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.

Minimum wages can improve public safety

Earlier this week, This Land Research released a study conducted by Scioto Analysis looking at the impact that raising the minimum wage in Oklahoma would have on crime rates. Crime and public policy  is one of my favorite applications of economic theory, and I think it is extremely important to understand the incentives behind crime if we want to address its root causes. 

In the study, we found that higher minimum wages would lead to reduced crime rates in Oklahoma. The main reason for this is that the effect of increased wages outweighed the effect of reduced employment in the majority of scenarios we simulated. 

When we look at what types of crimes would be prevented by a higher minimum wage, we find the largest impact would be for young adults committing larceny. Intuitively, this makes a lot of sense. Larceny is non-violent and very often financially motivated, so if people have better outcomes in the labor market they might prefer to work in the legal market rather than steal. 

However, when we look at the monetized value of the crime reductions, the vast majority of the social benefit came from a reduction in homicides.

A 2020 study found that there was a connection between higher state minimum wages and reductions in the number of firearm homicides. We used this insight to determine what a similar effect might mean for the number of homicides in Oklahoma, and we calculated it would lead to 55 fewer homicides on average.

Despite making up less than 1% of the total number of the avoided crimes, these 55 fewer homicides were responsible for almost 90% of the total social value of crime reductions due to the higher minimum wage. Conversely, the prevented larcenies accounted for nearly 70% of the total avoided crimes, but only 2% of the total social benefit. 

I think there are two major takeaways from this particular finding, one for policy analysts and one for policymakers.

For analysts, this demonstrates the importance of looking for costly connections between a policy and an outcome, even if the connection between the two is small in magnitude. This doesn’t mean it is appropriate to shoehorn in a mortality impact where it doesn’t belong, but if there is empirical evidence to suggest a connection between the policy you are studying and some very important outcome, it is often worth exploring. 

For policymakers, this shows how certain policies can have effects on things they are not designed to change. The purpose of this study was to highlight the connection between minimum wages and public safety, but most people who participate in the discussion about minimum wages are solely focused on the labor market impacts. Minimum wage policies are not implemented as crime reduction policies, it just so happens that they have a spillover effect.

We can learn a lot about policies when we focus on the social impacts. The total volume of homicides prevented is not close to the total number of other crimes, but because we know how much more severe a homicide is we see that preventing even a handful can lead to major benefits for everyone.

New Report Finds Raising Minimum Wage to $15 Would Deliver Major Public Safety Benefits in Oklahoma

A new report “Public Safety and the Minimum Wage” released today by This Land Research and Communications Collaborative highlights the connection between wages and public safety in Oklahoma. The analysis, conducted by Scioto Analysis, shows that raising the state’s minimum wage to $15 an hour by 2029 could reduce crime, incarceration, and corrections spending—while delivering hundreds of millions of dollars in social benefits to Oklahoma families and communities.

In this analysis, we estimate a $15 minimum wage in Oklahoma will lead to the following:

• Nearly 7,000 fewer crimes each year — including an estimated 55 fewer homicides annually and over 4,900 fewer incidents of larceny. 

• $840 million in avoided social costs each year, with the majority of savings driven by reductions in violent crime. 

• The public safety impact of a $15 minimum wage would be equivalent to hiring nearly 1,000 additional police officers—without the additional $58 million in costs to taxpayers. 

• Oklahoma’s incarcerated population could decline by 370 individuals annually, reducing corrections spending by an estimated $5.7 million each year. 

• Recidivism rates are projected to fall by six percentage points, helping more Oklahomans successfully reenter society and stay out of prison. 

“These findings make clear that wages are not only an economic issue, but a public safety issue,” Rob Moore, Principal for Scioto Analysis, said. “When wages rise, workers are less likely to be pushed toward crime and more likely to build human capital in the legal workforce. This new analysis shows raising the minimum wage isn’t just about higher wages, it’s about building better, safer communities, while saving taxpayers millions of dollars.” 

While Oklahoma has made great strides in reducing the number of people in prison, it still has one of the highest incarceration rates in the nation, with 1 in 178 residents behind bars. The report underscores that higher wages could help reduce that number even further and reduce the burden on law enforcement and Oklahoma’s corrections system.

What are “sticky prices?”

In a recent blog post, I talked about different types of market failures and how they can change the way we see markets operate in practice. In this post, I covered externalities, information asymmetries, public goods, and monopolies. 

Of course, this is not an exhaustive list of every possible type of market failure. These are just the ones that we most frequently run into with our work. 

I wanted to talk today about another aspect of markets that don’t quite qualify as market failures but do play a big role in real world markets deviating from our simple economic models: “stickiness.”

When we talk about stickiness in markets, we refer to the fact that in many cases, prices don’t respond right away to changing market conditions. The best example of this is in the labor market. Many employees work under contracts that specify what their wages will be for some fixed duration. 

It sounds crazy on its surface, but if every person was a totally rational economic actor and had perfect information, it might increase efficiency to allow people to negotiate their wages every single day. The reason this is crazy is because nobody is a perfectly reasonable economic actor, perfect information rarely exists, and there are significant transaction costs to renegotiation of contracts. Imagine the first hour of every work day being taken up by wage negotiations. Not only would it waste time, it would be mentally exhausting.
Instead, both employers and employees agree that signing contracts and having some certainty about the future is a better system. The reasons I wouldn’t classify this as a market failure are 1) I suspect that nobody would be better off without these types of contracts and 2) it does not lead to an inefficient allocation of resources. 

At any single point in time, participants in the labor market can negotiate the price of labor and choose an efficient rate that takes into consideration some basic ideas about what both parties expect the economy to look like in the future. If the economy is generally stable, then a fair price today should largely be a fair price into the future. 

Another key point about sticky markets is that they do eventually respond to changes in broader economic conditions, just not right away. This can create issues in the short run that public policy might need to address. Take the recent high inflation as an example. 

There is mixed evidence about how well wages have kept up with inflation in recent years, but in general they have been able to keep pace overall. Still, we all remember how challenging it was for so many people in the early days of that high inflation. 

Many people struggled with paying for basic needs because their wages were still stuck behind. Eventually they may have caught up, but by that point, the damage had been done for a lot of people. 

While sticky wages can be a rational choice for businesses and employees, they do create problems that public policy can help address. A classic example is rising unemployment during an economic downturn. Because wages are sticky, companies are unable to reduce wages when they lose revenue. Instead, they have to lay off a portion of their employees. 

Unemployment insurance is a direct response to this problem. By requiring companies to contribute to a shared fund, the government can provide a safety net for workers who lose their jobs due to these rigidities. This helps to stabilize the economy and reduce the harm caused by sticky prices.

Another market that is affected by sticky prices is housing. For many people, rents and mortgages make up the majority of their housing costs and those almost always come with long-term fixed payment schedules. 

There are some variable housing costs like utilities that can fluctuate more regularly, but for most people participating in the housing market the price they pay is largely fixed. Again, this isn’t the same as a market failure because people participating in the market can account for future uncertainty and make efficient decisions in the short term. It does, however, constitute a departure from our classical economic models.

While we often focus on traditional market failures like externalities and monopolies, it's also important to understand other deviations from our simplified economic models. While sticky prices don’t cause the same type of inefficiency as a true market failure, it can still lead to short-term challenges that policymakers may need to address.