Is Massachusetts ready for a candy tax?

Last week, Massachusetts Governor Maura Healy released her budget proposal for the upcoming year and she has an unlikely commodity in the crosshairs with her new budget: candy.

Her new proposed budget includes a provision to remove the exemption for candy from the state sales tax, making it no longer a nontaxable item and subject to state sales tax.

While a tax on candy may seem like a frivolous matter, there is more at stake here than jobs for the state’s Oompa Loompas. CBS News reports removing the sales tax exemption for candy could raise $25 million for the state to spend on investments the governor wants to make in transportation and education.

The search for new sources of revenue is likely the origin of this policy change. Needling around the tax code and finding politically palatable ways to raise tens of millions of dollars of revenue is no easy task, so when a policymaker finds an opening, she often is willing to take it to raise revenues for programs she wants to fund.

That is why the governor says “this isn’t about a new tax.” This is “about” expanding the definition of what is funded under a tax that Massachusetts already has and a tax that is probably the broadest tax in the state: the state sales tax.

Despite the political motivation of the policy change, conventional wisdom among economists is that broader taxes are better for the economy. An exemption of something like candy from the state sales tax creates an incentive for people to purchase it relative to other goods that are subject to the state sales tax. If the state sales tax applies as widely as possible to many forms of purchases of goods and services, the incentives will be less distortionary and the economy will function most efficiently.

This is why many economists are wary of sales tax exemptions like exempting tampons from taxation–they narrow the tax base and create distortions in the economy.

But sales tax exemptions can have certain outcomes that policymakers may desire. One of them is offsetting the regressivity of sales taxes. Sales taxes fall more heavily on low-income households than on upper-income households since low-income households spend a larger percentage of their income on consumption. Carving essential goods like groceries, healthcare, and utilities out from sales taxes can help address this regressive aspect of a sales tax.

Candy falls under this category. A study by researchers at the University of Michigan and the University of Alabama-Birmingham found people living in lower-income neighborhoods and in areas without local food stores eat more snacks and sweets than those in higher-income areas. This means that subjecting these goods to taxation will likely mean the tax will fall more heavily on low-income households than on high-income households.

Those who are wary of specific exemptions to sales taxes argue that a better way to deal with the regressivity problems of a tax is to offset it with a rebate system. If you fund programs like an earned income tax credit with sales taxes, you can give cash to low-income people without giving an exemption to all families. This can be a more efficient way to handle the regressivity of a sales tax than exempting categories of goods from the tax altogether.

Another consideration with the taxation of candy is the public health impacts. Ten years ago, many local jurisdictions were making headlines for taxing soft drinks, citing their public health impacts. Making candy subject to sales taxes could be a way to reduce the public health impacts of candy.

Some researchers have found that dental guidelines around avoiding foods that stick to your teeth have little impact on consumers because consumers do not know which foods stick to their teeth and which do not. Candy consumption can also be a cause of weight gain, which can lead to a host of health conditions that can threaten lives. Candy and sugar consumption can also lead to cardiovascular disease and can even lead to nutrient deficiencies.

Correcting for these effects of candy consumptions could be seen as promoting economic efficiency if they lead to better health outcomes. If parents are feeding candy to children and that is leading to tooth decay, weight gain, cardiovascular disease, and nutrient deficiencies, then levying a tax on candy could help shift spending away from candies toward substitutes with less negative health impacts. Previous work on taxes on soda have shown these taxes lead to reductions in consumption.

Another way removing the exemption for sales taxes for candy could promote economic efficiency is by curbing economic internalities, or irrationalities people have that lead them to make choices they would not make in sound mind. If candy consumption is linked to compulsive behavior, then taxing it could help bring people’s actual consumption of candy closer to their clearheaded goal consumption levels.

Similarly, a tax could help correct information problems. If information tools like nutrition labels are not effective at helping people understand the health impacts of candy, then a tax could be a more effective way at reducing consumption to levels that someone would consume at with better information.

Another consideration for policymakers weighing a candy tax is the administrative feasibility of such a tax. The definition of “candy” is slippery and a line will have to be drawn at some place to define certain foods as “candies” and other foods as “not candies.” Where this line is drawn will impact revenue, the efficiency of the policy, the effectiveness of the policy, the equity ramifications of the policy, and the public health impacts of the policy.

From the perspective of an analyst, I am curious to see what the impacts of this policy will be. Will this increase in taxes lead to precipitous decreases in candy consumption? Will there be detectable public health impacts? Will revenues raised exceed expectations? All of these are questions economists should be prepared to answer if this policy change goes into effect. Because this is where the rubber meets the road in public policy analysis: determining how changes like this impact real people’s lives.

Original Research: Bicycling and Trails Contribute $1.4 Billion to Iowa’s Economy

On Saturday, the Iowa Bicycle Coalition and Scioto Analysis released a report highlighting the economic and health impacts of bicycling and trails across Iowa. Analysts estimate in the report that bicycling contributes $1.4 billion annually to the state’s gross product, supports over 21,000 jobs, and generates $690 million in wages.

The study, conducted with data from over 2,500 surveys and data from government and nonprofit organizations, investigated the economic and health impact of bicycling and trails in the state.

Iowa has over 2,000 miles of multi-use trails and approximately 900,000 state residents cycle each year. The report underscores that cycling and trail use is not just a leisure activity but also an economic driver for the state. Retail trade and food services emerge as the biggest beneficiaries, with recreational riding alone accounting for over half a billion dollars in retail trade revenue annually.

“Bicycling is not only a leisure activity. It’s also a contributor to a strong economy and promotes public health,” said Rob Moore, Principal for Scioto Analysis. “From creating jobs to promoting healthier lifestyles, the benefits of bicycling accrue to communities and businesses across the state.”

Analysts found evidence that cycling reduces obesity rates and leads to fewer cases of diabetes, high blood pressure, and deadly cancers, saving millions in healthcare costs and saving lives. It also reduces incidence of excess BMI and promotes mental health. Bicycle commuters promote a more eco-friendly commuting lifestyle, preventing as much as 1,500 tons of carbon dioxide from being released in a given year.

The report demonstrates the value of sustained investments in cycling infrastructure to enhance safety and accessibility, particularly as Iowa ranks in the bottom ten states for cycling safety and laws. If cycling is supported and safe, the economic, health, and environmental benefits it contributes will only grow.

Mapping concentrated poverty in Minneapolis-St. Paul

Back in 2019, my colleague Rob wrote a blog post looking at areas of high poverty in Columbus. This blog post still resonates with a lot of people who understand the history and context of Columbus, and can see how the current concentration of poverty reflects the history of the city. 

Since I grew up and now currently live in Saint Paul, Minnesota, I wanted to do this exercise with my own city. I plotted each census tract in Ramsey and Hennepin counties (the home of the cities of Saint Paul and Minneapolis, respectively), highlighting the tracts with a poverty rate of at least 20%. You can see the whole map here.

I-94

Anyone who knows the history of Saint Paul knows that the construction of I-94 in the late 50s completely changed the fabric of the city. The most famous example of this disruption is the demolition of the Rondo neighborhood, one of the few predominantly Black communities in the city. Today, much of the poverty in Saint Paul follows the I-94 corridor, largely on the North side. The Saint Anthony Park, Midway, Frogtown, and Payne-Phalen neighborhoods all have multiple census tracts with over 20% poverty rates. 

In Minneapolis, the I-94 corridor was built through the heart of the Black community in the North neighborhood. Both North Minneapolis and the Rondo neighborhoods were historically redlined parts of the Twin Cities. Like the old Rondo neighborhood in Saint Paul, the disruption caused to North Minneapolis by the creation of I-94 is still felt to this day. That legacy of disruption has resulted in areas of high poverty for many people. 

West Side

Confusingly, directly South of downtown Saint Paul lies the West Side neighborhood (named because it is on the West bank of the river). This neighborhood currently is home to one of the city's largest Mexican populations, and is one of the few neighborhoods of concentrated poverty that is not along the I-94 corridor. 

Seward to Uptown

South of downtown Minneapolis, there is a band of high poverty neighborhoods that stretch from the Seward neighborhood near the river, through the Ceder-Riverside neighborhood, and almost to Uptown and Lake of the Isles. There is a sharp cutoff at Lyndale Avenue, where people living in the Whittier neighborhood to the East experience much higher rates of poverty than their Uptown neighbors to the West. There is an especially sharp disparity when we look at the people who live immediately around Lake of the Isles, one of the wealthiest neighborhoods in Minneapolis.

University of Minnesota

The part of Minneapolis that is on the East bank of the Mississippi river is largely divided into two chunks separated by I-35W. There is Northeast Minneapolis and its many neighborhoods in the North, and the neighborhoods surrounding the University of Minnesota in the South.

Of these two sections, there is much more concentrated poverty surrounding the University campus to the south. These neighborhoods also fall along the I-94 corridor, creating a continuous network of high poverty areas that stretches from downtown Saint Paul all the way to North Minneapolis. 

Suburbs

The majority of the suburbs surrounding the Twin Cities have very low poverty rates. Still, there are a few census tracts that have poverty rates over 20%. There are neighborhoods in Bloomington, Eden Prairie, Saint Louis Park, and Brooklyn Park that all have very concentrated poverty rates. 

Ohio’s Medicaid work requirements are back from the dead

With a new administration in Washington, state policymakers are reviving their zombie policy of Medicaid work requirements.

Work requirements have been a bit of a political football over the past couple of administrations. While food and income went from being a right for all to a right for all who work during the welfare reform era of the 1990s, health insurance managed to dodge that bullet. During the Obama Administration, however, congressmen and state leaders began kicking around the idea of making health insurance subject to a requirement to work, especially for a newly-covered category of low-income adults without children.

This policy became a reality in states across the country in 2018 as the Trump Administration began issuing waivers to states looking to impose work requirements on Medicaid recipients. A total of 13 states including Ohio were granted waivers and authority to revoke health insurance from low-income adults without children who could not prove they met requirements for paid work hours.

Judges started striking these requirements down soon after they were imposed before the Biden Administration rescinded and withdrew the waivers that allowed them. With the incoming Trump administration, though, supporters of Medicaid work requirements are bullish on the opportunity to reimpose requirements on health insurance recipients.

The imposition of work requirements during the Trump administration gave us a perspective on what the impact of these work requirements were on Medicaid recipients. If work requirements are reimposed, we can expect people to lose their health insurance and for it to threaten their economic security.

According to the Congressional Budget Office, the state experiments of the Trump Administration showed tepid results. Many people lost health insurance coverage under the requirements and there was little evidence that people worked more because of them.

Arkansas was the only state that kept the requirements in place for more than a few months, with their requirement in place for almost a year before being struck down by a federal judge. Over that time period, about a quarter of people subject to the requirement lost their Medicaid coverage.

Researchers studied the employment impact of Arkansas’s work requirements through surveys of people subject to it. One statistical approach found a small increase in employment, but not enough to be considered statistically significant. The other found a small decrease in employment among people subject to the requirements.

The study suggested work requirements also made households less stable. The researchers said the proportion of adults subject to the requirement with serious problems paying their medical bills doubled after institution of the requirements.

Why did enrollment go down and employment not budge under the Arkansas work requirement? It seems that much of the problem was administrative. A third of people subject to the requirement reported they were not aware of the new requirement. Analysis by the Kaiser Family Foundation suggests reporting requirements was the primary driver of failure to meet requirements: many people who lost coverage were working enough to qualify but administrative red tape pushed them off the program.

Medicaid is not cheap, but it is a powerful tool for creating financial stability in low-income households. For the 780,000 low-income Ohioans who may be subject to these work requirements, this extra red tape could be the difference between financial stability and crippling medical debt.

This commentary first appeared in the Ohio Capital Journal.

What is cost-benefit analysis?

“Cost-benefit analysis” is a phrase nearly everyone has heard at some point in their lives. Even if it was as simple as getting advice when making a hard decision to write down all the pros and all the cons of making a decision, you have likely come across some sort of deployment of the concept of cost-benefit analysis in the past.

In the public policy world, “cost-benefit analysis” has a much more specific definition. Cost-benefit analysis is the systematic inventorying of the benefits and costs of a public policy and expression of these benefits and costs in monetary terms. There are widely-accepted textbooks on how to conduct cost-benefit analysis, executive orders governing how cost-benefit analysis is to be carried out on federal regulatory actions, and even an entire association of practitioners of the technique that holds a conference in Washington D.C. every spring.

Most scholars of cost-benefit analysis trace its theoretical roots to late 19th- and early 20th-century welfare economics. In particular, Arthur Pigou’s welfare economic framework laid the groundwork for cost-benefit analysis. In Pigou’s eyes, the economy can be understood as a system of preferences and preference fulfillment across a community. Transactions generate private costs and benefits and social costs and benefits. The sum of the benefits and costs across all transactions in a society comprises the totality of the economy.

The implication of Pigou’s understanding of the economy is that incentives can be realigned to grow the size of the economy. So if an economic activity has public benefits, it can be subsidized so the private benefits align with public benefits, increasing the activity and growing the economy. Public education is a great example of this. Without subsidy, public education will be underprovisioned. Subsidies bring private benefits in line with public benefits, growing the overall size of the economy. Similarly, activities that create public costs like pollution can be taxed to reduce their prevalence.

Cost-benefit analysis first made its appearance in U.S. federal policy around the turn of the century when large public water infrastructure programs were required to be subject to evaluation by the Army Corps of Engineers by the Rivers and Harbor Act of 1902. This approach was more of a fiscal accounting exercise rather than an economic analysis exercise at first, but by the 1950s, economists were bringing welfare economics into the practice, bringing public costs and benefits into the limelight.

The watershed moment for cost-benefit analysis in the United States occurred in 1981, when Ronald Reagan issued an executive order requiring regulatory impact analysis on major initiatives. Cost-benefit analysis became the standardized practice for major rulemaking throughout the federal government and agencies across the government started applying the practice to a range of different issue areas. His original executive order has been reaffirmed by six presidential administrations of different parties, including major revisions under George W. Bush and Joe Biden.

Okay, so that’s the history of the practice. But what actually is cost-benefit analysis?

Unfortunately, there is not a single, agreed-upon answer to this question. Some could say if a policy analysis follows what is in Boardman et al’s textbook on cost-benefit analysis that it qualifies. Others could use federal Circular A-4 as a guidance. The Society for Benefit-Cost Analysis has not adopted formal standards for cost-benefit analysis.

We have written a handbook on cost-benefit analysis that we have created as an approachable guide to the practice for analysts interested in conducting cost-benefit analysis at the state and local level. Within this handbook, we cover the eight elements of a cost-benefit analysis as laid out in a Pew Research Center study of the use of cost-benefit analysis in the states. The elements we identified are the following.

The study comprehensively measures direct costs. Direct costs of a policy, often measured as the government outlays required by a policy, should be included in any comprehensive cost-benefit analysis. This is usually what comes to mind when we talk about “costs” of a public policy.

The study comprehensively measures indirect costs. Outside of the direct costs, policies often have spillover costs associated with them. For instance, a recent cost-benefit analysis Scioto Analysis conducted on recreational marijuana legalization considered the productivity costs the economy would incur due to increased use of marijuana in a state.

Tangible benefits are monetized to the extent possible. A good cost-benefit analysis will not only quantify benefits, but will monetize them. This means trying to estimate how benefits translate into dollar figures that measure the strength of preferences people impacted by the policy have for benefits and costs associated with the policy.

Intangible benefits are monetized to the extent possible. While tangible benefits such as financial savings, increased revenue, or time savings should be monetized, a cost-benefit analysis should also include monetization of intangible benefits, like quality of life, environmental preservation, and knowledge and learning.

Program costs and benefits are measured against alternatives or a baseline. Cost-benefit analysis is ultimately a specific form of policy analysis. This means that a cost-benefit analysis should measure itself against another alternative. A standard alternative to measure against is “status quo,” or what would happen if the policy were not put in place.

Future costs and benefits are discounted to current year values (net present value). A dollar today is not worth the same as a dollar a year from now. Because of the investment value of that dollar and the uncertainties of the future, a dollar today is worth more than a dollar a year from now. A good cost-benefit analysis discounts future impacts to account for this.

Key assumptions used in calculations are disclosed. Assumptions in analysis are inevitable. A good cost-benefit analysis makes as many of these assumptions as clear as possible.

Sensitivity analysis is conducted to test how the results would vary if key assumptions were changed. Sensitivity analysis is the best tool we have to deal with the contingencies of uncertainty in an analysis. A good cost-benefit analysis will subject its assumptions to sensitivity analysis and a great cost-benefit analysis will conduct a simulation like a Monte Carlo simulation to test many of its assumptions in tandem.

This definition may change over time, but as far as I am concerned, this is the best definition of “cost-benefit analysis” I have found to date. If this sort of analysis were used in more public decisions, policymakers would come to those decisions armed with much more information than they currently do. And with that information, they will be better prepared to make the difficult decisions that constitute public policy.

Scioto Analysis is hiring!

We are no longer accepting applications for this position. Sign up for our newsletter at the bottom of this page to be informed when new positions are available.

Today, we began our search for a new policy analyst for Scioto Analysis.

I am going to be frank with you: our goal at Scioto Analysis is not to grow. Our mission as an organization is to improve the quality of public policy analysis at the state and local level. To do that, we partner with state and local governments, university centers, and mission-driven organizations interested in bringing better public policy analysis to pressing questions at the state and local level.

When I started this organization in 2018, I was renting out my apartment with Airbnb and trying to get anyone to listen to the story I was trying to tell: that public policy analysis at the state and local level can be better. That we can think of the economy in a more comprehensive way. And that better information will lead to better public policy.

People have been listening. They have been listening so much that in 2022, I needed to hire Michael Hartnett, a statistician out of the Twin Cities, to join our team as our first employee. Over the past two years, he has allowed us to take on more clients, has led studies on water quality, recreational marijuana legalization, Ohio’s economy, and poverty in the state, and has managed our newsletter and economic experts panel.

The need for better public policy analysis keeps growing, though. Over the past year, we conducted studies on poverty in Ohio, subjective well-being, a $15 minimum wage, lead service line replacement, benchmarking metropolitan areas, poverty in Franklin County, and immigrants and new Americans in Central Ohio.

Every week I am having more conversations with people who think we need better public policy analysis to help inform key state and local issues. If we want to do the work that needs to be done, we need more help.

We are looking for a policy analyst to help us analyze public policy in the tax and budget, social safety net, and energy and environment sectors. This will be a full-time role for someone with strong quantitative and writing skills who cares about making public policy analysis better. This is a good position for people who are early in their public policy careers but we are also open to people who already have some experience with public policy analysis.

We are also looking for a policy analysis intern this summer to help us conduct a cost-benefit analysis on a pressing public policy issue. This is a good position for someone who is still in school and wants to dip their toes into the policy world.

If you know anyone who would be a good fit for either of these positions, please forward this page to them. And if you are interested, send your resume to michael@sciotoanalysis.com. We are excited to talk with you.

We need better minimum wage data

Earlier this month, I wrote about what it looks like when we adjust minimum wages for costs of living across the country. My initial plan was to write a follow up blog post where I looked at publicly available data and estimated the number of people who are paid below their state’s minimum wage. I’m writing this blog post instead though because I wasn’t able to make these estimates. The quality of the data just wasn’t there. 

This is one of those questions that seems like something we should have lots of data on, but we for some reason don’t. You’d think with how accessible wage data is for all different industries that someone would have figured out how to estimate the number of people earning their states minimum wage, but that just isn’t the case.

It is possible to find estimates of the number of people below the federal minimum wage line. The Bureau of Labor Statistics publishes statistics on federal minimum wage workers each year, but they don’t make any estimates for the number of people who fall below their effective minimum wage.

There are a lot of reasons why trying to move past the federal minimum wage is an extremely difficult task. The most important one is determining what a survey respondent’s effective minimum wage is. The Current Population Survey records where its respondents live, which does not have to be the same as where they work. 

If someone crosses state lines for their job, or even if they work in a different city that has its own minimum wage, they might be exposed to a different minimum wage than if they worked exactly where they lived. 

This becomes a larger issue when we are trying to use Current Population Survey data which can have sample size problems when trying to get high geographic resolution. Even looking at state level data, there can be significant sampling errors. We can adjust for these with survey weights which the Current Population Survey has, but those can only go so far. If the survey doesn’t reach enough people with low-wages, we won’t be able to accurately estimate the number of people at the minimum wage.

This is a pretty significant gap in the data. Knowing precisely how many people are experiencing the minimum wage is a really valuable piece of information that could really help drive policy decisions. This is because when we talk about making a change to the minimum wage, the really critical piece of information we need to know is how many people are actually going to be impacted by this change. 

To bridge this data gap, we need more robust data collection methods. Enhanced collaboration between state and federal statistical agencies, along with surveys specifically designed to capture this data could help provide a clearer picture of the labor market. This would empower policymakers with the detailed information necessary to craft legislation that truly reflects the economic realities faced by workers across different regions.

While my original goal of estimating the number of people earning below their state’s minimum wage was hampered by data limitations, this experience highlights the importance of quality data in policymaking. Understanding the true impact of minimum wage laws requires comprehensive, accurate data that captures the complexities of the labor market. 

Should Ohio taxpayers give Jimmy Haslam $600 million for a new Cleveland Browns stadium?

It’s budget season, so the lobbyists are out in full swing.

Tennessee Billionaire and Gas Station Tycoon Jimmy Haslam, known up here as the owner of the Cleveland Browns, is purportedly drumming up support among lawmakers for a $600 million subsidy for a new Browns stadium and that money could be proposed as soon as the Governor’s budget request.

For comparison, this is about as much as the state allocated for highway maintenance across the entire state in 2025. It’s a chunk of change.

So what will we get for this investment? Will the Browns be able to scrounge up more than three wins by a combined 13 points and a three-way tie for last in the league if we throw hundreds of millions of dollars at them?

To be fair, there have been no public promises that Haslam and Company will produce a team that avoids embarrassing the state if they get this subsidy. Public arguments have been pretty threadbare: the City of Cleveland has been hostile to the idea of a new stadium. This seems to have shifted Haslam’s eyes down I-71 to see what kind of success he can have under the dome in Columbus getting help to pay for the project.

So far, the reception has been tepid. New Senate President Rob McColley said he was opposed to a “handout” to the Browns when he heard about the proposal. Some policymakers are kicking around backing the project with state bonds, bumping the cost up to $3 billion and using some of that money to develop nearby hotels, restaurants, and housing.

So let’s get back to the meat of the issue: why would we do this? What is it about football stadiums that makes a businessman or a lobbyist think he can credibly waltz into a lawmaker’s office and shamelessly ask for hundreds of millions of taxpayer dollars? I mean, these aren’t utility companies we’re talking about.

The case lobbyists make for stadium subsidies is fundamentally economic. With a professional football team, your state will get on television. People will travel from far away to visit your city, they will stay at your hotels, they will eat at restaurants, and you will become a destination.

The consensus among economists is that this story is a fantasy. Yes, economic activity will increase around a football stadium: it can be an anchor for a flurry of economic activity once a week twenty times a year. But where does this money come from?

Entertainment budgets are not flexible. If someone didn’t go to a stadium, they would probably go to a bar, restaurant, movie, play, or live performance somewhere else in the city. So new economic activity is not created, it simply is shifted from one part of the city to another.

A study published in the Journal of Benefit-Cost Analysis just a few months ago underscores this economic consensus. For a professional sports team or stadium to be anything other than a net negative on the local economy, it needs to (a) attract visitors from other cities, and (b) get its owner and players to spend a significant share of their income in the area.

So if legislators are going to take this seriously, they need evidence of three things. First, they need to see that this new stadium will bring significant numbers of new visitors to Ohio. Second, they need to see that Jimmy and his team are spending a lot of their own money in Ohio. And third, they need to see that this is a better investment than transportation infrastructure, education, broadband, and the many other priorities they will have to put aside to give Jimmy a new place for his team to play.

This commentary first appeared in the Ohio Capital Journal.

Scioto Analysis releases report on Central Ohio’s New American community

New Scioto Analysis report explores the economic potential of one of central Ohio’s most rapidly-growing populations.

Central Ohio is home to a growing immigrant and new American community, which is playing an important role in shaping the region's social and economic fabric. A new Scioto Analysis study, conducted in partnership with Ethiopian Tewahedo Social Services, sheds light on the needs, challenges, and opportunities facing this population.

In interviews with dozens of community leaders, nonprofit workers, and new Americans, analysts asked questions about economic and financial barriers faced by immigrants in central Ohio. The study highlights six key barriers for new Americans: language skills, housing, financial services, education, transportation, and employment. It also highlights the struggles of immigrant-serving organizations in overcoming funding and coordination challenges and the pressing need for legal services. By addressing these barriers, the region can support immigrants and the broader Central Ohio community.

Key Findings:

• Over two-thirds of interviewees identified language barriers as a top challenge, which limit access to employment, financial services, and social integration.

• Half of respondents cited the lack of affordable and quality housing as a major issue, with many immigrants facing exploitation from housing providers.

• Immigrants in Central Ohio often experience underemployment, with many unable to use their professional credentials and skills due to bureaucratic and cultural obstacles.

• Nearly half of the respondents noted financial literacy as a barrier, particularly around the complexities of the U.S. credit system.

The report also highlights significant data gaps, including limited information on undocumented immigrants, second-generation immigrants, and the economic contributions of new Americans.

Recommendations:

1. Address the pressing need for affordable English classes and translation services to foster integration and accessibility by expanding language and translation services.

2. Develop programs to demystify the U.S. credit and banking system for immigrants by promoting financial literacy programs.

3. Work with policymakers to reduce barriers for skilled immigrants to contribute to the workforce by streamlining licensing and credentialing.

4. Improve practices in data collection to better understand and serve Central Ohio's immigrant communities.

The report identifies potential avenues for community investment, including language skill development, financial literacy programs, and enhanced coordination between community organizations and larger nonprofits.

“Central Ohio’s new American community will play a key part in the region’s growth and success over the next twenty years,” said Scioto Analysis Principal Rob Moore. “By acting to support immigrants and new Americans, policymakers and grantmakers can improve quality of life for all its residents.”

The economics of crime

In my first semester of college I took a class on the philosophy of law. We went through the history of philosophers discussing why we have laws and what enforcing them did for society. This is a gross oversimplification, but most of these philosophies essentially boiled down to “we don’t want people to commit crimes because that is inherently wrong and it doesn’t fit in with our broader social norms. This is why when people break the law, we punish them.”

I did quite poorly in this class so I couldn’t explain more of the nuance even if I wanted to, but these ideas about crime and punishment left me feeling unsatisfied. It wasn’t until later when I was exposed to the economic theory behind crime that I felt like I began to agree with a general understanding of why crime is a problem and what our society could do about it. 

So, I’d like to provide a brief introduction to the way that economists think about crime and the criminal justice system. These are the broad ideas of why economists think crime is a negative part of our society, why people choose to do it, and what policy options we have for reducing crime.

Why crime is an economic problem

At Scioto Analysis, we think a lot about the value that non-market activity has on the economy. Generally, we think of non-market activity as an addition to the formal economy because people who participate in non-market activity are adding value despite the fact that they are not being formally compensated. 

Criminal activity is different from other forms of non-market activity because it largely falls under the umbrella of “rent-seeking behavior.” Rent-seeking is a poorly worded term that has nothing to do with our general understanding of what rent is, but instead describes activity that benefits one individual but does not create any additional value for society. While rents are traditionally earned by ownership of a resource, rent-seeking behavior is characterized by manipulation of markets to gain an advantage that siphons resources from others.

Stealing is a good example of rent-seeking because the person who steals receives some benefit for themselves, but that benefit strictly comes from another part of the economy. In fact, stealing is likely to shrink the overall economy, since other people now have to spend some money on security systems to prevent falling victim, an otherwise unnecessary drag on their capacity to get the things they want.

Crime through an economic lens

In order to think of economic solutions to the problem of crime, we need to understand the incentives that exist for people to choose criminal activity in the first place. To do this, we will construct a very simple decision model.

Consider an individual whose goal is to maximize their individual utility. To do this, they get to decide whether they will participate in criminal activity, or alternatively some sort of formal market activity. We can describe their utilities very simply with the following functions:

In the first equation, the individual’s utility is exactly the value they expect to get from their regular market activity. This could easily be thought of as the wage they expect to earn by working some job. The key assumption here is that this value is fixed for our individual, and it is easily known. 

In the second equation, this person’s utility relies on the probability that they will be arrested for committing a crime. If this person is arrested, they gain no utility and instead incur some negative cost associated with being arrested. If they are not arrested, then they receive the full benefit for committing a crime. Their expected utility is then the benefit they will get from committing the crime multiplied by the probability of not being arrested, minus the cost of being arrested times the probability of being arrested. In this very simple scenario, our individual will choose the option that maximizes their utility. 

In the above equations, there is really only one variable that public policy can’t have any impact on — the benefit of committing crime. All of the other factors are things that can at least be influenced by policymakers.

Often, discussions around how to prevent crime focus on the illegal market side of the equation. The “tough on crime” attitude that rose to the forefront in the 1990s is a hallmark of this type of policymaking. More police and more severe punishments are ways to decrease the expected utility of committing crimes and push some people on the margins towards formal market decisions. 

But this isn’t the only approach. Another strategy is to raise the expected value of formal market activity. Higher wages, better hours, more benefits–these are all ways we could discourage crime by making the alternative more appealing. 

This is especially true for people who have committed crimes in the past. One major shortcoming of the current criminal justice system is that individuals often experience a significant reduction in their expected utility for formal market employment upon leaving prison. It is more difficult for people with criminal records to find high-quality jobs, making returning to criminal behavior relatively more attractive. 

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The economic research on the criminal justice system is far deeper than I can go into in a blog post. There are countless issues concerning the effectiveness, efficiency, and equity of the criminal justice system that warrant a lot of attention. Hopefully, this has allowed you to see crime through a new lens, where rational actors are making utility maximizing decisions like everyone else in our society. The problem we should be solving is how we can get individual decisions to align with social goals.