovation.

Usage Fees

A final strategy would be to attach a usage fee to fertilizer. This would theoretically work similar to tradable limits on phosphorus runoff because it would essentially price the use of fertilizer but would require the state to estimate the correct price needed to bring about sufficient reduction in phosphorus runoff. 

The benefit of a usage fee, however, is that it would greatly reduce monitoring and compliance costs since it would come in the form of a fee paid on each unit of phosphorus fertilizer sold. Fee administration would have a cost, but this cost would likely be much lower than monitoring and enforcing limits for dumping on farms across the state since it would be levied at the retail level. Fees could be spent on cleanup, environmental measures, or even remitted to farmers to reduce their costs incurred while still maintaining the incentive to reduce pollution.

Each approach has costs and benefits, though hard caps may only have political benefits with significant economic costs for farmers without the benefits that tradable limits or usage fees provide. 

It will be up to the EPA and other policymakers to decide which path they want to take to mitigate this significant environmental issue for northern Ohio.

This commentary first appeared in the Ohio Capital Journal.

Should states tax inheritances?

With Iowa and New Hampshire in the rearview mirror, many are predicting a collision course between leftist populist Bernie Sanders and centrist technocrat Michael Bloomberg. Despite their obvious differences, the two candidates share one thing in common: they both have endorsed an expansion of the federal estate tax, a tax on wealth passed from one generation to another. An estate tax is a brand of inheritance tax, designed to reduce inequality by reducing the amount of wealth that can be passed on from one generation to the next and thus limiting intergenerational perpetuation of inequality.

But states that are interested in reducing intergenerational inequality don’t have to wait for the federal government to levy an estate tax. Currently, seventeen states have either an estate tax (assessed on the estate of wealthy people) or a direct inheritance tax (assessed as income for a beneficiary of an inheritance).

Ohio does not currently have an estate tax, since its was repealed in 2013. Ohio’s estate tax was previously a significant source of revenue, raising between $25 and $170 million per year from 1975 to 2014 according to Ohio Legislative Service Commission historical numbers. When comparing the estate tax to Ohio’s GDP, it was fairly stable early on, raising between 0.025% and 0.035% of GDP from the mid 70s to the mid 80s save a spike in revenue in 1983. After dipping to 0.02% of GDP in 1985, the estate tax increased steadily until it hit a localized peak in 2001 at a little over 0.04% of GDP. Estate tax reform at this point cut the relative size of the estate tax by three quarters by 2006, then subsequent reform all but eliminated it by 2015.

Data from the Ohio Legislative Service Commission and the Bureau of Economic Analysis. GDP for 2019 imputed using historical GDP growth trends.

Ohio’s neighbors take a mixed approach to taxation of inheritance. Indiana, Michigan, and West Virginia do not have inheritance taxes, having effectively repealed their own estate taxes in 2013 in Indiana and 2005 in Michigan and West Virginia. Kentucky, on the other hand, has a fairly substantial inheritance tax, which applies to extended family and beyond but covers a large proportion of inheritance transfers. This results in a tax that raises about $50 million per year, which comes out to about 0.025% of GDP, about the rate of Ohio’s estate tax in 1990. Pennsylvania’s inheritance tax is even broader, covering all transfers besides transfers to spouses and parents and raising about a billion dollars per year. With these elements, the estate tax amounted to about 0.128% of state GDP in Pennsylvania in 2018, making it about fives times as large a program as Kentucky’s on a relative scale and twice as large as Ohio’s at its 1983 peak.

If Ohio instituted an inheritance tax at Kentucky’s rate, it could raise about $180 million in revenue in 2020 if the state grows at historical rates. If its inheritance tax were closer to the size of Pennsylvania’s, it could raise revenue of about $960 million. For reference, with $180 million Ohio could fund all of its state Supreme Court and Judiciary services for the year and with $960 million it could fund the entire operations of the Ohio Department of Job and Family Services, in charge of all state job, unemployment, food assistance, and child support services. An inheritance tax for the state of Ohio could potentially reduce inequality and raise revenue for state services at the same time.

The fiscal cost of Ohio’s death penalty

In the spring of 2015, I was living in Omaha, Nebraska, and my friends and I, being the political junkies we are, were all watching as the Nebraska legislature voted one by one to override the governor’s veto to end the use of the death penalty in the state.

It wasn’t the problem of potential misplaced justice that ultimately led to that repeal. It wasn’t the well-documented racial disparities in death penalty sentencing. It was the problem of costs.

“If any other program was as inefficient as this, we would eliminate it,” said Republican state Sen. Colby Coash, a lead sponsor of the Nebraska bill.

Earlier this week, Ohio House Speaker Larry Householder channeled Coash, saying he looked at the issue “from a pure fiscal standpoint,” arguing the law is leading to higher costs without better outcomes.

The weight of the evidence suggests that death penalty cases are more expensive than life without parole cases: a 2016 fiscal analysis reviewed fourteen state and federal studies on the topic and all found death penalty cases to be more expensive than life without parole cases, usually to the tune of $1.2 million more spent on death penalty cases in 2015 dollars. 

The reason for this disparity in cost is that death penalty cases are usually much longer and require more defense attorneys and cases to make final determinations, much of which is due to US.. Supreme Court rulings on the practice.

Unfortunately, we don’t have good data on costs associated with the death penalty in Ohio. A study comparing costs of death penalty cases and life without parole cases in the state of Ohio hasn’t been conducted in over a decade.

Despite this lack of state-specific data, Ohio’s Legislative Service Commission, the research arm of the state legislature, has weighed in on this topic. 

In a 2018 fiscal note on a bill that would have prohibited death penalty sentences for people with “serious” mental illness, the Commission found that studies of the death penalty in other state suggested capital cases could cost $1-3 million more than life imprisonment cases and that capital cases cost 2.5 to 5 times as much as non-capital cases.

The Indiana Legislative Services Agency also conducted an analysis of the death penalty in 2010. In this study, the Agency found that the average death penalty case in Indiana from 2000 to 2007 cost about $170,000 more than the average life without parole case, which comes out conservatively to about $210,000 in 2020 dollars.

The state of Ohio currently has a total of 138 people on death row. This means that if these cases were tried as life without parole, the state could have saved $29 million under the more conservative Indiana Legislative Agency numbers to over $400 million under the higher-end Ohio Legislative Service Commission estimates.

Most people come to their opinion about the death penalty for moral, ethical, or religious reasons. But a low-end estimate of the cost of this seldom-used program could fund state fraud prevention efforts for a year and a high-end estimate could fund all the school construction in the state for a year. Whatever your moral commitments, those are numbers worth paying attention to.

This commentary first appeared in the Ohio Capital Journal.