Four ways to help people with disabilities get work

A bill currently in the Ohio General Assembly would eliminate the subminimum wage for people with disabilities.

Currently, companies in Ohio are allowed to apply for a waiver from the state minimum wage to hire people with disabilities. The goal of this program is to make it easier for companies to hire people with disabilities and therefore to give more people with disabilities jobs.

I was talking to Michael Hartnett, a policy analyst I work with at Scioto Analysis about this problem earlier today. He brought up a few options for the state to increase employment of people with disabilities without paying them less.

Job training

Providing more funding for job training programs for people with disabilities can help give people with disabilities skills that are valuable for employers. The federal Employment and Training Administration provides funds for training people with disabilities.

The state of Ohio even has an office called the Bureau of Vocational Rehabilitation. The Bureau specifically focused on providing individuals with disabilities the services and support necessary to help them attain and maintain employment. More funding for training programs referred through the Bureau could increase employment of people with disabilities.

Grants for making workplaces accessible

One reason it is hard to hire people with disabilities is because employers may have trouble accommodating workers with disabilities in traditional workplaces. For instance, if a job traditionally requires typing, people with limited dexterity would typically not be a candidate. A grant for a job that requires some typing could allow a company to hire a scribe part- or full-time to type for that person.

One example of this type of program is the Retaining Employment and Talent after Injury/Illness Network (RETAIN) Initiative, a federal program that Ohio takes part in. Eight state teams received competitive awards to develop and run pilot programs aimed at helping workers stay at or return to the workforce following an illness or injury. A similar program could be developed for counties and cities if this program is successful.

Subsidizing wages for people with disabilities

The Earned Income Tax Credit is a popular wage subsidy aimed at bringing low-wage people into the labor force. A weakness of the Earned Income Tax Credit is that it is targeted at families, so people without children often have a small credit. Having a larger credit for people with disabilities or making the state earned income tax credit refundable for people with disabilities are two policy levers policymakers have for making it easier for people with disabilities to go to work.

Mandates for accommodation

A final option is to just tell employers they need to accommodate. The Americans with Disabilities Act requires employers to reasonably accommodate workers with disabilities. Strengthening state law around accommodations could require employers in Ohio to work harder to accommodate people with disabilities.

A 2018 study estimated that making it easier for people with disabilities to work would bring 10.7 million people into the U.S. workforce and would increase national GDP by $25 billion. If this is the case, that means more people with disabilities in Ohio’s workforce would mean hundreds of thousands of new workers and hundreds of millions of more dollars in the state economy. This looks like a win for everyone.

Economic costs we don't talk about

At Scioto Analysis, we love talking about new ways for policymakers to think about the economy. When we talk about strengthening the economy through the narrow lens of GDP growth, we’re often talking about people getting more things they want. If “the economy” is the total value of things people want, then this makes sense to an extent. 

But the economy isn’t just the sum total of things people have that they want, it’s also offset by the cost of things people don’t want. Below is a simplified model of the economy factoring in this insight.

“The Economy” = The Total Value of Stuff People Want - The Total Cost of Stuff People Don’t Want

Just as an economy grows as it adds jobs (something people want), it also grows as it reduces car crashes (something people don’t want). 

Below are three economic costs that further illustrate this point.

Underemployment

When we talk about the current conditions in the labor market, we often focus on unemployment as the main indicator. Unemployment is certainly very important, but the official U3 unemployment measure doesn’t include underemployment. We know it is bad when someone wants to be able to work but can’t find a job, but it is also bad when someone can’t find enough work. 

If during an economic downturn, an employer chooses to reduce hours rather than lay off employees, the unemployment rate doesn’t change. Including underemployment as part of the discussion paints a much more complete picture of conditions in the labor market. 

Homelessness/Houselessness

People who don’t have somewhere consistent to spend the night regularly fall through the cracks when it comes to provision of public services and in discussions about the economy. 

Consider what happens if a houseless person has to go to the emergency room because of the cold. First and foremost, there is a social cost (e.g. hypothermia) that goes unmeasured by GDP. Then, because a healthcare provider ends up providing a service that has to be paid for, GDP actually grows slightly. If the goal of economic indicators is to show us where we can enact policy to help make people more well off, then including houselessness in that discussion is very important.

Defensive Expenditures

Defensive expenditures refers to personal spending on things that do not increase welfare or are used to prevent a loss in welfare. Take home security for example. If people didn’t have to spend anything on home security, they’d be able to use those resources on things they actually wanted. A neighborhood without crime would have less spending on home security systems, which would be a good thing for families.

If we don’t intentionally include defensive expenditures in the discussion, then most measures of the economy will take these pieces of economic activity and count them as positives. Separating consumer spending into categories is difficult, but an important nuance that helps us better understand how people are doing in the economy.
These three measures, underemployment, homelessness/houselessness, and defensive expenditures, are accounted for in the Genuine Progress Indicator (GPI). GPI is a “GDP+” measure that accounts for both sides of the ledger: economic benefits and economic costs. It also includes economic benefits such as home child care and volunteering not included in GDP. If we want to talk about the economy in a thoughtful way, we need to ensure we’re looking at a complete picture.

Defining a public policy problem: describe, then diagnose

One easy mistake to make as a policy analyst is to get ahead of yourself.

When analyzing a public policy problem, policymakers are often already bringing diagnoses of the problem to the table before the analysis has even begun. This is why problem definition is such a crucial step in the policy analysis process: it helps us strip away assumptions we bring to the table and analyze a public policy on the merits of its core goal. This keeps our problem definitions squarely rooted in our goal of advancing social values.

In Eugene Bardach’s A Practical Guide for Policy Analysis, the political scientist makes a distinction between two ways of thinking about problem definitions that is helpful here: problem definitions can be both descriptive and diagnostic. The more descriptive a problem definition is, the closer we can tie it to empirical evidence. The more diagnostic it is, the more we can construct concrete policy options to address the problem.

One way to think about problem definition is a type of criteria selection: we are describing what public problems policymakers care about. When we define a problem such as “the quality of air in the state of Michigan is too low,” we are laying the groundwork for us to construct certain types of policy options. We are also already implying one criteria: the effectiveness of a policy option in improving air quality.

Bardach talks about the treacherous line policy analysts walk when they define a problem. He uses the following example to show what a more diagnostic problem definition looks like:

One of the problems in the air pollution area is that states have not been willing to force motorists to keep their engines tuned up and their exhaust systems in proper order.

He says that on the one hand, this more diagnostic problem definition is useful. By more narrowly defining the problem, we can come up with more practical policy options to address this problem. “How can the public sector force motorists to maintain their vehicles?” is much more concrete than “how can the public sector improve air quality?”

On the other hand, such a strongly diagnostic problem definition can (a) limit the range of policy options to address the underlying problem, and (b) detract focus from larger causal factors to small causal factors for the underlying problem.

Policy analysis is an iterative process, and remembering this is an important way to figure out how to navigate the treacherous territory of description versus diagnosis in problem definition. Your first pass at problem definition will look different from your approach to problem definition in the eighth step when you are telling your story.

For this reason, I provide the following advice: describe, then diagnose. In the earliest phase of your policy analysis, focus on description. Make your problem definition abstract and idealistic: strip what your client wants down to its most naked connection to public interest. “The quality of air in the state of Michigan is too low” is an excellent first-pass problem definition.

Later, particularly after the second step of “assembling evidence,” diagnose. Say why air quality is low. Compare air quality in Michigan to that of other states. Talk about causal mechanisms. Build a model.

At this point, your problem definition can change. And the changes should be driven by (a) empirical evidence, and (b) client needs. This allows your problem definition to be both truthful and helpful.

If your problem definition starts out rooted in social values, then it can be further specified with empirical evidence and client needs. If you don’t start with social values, however, it can be a lot harder to add those in later in the policy analysis process.

5 Takeaways from Scioto Analysis's new Water Quality CBA

As Scioto Analysis’s newest member, I had the opportunity to conduct my first cost-benefit analysis about water quality in Ohio over the past few months. Here are five key takeaways from the project.

1: Ohio’s water quality is quite poor

For any policy analysis, it is important to begin by defining the problem we are trying to solve with policy. Using data made available by the University of Vermont, we can see that water pollution costs the average Ohio resident $219 compared to only $139 for a resident of the average state. These costs include lower property values, decreased recreation, and higher costs associated with water treatment. This means Ohioans have less recreational opportunities, lower property values, and higher water treatment costs than other states due to surface water degradation.

2: The H2Ohio program has helped reduce agricultural pollution

In their fiscal year 2022 report, the H2Ohio program reported that over 200,000 fewer pounds of phosphorus are loaded into the Western Lake Erie basin annually because of its programming. As the H2Ohio program continues to operate and grow, Ohioans could see fewer harmful algal blooms as a result. There is still a long way to go, but the H2Ohio program has been a first step in reducing phosphorus runoff into Ohio’s lakes and rivers. 

3: The social benefits of improved water quality are significant

Strong economies are able to give people access to the things they want despite the fact that resources are limited. Clean water is an extremely valuable resource that often gets overlooked in a country where drinking water is often easily accessible. Research on the willingness to pay to prevent water pollution has shown that one excess kilogram of phosphorus due to runoff from livestock waste causes nearly $75 of economic losses. 

4: Expanding successful programs is difficult

We’ve talked in the past about the problems associated with scaling programs, and H2Ohio is no exception. In this cost-benefit analysis, we chose to model these diminishing returns by assuming that future reductions in phosphorus would be as much as 50% lower. Fortunately, even with this conservative assumption, the program still has positive net benefits the majority of the time.

5: Subsidies are effective at fixing market failures

One of the most well-known drawbacks of classical economic markets is that they often have external costs levied on people not involved in a given market transaction. However, if policymakers understand these externalities, they can use their ability to levy taxes and increase spending on subsidies to push markets towards more efficient outcomes. Taxes and subsidies are often the simplest tool policymakers wield for correcting market failures.

Scioto Analysis releases cost-benefit analysis of Ohio water quality program

Scioto Analysis released a cost-benefit analysis analyzing the effectiveness of the H2Ohio water quality program this morning.

Analysts found that under its current expansion to ten new counties, the H2Ohio voluntary nutrient management program could provide net social benefits exceeding $2 million. Assuming reductions in phosphorus runoff remain high, expanding the voluntary nutrient management program to the entire state could generate nearly $13 million in net social benefits. 

Economic benefits of improving Ohio’s water quality include increased property values, increased access to recreation, and decreased costs associated with water treatment.

“We found that the H2Ohio program has been successful in reducing nutrient load in a cost-effective manner,” said analyst Michael Hartnett. “Assuming farmers across the state apply nutrients in similar ways and that reductions would be comparable, offering the same subsidy to farmers in every county could provide millions of dollars worth of benefits to Ohioans.”

Due to nutrient runoff from agricultural practices and industrial waste, Ohioans on average incur higher costs from water quality problems than 46 other states.

“The average Ohioan incurs over $200 a year in costs from low quality water in the form of lower property values, decreased access to recreation, and higher costs for water treatment,” said Scioto Analysis Principal Rob Moore. “Programs like nutrient management can reduce fertilizer runoff and improve the water of Ohio’s rivers and lakes, which will lead to health, environmental, and economic gains for Ohio.”

This study is the most recent cost-benefit analysis conducted by Scioto Analysis. Previous cost-benefit analyses include research on municipal tree planting, reductions of carbon emissions, and Covid-19 school closures.

What will happen if Ohio abolishes its income tax?

For years, legislators in the Ohio General Assembly have been working to abolish the state income tax. Republicans now command historic majorities after the 2022 midterm elections. Because of this, Cleveland.com politics reporter Jeremy Pelzer is saying income tax abolition is now closer than ever.

The caveman argument for abolition of the income tax is “tax bad.” I don’t have much to say about this: taxes can distort the economy but they also fund important public services, can help reduce inequality, and even fix distortions in the economy when deployed correctly.

The more nuanced argument being made by some policymakers is that income tax is more distortionary than sales tax. This is because it is easier to change how much you work than how much you consume. This means that income taxes theoretically drag the state economy more than sales taxes do.

Cutting income taxes on its own is unlikely to generate enough new revenue to pay for itself, as Kansas painfully demonstrated a few years ago. Due to Ohio’s balanced budget mandate, abolishing the income tax would require either steep reductions in spending (with cuts in education spending being the only likely path) or an increase in the state sales tax.

Abolishing Ohio’s income tax would not be unprecedented among states. Eight southern and western states currently have no state income tax: Alaska, Florida, Nevada, South Dakota, Tennessee, Texas, Washington, and Wyoming.

Some of these states are able to take this approach because they either have alternate sources of revenue (oil in Alaska, Texas, and Wyoming, gaming in Nevada) or have a relatively small income tax base due to a high retiree population like Florida. Ohio has none of these luxuries. Zach Schiller from Policy Matters Ohio argues Ohio would need to raise sales taxes higher than any other state to make up for the lost revenue from income tax abolition.

The big problem with a shift from income tax to sales taxes is the impact the shift would have on poverty and inequality. Income taxes are higher for workers who earn more and increase in rates for higher levels of income. 

Sales taxes are flat and end up taking up a larger percentage of low-income earners’ budgets relative to high-income earners’ budgets. A high-sales-tax regime will, all things being equal, lead to higher poverty and inequality than a high-income-tax regime.

Is there a way to shift from income to sales taxes while addressing the equity problems caused by such a shift? Yes, theoretically. By increasing the sales tax enough to fund an expanded earned income tax credit, child tax credit, or other antipoverty program, Ohio can theoretically offset the equity impacts of the tax shift with new antipoverty spending.

This type of change happened in 2019 when Ohio increased its gas tax (a specialized sales tax) and expanded the state earned income tax credit at the same time. The earned income tax credit increase was used as a way to offset the regressive elements of a gas tax increase.

Moving to a sales tax regime with heavy investment in pro-poor programs would actually make Ohio’s public finance look a lot more like Europe’s. The U.S. relies less on consumption taxes than any other OECD country, instead using income taxes to finance its public spending.

It would take a bit of spending to make a significant dent in poverty — my firm estimates there are over a million Ohioans living in poverty, so a $1,000 rebate only targeted at those in poverty would cost over a billion dollars. A four percentage-point increase to the cost of all sales would put a family spending $24,000 at nearly that much on its own, so it would make this policy a breakeven policy for poverty.

An alternative would be an increase in the earned income tax credit. An analysis we did on earned income tax credit expansion a few years ago estimated a robust earned income tax credit expansion would cost the state about $760 million. This would also provide about $1,000 each to those in poverty according to our estimates, only making these families break even after new costs. This means larger programs might be needed to reduce poverty depending on what is exempted from sales tax.

In the scheme of a $10-billion-odd tax reform, a billion or two focused on poverty does not seem like a difficult lift. Unfortunately, the politics of a couple billion dollars for the poor can be more sticky than the politics of $10 billion for the rich. 

Conducting tax reform that promotes efficiency and equity is not impossible. It will, however, require policymakers to be as committed to the latter as they are to the former.

This commentary first appeared in the Ohio Capital Journal.

8 Overrated and Underrated Economic Indicators

According to a survey conducted by Pew Research, the state of the economy was the most important concern voters had before this year’s midterms. Because the economy is so important, we should be able to understand whether or not it is doing well, right? 

Unfortunately, “the economy” is a nebulous phrase and there is no definitive way to measure how it is doing. There are a variety of metrics and statistics that policymakers can look at to see how the economy is faring, and in today’s blog we are going to talk about a few of them that are overrated or underrated. 

We should mention that these are just our thoughts on this issue. Certainly there is room for discussion and disagreement, but we hope this offers some new ways of thinking about the economy. 

Overrated - GDP

If you ask a friend how they are doing, you probably wouldn’t expect them to respond by telling you how much stuff they have. While it is generally true that having more things often means that an individual has more access to resources, this is not the whole story of wellbeing. Similarly, because GDP only measures how much stuff is in an economy, it can sometimes miss the bigger picture of how people are doing in the economy. 

Imagine two countries that each have the exact same GDP. Country A has high levels of poverty and extreme levels of pollution. Country B has low levels of poverty, and generates its production without the need for pollution. Clearly country B has a more sustainable economy, but GDP just doesn’t capture that. 

Underrated - GPI

The Genuine Progress Indicator (GPI) is a relatively new alternative to GDP. GPI serves much of the same purpose as GDP, trying to measure how much economic activity is in a country, state, or local area, but it also takes into account things like how sustainable an economy is, or how educated the population is, recognizing that these have economic impacts that are not traded on formal markets.

One of GPI’s biggest advantages over GDP is that it measures the value of non-market activity such as at-home childcare and volunteering. There are lots of extremely valuable ways for people to spend their time that improve the economy even though no dollars change hands to make it happen. 

Overrated - Stock Market

The stock market doesn’t get used as a signal for how the economy is doing as much as it used to, but the past two presidents have both mentioned it so it deserves some discussion here.  

The main difference between the stock market as an indicator and an alternative like the yield curve is that the stock market doesn’t have a neat cutoff point where we can see something is wrong. If the yield curve is inverted, we know that people think the short term is riskier than the long term. If there is a 50% rise or fall in the stock market, that just means there was a change in the prices of stocks. Maybe it was due to variance, maybe it was due to fundamental shifts in the economy, but there is usually no way to know until much later. 

Underrated - Yield Curve

The yield curve is often touted as one of the best recession indicators we have, but since we just talked about GDP being overrated we want to talk more generally about how the yield curve is beneficial outside that context.

The yield curve is the difference between the interest rates for 10-year treasury bonds and 2-year treasury bonds. In normal conditions, we should expect 10-year bonds to have higher interest rates, since it is riskier to hold bonds for longer periods of time where there is more uncertainty. 

When the yield curve is inverted, 2-year bonds have higher interest rates than 10-year bonds, meaning the people who are buying and selling bonds are more nervous about short term economic trends than they are about long term trends. It becomes safer to hold money for 10 years rather than 2. It is always a bad sign when people are more nervous about the short term in the economy than the long term. 

Overrated - U-3 Unemployment

The bureau of labor statistics reports six different unemployment measurements that each include different categories of people in the labor market. U-1 is the most optimistic, only accounting for people in the labor force who have been unemployed for at least 15 weeks. 

In the middle of the spectrum is U-3 unemployment, what is considered the official unemployment rate. U-3 is the most straightforward measure of unemployment, calculating the percentage of the labor force that do not currently have a job. 

U-3 is a useful unemployment measure, but it misses one crucial point that is critical to understanding the state of the labor force, underemployment. 

Underrated - U-6 Unemployment

On the other end of the unemployment measure spectrum is U-6 unemployment. U-6 is often a more useful measure of unemployment than U-3 because it actually does account for underemployment. 

If there is an economic downturn, employers are often faced with the need to cut costs. If they choose to cut costs by reducing the hours people work without laying them off, then other unemployment measures won’t capture the lost economic activity. 

Overrated - Official Poverty Rate

The official poverty rate was created in the mid 1960s by economist Mollie Orshansky as a tool to measure progress in the War on Poverty. At the time, the average family in the United States spent a third of their income on food, so the poverty line was set at three times the cost of a “thrifty food plan” for minimum nutritional intake in the United States and adjusted to family size. This measure is updated every year by the Census Bureau to adjust for inflation.

The Official Poverty Rate has a lot of problems. One is that family budgets have changed significantly over the past half century since the Official Poverty Measure was first adopted. While food cost a third of a family budget in the mid 1960s, agricultural and supply chain advances have dropped that number to about an eighth today. Meanwhile, costs of housing and health care have increased precipitously. Add this to the fact that the Official Poverty Measure does not make geographic adjustments for cost of living and we have a potential for overestimating poverty in some parts of the country and underestimating it in other parts of the country.

Underrated - Supplemental Poverty Rate

Since 2010, the Census Bureau has been calculating an alternative poverty indicator called the Supplemental Poverty Rate. Starting from a basis of two-thirds of average spending, the Supplemental Poverty Rate then counts total income (including both wage income and public benefits) and makes adjustments for geography and work expenses. The Supplemental Poverty Measure gives us a more accurate picture of what poverty looks like in the United States over a half century after the War on Poverty.

Scioto Analysis calculates the Ohio Poverty Measure using a similar methodology to the Supplemental Poverty Measure, but using a larger dataset to allow for more geographic precision.

There is no perfect measure for how well the economy is “doing.” But a dashboard of GPI, the yield curve, U-6 unemployment, and the Supplemental Poverty Rate will give you a more accurate picture of what the economy looks like than a dashboard of GDP, the S&P 500, U-3 Unemployment, and the Official Poverty Measure. So next time when someone talks about “the economy,” don’t be afraid to ask “what do you mean?”

How can a policy analyst define a problem better?

One thing I love about Eugene Bardach’s A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving is the guidance Bardach gives to policy analysts to avoid common mistakes they make in the analysis process.

One tool Bardach uses is called “pitfalls and semantic remedies.” The general idea Bardach presents is that there are common pitfalls in how we do policy analysis and if we articulate our problems and approaches in certain ways, we can avoid these pitfalls.

We can find an example of this in problem definition, the first step of the Eightfold Path. One mistake policy analysts can make is to define the solution into the problem. 

Let’s take student loans as an example. If we were to say “students have not had enough student loan forgiveness,” we are assuming that “forgiveness” is the best solution to the underlying problem. By redefining the problem as “too many students are burdened by student loans” or “students with student loans have too heavy burdens,” we open ourselves to solutions besides student loan forgiveness.

As a former undergraduate philosophy major, of course my mind goes to “well, too many students are burdened by student loans” isn’t our final question, right? Isn’t the deeper problem “college graduates do not have enough resources?” Or is it rather “student loans are an unfair burden to place on adults that young people do not understand the financial ramifications of?”

You can see how defining this question takes us in different directions. On the one hand, we could be talking about burden as a utilitarian problem: people aren’t able to get as much of what they want because their resources go toward student loans. On another hand, we could be talking about norms of fairness: students should not be burdened with unfair loans they do not understand the gravity of.

There are a couple of interesting questions this opens up. As analysts, we are usually asked to be utilitarians. This problem can seem like a hammer searching for a nail. Yes, we are (relatively) good at measuring things like consumer surplus, but often questions of fairness are what policymakers are more interested in. Maybe that’s not the place for a policy analyst, though. Questions of fairness are often better handled by the political process, reasoned debate, or by decisions of policymakers.

So where does this leave us as policy analysts? I’ll put forth a few problems that crop up when trying to apply the semantic tip of stripping a problem to mere description.

1. Where do we stop? We can keep digging deeper and deeper and getting to more and more philosophical questions. How do we know when to stop stripping our question down?

2. What do we do when our questions branch? If we end up facing multiple different problem definitions, which one do we choose?

I will offer two pieces of guidance for policy analysts stuck in this muck around stripping down problem definitions.

First, maintain client orientation when defining the problem. While we can push our clients to think about problems in a larger way, we also have to meet them where they are. 

The policymakers who we are working with may be further along in the decision making process than we are as analysts and if we get bogged down in philosophical questions, they can leave us in the dust. So try to define your problem in a way that stretches your client to open their mind to different possibilities, but not so much that the alternative possibilities opened by the problem definition become irrelevant to the client.

For instance, if you are writing a policy analysis on student loan burden for a state senator who ran on a platform of reducing student loans, coming back with a problem definition of “poverty is too high” would likely be astray of what she is looking for. Instead, a problem definition of “too many college graduates are in poverty” could be closer to what she is interested in actually having a policy analysis written around, depending on her political orientation.

Second, embrace the tools of policy analysis. If you are stuck between different ways to define a problem, sometimes it is better to ask yourself which question looks more like a nail. Policy analysts are not philosophers or politicians–they are applied social scientists. Leave the questions about metaethics to the metaethicists and the questions about political feasibility to the political strategists: as a policy analyst, you are best at applying the insights of economics to policy problems.

In this example, a path of “too many people are burdened by student loans” is a more straightforward problem definition than “the student loan system is too unfair.” If a client is ambivalent between the two, you are going to be able to analyze the former better than the latter and give better insight because of your particular technical expertise.

Policy analysis is messy, but by (a) understanding what our clients want, and (b) understanding what you are good at, you will be able to produce analysis that is more relevant to a policymaker. And relevant, insightful analysis is ultimately what we mean when we talk about good analysis.

Ohio economists do not think state loan forgiveness would impact tuition rates, inflation

In a survey published by Scioto Analysis this morning, economists in Ohio did not believe state student loan forgiveness would increase tuition rates or inflation. 

The respondents were split on the question of whether an Ohio student loan forgiveness would help Ohio retain educated workers. Some believed Ohio would retain more workers only if the loan forgiveness was contingent on years spent living and working in Ohio. 

Most economists believed that student loan forgiveness would not affect tuition prices or inflation. Some economists said whether loan forgiveness could be expected again in the future would impact tuition prices more than a one-time forgiveness. Most economists also said such a program would likely have a negligible impact on inflation if any.

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

Does GDP make states happy?

Earlier this week Gross National Happiness USA, a national grassroots organization for which Scioto’s principal Rob Moore is president, released a landmark survey about happiness in the US. This is the first time a national survey of happiness has been conducted on four questions of happiness that have been asked in the U.K. for a decade and it offers some very valuable insights for those of us in the public policy field. 

One particularly important takeaway is that GDP per capita is not correlated with happiness. The correlation coefficient, the main statistical test for how two datasets relate to one another, between state GDP per capita and state happiness is only 0.09. This constitutes a weak relationship between GDP per capita and state happiness. Many people recognize that GDP is a way of measuring how much stuff is in an economy, not how well people are doing in that economy. Here at Scioto, we recommend the Genuine Progress Indicator (GPI) as a more complete metric to measure economic growth. Still, GDP is the most commonly used measure of the economy, and perhaps this survey is more evidence that broader measures of economic growth are needed in the policymaking world. 

Another interesting finding in the study is that among Americans, there does not seem to be a u-shaped happiness curve. The “u-shaped curve” is a widespread phenomenon in happiness that suggests people are least happy in their 40’s. It has been found in similar surveys across multiple other countries and within the U.S. In this study younger people are less satisfied with their lives than a u-shaped relationship would suggest. 

Although this finding is unexpected, Gross National Happiness speculates that perhaps the Covid-19 pandemic might be responsible, given that younger Americans reported more feelings of loneliness during the pandemic. 

The researchers also found that 45% of respondents reported that family was the most common factor people attributed their happiness to. The next most common topic reported was health, where 6.3% of respondents mentioned it. 

For policymakers interested in the happiness of people in society, this survey is a great tool to find areas for improvement. With more data like this, it will be easier and easier for researchers and analysts to include happiness as a criteria when evaluating public policy options.