State carbon abatement policies could generate $1 trillion in benefits

(Columbus, OH) – On Monday, Scioto Analysis released an analysis of options for reducing carbon emissions in the state of Ohio. Analysts found that renewable portfolio standards, cap-and-trade, or carbon tax approaches could generate up to a trillion dollars in economic benefits for the state through 2050.

Benefits would be accrued in the form of reduced health risks, less spending on infrastructure maintenance, and avoided cases of food insecurity driven by high carbon emissions.

“In this analysis, we found that stronger renewable portfolio standards, a cap-and-trade program, or a carbon tax would all lead to a reduction in economic impacts in the next thirty years by $800 billion to $1 trillion,”  said Aayush Nema, lead analyst for the project. "These numbers are consistent with extremely conservative values for the social cost of carbon and its discount rate. Moreover, each of our policy recommendations are consistent with bipartisan bills and policies implemented or supported by utility providers in states similar to Ohio.” 

This analysis was released just weeks after the Biden Administration released goals to reduce U.S. carbon emissions to 50% of 2005 levels by 2030, the onus for achieving which might fall on individual states.

“If Biden’s plans for carbon emissions will look anything like the Obama Administration’s, requirements to find a way to reduce carbon emissions will fall in the lap of states,” said Scioto Analysis Principal Rob Moore. “This analysis shows the state of Ohio has three great options for abating carbon.”

For more information, contact Rob Moore, principal, Scioto Analysis, (614) 743-1840, rob@sciotoanalysis.com

The vaccination conversation changes

The vaccine conversation is changing, and it’s changing fast. 

Just a month ago, people across the state were tapping “refresh” on their browsers, hoping to book their spot at a local pharmacy for an assurance against infection delivered by Moderna, Pfizer or Johnson & Johnson. Just two weeks ago, I biked down to Grove City from my home in the Brewery District to get the closest shot I could find.

Now, supply is outstripping demand. Pharmacies in many rural areas are practically begging people to get vaccinated. The overriding public policy problem of vaccination shifted quickly from one of rationing to one of public education.

Over a year ago now, I wrote about what Ohio can do to fight COVID-19, and the first strategy I listed was vaccination, understanding it would be awhile before we could implement such a strategy. That’s as true now as it was then: An ounce of prevention is worth a pound of cure, and two pin pricks is well worth reducing someone’s chance of contracting, suffering from, and passing on this deadly virus.

As of this week, a third of Ohioans are fully vaccinated. Public health experts across the country, though, are worried “herd immunity” will not be achieved. The story of the changing market for vaccines is not just one of supply, it’s also one of demand. While getting an appointment has become easier and easier over the past few weeks, the number of daily vaccinations has gone down over that time period.

What sort of dynamics will drive the vaccination trend in the Buckeye State going forward? She state has some things going for it. As of last weekend, Ohio led all of its neighboring states in number of people fully vaccinated per capita. Gov. Mike DeWine has been a strong and consistent voice for the importance of vaccination and has pushed for increasing access to the vaccine when given the chance.

On the other hand, Ohio has some demographic pressures that may make it hard for it to achieve herd immunity. For one, there is growing evidence that being a Trump voter is associated with passing on a vaccine. This does not bode well for a state where 53% of voters opted for Trump in 2020.

A large demographic of largely non-Trump voters also have been slow to be vaccinated: Black Ohioans. Black Ohioans make up 12% of the state’s population, COVID cases, and COVID deaths, but only 8% of the state’s vaccinated.

These twin problems create a dilemma for the state. It’s hard to imagine the state reaching 70% vaccinated without an uptick in vaccinations among Black and Republican Ohioans.

So what does a public education campaign look like to improve vaccination rates in Ohio? I won’t hazard to pretend I know the answer to this. There seems to be some agreement that public education played a part in the decades-long slide we’ve seen in smoking rates. But this is a problem with a lot of urgency where rapid vaccination could save a lot of lives in the short-term. Let’s hope we have some answers for helping people get vaccinated who haven’t yet decided to.

This commentary first appeared in the Ohio Capital Journal.

All tax cuts are not created equal

At the federal and state level, in governments run by both Republicans and Democrats, policymakers are cutting taxes. The federal American Rescue Plan, passed with no Republican votes, featured one of the largest one-year tax cuts in modern U.S. history. The Ohio House’s Republican-backed state budget bill features a 2% income tax cut across the board.

Part of this bipartisan consensus around tax cuts owes to economic conditions and part owes to ideological considerations. On the rebound from a sharp recession, both parties are interested in jump-starting the economy with cash while also supporting families and businesses struggling due to social distancing measures.

Meanwhile, policy recommendations coming from leading wonks at prestigious research institutions to celebrity political candidates have extolled the virtue of cash as a tool for alleviating poverty and providing flexible support for families in the 21st century.

Looking at these two plans, however, the divide between Republican and Democratic administrations becomes clear. Despite prominent Republicans like Mitt Romney, Marco Rubio, and Mike Lee backing pro-poor cash programs, federal polarization still led them to “no” votes on the American Rescue Plan. At the state level, there is more crossing the aisle: Democrats were split on their votes for the state budget, though many who voted for it were likely more drawn to the inclusion of school funding reform than the income tax cut.

While the American Rescue Plan directs funds to low-income households, the Ohio House tax cuts accrue more heavily to high-income households. This is because the Ohio House’s budget is more interested in reducing state reliance on income tax overall.

This isn’t necessarily bad policy. Income taxes tend to be higher in the United States than in most developed countries, which rely much more heavily on taxes on goods and services. The U.S. in fact taxes goods and services lower than any OECD country. 

This may seem counter to our understanding of Europe since income taxes impact the poor less than sales taxes, but sales taxes distort the economy less than income taxes. Coupled with payments to low-income families, a high-sales tax, low-income tax scheme can balance equity and efficiency goals effectively.

For instance, the Legislative Service Commission estimates the income tax cut in the House budget will reduce revenues by $380 million over the next two years. In 2019, my firm estimated that a 10% federal match refundable state earned income tax credit (a tax cut targeted toward low-income working families) would cost about $210 million a year, which would amount to $420 million over two years.

This is in the same ballpark as the House cut in size, but with an average of $250 going to each low-income worker compared to the $0-1 tax cut cited to accrue to poor and low-income families under the current plan. Thus, an earned income tax credit expansion could reduce income taxation while simultaneously promoting equity goals.

It’s easy to characterize tax cuts themselves as good or bad, but in today’s current political environment, tax cuts are a consensus tool for improving the economy and promoting equity. The question is what kind of tax cuts we want, and the economic evidence available to us tells us that all tax cuts are not created equal.

This commentary first appeared in the Ohio Capital Journal.

Most Ohio economists agree zoning reform would reduce housing costs

In a survey published by Scioto Analysis this morning, 22 of 26 Ohio economists agreed that less rigid residential zoning codes in Ohio municipalities would reduce future cost of housing.

Economists who agreed with the statement pointed to single-family zoning and minimum acreage requirements as drivers of higher pricing, though said they could lead to higher quality of housing, too. None of the 26 economists disagreed with the statement, though four were uncertain, noting housing costs have many drivers and that reducing zoning restrictions will only drive costs down if there is demand for smaller and multi-family housing.

Economists were split on whether less rigid residential zoning codes in Ohio municipalities would reduce levels of residential segregation, with 12 agreeing with the statement and 13 uncertain or disagreeing. Those who agreed said it could reduce income and class segregation while those who were uncertain wondered about demand, rigidity of current regulations, and whether segregation reduction would extend beyond income.

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.

If you would like to suggest a question for a future Ohio Economic Experts Panel, email your ideas to panel@sciotoanalysis.com.

Equality and Efficiency: Public Policy's "Big Tradeoff"

The summer before grad school, we were assigned nearly a dozen books for optional summer reading. Of course, me being the bright-eyed and bushy-tailed future grad student I was, I read book after book, trying my best to immerse myself in the world of policy analysis before moving to California to study it full-time. 

Some of the books were memorable, some I breezed through. I recall reading Bury the Chains, a journalist’s take on the worldwide movement in the 19th century to end slavery. I also recall the book Exit, Voice, Loyalty, a book about the different ways that consumers can “let themselves be heard” in the marketplace.

The book that had the biggest impact on me that summer, though, was Arthur Okun’s Equality and Efficiency: the Big Tradeoff. Published just five years before his untimely death of a heart attack at age 51, Okun’s Brookings Institution essay ruminates on the challenge policymakers face in balancing the two major goals of economic policy.

One of the things I found most convincing in Okun’s book was his insistence on the importance of balance. At the time I was an organizer and admittedly saw the public policy world as a zero-sum game. Doing high school debate and being the competitor I was, I saw the public policy world as one of winners and losers, where one person’s gain was necessarily another’s loss. Okun saw it differently. He saw the public policy world as one in which competing social goals had merit and the real challenge was figuring out how much of each outcome was “best” combination for society.

His most famous example of this is what he calls the “leaky bucket” thought experiment. He characterizes a redistributive program as taking resources from one person and giving them to another. Along the way, resources will be lost to both parties through administrative costs, deadweight loss, or other costs imposed by the program. So a redistributive program can be seen as a leaky bucket that takes water from one well to another, losing water along the way. 

The thought experiment he poses is as follows: how much water would you be willing to lose from the bucket before you determined it wasn’t worth using the bucket in the first place?

Okun wagers most people would not tolerate 100% leakage (all the redistribution evaporates before it gets to the least well-off) and most people would agree to use a 0% bucket (zero administrative cost, zero deadweight loss, all the money redistributed goes to the less well-off). He says if you don’t agree with both of those, you’re an ideologue and this reasoning will not make sense to you. But most people are somewhere in between.

This reasoning opened me up to the world of policy analysis. It’s a world of tradeoffs, a world where there’s always a hidden cost, an unintended consequence. And it’s up to the policy analyst to help the policymaker understand what those are.

But that latter point matters, too: if we can find situations where there are win-wins, we should implement those policies.

I wonder if we are coming into an era where people are starting to embrace this logic that Okun put forth almost fifty years ago now. I wonder if early childhood and child allowance policies combined with what we’ve learned about child development could be something that could both advance equity and grow the economy. We still have time to find out, but Okun may just be smiling down on us these days.

The "Other Epidemic" of Opioids Rages On

Last week, the Ohio Department of Mental Health and Addiction Services announced $13 million in new grants awarded to community organizations trying to reduce opioid overdoses in the state. That’s right, another epidemic is still raging while we tap the “refresh” buttons on our browsers hoping for our COVID-19 vaccination appointments.

According to the most recent data from the CDC, about 5,000 Ohioans died from drug overdoses from September 2019 to August 2020. This is nearly 14,000 less than died from COVID-19 in the state so far, but would still put drug overdoses in the top ten causes of death in Ohio in 2017, the year we have the most recent data for.

Also concerning is that drug overdoses are up in Ohio. While the state is still a few hundred annualized deaths below the drug overdose peak in 2016 and 2017, recent overdoes are up from the recent trough of 4,000 annualized deaths in 2018.

The CDC has sounded the alarm on the increase in overdose deaths that has coincided with the COVID-19 pandemic. Whether this is a result of economic uncertainty, widespread social isolation, or a sort of co-occurrence with other health phenomena is yet to be determined, but deaths are certainly up.

Social distancing provides new challenges for people seeking treatment as well. The best practice for treatment of opioid abuse is medication assisted treatment. But due to the addictive nature of medications used to wean people off painkiller and street drug addiction, effective medications like methadone and buprenorphine can only be disbursed daily or weekly. This means people needing treatment must go for in-person meetings every day or once a week in order to get the treatment they need.

The problem with a treatment like this should be obvious even outside of a global pandemic marked by social distancing. But it is made even harder under the circumstances of the past year.

So what solutions are there to this problem? Well, this is a tough question to answer. Medication assisted treatment is the best tool we have for treating opioid addiction and preventing overdoses. Some states, like Vermont, have created effective statewide treatment systems that connect patients with the kind of treatment they need and make the geography meet the patient where her need is, not the other way around.

Ultimately, though, we want to get to the point where we are preventing opioid addiction rather than just treating it after the fact. The limitation we face here is that we still don’t know what it is that is causing opioid addiction. Some of the most cutting-edge research on the opioid epidemic seemed to suggest that prescription prevalence was the biggest driver of opioid deaths. In this case, prescription drug monitoring programs should have made a dent in opioid deaths.

And maybe they have. There is a distinct possibility that we haven’t risen above 2017 overdose death numbers because of prescription drug monitoring and other steps that have been taken to reduce the supply of addiction painkillers. But we’re still seeing persistent death numbers.

It will be interesting to see if the American Recovery Act has any impact on death rates. Maybe the old “deaths of despair” narrative has more to it than we realized. If so, injecting a bunch of money into households could hold back these deaths. Then again, we might have dug ourselves in so deep with this current epidemic that there will be little attention paid to the other one, despite the work community groups continue to do to reduce drug overdoses across this state.

This commentary first appeared in the Ohio Capital Journal.

You can’t solve problems without proper problem definition

Public policy is supposed to solve problems. This means that the first job of a policy analyst is to understand what problem a policy is trying to solve.  

Problem definition can be overlooked at times but is a crucial part of the policy analysis process. This step not only helps an analyst understand what a policymaker is trying to do with a policy, but also helps the policymaker understand what she is trying to accomplish with it. Problem definition can also be the first step toward validating a policy or even opening the discussion for a policy alternative the policymaker wasn’t anticipating at first.

The first step in the policymaking process in Eugene Bardach’s A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving is problem definition. Bardach underscores some key elements of the problem definition process and offers guidance for policy analysts trying to improve their problem definition work.

First, Bardach suggests analysts think of deficit and excess when defining a problem. Specifically, he suggests using the word “too.” We do this all the time at Scioto Analysis: “there is too little social welfare as defined by the Genuine Progress Indicator,” or “there is too much poverty in the state of Ohio.” By defining a problem as a deficit or excess, you both make it clear what policy is trying to improve and you lay the groundwork for rigorous analysis of the problem.

Past deficit and excess, Bardach also suggests making the definition evaluative, or defining what makes a problem rise to the level of public concern. A classic way to deal with this is by defining a market failure, but this can also be done by identifying a classic social ill or appealing to the authority of the public body you are doing the evaluation for, usually laid out in law.

One special type of problem definition Bardach highlights is that “uncertainty” is the problem that evaluation addresses. Bardach says this is of particular interest when evaluating a program that already exists because the data is already there—what the analyst must do is reduce the amount of uncertainty—or certainty!—that a program is “working.”

Building on the idea of deficit and excess, problem definition can lay the groundwork for rigorous analysis if the analyst can quantify the problem. While some analysis can be done qualitatively, quantification can provide guidance to policymakers trying to set budgets or evaluate alternatives with significant economic components, which there are no shortage of in the policy world.

Part of the problem definition process is helping a policymaker take a step back and look at root problems a policy is trying to solve. In this case, diagnosing a condition that causes a problem can be a helpful tool. For instance, a policymaker might be considering capping interest rates at payday lending establishments because “too many people are going into debt due to payday lending interest rates.” If the real problem, though, is that “too many people are going into debt,” alternative policy options such as making EITC payments monthly or providing check cashing services at post offices start to arise that may be more effective at solving the root problem.

When it comes to problem definition, sometimes the problem itself is the risk or odds of an outcome occurring. When it comes to policy around nuclear meltdown, there are certainly not too many nuclear meltdowns in the state of Ohio, but the risk of one may be too high. Low-cost interventions to reduce that risk might be worthwhile even with lack of a live problem.

Similarly, sometimes a policymaker asks an analyst to work on hypothetical problems, like current procedures not being efficient. Inefficiency only exists if a better alternative exists that is more efficient. Thus, sometimes a problem needs to be stated as a hypothetical until the analysis is completed. 

While policy analysis is built for providing information to a policymaker, it should not stop at the imagination of the policymaker. Sometimes the analyst should be in the business of identifying latent opportunities. This means seeing what the policymaker is trying to do and bringing a new perspective on the problem to light. If this speaks to the policymaker, it could lead to innovative new policy. I expect this is what happened with the American Recovery Act’s inclusion of groundbreaking child poverty provisions. Maybe Joe Biden didn’t go into this policymaking process thinking about child poverty, but someone convinced him it was a problem that was intertwined with the larger economic problem presented by COVID-19, and it became a centerpiece of the bill.

Also important is to avoid common pitfalls in problem definition. Don’t write the solution into your problem definition: keep it focused on the real problems people are experiencing. Don’t accept causal claims advocates are making about the problem too quickly. Don’t ignore the context of the problem. The problem definition should be narrow enough to say what the problem is and how we can find out the answer without saying what the answer is: it is a framework, not a conclusion.

Last, understand the problem definition process is iterative. Policy analysis works best with consistent communication between the analyst and the policymaker. During this communication, the question can change. Don’t be so married to a problem a policymaker asked you about two years ago that you don’t pay attention to the one she is asking you about today. She likely has a vote about it coming up and needs your guidance now.

There is a reason A Practical Guide for Policy Analysis is taught in public policy schools across the country: Bardach’s guidance is relevant to policy analysis and problem solving in general. And in order to solve a problem, you need to understand what that problem really is. Problem definition provides a framework for doing just that.

Recreational cannabis could raise hundreds of millions in new revenue

In November of last year, Arizona, Montana, New Jersey, and South Dakota all legalized recreational use of cannabis. While reasoning for legalization of recreational cannabis range from racial justice to economic growth, one benefit that has many state legislators interested is tax revenue.

Last year, each state that had legalized recreational cannabis raised at least $20 million in revenue from state taxes, with California’s haul topping $1 billion. If Ohio’s state revenue as a function of its total population were in line with other states, Ohio would have brought in about $300 million in recreational cannabis revenue in 2020.

There is a range of revenues being raised by states, though. While Illinois’s 13 million people raised about $52 million in revenue, Washington’s 8 million people raised $470 million. Ohio’s revenue could range from $50 million to $600 million depending on the size of the market for cannabis consumption and the size of the tax.

In FY2020, the state raised a little over $100 million in alcohol and liquor gallonage taxes and over $900 million in cigarette taxes. The $50 million to $600 million range seems reasonable given the range of revenues being raised for similar taxes right now.

Let’s say the state could raise $300 million with legalized recreational cannabis. What could we buy with $300 million?

According to the Legislative Service Commission, we could fund 37 state agencies for a year for $300 million. Alternatively, we could spend it all on large agencies, like funding the entire public works commission or both the Development Services Agency and the Department of Natural Resources with one budget line item.

This line item would only amount to a little over 1% of the state budget, so it’s not like the state could build its budget on the back of Mary Jane. But that is not such a bad thing: Excise taxes like those on cannabis can be quite volatile, so planning a state budget around an item like this could be setting a state up for corrections along the way and difficult fiscal planning.

Additionally, adding a new revenue line item can make the entire revenue picture more predictable. This is why we diversify investments: The more sources that function different from one another we have, the more we can stabilize our overall financial picture.

Cannabis revenue could even help during a recession. If cannabis sales are strong during a recession, as some analysts believe they are likely to be, then cannabis revenues could help cushion the blow during a recession, which is a period where state revenues are hit especially hard.

There are reasons to worry about cannabis as a revenue source. Besides volatility, excise taxes tend to be regressive, so they can be counterproductive toward the goal of reducing inequality. This means that a new excise tax might be well paired with an earned income tax credit expansion or some other low-income benefit to offset this regressivity the way the 2019 gasoline tax expansion was offset.

Revenue is only one in many considerations policymakers must weigh when deciding whether to legalize recreational cannabis. While public health and safety considerations must be weighed as well, raising hundreds of millions of dollars is not a bad bonus benefit.

This commentary first appeared in the Ohio Capital Journal.

25 of 29 Ohio Economists Agree Low-Income Stimulus More Cost-Effective than Broad Stimulus

In a survey published by Scioto Analysis this morning, 25 of 29 Ohio economists agreed that targeting checks at households making less than $75,000 per year would be more cost-effective at boosting the economy than providing checks to higher income households as well.

Economists who agreed with the statement said that lower-income households are more likely to spend stimulus payments rather than save them. They also acknowledged the complexity and difficulties that come with targeting funds. Of the four economists who did not agree with the statement, comments focused on priorities of these payments, suggesting relief, savings, and response can be more important than cost-effectiveness of economic stimulus.

Respondents were more split on a question in the survey asking whether stimulus should focus on keeping low-income individuals and families safe rather than on boosting current economic activity. 15 economists agreed with the statement and 12 disagreed, while only two were uncertain. In comments, however, both those who agreed and disagreed with the statement said the two goals can go hand in hand.

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.

If you would like to suggest a question for a future Ohio Economic Experts Panel, email your ideas to panel@sciotoanalysis.com.

The "Policy Wheel" Model of the Policy Process

Policy analysis. Policy implementation. Policy evaluation. These are phrases we hear thrown around a lot, sometimes sloppily, and sometimes making us feel like there is no coherent connection between these different concepts.

Policymaking in a democratic society is inherently sloppy. Decision-making processes are distributed and a coherent, “logical” system does not necessarily describe how policy is created and crafted over time. That being said, we can still use a model to make sense of these concepts from a design perspective.

One model I particularly like is the “policy wheel.” This model characterizes policy development as an iterative process that starts with problem definition then moves on to analysis, implementation, evaluation, and then back to the start again with a new iteration of problem definition. The diagram below is a slide I was exposed to in a class during my introduction to policy analysis course in graduate school taught by Mia Bird, an assistant adjunct professor at UC Berkeley’s Goldman School of Public Policy. I still use it today.

In this model, the steps of “problem definition” to “recommendation” all comprise policy analysis as characterized in Eugene Bardach’s A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving.

A rational policymaking process starts with problem definition: understanding what problem demands the need for the public sector to act. It then moves through the steps of construction of alternatives, analysis of these alternatives to see what their impacts would be, then recommendation to policymakers informed by this analytical process.

These four steps are the domain of the policy analyst. The step of “political passage,” however, is the domain of the policymaker. While political feasibility is a classic criteria of policy analysis, analysts rarely have a better understanding of political reality than policymakers themselves. It is in this step that policymakers contend with the competing interests of a democracy and craft a policy with at least some information provided by the previous policy analytic steps.

Next comes implementation. This is the step in the hands of the administrators and program staff. Implementation is the “doing” of policy, and is a step in the policy process all on its own. A number of different policy decisions are being made every moment that impact the outcome of the program, but this is the part of the policy process people are most closely exposed to: the people who process your tax forms, serve you at the DMV, pull you over for speeding. Decisions made at the policy analysis and policy passage stages impact the effectiveness of implementation and implementation is an animal in itself, with decisions being made every day that impact the effectiveness of the policy.

The final step in the policy wheel is evaluation. This is the domain of the program evaluator: the professional with the unenviable task of answering the question “does this work?” The evaluator collects data from the implementation process and uses it to determine if the policy is having the desired effects. This information is extremely valuable as the process begins again, this time incorporating these lessons learned.

I find this model an extremely helpful way to understand how policy analysis, politics, implementation, and evaluation work together to make better policy. Yes, it is a model, so it is imperfect, but it gives us an idea of what the policymaking process looks like at its best. I hope you will find this model as helpful as I have.