What are the states saying about Tylenol and autism?

With last week’s White House announcement about the link between acetaminophen (sold over the counter as Tylenol) and autism, state departments of health are going to have to craft state-level health guidance around consumption of the drug for pregnant mothers.

The Food and Drug Administration still maintains they have not found “clear evidence” that appropriate use of acetaminophen during pregnancy causes adverse pregnancy, birth, neurobehavioral, or developmental outcomes. The agency recommends consultation with a medical professional before taking it, basically devolving the decision down to the personal level. After administration officials held their press conference on the connection between autism and the drug, the Food and Drug Administration released a statement characterizing the link as “an ongoing area of scientific debate,” recommending doctors limit the use of acetaminophen during low-grade fevers and noting that aspirin and ibuprofen have well-documented adverse effects on fetal development.

States have already begun to take steps to craft their positions on acetaminophen use during pregnancy.

On September 23rd, the California Department of Developmental Services released a statement citing the Society for Developmental and Behavioral Pediatrics saying there is no strong evidence showing a causal relationship between the appropriate use of acetaminophen during pregnancy and harmful effects on fetal development.

In Florida, State Surgeon General Joseph Ladapo was previously most famous for opposing the COVID-19 vaccine and comparing vaccine mandates to “slavery.” Last week, he announced he would likely be adopting recommendations on the use of acetaminophen by pregnant women following the White House, saying they are “at a place that is more honest."

In Pennsylvania, one legislator has taken the announcement as a place for opening a dialogue. State Representative Abigail Salisbury, who chairs the Pennsylvania Autism Caucus and says she is on the autism spectrum, has asked house leaders to hold hearings with medical specialists and scientists to lay bare the current state of the research on autism.

The Illinois Department of Health wrote in a Facebook post last week that “there is no link between acetaminophen use during pregnancy and autism.” They note that untreated fevers can lead to pregnancy complications and that acetaminophen is a “safe fever reducer for use during pregnancy.”

In a Facebook post last week, the Michigan Department of Health and Human Services cited the American College of Obstetricians and Gynecologists’s position, saying they “support the use of acetaminophen in pregnancy when used in moderation.” The Department says acetaminophen is one of the few options available to pregnant patients to treat pain and fever, saying they both can be harmful to a woman and a “baby” during pregnancy when left untreated.

The New Jersey Department of Health and New Jersey Maternal and Infant Health Innovation Authority released a statement endorsing use of acetaminophen for pregnant women along with infant vaccination. They say they align their recommendations with professional organizations like the American Academy of Pediatrics, the American College of Obstetricians and Gynecologists, and the Society for Maternal-Fetal Medicine. Their official position is that “Pregnant patients should not avoid indicated treatment for fever or pain, including acetaminophen.” They justify this by saying that current evidence has not demonstrated a “causal link” between prenatal acetaminophen use and autism, ADHD, or intellectual disability. They also note that untreated fever and pain can cause health risks for mothers and infants and that decisions to treat should be made in consultation with a doctor.

The Washington State Department of Health communicated in a Facebook post that “years of research have shown that acetaminophen is a safe and reliable treatment for fever and mild pain, including when used during pregnancy.” In the same post, they affirmed the value of vaccines for protecting child and maternal health.

Robbie Goldstein, Commissioner of Public Health for the Massachusetts Department of Health, released one of the stronger statements on the state of the evidence of the use of acetaminophen during pregnancy. He called acetaminophen “one of the safest and most commonly used medicines to relieve pain and reduce fever in pregnancy” and went as far as to say that leaving fever or significant pain untreated is “far more dangerous” to a developing fetus than acetaminophen used as directed. He said the link between acetaminophen use and autism is “simply not supported by high-quality evidence.” He even went as far to say that public health statements should not be driven by “speculation or opinions from those without the training and knowledge to accurately assess the full scope of research and the associated clinical nuances,” implying opinions to the contrary were “harmful misinformation or disinformation.”

While I did not see any statements released by and state agencies in Wisconsin, I did see a statement made by the Facebook post by Public Health Madison & Dane County sharing the posting of the American College of Obstetricians and Gynecologists stating that two decades of research have found no causal link between acetaminophen use and pregnancy and that acetaminophen is a safe option for managing pain and fever during pregnancy–two conditions that can pose serious risks to patients and fetuses if untreated.

Similarly, I did not find any official statement by an agency of the state of Colorado, but Jefferson County, Colorado in suburban Denver posted a Facebook post sharing the American College of Obstetricians & Gynecologists’s statement that acetaminophen is safe for use during pregnancy, when taken as needed, in moderation, and in consultation with a specialist. They also shared infographics explaining that untreated fever and pain can harm mothers and fetuses, that there is no causal link between acetaminophen use and autism, and that acetaminophen use is one of the safest and most effective options for managing pain and fever in pregnancy.

In my quick review, I also did not find any prominent statements made by government officials in Arizona, Georgia, Indiana, Maryland, Missouri, North Carolina, Ohio, Tennessee, Texas, or Virginia.

Among these states, six had state agencies issuing strong statements in support of acetaminophen use for pregnant women when directed by a doctor, while only one state followed the White House’s lead in discouraging its use. Among the top 21 states in population, Florida was the only one I could find where a state official was following the White House’s lead to discourage acetaminophen use among pregnant women.

At least for now, it does not seem that the states are following the federal lead when it comes to radical shifts in public health guidance.

Ohio economists split on the impact of SB1

In a survey released this morning by Scioto Analysis, economists were split about the impact of Senate Bill 1, which adds regulations to Ohio’s public colleges and universities. Some of the most notable changes are the elimination of DEI trainings, a new requirement for students to study American Civics, and the elimination of undergraduate degrees with very few students.

Five economists agreed that these changes would reduce long-term enrollment in Ohio’s colleges and universities while seven disagreed, and six were uncertain. As Charles Kroncke from Mount Saint Joseph noted: “Many choose public universities because of cost and major, not political ideology.” Conversely, Bill LaFayette said this was “one of many initiatives of the General Assembly telegraphing that Ohio is an unwelcoming state.”

Similarly, nine economists agreed that these changes would lead to a less educated state work force in the long-run, while five disagreed and four were uncertain. Will Georgic from Ohio Wesleyan agreed, writing “If enrollment in state public universities falls in the long run then those missing students will either attend in-state private institutions or out-of-state institutions. Graduates of both types of schools would be less likely to permanently reside in Ohio than graduates of Ohio's public universities, so lower long-run enrollment directly leads to a less educated state workforce.” Conversely, Kevan Egan from the University of Toledo wrote: “Everyone still needs 120 credit hours to graduate so the same quantity of "education". Any topic can be discussed from the perspective of science with hypotheses IF this is done THEN this happens. This is science. No one is saying what we SHOULD do. Our role as educators is to inform students how the world IS. They can then be more informed about how they think the world SHOULD be such as changes to policy.” 

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

USDA stops collecting data on food insecurity

Last Saturday, the Department of Agriculture announced that they would be cancelling the Household Food Security Report, which until now has provided researchers with high-quality data about food insecurity across the country. This is a significant loss for policy analysts, policymakers, and the public, and it is another example of the current administration electing to allow public data to fall by the wayside. This press release announcing this decision is clear that this was a political decision rather than a policy decision, claiming that this survey had only been conducted as a political tool.

Plenty has been said by advocates and analysts who work on food insecurity questions about how this data is important to their work. At Scioto Analysis, we don’t have the same level of specialist subject matter knowledge on food insecurity as people who work every day on this topic, so I’d suggest seeking out their thoughts about the direct significance of this change.

Instead, I wanted to talk today about why I think this is a dangerous decision in general, and how we can be more thoughtful about how we talk about policy changes that impact benefit enrollment. 

As many others have pointed out, the loss of this survey has come after the Trump administration got work requirements for SNAP benefits passed as part of H.R. 1, the “Big Beautiful Bill” act. We’ve talked before about the impacts of work requirements on Medicaid, and it is not hard to see how work requirements for SNAP would similarly lead to fewer people receiving benefits. It follows that if fewer people receive SNAP benefits, then food insecurity rates might rise. However, we won't know by how much without this survey.

In practice, implementing work requirements has the same impact on enrollment as cutting benefits. Like how tariffs are essentially sales taxes, in their simplest forms we can understand what these policies are and what their goals are, and most importantly what the tradeoffs are in implementing these policies. Looking at these work requirements through this lens, we can ask the straightforward economic question “do the benefits of cutting SNAP benefits outweigh the costs?”

We can pretty easily understand what the benefits of cutting this program are: it reduces government spending, which we know creates drag on the economy. However, we now have lost information about what the costs of these cuts are going to end up being. 

Advocates who work every day in this space might be able to collect their own data, or we might come up with estimation methods that are good enough to get an idea of what the costs of these cuts are, but it is undeniable that the quality of our information has just gone down significantly without our top federal source of information about food insecurity. 

Not only do we lose our ability to fully understand the impacts of a timely federal policy change, analysts will no longer be able to study the impacts of other policy changes across the country. 

Earlier this week, I was speaking to a group of students in a local MBA program about the future of work. Our conversation was focused almost exclusively on how access to data has been increasing over the years and how using all of this information in an intelligent way was going to be critical to their success going forward. 

One student asked me near the end about how we answer questions in situations where we don’t have good data (in particular, she was interested in the lack of self-reported wellbeing data in the U.S.). I told her that this is one of the biggest roadblocks that analysts face.

We can collect new primary data, though this is often resource-intensive. We can also use proxy variables, which are related, measurable variables that can serve as an indirect stand-in for the variable of interest. Another option is to use imputation techniques to estimate and fill in missing values, or to shift to qualitative analysis like interviews or case studies, though these methods don’t allow us to fully understand the picture. Ultimately though, quantitative analysis is dependent on data.

When we have less information we end up making worse decisions on average. Removing a key data source because it might make one policy look bad is shortsighted. Policy analysis is not about deciding whether or not policy is good or bad, it is about understanding outcomes and informing future decisions. This decision makes everyone’s jobs more difficult.

New poverty data: which groups look worse under the official poverty measure?

Happy belated Poverty in the United States report release day to all who celebrate! Here at Scioto Analysis, understanding the current state of poverty is central to our mission, so we are always paying attention when the Census releases the most up to date data on one of America’s thorniest challenges.

Each year, this report lays out all the current information we have about both the Official Poverty Measure and the Supplemental Poverty Measure. This gives us the ability to look at both measures side-by-side and see how their differences impact the way we see the data. 

As a really quick reminder, the Official Poverty Measure just looks at household income and compares it to a fixed line depending on the number of people in the household. This means that a 4-person household in Jackson Mississippi has the same poverty line as a 4-person household in San Francisco. 

On the other hand, the Supplemental Poverty Measure makes adjustments for differences in cost of living across the country, and it also takes into consideration any non-wage income that a household might benefit from, such as SNAP benefits. 

In general, the Supplemental Poverty Measure is higher than the Official Poverty Measure across the country. Overall, the Supplemental Poverty rate is 12.9% compared to 10.6%. When we look at sub-groups, we see that this trend is fairly consistent.

In the report’s Figure 7, all of the different poverty rates are laid out for each demographic group identified in the data. Some of these groups stand out as having significantly different Supplemental Poverty rates compared to their Official Poverty rates.

Cohabitating partners

The biggest difference by far between Supplemental and Official Poverty belongs to cohabitating partners. Cohabitating partners have a Supplemental Poverty rate that is nine percentage points lower than their official poverty rate. The main reason for this is that cohabitating partners count as being part of the same resource group in the Supplemental Poverty Measure, but not the Official Poverty Measure. 

When people live together, there are economies of scale in terms of the resources those people need. We see this reflected in the Official Poverty thresholds, where the income required for an individual is $15,650, while the income required for a family of two is $20,440. If two people required exactly twice as many resources, then their poverty line should be $31,300, which is much closer to the poverty line for a family of four.

Children

The only other group whose Supplemental Poverty rate is lower than their Official Poverty rate is people under 18 years old. The difference here is quite small, only 0.9 percentage points, but this is notable given that all other groups have a Supplemental Poverty rate is higher than the Official Poverty rate.

I suspect the main reason that children have a lower Supplemental Poverty rate is due in large part to the special benefits families with children are eligible to receive. Policies like Child Tax Credits or the Earned Income Tax Credit provide key of supplemental income to families that do not get counted by the Official Poverty Measure.

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This poverty data release has a ton of amazing information in it. There is so much for policymakers and analysts to pick up and comb through. This kind of high quality public data is critical for better understanding the world around us and helping us make better decisions that might lessen the burden of poverty for everyone.

Who is poor in America?

Last week, the United States Census Bureau released “Poverty in the United States: 2024,” its most recent annual report on poverty in America. In this report, analysts at the United States Census Bureau comb through their data from the previous year to provide insights on poverty in the United States.

One of the most valuable things the report gives us is a breakdown of who is in poverty in the United States using different demographic groups as baselines. When I am looking at this data, I gravitate toward using the Supplemental Poverty Measure rather than the Official Poverty Measure because it is based on a methodology for poverty that is more updated for 2025. 

So who is poor in America?

12.9% of All People

According to the Supplemental Poverty Measure, 12.9% of Americans are under the poverty threshold for their household, meaning more than one in eight Americans are in poverty. This number is identical to the percentage of people in poverty in the 2023 report, but is up from the low point of 2021, when the poverty rate in the United States dipped below 8% due to expansion of the federal child tax credit. The current poverty rate is the highest rate the United States has seen since 2017.

Women

A total of 13.6% of women in the United States are in poverty, compared to 12.3% of men. Women tend to have lower incomes and larger households than men, which means they tend to have less resources to provide for households with more needs. This leads to a small gender gap in poverty rates in the United States.

Retirement-Age People

Among people age 65 or older, 15% of people have incomes below their household poverty line, compared to only 12.2% of working-age people. This is even higher than the child poverty rate of 13.4%. Retirement-age people tend to have lower incomes than working-age people due to their more limited capacity to work. They also have higher medical expenses which drive up their household needs compared to working-age households. Retirement-age people were one of two categories of people in this poverty report where poverty rates increased from 2023: the retirement age poverty rate increased by 0.8% from 2023 to 2024.

Renters

The gap in poverty rates between renters and homeowners is one of the most drastic we see in this report: the average renter is nearly four times as likely to be in poverty (23.3% poverty rate) as the average homeowner with a mortgage (6.1% poverty rate). An interesting wrinkle to this statistic is that homeowners without mortgages had poverty rates nearly double the poverty rate for homeowners with a mortgage. This suggests that the causality probably flows the other direction: people who are in poverty choose to rent, not that renting is making people poor. Often people mistake homeownership as a cause of pulling people out of poverty. The data suggests that no, homeownership is not a ticket out of poverty–it is just something that people who are not in poverty tend to take part in.

Nonwhite People

Black (20.7% poverty rate), Hispanic (20.3% poverty rate), American Indian (19.8% poverty rate), multiracial (13.5% poverty rate), and Asian (12.1% poverty rate) Americans all have higher poverty rates than White Non-Hispanic Americans (8.7% poverty rate). Black Americans were the other category of people who actually saw their poverty rate increase in 2024, going up a full 2.2 percentage points from 2023 to 2024. Each of these categories of people are hurt by limited access to education, employment, and intergenerational wealth and other resources that help people avoid and escape poverty.

People without a High School Diploma

People without a high school education (30.3% poverty rate) are five times more likely to be in poverty than people with bachelor’s degrees or higher (6.1% poverty rate). Even getting a high school diploma cuts the poverty rate in half (16.4% poverty rate). There is a lot of debate about what education means for people: is it about building human capital, making connections, or signaling your underlying value to employers? Whatever it is, in the United States, one of the best ways to know the likelihood someone is in poverty is to know what their education level is.

People without Jobs

Someone who was unemployed in 2024 was more than seven times more likely to be in poverty as someone who worked full-time, year-round in the United States. Even part-time, year-round workers were more than three times as likely to be in poverty as full-time, year-round workers. Having a job makes it a lot easier to have income, which leads to more resources and lower poverty rates.

So what can we take away from these results? It is easy to look at a statistic like “people without a high school diploma are five times as likely to be in poverty as those with a college degree” or “renters are four times as likely to be in poverty as homeowners with a mortgage” and conclude that education and homeownership are cures for poverty. The reality is that federal mortgage deductions have been a costly windfall to high-income households that has done little to budge homeownership and expansion of education has only exacerbated education disparities.

The single policy that has had the largest impact on poverty in the United States any year since the Census Bureau began to calculate the Supplemental Poverty Measure is the 2021 expansion of the Child Tax Credit. The expansion of a suite of income supports like unemployment insurance and the tax transfers of the 2020 pandemic dropped poverty from 12% to 8.5%, then the expansion of the child tax credit dropped it further to below 8%. The impact of the child tax credit was seen even more strongly in 2022 when it disappeared and poverty shot back over 12% again.

This should not be surprising: the child tax credit puts cash in the pockets of households, directly attacking the problem of poverty. Poverty is most directly a function of two things: availability of income and household needs. While public policy can’t do much about household needs, it has a lot of ability to impact income, which is the low-hanging fruit of U.S. poverty policy.

Four ways to reduce crime that are better than Ohio National Guard deployment

When Gov. Mike DeWine decided to send Ohio National Guard members to Washington D.C. to participate in President Trump’s militarized crime crackdown, he took a national issue and made it a state issue. Why he decided to do so is perplexing.

Ohio’s violent crime rate has hovered between three and four times the violent crime rate of D.C. over the past four years. So the idea that resources should be sent from Ohio to Washington to quell violent urban crime is a strange one.

But even if DeWine were to deploy national guard troops in Ohio to quell violent crime, is that the way to do it?

Research out of Brown University finds military policing is not an effective tool for reducing crime rates.

At best, this sort of approach is a band-aid: long-term military occupation of cities is not a feasible strategy in a democratic country. At worst, it can be a distraction from solutions that actually could reduce crime rates.

So what actually could reduce crime rates in Ohio?

The evidence shows there are strategies that can be used to reduce violent crime.

One is a suite of strategies called “focused deterrence.”

Basically this approach amounts to identifying groups like gangs that are responsible for a large share of violence, calling them in and offering services if people leave the gangs, and delivering swift punishment if further violence takes place.

Meta-analysis of dozens of studies on these techniques show they are effective at reducing crime rates.

Another is “hot-spot policing,” a strategy that concentrates resources towards geographic areas where crime occurs most often.

Cost-benefit analysis by the Washington State Institute for Public Policy shows that deployment of one police officer in a hot spot leads to nearly half a million dollars in net social benefits realized in lower property crime rates.

This amounts to over $5 in social benefits for every $1 in costs.

A third strategy is more mundane but nonetheless effective: street lighting.

A randomized controlled trial that placed lighting in New York City housing developments found areas that received lighting saw reductions in index crimes, felony crimes, and to a lesser degree, assault, homicide, and weapons crimes when compared to places that did not receive them.

Similarly, restoration of vacant lots have been found to lead to reductions in overall crime, gun violence, burglaries, and nuisances.

Another promising program is targeted cognitive behavioral therapy.

Whether this is deployed with at-risk youth in conjunction with summer jobs programs or as a part of correctional programs, cognitive behavioral therapy has been shown to reduce propensity to commit crime among people who undergo it.

By giving people control over their own decision-making, they often opt not to take part in criminal activity.

These are just four approaches that are effective at reducing crime.

If the governor or federal lawmakers wish to make a dent on crime in major cities, deploying these strategies is the way to do it.

But I guess these would probably get fewer headlines than what they are doing now.

This commentary first appeared in the Ohio Capital Journal.

Conducting my First Cost-Benefit Analysis

As my internship with Scioto Analysis concludes, I have reflected on this opportunity and the insights I gained from analyzing the Moving to Opportunity program. 

I am someone who loves to learn. As a graduate of the spring 2025 class at the University of Washington, Scioto Analysis has given me the opportunity to continue to develop my skills in policy research in a professional setting. To apply my educational background under the guidance of policy analysts with years of experience was deeply rewarding and will undoubtedly serve me well as I grow as an emerging professional.

I want to give special thanks to Scioto Analysis Principal Rob Moore for guiding me through the summer internship. His expertise was invaluable to completing my Cost-Benefit Analysis. From understanding the basics of social valuations, to developing the impact list, and handling the technical aspects of creating economic models, his support during our weekly meetings helped my understanding of policy analysis tremendously. 

The Moving to Opportunity Cost-Benefit Analysis was such a fulfilling project to work on; current iterations of the program have proven beneficial for low-income families in the short term and have shown strong promise for improving long-term outcomes for younger children. Expanding this program to 1,000 families is an exciting prospect with serious potential for improving the lives of the next generation of Ohioans. Every dollar of value created through this program represents the potential for a material improvement in the life of a child.

Developing and refining the list of impacts included in this analysis was the most rigorous yet satisfying portion of this project. This process involved theorizing a range of potential impacts, working with Rob to determine which effects would be included, analyzed qualitatively or quantitatively, and how they would be calculated, and how they would influence our model. Through this internship I was able to hone my skills in research and problem solving and built a complex model with many interdependent components. I consulted over 20 different sources while analyzing these impacts, with the National Institute of Health and the United States Census Bureau standing out as particularly valuable resources.

Much of my analysis draws from insights included in The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment by economists Raj Chetty, Nathaniel Hendren, and Lawrence F. Katz. Their follow-up study on the 1994 experiment provides valuable information on how the program has affected outcomes for children who moved at a young age and theorizes how the change in neighborhood conditions may continue to benefit their life trajectory as they grow into adulthood. Their study served as a blueprint for similar economic mobility programs like Families Flourish, which currently serves nearly 100 single mother households in Ohio and consistently receives positive participant feedback.

I am proud of the work that I’ve completed with Scioto Analysis and am thankful for the kindness and guidance the team has provided me. I plan to continue to closely follow Moving to Opportunity-styled programs like Families Flourish and the growing body of research evaluating their effects on children and families.

How can Ohio protect children from measles and polio?

Parents are increasingly putting their children in danger in Ohio schools.

According to the Ohio Department of Health, about 1 in 7 Ohio five-year-olds entered Kindergarten this year unvaccinated. This is up from about 1 in 10 in 2019, before the COVID-19 pandemic.

One in ten is not a great baseline. According to the World Health Organization, that number needs to be closer to 1 in 20 for “herd immunity” to stop measles from spreading. This is certainly part of the reason Ohio has seen 35 measles cases this year.

The speed vaccination rates are falling in Ohio puts children at risk for even more diseases, though. If Ohio creeps closer to 1 in 5 children unvaccinated, children will approach the point where they are no longer herd immune to polio.

What can we do about this?

Certainly we are living in an age of misinformation where trust in institutions like the World Health Organization, Centers for Disease Control and Prevention, and even the Ohio Department of Health have declined.

This has led to parents making decisions that the best medical science tells us is putting their children at risk for lifelong conditions or even death.

Are there public policy solutions to this problem?

If policymakers are interested in improving vaccination rates and saving lives in the progress, they have options.

First, they can tighten nonmedical exemptions.

A parent who leaves a gun unattended or a toddler next to a swimming pool in Ohio can be found negligent for endangering their child.

A parent who refuses to put their child in a car seat or leaves their child in a hot car can be found negligent for endangering their child.

But if a parent refuses to vaccinate their child, exposing them to life-threatening illnesses, they are protected by current Ohio law.

Eliminating “reasons of conscience” that allow parents to opt out of vaccination requirements for whatever reason they see fit can help protect children and their peers. 

If policymakers are too squeamish to protect children in this way, they can instead help educate parents by requiring in-person vaccine education sessions, which has had some positive effect in helping parents make better decisions for their children in Michigan.

Second, the state can use its immunization information system to improve compliance with vaccination requirements.

The state has a database that tracks immunizations across the state. The state can use this system to send auto-reminders like text messages, phone calls, or letters to families who are not up to date.

The state can then publish schools that have low compliance rates by the Oct. 15 deadline so the public knows which schools are struggling to keep their children safe.

These are just two examples of what the state can do to increase immunization rates and protect children from lifechanging illnesses like measles and polio.

Ohio has made so much progress in eradicating deadly diseases and immunization is a huge piece of the puzzle for how this has come to be.

If policymakers can find ways to protect more children, they should do it.

This commentary first appeared in the Ohio Capital Journal.

Investing in kids pays off

Earlier this week, Scioto Analysis released a cost-benefit analysis that looked at the impacts the Moving To Opportunity program would have if expanded in Ohio. In this study, we found that the benefits of expanding this program would be about three times the cost, with most of the benefit accruing to program participants who would be expected to have higher future earnings. 

The way Moving to Opportunity works is that low-income families are given housing assistance that is conditional on them finding a place to live in a low-poverty neighborhood. In the original experiment conducted by economists from MIT and Harvard, program participants were also given counseling to help them with their transition. 

The findings from the original study and our own are pretty dramatic. Children who grow up in wealthier neighborhoods tend to have better outcomes, even if they do not themselves come from a wealthy family. 

In health policy research, this concept is referred to as the social determinants of health. In short, they are the environmental conditions that impact health outcomes. The idea is that two physically identical people may have different outcomes if they have different social characteristics (say one is more educated than the other). With Moving to Opportunity, we see how these environmental characteristics can impact a wide range of other outcomes as well.

Like all public policies, Moving to Opportunity is not a silver bullet. The design of the program is important in determining its success. As the original study notes, positive effects are limited to families with children under the age of 13. Adolescents who moved as part of the program ended up with slightly worse outcomes compared to the control group. The researchers speculate that this may be because these children were older, they received less exposure to the environment with better outcomes, and the negative disruption associated with moving ended up being a stronger effect. 

This is an important caveat because it highlights the role that environment plays in early development. This is why policies that target very young children such as a Child Tax Credit can have such a massive return on investment. 

I think the biggest takeaway I have from this study is that economic segregation is a costly part of our society. We know that poverty is bad and impacts everyone in our society, but this is a reminder that we amplify that problem when high-income households try to isolate themselves from low-income households.

This is a case of short-term vs. long-term thinking. A single family home might be less valuable if it is across the street from an affordable housing development, but in the long-run, having single-family homes next to those apartments might lead to there being less poverty and crime for everyone. 

Overall, the Moving to Opportunity program provides a compelling example of how addressing economic segregation can create significant social benefits. While not a perfect solution, its impact on young children is clear. Research keeps showing us time and time again that investments made to help families with young children get off to a strong start are worth it.

Scioto Analysis releases cost-benefit analysis of Moving to Opportunity programs

This morning, Scioto Analysis released a cost-benefit analysis on an economic mobility program to help low-income families move to neighborhoods with more economic opportunity. The program is modeled after Moving to Opportunity, a 1994 experiment by the Department of Housing and Urban Development, and Families Flourish, a non-profit organization based in Columbus, Ohio. Based on evaluations of these programs, analysts estimate that a program expanded to 1,000 families would create $320 million in value through reduced crime, increased lifelong earnings, reduced welfare spending, and other impacts. 

Studies have shown that neighborhoods with lower rates of poverty produce better outcomes in health, economic standing, and education for children who live in them. The original Moving to Opportunity program enrolled 4,600 low-income families and moved roughly half of them to lower-poverty neighborhoods through subsidized housing vouchers. Children who moved before the age of 13 experienced the greatest benefit from the program. Through our analysis, analysts estimate that a Moving to Opportunity-styled program for 1,000 families in Ohio would result in:

• $140 million in increased lifelong earnings

• $9.5 million in reduced crime

• $450,000 in reduced welfare spending

Per family, the program is expected to cost $40,000 per child in discounted present dollars. Analysts conducted a Monte Carlo analysis with 10,000 simulations of the program. From this, they estimate the program will generate $5 to $7 in benefits for every $1 in costs. Net social benefits are expected between $250,000 and $310,000 per child. Analysts expect this program to be largely beneficial for low-income Ohioans, providing long-term benefits in income, crime, and health.