Why air conditioning in schools matters

One of the main reasons I love living in Minneapolis, Minnesota is that it is often colder than most other parts of the country. I personally prefer fall colors and the thrill of winter sports to sandy beaches and the ocean breeze. 

This year, however, the summer heat has stuck around much longer than it normally does. Only six days into September we have had four days where the high temperature has been at least 90 degrees. For reference, last year there was only one day in September that met that mark. 

As someone who lives in a house that doesn’t have air conditioning, this made the holiday weekend much less pleasant.

My discomfort aside, the fact that a heatwave of this magnitude has hit the Midwest this late in the year is a troubling sign. One of the main reasons we should be worried is that students are coming back to schools that have historically been able to get by without AC during this time of year.

A report from the US Government Accountability Office found that in 2020, over 40% of school districts needed to update or replace HVAC in at least half of their schools. 
High temperatures are more than just an inconvenience for students. Studies have shown that an increase in the number of hot days can decrease test scores and overall academic achievement. 

Of particular concern is how hot days disproportionately affect minority students because they often attend schools in poorer districts with less funding. This means that as our climate continues to heat up, we might see gaps in educational attainment widen unless something is done. 

Also of concern is when summer temperatures begin at the end of the school year when students are taking final exams. One study from 2016 found that students were 11% more likely to fail an exam if they took it on a 90 degree day compared to a 70 degree day. 

Policymakers should be concerned about the temperatures students are exposed to. It is a major financial investment, but in the face of climate change, public schools across the country will need to improve their air conditioning systems or suffer worse outcomes for children. Temperatures are going to continue to increase, and a larger portion of the school year is going to require cooling for students to get the full benefit of their education. 

Air conditioning is also going to be required to keep students safe during the day. The worst case scenario would be if students began experiencing forms of heat related illness such as heat exhaustion or heat stroke during the school day.

This is not to suggest that schools failing to install air conditioning is going to necessarily lead to poor health outcomes, but it does make the margin for error around student health smaller. At the very least, this will require teachers and other school personnel to keep an eye out and make sure students have enough access to water and appropriate clothing. 

The reality of the next few decades is that average temperatures across the world will rise. All across the world, people are going to have to adapt to hotter days. Schools present an interesting public challenge because their schedule has historically kept them safe from the worst of the summer heat. Policymakers need to understand that this gap exists and work to close it quickly.

How to apply behavioral economics to policy analysis

Earlier this year, the National Academies of Science, Engineering, and Medicine released a new report detailing how insights from behavioral economics can be applied to a policy context. 

Behavioral economics is a sub-branch of economics that focuses on understanding why humans make the choices they do, specifically in situations where classical economic models fail. Sitting at the intersection of classical economics and psychology, behavioral economics is especially suited for quantitatively measuring seemingly irrational actions.

One of the key takeaways from the report is five behavioral principles that the National Academies identified as having a strong influence on people’s decision making. Understanding these principles is key to designing good policy options. 

Limited Attention and Cognition

Humans only have a limited ability to process information. This is a problem for classical economic models that often assume that all parties have perfect information and are perfectly rational. 

For policy analysts, this means we should be careful when using research that relies on individuals' attention and cognition, as the results might not hold in a new context. Policymakers should attempt to focus on policies that are as simple as possible and don’t require a great deal of understanding in order to be effective. 

One example of this is the market for health insurance plans. In theory, it might seem optimal to have a massive amount of options so everyone can tailor their plan to meet their specific health needs. But often consumers do not have the time or energy to fully understand different plans and they end up with sub-optimal outcomes.

Inaccurate Beliefs

People make mistakes. We might mistake spurious correlations as causal trends, misread a question on a survey, or we might over/underestimate the severity of a problem. This is often the result of our limited attention and cognition, but the result is that sometimes it is worthwhile for policies to come with education in order to make sure everyone is on the same page.

For example, some people may overestimate the probability of dying in a terrorist attack and underestimate the probability of dying in a car crash. This can lead to a market failure where people were spending more resources than they need to prevent terrorist attacks and less resources preventing car crashes. 

Present Bias

People tend to focus on what is in front of them. It is much harder to fully understand the effects of a policy if it takes years for them to come into place. In policy analysis, we partially represent people’s preference for the short term by discounting future benefits. 

Still, discounting relies on the assumption that there is some uncertainty about the future that we need to price into our estimates. Present bias implies that people tend to prefer short term rewards beyond what would be optimal given their preference for risk. 

It is important that policymakers take a step back and see the bigger picture. Some policies like early childhood education don’t have payoffs until generations later, but their impacts can be so massive that they should still be prioritized. 

Reference Dependence and Framing

Humans tend to make risk decisions based on a particular reference point rather than evaluating all possible options. For example, a policymaker might believe the best way to improve test scores in a school might be to increase the number of teachers, while missing a more creative and effective solution like ensuring students have enough food to eat outside of school hours. 

When discussing policy options, both analysts and policymakers need to be careful that they are exploring all possible alternatives. 

Social Preferences and Social Norms

People tend to make decisions that conform with social norms. Asking people to break social norms is very difficult, and would presumably require more effort than asking people to conform. 

From a policy perspective, this suggests that we should look for policies that are designed in such a way that they either align with social norms, or create new norms. For example, if we want to encourage people to recycle, then it would probably be more effective to drop off bins at every house as opposed to making them free to those who ask. 

Policymakers and analysts need to make sure that they are considering behavioral economics each time they approach an issue. Doing so will help us design more effective and efficient policies, as well as making it more likely that people will respond to policies in a predictable way.

How much does a ton of carbon cost?

The social cost of carbon is probably the most important statistic in the economics of climate change.

Estimating the social cost of carbon is an ambitious undertaking. Using projections for future emissions based on population, economic growth, and other factors, economists attempt to estimate how temperature increases and sea level rise will impact agriculture, health, energy use, and other social impacts in the future. They then monetize these impacts and discount them to present dollars and come up with a single estimate of the social cost of the release of a ton of carbon into the atmosphere.

This leads to a single number that tells us how much carbon emissions cost our economy.

This number is important because regulators use it to estimate the benefits of federal interventions that reduce carbon emissions. This means that a higher social cost of carbon will lead to more policies being deemed to have net economic benefits and a lower social cost of carbon will lead to more policies deemed to have net economic costs.

The social cost of carbon is also the implied efficient price for a carbon tax, so it has direct relevance for policy design as well.

These two reasons, the difficulty of calculating and the public policy importance of the measure, have led to a number of different estimates of the social cost of carbon. Below are some of the estimates that have existed over the years.

$1

The Trump Administration estimated the social cost of carbon could be as low as $1 per metric ton of carbon emitted. The estimate the Trump Administration made was based on domestic impacts alone, ignoring international impacts. While this is not an analytically unsound way to calculate the social cost of carbon, it does overlook a clear political problem with climate change: collective action. 

The goal of the Paris Agreement was to get the international community to get on the same page about carbon emissions. This is because everyone in the world suffers if carbon emissions are not abated. Endorsing a social cost of carbon so low was a message rejecting the notion that the United States had any intention to cooperate with the international community in abating carbon emissions and reducing the severity of global climate change.

$37

The Obama Administration was the first federal administration to officially put a price on carbon emissions at $37 per metric ton in 2015, with the value increasing over time. This number was groundbreaking as the first social cost of carbon adopted by a federal administration, but was soon replaced by the Trump Administration estimate.

$51

The recent estimate of the social cost of carbon from the Biden administration was $51, using similar methodology to the social cost of carbon estimated by the Obama administration. This was a substantial change from the Trump Administration number but still on the low end of what mainstream climate economists were estimating at the time.

$190

The current proposal from the Biden Administration brings the social cost of carbon closer to academic estimates of the social cost of carbon. While this estimate is less than a year old, it stands as the highest estimate of the social cost of carbon by a federal administration. This number brings the estimate closer to a September 2022 article in Nature that estimated the social cost of carbon at $185 per metric ton of CO2.

$305

Some estimates of the social cost of carbon in the academic literature exceed $300. A recent study put its estimate at $305-312 per metric ton of carbon dioxide.

On the opposite side of the Trump Administration figure, a high social cost of carbon implies a responsibility for the United States to be a leader in curbing carbon emissions. Some could see this as the United States taking on more of its responsibility than it should, while others could see it as the United States taking its part in ameliorating a global problem.

If a federal or state administration puts the social cost of carbon at $1 or $305, it can have a big impact on public policy. A direct tax on carbon of $1 per metric ton of carbon dioxide versus $305 per ton would have drastically different impacts on the economy. And the indirect impacts of evaluating regulations under these different costs could be large as well. These estimates matter and care should be taken to make sure that we have a good handle on the true cost of carbon emissions to the economies of future generations. 

Analyst perspective: who really pays for taxes?

In our work as policy analysts, we rely heavily on some of the fundamental theories of economics in order to determine the value of impacts. This has recently come up in a research project we are currently working on, where we need to estimate the elasticity of demand for a good in order to understand what the effects of an excise tax will be. In particular, we are looking at the market for recreational marijuana.

Briefly, the elasticity of demand (or supply) is a numerical measure of how much effect a change in price has on the quantity demanded. For example, if a 1% increase in the price leads to a 2% decrease in quantity demanded, then we say a good has a demand elasticity of -2. 

There are many important results that we can derive from elasticities, but I want to focus on how they interact with taxes. Consider a competitive market for a good that we want to tax:

We can see in our simple setup that the demand curve is much steeper (more inelastic) than the supply curve. Intuitively, this means that changes in price have little effect on the quantity demanded. Conversely, the supply curve is quite flat, suggesting that a small change in price would have a large effect on the quantity supplied. In the above picture, the new tax we are adding to this market is represented by the vertical dotted line, often called the tax wedge. 

Because demand is more inelastic than supply in this market setup, the consumers of this product will have a higher tax incidence. In other words, a larger percentage of this tax will get passed onto them. If we assume that this is a flat $10 tax per item sold, then this tax might  cause the price consumers pay to rise by $8 (the suppliers eat the other $2 via lost revenue).

Who ends up paying for taxes is an interesting question in its own right. In our forthcoming cost-benefit analysis of recreational cannabis legalization in Ohio, this matters to us because we need to fully understand how the proposed excise tax will impact consumer surplus.

As a reminder, consumer surplus represents the difference between the cost of a good in a market and people’s willingness to pay for that good. If people are willing to pay large amounts, but the market price for a good is very cheap, then there is large consumer surplus. People are getting a lot of value for the price they pay. 

In our model for the benefits of legalizing recreational cannabis, one of the major components is going to be how much consumer surplus is generated in a regulated and taxed market. In order to accurately estimate this, we will need to know about the elasticities in our market so that we can accurately assign the tax incidence. 

In practice, this is going to require empirical data. There are econometric methods for estimating supply and demand curves, and because many other states have legal cannabis markets we should have some data to work with. 

Hopefully, we can accurately predict the shape of the recreational cannabis market in Ohio. Then, it will be up to the voters to decide whether they want this market to exist in November.

Three steps for analyzing equity in public policy

Earlier this month, Scioto Analysis released an analysis we did in partnership with the Center for Climate Integrity on the cost of climate change in Pennsylvania.

In this study, we built on the work we did on our Ohio cost of climate change report to estimate how climate change will impact different types of communities.

A lot of lip service is paid to “equity” in public policy analysis these days. Equity is one of the “big three” criteria for analyzing public policy along with effectiveness and efficiency. But unlike effectiveness analysis, which has tools like randomized controlled trials and quasi experimental methods, and efficiency analysis, which has cost-benefit analysis, equity analysis has no go-to methodology for its conduct.

So how do we conduct equity analysis? The steps we took ended up looking a lot like a broader policy analysis. While you could go through the steps of the Eightfold Path to conduct an equity analysis, our approach in this study boiled down to three major steps.

Step 1: Define Criteria

One of the major reasons equity analysis is not as standardized as effectiveness or efficiency analysis is because of the many dimensions equity can be analyzed on. Race, income, sex, rurality, age, education, sexual orientation, geography, employment, immigrant status, language spoken at home, and housing are just a handful of different examples of dimensions of equity.

Criteria should be defined based on (a) what is informative to your client, (b) what you have reliable data on, and (c) what is relevant to the content of the study. 

The former consideration is always paramount in public policy analysis: what will people listen to? When speaking truth to power, an analyst needs to be aware of what her client is interested in and what she will listen to if policy analysis is to be useful.

Also important is whether data is available. A client might be eminently interested in how their policy impacts high-IQ students, but if the data is not available on how those students are impacted by the policy, an analyst is not very useful.

Step 2: Calculate Impacts

This is the “technical” part of the analysis. This phase of equity analysis consists of gathering data and estimating what the range of impacts are for different groups. 

For our Pennsylvania analysis, we had defined municipalities as municipalities of interest based on them having larger racial minority, impoverished, rural, non-English-speaking, or foreign-born populations. We then calculated what these communities’ per-capita costs were compared to the per-capita costs of the average municipality statewide.

Step 3: Communicate Results

Policy analysis requires good communication, and equity is no exception to this. Communication of equity results can demand extra care because of the sensitive political dynamics associated with communities of interest defined by equity categories. Knowing the right language to use around race, income, and gender is tantamount, especially when making sure a client will take this analysis seriously.

Also important is making sure that results are communicated in a way that transparently and clearly shows the differences between equity categories. In our results, we showed the dollar figure difference between communities. This showed how much different communities would have to pay based on the type of community they were.

When all was said and done with this study, we found that high-poverty and rural municipalities would pay more per-capita than the average Pennsylvania municipality. This was a useful insight: it told us something about who will shoulder the burdens of the cost of climate change. And this is just the sort of insight that helps us understand who will benefit from policy interventions.

Ohio economists agree abortion protections will improve outcomes

In a survey released this morning by Scioto Analysis, 13 of 18 economists agreed that women who receive abortion services will have improved economic outcomes, such as higher educational attainment, higher labor force participation, and higher wages. However, there is some disagreement about how large the effect might be. 

Additionally, economists indicated they believed abortion protections in Ohio will spill over into neighboring states like West Virginia, Indiana, and Kentucky, all of which currently have bans on abortion.

The majority of survey respondents agreed that abortion protections in Ohio would likely lead to people crossing the border in order to access those services. Assuming people who receive abortions will have higher economic attainment, this could mean a slight boost in the economies of those neighboring states. 

As Ohio prepares to vote in November on a ballot initiative that would in practice make the majority of abortions legal, these results are an important consideration. Although this is often painted strictly as a social issue, there are important economic considerations that policymakers should be aware of. 
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. Individual responses to all surveys can be found here.

What would recreational marijuana in Ohio look like?

While the conversation about the November election has revolved around abortion protections, that won’t be the only issue Ohio voters decide on. The Coalition to Regulate Marijuana Like Alcohol recently submitted enough signatures to get a vote on recreational cannabis on the ballot.

The proposal, known as the Ohio Marijuana Legalization Initiative, would legalize the cultivation, processing, sale, purchase, possession, and home growth of marijuana for individuals age 21 and up. It would create a state Division of Cannabis Control, which would regulate and license marijuana operators and facilities and would oversee the compliance and standardization of marijuana in Ohio.

The proposal would also tax marijuana sales at 10%, putting funds toward a “cannabis social equity and jobs program” that would support individuals affected by marijuana law enforcement.

Currently, Michigan is the only neighboring state that has a recreational marijuana program. Like Ohio, Kentucky, Pennsylvania, and West Virginia each have medical marijuana programs in place. Indiana is the only state bordering Ohio without a medical marijuana program, though it allows CBD and low-THC products.

If this initiative gets on the ballot and Ohio voters approve it, then Ohio would join Michigan in having a recreational marijuana program with a 10% excise tax. Unlike Michigan’s excise tax, though, which goes toward public schools, transportation, and other local initiatives, Ohio’s would be specifically earmarked for the cannabis social equity and jobs program.

In 2022, Michigan brought in $325 million in excise and sales tax from marijuana sales. Since Ohio has a similarly-sized population to Michigan, it is likely to bring in hundreds of thousands of dollars in revenue as well once its program is up and running.

Besides raising revenue, legalization of marijuana in Ohio would have some other impacts as well.

First, it will almost certainly increase consumption. While many people inside Ohio use marijuana for medical reasons and others purchase marijuana in informal markets currently, full recreational legalization would increase access and would likely lead to more consumption of marijuana.

It also would provide more opportunity for residents of Indiana, Kentucky, Pennsylvania, and West Virginia to purchase marijuana legally, which may lead to more cross-state travel and sales. It could even lead to arrests in those states.

While it is not guaranteed, legalization of sales of recreational marijuana could lead to a reduction in the informal (often called “black”) market in marijuana sales. This could lead to less criminal activity associated with sales and less public costs around arrests and imprisonment.

There are also likely to be public health costs associated with legalization of recreational marijuana. One impact is car crashes. We could see an increase in car crashes due to an increase in driving while under the influence of marijuana. We also may see a decline in productivity as marijuana use may have an impact on the workforce.

Some evidence shows we could also see a reduction in some public health ills. In particular, some states that have legalized medical marijuana use have seen declines in male suicide rates driven by substitution away from alcohol use, a risk factor for suicide.

We don’t yet know which of these effects will predominate and how drastic they will be. My practice Scioto Analysis is currently conducting a cost-benefit analysis on recreational marijuana legalization and should have results in the next couple of months. We look forward to studying this question and seeing what legalization of marijuana will do to the public.

This commentary first appeared in the Ohio Capital Journal.

Spillover effects of early childhood education

Among policy analysts, the Perry Preschool Project is one of the most famous randomized control trials ever undertaken. In the 1960s, over 100 disadvantaged black children in Michigan were randomly selected to receive additional education and support starting at age three.

What makes this study unique is that researchers have been able to follow up with the participants in both the treatment and control groups for decades after the formal program ran its course. This means that we can directly see how this program influenced outcomes like adult wages directly, instead of relying on intermediary effects like school test scores.

What’s even better is that there is robust data not only on the control and treatment groups, but on those peoples’ siblings and children. This makes the Perry Preschool Project not only one of the best studies ever conducted for understanding the effects of early childhood education, but it also makes it one of the best examples of how programs focused on benefiting disadvantaged children can have effects that spillover to nearby children and even the next generation. 

Results from the most recent follow-up survey have been analyzed and published in a new working paper. Today, I want to explain what these effects are, and what the implications might be for related policies.

Intergenerational Effects

The larger of the two spillover effects was how the Perry Preschool Program influenced outcomes for the children of the participants. The way this was measured was by comparing adult outcomes such as employment for the children of participants in the control and treatment groups. 

The researchers found that children of people in the treatment group were more likely to be employed as adults, were more likely to be in good health, they were less likely to be divorced, and perhaps most importantly they were less likely to be arrested. 

Additionally, male children of people in the treatment group were more likely to have a college degree, while female children were more likely to have a highschool degree. 

What's so exciting about these intergenerational effects is that despite not taking place until over 50 years after the intervention, and therefore being subjected to over 50 years of discounting, they still have massive and positive net present benefits. 

Sibling Effects

When exploring the effect that the Perry Preschool Project had on participants' siblings, the researchers chose to limit themselves to a subset of all siblings. Specifically, they only considered siblings that were older than the participants, but not more than 5 years older. 

The justification for this small range is that (1) Younger siblings might experience different outcomes because their parents might act differently after participation in this program (a worthwhile effect to understand but not the effect they were interested in) and (2) Children more than five years older might already be experiencing some of these outcomes. 

The most notable sibling effects are that female siblings of participants were more likely to finish high school and male siblings were less likely to have been arrested. The effect sizes for siblings are smaller than those for children of program participants, but they still make a big difference. 

From a policy perspective, there are a few key takeaways from this research. First, we may be underestimating the value of anti-poverty programs. The intergenerational effects of these projects is enormous, and unless we account for that we are likely not accurately portraying the benefits of many projects. 

Second, we should be aware of who we are enrolling in pilot programs. The total benefits of programs will often spillover into nearby people and communities. On one hand, targeting communities to maximize these spillover effects will likely increase the value of a project, but we must also be careful and understand that if these effects exist, then people or communities with less opportunity for spillover might have smaller effects. 

November vote could give Ohio among the strongest abortion protections in the region

Last week, Ohio voters rejected Issue 1. This was a constitutional amendment put forth by abortion opponents in the state legislature to make it harder for Ohio voters to enshrine abortion protections in the Ohio Constitution.

After this vote, the next big policy decision for Ohio around abortion protections will be the “Ohio Right to Make Reproductive Decisions Including Abortion Initiative,” which Ohio voters will decide on in November.

This initiative will establish a right for Ohio residents to make and carry out their own reproductive decisions. This will include the right to abortion, contraception, fertility treatment, miscarriage care, and continuing pregnancy.

The bill puts specific limits on how the state can restrict this right, in particular only allowing the state to restrict abortion after the point of fetal viability, which is at about 24 weeks. It also specifically prohibits restriction of abortion in any case where abortion is necessary to protect the pregnant patient’s life or health.

Currently, Ohio has a six-week abortion ban on the books which has been frozen by the courts. The current practical limit on abortion is up to 22 weeks of pregnancy, the threshold that existed when Roe v Wade was the law of the land. This means that Ohio would likely have more abortion protections under this new change than it did before the Supreme Court overturned Roe v Wade.

Currently, states bordering Ohio have a range of different laws regulating abortion. According to the Guttmacher Institute, Kentucky and West Virginia have essentially banned abortion in its entirety in their states. Indiana took a similar step this month when legislation was enacted banning essentially all abortions in the state. 

Michigan and Pennsylvania have more protections for abortion rights. Pennsylvania guarantees abortion rights up to 24 weeks of pregnancy and Michigan guarantees up to fetal viability, around the same timeframe. 

So as far as weeks of pregnancy go, adopting this constitutional amendment would put Ohio on the forefront of its neighboring states, using the viability threshold Michigan also has.

I’ll be interested to see what happens to many of the other abortion restrictions Ohio has in place if this amendment is put in place. For instance, Ohio requires two separate visits to a clinic at least a day between. It also requires parental consent, which can pose problems for victims of incest and rape. There also are a number of laws put in place designed to make it harder for clinics to operate.

The amendment requires that the state uses the least restrictive means to advance the individual’s health in accordance with widely accepted and evidence-based standards of care. This would likely lead to many of Ohio’s abortion restrictions being struck down.

Overall, this constitutional amendment would give Ohio some of the strongest protections for abortion rights in the region. This could be a lifeline for not only Ohioans, but also people living in Indiana, Kentucky, and West Virginia would need access to abortion care. In November, we will find out if Ohio is ready for a right to abortion.

This commentary originally appeared in the Ohio Capital Journal.

New research: the cost of climate change in Pennsylvania

For the past year, Scioto Analysis has been working with the Center for Climate Integrity on a project estimating the financial costs that local governments will incur as a result of climate change. The study was released last month and has already been getting some coverage in the Pennsylvania media.

The study looked at the costs associated with eight different categories of infrastructure that would be impacted by rising temperatures, increased precipitation, and rising sea levels. An online visual representation of these costs estimated by engineering firm Resilient Analytics can be found here.

We contributed the equity and budget analysis to this project, helping explain who is going to be bearing these costs and providing some context for what these costs might actually feel like in a municipal budget. Here are some of our key findings and what they mean for Pennsylvania.

Rural municipalities have the highest per capita costs

Despite incurring lower total costs, rural communities across Pennsylvania are going to face higher per-capita costs compared to the statewide average. 

This is mostly due to the fact that rural municipalities have smaller populations spread out across a large area. This often means that a smaller number of people are responsible for maintaining a large area of roads. 

Road related costs ended up being some of the most significant drivers of spending across the state. Increased heat and precipitation will necessitate greater spending on road maintenance and the increased risk of landslides (a problem that is particularly prevalent in rural, Western PA) will lead to significant spending on prevention and road repair. 

All of this adds up to people living in rural municipalities needing to spend a greater amount on climate change adaptations. 

Communities subject to sea level rise have large racial minority populations 

Because the Delaware river is a tidal river, people who live along its banks are going to experience the effects of sea level rise despite not living on the ocean. As a result, those people are going to need to build preventative infrastructure to hold back the rising water in order to keep their homes on dry ground. 

In Pennsylvania, the municipalities projected to be affected by sea level rise have much higher poverty rates, are less white, and have larger immigrant populations than the rest of the state. 

Compared to Pennsylvania as a whole, there are only a small number of municipalities that are going to feel the effects of sea level rise. However, these costs represent one of the greatest examples of climate inequity in the state. The populations that are going to be exposed to sea level rise have historically been marginalized, and will not have the capacity to adapt that other municipalities might. 

Four municipalities will experience severe fiscal stress

Climate change will be costly for everyone in Pennsylvania, but for a select few municipalities the costs will be nearly impossible to bear. 

Our measure of severe fiscal stress is based on our research of the Census Bureau’s Annual Survey of State and Local Government Finance. What we found was that over the past 20 years, local government budgets have increased by roughly $1,000 per person per year. 

This means that if a municipality is projected to have per capita annual costs of $1,000 by 2040, then they would essentially need to commit the entirety of their budget growth to climate adaptations.

These municipalities will have no money to offer raises for city employees over the next 17 years, no ability to renovate old buildings. If some other emergency occurs, the city would have no capacity to respond. 

Thankfully, only four municipalities across the state have per capita costs this high. Still, policymakers need to be aware of these costs, and understand just how debilitating they could be.