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Graduate School Opportunities Available Through Mercatus

One of the great parts of working at Mercatus is getting to interact with all of the bright and ambitious students that participate in our academic programs. Mercatus offers four unique graduate programs for students interested in political economy and public policy. The training and education that Mercatus provides are one of a kind.

As part of each program students get access to funding, practical experience, and a wide network of passionate, dedicated scholars. Many graduates from each program go on to develop successful careers in academia and public policy. Ninety-two percent of MA Fellowship graduates, for example, receive a job within 9 months of graduation. Whether you’re pursuing a Master’s, PhD, or law degree, there may be something for you at Mercatus.

The four programs and their details are below.  If you’re interested in learning more and applying, check out our website. Deadlines are right around the corner, with the PhD Fellowship deadline approaching at the end of this week.

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Mercatus PhD Fellowship

The PhD Fellowship is a competitive, full-time fellowship program for students pursuing a doctoral degree in economics at George Mason University. PhD Fellows take courses in market process economics, public choice, and institutional analysis and work on projects that use these lenses to understand global prosperity and change.

Students receive an award up to $200,000 (over five years) for full tuition support and a monthly stipend, as well as experience as a research assistant working closely with Mercatus-affiliated Mason faculty. The application deadline is February 1, 2018.

Mercatus MA Fellowship

The MA Fellowship is a tw0-year, competitive, full-time fellowship program for students pursuing a master’s degree in economics at George Mason University in preparation for a career in public policy. Fellows attend readings groups and career development workshops, spend at least 20 hours per week working with Mercatus scholars and staff, and complete a Mercatus Graduate Policy essay.

Students receive an award of up to $80,000 (over two years) for full tuition support and a monthly stipend, as well as practical experience conducting and disseminating research with Mercatus scholars and staff on pertinent policy issues. The application deadline is March 1, 2018.

Mercatus Adam Smith Fellowship

The Adam Smith Fellowship is a one-year, competitive fellowship program for PhD students at any university and in any discipline. The goal of this fellowship is to introduce students to a framework of ideas they may not otherwise encounter in their studies. Fellows meet a few times out of the year to engage in discussions on key foundational texts in the Austrian, Virginia, and Bloomington schools of political economy and learn how these texts may apply to their research interests.

Students receive a stipend up to $10,000 as well as travel, lodging, and all materials to attend workshops and seminars hosted by the Mercatus Center. The application deadline is March 15, 2018.

Mercatus Frédéric Bastiat Fellowship

The Frédéric Bastiat Fellowship is a one-year, competitive fellowship program for graduate students attending master’s, juris doctoral, and doctoral programs in a variety of disciplines. The goal of this fellowship is to introduce students to the Austrian, Virginia, and Bloomington school of political economy as academic foundations for pursuing contemporary policy analysis. Fellows meet a few times out of the year to engage in discussions on key foundational texts and interact with scholars that work on the cutting edge of policy analysis.

Students receive a stipend of up to $5,000 as well as travel, lodging, and all materials to attend workshops and seminars hosted by the Mercatus Center. The application deadline is March 15, 2018.

 

 

State tax refunds and limiting spending growth

This fall eligible Alaskans will be receiving a check of $1,100 from their state government. Although the amount of the check can vary, Alaskans receive one every fall – no strings attached. Other state residents are probably more familiar with IRS tax refunds that come every spring, but this “tax refund” that Alaskans receive is unique. It’s a feature that residents have benefited from for decades, even in times when the government has experienced fiscal stress. Considering the state’s unique and distressed budget situation that I’ve described in an earlier post, I think it warrants a discussion of the fiscal viability of their refunds.

A narrow tax base reliant on volatile revenue sources, restricted funds, and growing spending are all factors that made closing Alaska’s budget gap this year very difficult. It even contributed to pulling down Alaska from 1st in our 2016 ranking of states by fiscal condition to 17th in our 2017 edition. Given this deterioration, it will be helpful to look into how and why Alaska residents receive dividend payments each year. There is no public finance rule that says giving refunds to residents is fiscally irresponsible, but there definitely are better ways to do it, and Alaska certainly hasn’t proven to display best practices.

Another state that we can look at for comparison is Colorado, which has a similar “tax refund” for residents but is structured very differently. Colorado’s Taxpayer Bill of Rights (TABOR) requires that higher than expected tax revenues each year be refunded to taxpayers and acts as a restraint on government spending growth. In contrast, Alaska’s check comes from the state’s Permanent Fund’s earnings that are generated from oil severance taxes each year, and acts more like a dividend from oil investment earnings.

Are distributing these refunds to taxpayers fiscally responsible? I am going to take a deeper look at these mechanisms to find out.

First, Alaska’s refund.

The figure below displays Alaska’s Permanent Fund checks since 2002 overlaid with the state’s revenue and expenditure trends, all adjusted for inflation. The highest check (in 2015 dollars) was $2,279 in 2008 and the lowest was $906 in 2012, with the average over this time period being about $1,497 per person. Although the check amounts do vary, Alaska has kept on top of delivering them, even in times of steep budget gaps like in 2002, 2009, and 2015. The Permanent Fund dividend formula is based on net income from the current plus the previous four fiscal years, so it makes sense that the check sizes are also cyclical in nature, albeit in a slightly delayed fashion behind oil revenue fluctuations.

Alaska’s dividend payments often end up on the chopping block during yearly budget debates, and there is growing pressure to at least have them reduced. Despite this, Alaska’s dividends are very popular with residents (who can blame them?) and probably won’t be going away for a long time; bringing a new meaning to the Permanent Fund’s name.

The Alaska Permanent Fund was established in 1976 by constitutional amendment and was seen as an investment in future generations, who might no longer have access to oil as a resource. Although this may have been decent forward-thinking, which is rare in state budgets, it does illustrate an interesting public finance story.

Alaska is a great example of a somewhat backwards situation. They generate high amounts of cash each year, but because of the way many of their funds are restricted they are forced to hoard much of it, and give the rest to citizens in the form of dividends. If a different state were to consider a similar dividend before dealing with serious structural budget flaws would be akin to putting the cart before the horse.

Luckily for Alaskan dividend recipients, there are many other areas that the state could reform first in order to improve their budget situation while avoiding cutting payments. As my colleague Adam Millsap has recommended, a fruitful area is tax reform. Alaska doesn’t have an income or sales tax; two of the most common sources of revenue for state governments. These are two potentially more stable sources of income than what the state currently has.

How does Colorado’s “tax refund” compare?

Colorado’s Taxpayer Bill of Rights (TABOR) has a feature that requires any tax revenue growth beyond inflation and population growth be refunded to taxpayers. It was adopted by Colorado voters in 1992 and it essentially restricts revenues by prohibiting any tax or spending increases without voter approval.

A recent example of this playing out was in 2014 when the state realized higher than expected tax revenues as a result of marijuana legalization. At the point of legalization, the plan was to direct tax revenues generated from the sale of marijuana towards schools or substance abuse program funding. But because of the higher than expected revenues, TABOR was triggered and it would require voter approval to decide if the excess revenues would be sent back to taxpayers or directed to other state programs.

In November of 2015, Colorado voters approved a statewide ballot measure that gave state lawmakers permission to spend $66.1 million in taxes collected from the sale of marijuana. The first $40 million was sent to school construction, the next $12 million to youth and substance abuse programs, and the remainder $14.2 billion to discretionary spending programs. A great example that although TABOR does generally restrain spending, citizens still have power to decline refunds in the name of program spending they are passionate about.

 

The second figure here displays TABOR refunds compared with state revenues and expenditures over time. Adjusted for inflation, checks have varied from $18 in 2005 to $351 in 1999, much smaller than the Alaska dividend checks. TABOR checks have only tended to be distributed when revenues have exceeded expenses. The main reason why checks weren’t distributed between 2006 and 2009, despite a revenue surplus, was because of Referendum C which removed TABOR’s revenue limit for five years, allowing the state to keep collections exceeding the rule. The revenue limit has since been reinstated, but some question the effectiveness of TABOR given an earlier amendment in 2000 which exempts much of education spending from TABOR restrictions.

The main distinguishing factor between Colorado’s refund and Alaska’s Permanent Fund dividend is that the former also acts as a constraint on spending growth. By requiring the legislature to get voter approval before any tax increase or spending of new money, it implements automatic checks on these activities. Many states attempt to do this through what are called “Tax and Expenditure Limits” or TELs.

The worry is that left unchecked, state spending can grow to unsustainable levels.

Tax and Expenditure Limits

A review of the literature up to 2012 found that although the earliest studies were largely skeptical of the effectiveness of TELs, as time has passed more research points to the contrary. TELs can restrain spending, but only in certain circumstances.

My colleague Matt Mitchell found in 2010 that TELs are more effective when they (1) bind spending rather than revenue, (2) require a super-majority rather than a simple majority vote to be overridden, (3) immediately refund revenue collected in excess of the limit, and (4) prohibit unfunded mandates on local government.

Applying these criteria to Colorado’s TABOR we see that it does well in some areas and could improve in others. TABOR’s biggest strength is that it immediately refunds revenue collected in excess of the limit in its formula, pending voter approval to do otherwise. Automatically refunding surpluses makes it difficult for governments to use excess funds irresponsibly and also gives taxpayers an incentive to support TABOR.

Colorado’s TABOR does well to limit revenue growth according to a formula, rather than to a fixed number or no limitation at all. The formula partially meets Mitchell’s standards. It stands up well with the most stringent TELs by limiting government growth that exceeds inflation and population growth, but could actually be improved if it limited actual spending growth rather than focusing on tax revenue. When a TEL or similar law limits revenues, policymakers can respond by resorting to implementing more fees or borrowing. There’s some evidence of this occurring in Colorado, with fees becoming more popular as a way to raise revenue since TABOR’s passing. A spending-based TEL is more difficult to evade.

Despite its faults, Colorado’s TABOR structure appears to be doing better than attempts to constrain spending growth in other states. The National Conference of State Legislatures still considers it one of the strictest TELs in the nation. Other states, like Arkansas, could learn a lot from Colorado. A recent Mercatus study analyzes Arkansas’ Revenue Stabilization Law and suggests that it is missing a component similar to Colorado’s TABOR formula to refund excess revenues.

How much a state spends is ultimately up to its residents and legislature. Some states may have a preference for more spending than others, but given the tendency for government spending to grow towards an unsustainable direction, having a conversation about how to slow this is key. Implementing TEL-like checks allows for spending to be monitored and that tax dollars be spent more strategically.

Alaska’s Permanent Fund dividend is not structured as well as Colorado’s, but perhaps the state’s saving grace is that it has a relatively well structured TEL. Similarly to Colorado’s TABOR, Alaska’s TEL limits budget growth to the sum of inflation and population growth and is codified in the constitution. Alaska’s TEL doesn’t immediately refund revenue that is collected in excess of the limit to taxpayers as Colorado’s TABOR does, but it does target spending rather than revenues.

Colorado’s and Alaska’s TELs can compete when it comes to restraining spending, but Colorado’s is certainly more strict. Colorado’s expenditures have grown by about 55 percent over the last decade, while Alaska’s has grown approximately 120 percent.

The Lesson

Comparing Colorado and Alaska’s situations reveals two different ways of giving tax refunds to residents. Doing so doesn’t necessarily have to be fiscally irresponsible. Colorado has provided refunds to residents when state revenues have exceeded expenses and as a result this has acted as a restraint on over-spending higher than expected revenues. Although Colorado’s TABOR has been amended over time, its general structure illustrates the effectiveness of institutional restrains on spending. The unintended effects of TABOR, such as the increase in fees, could be well addressed by specifically targeting spending rather revenue, like in the case of Alaska’s TEL. Alaska may have had their future residents’ best intent in mind when they designed their Permanent Fund Dividend, but perhaps this goal of passing forward oil investment earnings should have been paired with preparing for the potential of cyclical budget woes.

Manufacturing employment and the prime-age male LFP rate: What’s the relationship?

Recently I wrote about the decline in the U.S. prime-age male labor force participation (LFP) rate and discussed some of the factors that may have caused it. One of the demand-side factors that many people think played a role is the decline in manufacturing employment in the United States.

Manufacturing has typically been a male-dominated industry, especially for males with less formal education, but increases in automation and productivity have resulted in fewer manufacturing jobs in the United States over time. As manufacturing jobs disappeared, the story goes, so did a lot of economic opportunities for working-age men. The result has been men leaving the labor force.

However, the same decline in manufacturing employment occurred in other countries as well, yet many of them experienced much smaller declines in their prime-age male LFP rates. The table below shows the percent of employment in manufacturing in 1990 and 2012 for 10 OECD countries, as well as their 25 to 54 male LFP rates in 1990 and 2012. The manufacturing data come from the FRED website and the LFP data are from the OECD data site. The ten countries included here were chosen based on data availability and I think they provide a sample that can be reasonably compared to the United States.

country 25-54 LFP rate, manuf table

As shown in the table, all of the countries experienced a decline in manufacturing employment and labor force participation over this time period. Thus America was not unique in this regard.

But when changes in both variables are plotted on the same graph, the story that the decline in manufacturing employment caused the drop in male LFP rate doesn’t really hold up.

country 25-54 LFP rate, manuf scatter plot

The percentage point change in manufacturing employment is across the top on the x-axis and the percentage point change in the prime-age male LFP rate is on the y-axis. As shown in the graph the relationship between the two is negative in this sample, and the change in manufacturing employment explains almost 36% of the variation in LFP rate declines (the coefficient on the decline in manufacturing employment is -0.322 and the p-value is 0.08).

In other words, the countries that experienced the biggest drops in manufacturing employment experienced the smallest drops in their LFP rate, which is the opposite of what we would expect if the decline in manufacturing employment played a big role in the decline of the LFP rate across countries.

Of course, correlation does not mean causation and I find it hard to believe that declines in manufacturing employment actually improved LFP rates, all else equal. But I also think the less manufacturing, less labor force participation story is too simple, and this data supports that view.

America and Italy experienced similar declines in their male LFP rates but neither experienced the largest declines in manufacturing employment over this time period. What else is going on in America that caused its LFP decline to more closely resemble Italy’s than that of Canada, Australia and the UK, which are more similar to America along many dimensions?

Whatever the exact reasons are, it appears that American working-age males responded differently to the decline in manufacturing employment over the last 20 + years than similar males in similar countries. This could be due to our higher incarceration rate, the way our social safety net is constructed, differences between education systems, the strength of the economy overall or a number of other factors. But attributing the bulk of the blame to the decline of manufacturing employment doesn’t seem appropriate.

Many working-age males aren’t working: What should be done?

The steady disappearance of prime-age males (age 25-54) from the labor force has been occurring for decades and has recently become popular in policy circles. The prime-age male labor force participation rate began falling in the 1950s, and since January 1980 the percent of prime-age males not in the labor force has increased from 5.5% to 12.3%. In fact, since the economy started recovering from our latest recession in June 2009 the rate has increased by 1.3 percentage points.

The 12.3% of prime-age males not in the labor force nationwide masks substantial variation at the state level. The figure below shows the percentage of prime-age males not in the labor force—neither working nor looking for a job—by state in 2016 according to data from the Current Population Survey.

25-54 males NILF by state 2016

The lowest percentage was in Wyoming, where only 6.3% of prime males were out of the labor force. On the other end of the spectrum, over 20% of prime males were out of the labor force in West Virginia and Mississippi, a shocking number. Remember, prime-age males are generally not of school age and too young to retire, so the fact that one out of every five is not working or even looking for a job in some states is hard to fathom.

Several researchers have investigated the absence of these men from the labor force and there is some agreement on the cause. First, demand side factors play a role. The decline of manufacturing, traditionally a male dominated industry, reduced the demand for their labor. In a state like West Virginia, the decline of coal mining—another male dominated industry—has contributed as well.

Some of the most recent decline is due to less educated men dropping out as the demand for their skills continues to fall. Geographic mobility has also declined, so even when an adjacent state has a stronger labor market according to the figure above—for example West Virginia and Maryland—people aren’t moving to take advantage of it.

Of course, people lose jobs all the time yet most find another one. Moreover, if someone isn’t working, how do they support themselves? The long-term increase in female labor force participation has allowed some men to rely on their spouse for income. Other family members and friends may also help. There is also evidence that men are increasingly relying on government aid, such as disability insurance, to support themselves.

These last two reasons, relying on a family member’s income or government aid, are supply-side reasons, since they affect a person’s willingness to accept a job rather than the demand for a person’s labor. A report by Obama’s Council of Economic Advisors argued that supply-side reasons were only a small part of the decline in the prime-age male labor force participation rate and that the lack of demand was the real culprit:

“Reductions in labor supply—in other words, prime-age men choosing not to work for a given set of labor market conditions—explain relatively little of the long-run trend…In contrast, reductions in the demand for labor, especially for lower-skilled men, appear to be an important component of the decline in prime-age male labor force participation.”

Other researchers, however, are less convinced. For example, AEI’s Nicholas Eberstadt thinks that supply-side factors play a larger role than the CEA acknowledges and he discusses these in his book Men Without Work. One piece of evidence he notes is the different not-in-labor-force (NILF) rates of native born and foreign born prime-age males: Since one would think that structural demand shocks would affect both native and foreign-born alike, the difference indicates that some other factor may be at work.

In the figure below, I subtract the foreign born not-in-labor-force rate from the native born rate by state. A positive number means that native prime-age males are less likely to be in the labor force than foreign-born prime age males. (Note: Foreign born only means a person was born in a country other than the U.S.: It does not mean that the person is not a citizen at the time the data was collected.)

25-54 native, foreign NILF diff

As shown in the figure, natives are less likely to be in the labor force (positive bar) in 34 of the 51 areas (DC included). For example, in Texas the percent of native prime-age men not in the labor force is 12.9% and the percentage of foreign-born not in the labor force is 5.9%, a 7 percentage point gap, which is what’s displayed in the figure above.

The difference in the NILF rate between the two groups is also striking when broken down by education, as shown in the next figure.

25-54 native, foreign males NILF by educ

In 2016, natives with less than a high school degree were four times more likely to be out of the labor force than foreign born, while natives with a high school degree were twice as likely to be out of the labor force. The NILF rates for some college or a bachelor’s or more are similar.

Mr. Eberstadt attributes some of this difference to the increase in incarceration rates since the 1970s. The U.S. imprisons a higher percentage of its population than almost any other country and it is very difficult to find a job with an arrest record or a conviction.

There aren’t much data combining employment and criminal history so it is hard to know exactly how much of a role crime plays in the difference between the NILF rates by education. Mr. Eberstadt provides some evidence in his book that shows that men with an arrest or conviction are much more likely to be out of the labor force than similar men without, but it is not perfectly comparable to the usual BLS data. That being said, it is reasonable to think that the mass incarceration of native prime-age males, primarily those with little formal education, has created a large group of unemployable, and thus unemployed, men.

Is incarceration a supply or demand side issue? On one hand, people with a criminal record are not really in demand, so in that sense it’s a demand issue. On the other hand, crime is a choice in many instances—people may choose a life of crime over other, non-criminal professions because it pays a higher wage than other available options or it somehow provides them with a more fulfilling life (e.g. Tony Soprano). In this sense crime and any subsequent incarceration is the result of a supply-side choice. Drug use that results in incarceration could also be thought of this way. I will let the reader decide which is more relevant to the NILF rates of prime-age males.

Criminal justice reform in the sense of fewer arrests and incarcerations would likely improve the prime-age male LFP rate, but the results would take years to show up in the data since such reforms don’t help the many men who have already served their time and want to work but are unable to find a job. Reforms that make it easier for convicted felons to find work would offer more immediate help, and there has been some efforts in this area. How successful they will be remains to be seen.

Other state reforms such as less occupational licensing would make it easier for people— including those with criminal convictions—to enter certain professions. There are also several ideas floating around that would make it easier for people to move to areas with better labor markets, such as making it easier to transfer unemployment benefits across state lines.

More economic growth would alleviate much of the demand side issues, and tax reform and reducing regulation would help on this front.

But has something fundamentally changed the way some men view work? Would some, especially the younger ones, rather just live with their parents and play video games, as economist Erik Hurst argues? For those wanting to learn more about this issue, Mr. Eberstadt’s book is a good place to start.

What’s going on with Alaska’s budget?

Alaska is facing another budget deficit this year – one of $3 billion – and many are skeptical that the process of closing this gap will be without hassle. The state faces declining oil prices and thinning reserves, forcing state legislators to rethink their previous budgeting strategies and to consider checking their spending appetites. This shouldn’t be a surprise to state legislators though – the budget process during the past two years ended in gridlock because of similar problems. And these issues have translated into credit downgrades from the three major credit agencies, each reflecting concern about the state’s trajectory if no significant improvements are made.

Despite these issues, residents have not been complaining, at least not until recently. Every fall, some earnings from Alaska’s Permanent Fund get distributed out to citizens – averaging about $1,100 per year since 1982. Last summer, Governor Walker used a partial veto to reduce the next dividend from $2,052 to $1,022. Although politically unpopular, these checks may be subject to even more cuts as a result of the current budget crisis.

The careful reader might notice that Alaska topped the list of the most fiscally healthy states in a 2016 Mercatus report that ranks the states according to their fiscal condition (using fiscal year 2014 data). For a state experiencing so much budget trouble, how could it be ranked so highly?

The short answer is that Alaska’s budget is incredibly unique.

On the one hand, the state has large amounts of cash, but on the other, it has large amounts of debt. Alaska’s cash levels are what secured its position in our ranking last year. Although holding onto cash is generally a good thing for state governments, there appears to be diminishing returns to doing so, especially if there is some structural reason that makes funds hard to access for paying off debt or for improving public services. It is yet to be seen how these factors will affect Alaska’s ranking in the next edition of our report.

Another reason why Alaska appeared to be doing well in our 2016 report is that the state’s problems – primarily spending growth and unsustainable revenue sources – are still catching up to them. Alaska has relied primarily on oil tax revenues and has funneled much of this revenue into restricted permanent trusts that cannot be accessed for general spending. When the Alaska Permanent Fund was created in the 1980s, oil prices were high and production was booming, so legislators didn’t really expect for this problem to occur. The state is now starting to experience the backlash of this lack of foresight.

The first figure below shows Alaska’s revenue and expenditure trends, drawing from the state’s Comprehensive Annual Financial Reports (CAFRs). At first look, you’ll see that revenues have generally outpaced spending, but not consistently. The state broke even in 2003 and revenues steadily outpaced expenditures until peaking at $1,266 billion in 2007. Revenues fell to an all-time low of $241 billion following the recession of 2008 and then fluctuated up and down before falling drastically again in fiscal year 2015.

alaska-revenues-exp4.5.17

The ups and downs of Alaska’s revenues reflect the extremely volatile nature of tax revenues, rents, and royalties that are generated from oil production. Rents and royalties make up 21 percent of Alaska’s total revenues and oil taxes 6 percent – these two combined actually come closer to 90 percent of the actual discretionary budget. Alaska has no personal income tax or sales tax, so there isn’t much room for other sources to make up for struggling revenues when oil prices decline.

Another major revenue source for the state are federal grants, at 32 percent of total revenues. Federal transfers are not exactly “free lunches” for state governments. Not only do they get funded by taxpayers, but they come with other costs as well. There is research that finds that as a state becomes more reliant on federal revenues, they tend to become less efficient, spending more and taxing more for the same level of services. For Alaska, this is especially concerning as it receives more federal dollars than any other state in per capita terms.

Federal transfers as an income stream have been more steady for Alaska than its oil revenues, but not necessarily more accessible. Federal funds are usually restricted for use for federal programs and therefore their use for balancing the budget is limited.

A revenue structure made up of volatile income streams and hard-to-access funds is enough by itself to make balancing the budget difficult. But Alaska’s expenditures also present cause for concern as they have been growing steadily, about 10 percent on average each year since 2002, compared with private sector growth of 6 percent.

In fiscal year 2015, education was the biggest spending category, at 28% of total expenditures. This was followed by health and human services (21%), transportation (11%), general government (10%), the Alaska Permanent Fund Dividend (9%), public protection (6%), and universities (5%). Spending for natural resources, development, and law and justice were all less than 5 percent.

The next figure illustrates the state’s biggest drivers of spending growth since 2002. Education and general government spending have grown the most significantly over the past several years. Alaska Permanent Fund spending has been the most variable, reflecting the cyclical nature of underlying oil market trends. Both transportation and health and human services have increased steadily since 2002, with the latter growing more significantly the past several years as a result of Medicaid expansion.

alaska-spendinggrowth4.5.17

Alaska’s spending is significantly higher than other states relative to its resource base. Spending as a proportion of state personal income was 31 percent in fiscal year 2015, much higher than the national average of 13 percent. A high level of spending, all else equal, isn’t necessarily a bad thing if you have the revenues to support it, but as we see from this year’s budget deficit, that isn’t the case for Alaska. The state is spending beyond the capacity of residents to pay for current service levels.

What should Alaska do?

This is a complicated situation so the answer isn’t simple or easy. The Alaska government website provides a Microsoft Excel model that allows you to try and provide your own set of solutions to balance the budget. After tinkering with the state provided numbers, it becomes clear that it is impossible to balance the deficit without some combination of spending cuts and changes to revenues or the Permanent Fund dividend.

On the revenue side, Alaska could improve by diversifying their income stream and/or broadening the tax base. Primarily taxing one group – in this case the oil industry – is inequitable and economically inefficient. Broadening the base would cause taxes to fall on all citizens more evenly and be less distortive to economic growth. Doing so would also smooth revenue production, making it more predictable and reliable for legislators.

When it comes to spending, it is understandably very difficult to decide what areas of the budget to cut, but a good place to start is to at least slow its growth. The best way to do this is by changing the institutional structure surrounding the political, legislative, and budgeting processes. One example would be improving Alaska’s tax and expenditure limit (TEL), as my colleague Matthew Mitchell recommends in his recent testimony. The state could also look into item-reduction vetoes and strict balanced-budget requirements, among other institutional reforms.

Ultimately, whatever steps Alaska’s legislators take to balance the budget this year will be painful. Hopefully the solution won’t involve ignoring the role that the institutional environment has played in getting them here. A narrow tax base reliant on volatile revenue sources, restricted funds, and growing spending are all factors that have led many to think that Alaska is and always will be “different.” But what constitutes sound public financial management is the same regardless of state. Although Alaska’s situation is unique, their susceptibility to fiscal stress absent any changes is not.

An Overview of the Virginia State Budget and Economy

By Adam Millsap and Thomas Savidge

Virginia’s economy has steadily grown over time in spite of expenditures outpacing revenues each year since 2007. However, economic growth within the state is not evenly distributed geographically.

We examine Virginia’s revenue and expenditure trends, highlighting the sources of Virginia’s revenue and where it spends money. Then we discuss trends in state economic growth and compare that to recent personal income data by county.

Government Overview: Expenditures and Revenue

Figure 1 shows Virginia’s general spending and revenue trends over the past ten years. According to the Virginia Comprehensive Annual Financial Report (CAFR), after adjusting for inflation, government expenditures have outpaced revenue every single year as seen in Figure 1 below (with the exception of 2006). The red column represents yearly expenditures while the stacked column represents revenues (the lighter shade of blue at the top represents revenue from “Federal Grants and Contracts” and the bottom darker shade of blue represents “Self-Funded Revenue”).

VA expend and rev 2006-16

During the recession in 2009, expenditures climbed to $40 billion. Expenditures hovered around this amount until 2015 when they reached $41 billion. Then in 2016 expenditures dropped to just under $37 billion, a level last seen in 2006.

On the revenue side, the majority of Virginia’s government revenue is self-funded i.e. raised by the state. Self-funded revenue hovered between $24 and $29 billion over the ten year period.

However, revenue from federal contracts and grants steadily increased over time. There were two sharp increases in federal contracts and grants: 2008-2009 jumping from $8 to $10 billion and then 2009-2010 jumping from $10 to $13 billion. While there was a drop in federal contracts and grants from 2015-2016, the amount of revenue received from federal contracts and grants has not returned to its pre-2009 levels.

What is the state of Virginia spending its revenue on? According to the Virginia CAFR, state spending is separated into six major categories: General Government, Education, Transportation, Resources & Economic Development, Individual & Family Services, and Administration of Justice. The spending amounts from 2006-2016 (adjusted for inflation) are depicted in Figure 2.

VA expend by category 2006-16

As shown, the majority of spending over the ten year period was on Individual and Family Services. Prior to 2008, spending on Education closely tracked spending on Individual and Family services, but from 2008 to 2010 spending on the latter increased rapidly while spending on education declined. From 2010 through 2015 spending on Individual & Family Services was just over $15 billion per year. It dropped from 2015 to 2016, but so did spending on education, which maintained the gap between the two categories.

During the ten year period, Education spending hovered between $10 and $12 billion until it dropped to $9 billion in 2016. With the exception of Transportation (steadily climbing from 2010-2016), spending on each of the other categories remained below $5 billion per year and was fairly constant over this period.

Virginia Economic Growth & County Personal Income

After examining Virginia’s revenue and expenditures in Part 1, we now look at changes in Virginia’s economic growth and personal income at the county level. Data from the Bureau of Economic Analysis (BEA) shows that Virginia’s GDP hovered between $4 and $4.5 billion dollars (after adjusting for inflation), as shown in Figure 3 below. The blue columns depict real GDP (measured on the left vertical axis in billions of chained 2009 dollars) and the red line depicts percent changes in real GDP (measured on the right vertical axis).

VA GDP 2006-15

While Virginia’s GDP increased from 2006-2015, we’ve condensed the scale of the left vertical axis to only cover $3.9-4.35 billion dollars in order to highlight the percent changes in Virginia’s economy. The red line shows that the percent change in real GDP over this period was often quite small—between 0% and 1% in all but two years.

Virginia’s GDP rose from 2006-2007 and then immediately fell from 2007-2008 due to the financial crisis. However, the economy experienced larger growth from 2009-2010, growing from roughly $4.07-$4.17 billion, a 2.3% jump.

Virginia’s economy held steady at $4.17 billion from 2010 to 2011 and then increased each year up through 2014. Then from 2014-2015, Virginia’s economy experienced another larger spike in growth from $4.24-$4.32 billion, a 2% increase.

Virginia’s economy is diverse so it’s not surprising that the robust economic growth that occurred from 2014 to 2015 was not spread evenly across the state. While the BEA is still compiling data on county GDP, we utilized their data on personal income by county to show the intra-state differences.

Personal Income is not the equivalent of county-level GDP, the typical measure of economic output, but it can serve as a proxy for the economic conditions of a county.[1] Figure 4 below shows which counties saw the largest and smallest changes in personal income from 2014 to 2015. The red counties are the 10 counties with the smallest changes while the blue counties are the 10 counties with the largest changes.

VA county pers. inc. map

As depicted in Figure 4 above, the counties with the strongest personal income growth are concentrated in the north, the east and areas surrounding Richmond. Loudon County in the north experienced the most personal income growth at 7%. The counties surrounding Richmond experienced at least 5.5% growth. Total personal income in Albemarle County grew by 5.7% while the rest of the counties—Hanover, Charles City, Greene, Louisa, and New Kent—experienced growth between 6.2% and 6.7%.

With the exception of Northumberland, the counties in which personal income grew the least were along the western border and in the southern parts of the state. Four of these counties and an independent city were concentrated in the relatively rural Southwest corner of the state—Buchanan, Tazewell, Dickenson, Washington and the independent city of Bristol. In fact, Buchanan County’s personal income contracted by 1.14%.

Cross-county differences in personal income growth in Virginia from 2014 to 2015 are consistent with national data as shown below.

US county pers. inc. map

This map from the BEA shows personal income growth by county (darker colors mean more growth). Nationwide, personal income growth was lower on average in relatively rural counties. Residents of rural counties also have lower incomes and less educational attainment on average. This is not surprising given the strong positive relationship between human capital and economic growth.

And during the most recent economic recovery, new business growth was especially weak in counties with less than 100,000 people. In fact, from 2010 to 2014 these counties actually lost businesses on net.

Conclusion:

Government spending on Individual and Family Services increased during the recession and has yet to return to pre-recession levels. Meanwhile, spending on education declined while spending on transportation slightly increased. This is consistent with other research that has found that state spending on health services, e.g. Medicaid, is crowding out spending in other areas.

Economic growth in Virginia was relatively strong from 2014 to 2015 but was not evenly distributed across the state. The counties with the smallest percentage changes in personal income are relatively rural while the counties with the largest gains are more urban. This is consistent with national patterns and other economic data revealing an urban-rural economic gap in and around Virginia.


[1] Personal Income is defined by the BEA as “the income received by, or on behalf of, all persons from all sources: from participation as laborers in production, from owning a home or business, from the ownership of financial assets, and from government and business in the form of transfers. It includes income from domestic sources as well as the rest of world. It does not include realized or unrealized capital gains or losses.” For more information about personal income see https://www.bea.gov/newsreleases/regional/lapi/lapi_newsrelease.htm

Economic policies and institutions matter

Economists often talk about the important role institutions and policies play in generating economic growth. A new paper that examines the role of urban governance and city-level productivity provides some additional, indirect evidence that institutions and policies impact economic productivity at the local level. (The focus of the paper is how administrative fragmentation affects city-level productivity, not what I present here, but I thought the following was interesting nonetheless.)

The authors graph the correlation between city population and city productivity for five different countries. There is a positive relationship between population and productivity in all of the countries, which is consistent with other studies that find a similar relationship. This relationship is largely due to agglomeration economies and the greater degree of specialization within large cities.

One of the figures from the study—for the U.S.—is shown below. City productivity is measured on the y-axis and the natural log of city population is on the x-axis. (Technical note for those interested: city productivity is measured as the coefficient on a city dummy variable in an individual-level log hourly wage/earnings regression that also controls for gender, age, age squared, education and occupation. This strips away observable characteristics of the population that may affect city productivity.)

US city productivity

Source: Ahrend, Rudiger, et al. “What makes cities more productive? Evidence from five OECD countries on the role of urban governance.” Journal of Regional Science 2017

 

As shown in the graph there is a relatively tight, positive relationship between size and productivity. The two noticeable outlies are El Paso and McAllen, TX, both of which are on the border with Mexico.

The next figure depicts the same information but for cities in Germany.

german city size, product graph

What’s interesting about this figure is that there is a cluster of outliers in the bottom left, which weakens the overall relationship. The cities in this cluster are less productive than one would expect based on their population. These cities also have another thing in common: They are located in or near what was East Germany. The authors comment on this:

“In Germany, the most noteworthy feature is probably the strong east-west divide, with city productivity premiums in eastern German cities being, on the whole, significantly below the levels found in western German cities of comparable size. In line with this finding, the city productivity premium in Berlin lies in between the trends in eastern and western Germany.”

The data used to construct these figures are from 2007, 17 years after the unification of Germany. After WWII and until 1990, East Germany was under communist control and had a centrally planned economy, complete with price controls and production quotas, while West Germany had a democratic government and market economy.

Since 1990, both areas have operated under the same country-level rules and institutions, but as shown above the productivity difference between the two regions persisted. This is evidence that it can take a considerable amount of time for an area to overcome damaging economic policies.

Today’s public policies exacerbate our differences

The evidence that land-use regulations harm potential migrants keeps piling up. A recent paper in the Journal of Urban Economics finds that young workers (age 22 – 26) of average ability who enter the labor force in a large city (metropolitan areas with a population > 1.5 million) earn a wage premium equal 22.9% after 5 years.

The author also finds that high-ability workers experience additional wage growth in large cities but not in small cities or rural areas. This leads to high-ability workers sorting themselves into large cities and contributes an additional 3.2% to the urban wage-growth premium.

These findings are consistent with several other papers that have analyzed the urban wage premium. Potential causes of the wage premium are faster human capital accumulation in denser, more populated places due to knowledge spillovers and more efficient labor markets that better match employers and employees.

The high cost of housing in San Francisco, D.C., New York and dozens of other cities is preventing many young people from earning more money and improving their lives. City officials and residents need to strike a better balance between maintaining the “charm” of their neighborhoods and affordability. This means less regulation and more building.

City vs. rural is only one of the many dichotomies pundits have been discussing since the 2016 election. Some of the other versions of “two Americas” are educated vs. non-educated, white collar vs. blue collar, and rich vs. poor. We can debate how much these differences matter, but to the extent that they are an issue for the country our public policies have reinforced the barriers that allow them to persist.

Occupational licensing makes it more difficult for blue-collar manufacturing workers to transition to middle-class service sector jobs. Federal loan subsidies have made four-year colleges artificially cheap to the detriment of people with only a high school education. Restrictive zoning has made it too expensive for many people to move to places with the best labor markets. And once you’re in a city, unless you’re in one of the best neighborhoods your fellow citizens often keep employers and providers of much needed consumer staples like Wal-Mart out, while using eminent domain to build their next playground.

Over time people have sorted themselves into different groups and then erected barriers to keep others out. Communities do it with land-use regulations, occupations do it with licensing and established firms do it with regulatory capture. If we want a more prosperous America that de-emphasizes our differences and provides people of all backgrounds with opportunity we need more “live and let live” and less “my way or the highway”.

Washington DC is set to become the latest city to make it illegal for low-skill people to work

In the latest example of politics trumping economics, Washington DC’s city council voted to increase the city’s minimum wage to $15 per hour by 2020. The economic arguments against a minimum wage are well-known to most people so I won’t rehash them here, but if you want to read more about why the minimum wage is bad policy you can do so here, here, and here.

In a nutshell, the minimum wage prices lower-skill workers out of the market by setting the wage higher than the value they can produce for their employer; if a worker only produces $9 worth of value in an hour an employer can’t pay her $10 per hour and stay in business.

The minimum wage has the strongest impact on low-skill workers since they tend to produce the least amount of value for their employers. Two categories of such workers are teenagers, who lack experience and have yet to finish their education, and adults with less than a high school degree. The figures below depict the employment and unemployment rates for these two groups in the Washington DC metro area (MSA) and the city proper (District only) from 2009 to 2014 (most recent data available) using 5-year American Community Survey data from American FactFinder.

DC 16-19 employed

As shown in the figure only about 15% of DC’s 16 – 19 year olds were employed (orange) in 2014 compared to about 25% in the MSA as a whole. The percentage has fallen since 2009 and doesn’t appear to be recovering. Increasing the price of such workers certainly won’t help.

The next figure shows the percentage of people with less than a high school degree who were employed.

DC less HS employed

Again, the percentage has fallen in DC since 2009 and is far below the MSA as a whole. Less than half of adults with less than a high school degree are employed in DC compared to 67% in the Washington metro area. If employers relocate to other jurisdictions within the MSA once the minimum wage law takes effect it will make it more difficult for the less-educated adults of DC to find a job.

The next two figures show the unemployment rates for both groups in both areas. As shown, the unemployment rate is higher in DC than in the MSA for both groups and has been trending upward since 2009.

DC 16-19 unemp

DC less HS unemp

It’s outlandish to think that raising the minimum wage will improve things for the 35% of 16 – 19 year olds and 21% of high school dropouts who were looking for a job and couldn’t find one under the old minimum wage of only $9.50.

Politicians and voters are free to ignore economic reality and base their decision making on good intentions, but when doing so they should at least know the employment facts and be made aware of the futility of their intentions. I predict that we will see more automation in DC’s restaurants, hotels, and bars in the future as workers get relatively more expensive due to the higher minimum wage. This will only make it harder for DC’s teenagers and less-educated residents to find work, which as shown above is already a difficult task.

Northern Cities Need To Be Bold If They Want To Grow

Geography and climate have played a significant role in U.S. population growth since 1970 (see here, here, here, and here). The figure below shows the correlation between county-level natural amenities and county population growth from 1970 – 2013 controlling for other factors including the population of the county in 1970, the average wage of the county in 1970 (a measure of labor productivity), the proportion of adults in the county with a bachelor’s degree or higher in 1970 and region of the country. The county-level natural amenities index is from the U.S. Department of Agriculture and scores the counties in the continental U.S. according to their climate and geographic features. The county with the worst score is Red Lake, MN and the county with the best score is Ventura, CA.

1970-13 pop growth, amenities

As shown in the figure the slope of the best fit line is positive. The coefficient from the regression is also given at the bottom of the figure and is equal to 0.16, meaning a one point increase in the score increased population growth by 16 percentage points on average.

The effect of natural amenities on population growth is much larger than the effect of the proportion of adults with a bachelor’s degree or higher, which is another strong predictor of population growth at the metropolitan (MSA) and city level (see here, here, here, and here). The relationship between county population growth from 1970 – 2013 and human capital is depicted below.

1970-13 pop growth, bachelors or more

Again, the relationship is positive but the effect is smaller. The coefficient is 0.026 which means a 1 percentage point increase in the proportion of adults with a bachelor’s degree or higher in 1970 increased population growth by 2.6 percentage points on average.

An example using some specific counties can help us see the difference between the climate and education effects. In the table below the county where I grew up, Greene County, OH, is the baseline county. I also include five other urban counties from around the country: Charleston County, SC; Dallas County, TX; Eau Claire County, WI; San Diego County, CA; and Sedgwick County, TX.

1970-13 pop chg, amenities table

The first column lists the amenities score for each county. The highest score belongs to San Diego. The second column lists the difference between Green County’s score and the other counties, e.g. 9.78 – (-1.97) = 11.75 which is the difference between Greene County’s score and San Diego’s score. The third column is the difference column multiplied by the 0.16 coefficient from the natural amenity figure e.g. 11.75 x 0.16 = 188% in the San Diego row. What this means is that according to this model, if Greene County had San Diego’s climate and geography it would have grown by an additional 188 percentage points from 1970 – 2013 all else equal.

Finally, the last column is the actual population growth of the county from 1970 – 2013. As shown, San Diego County grew by 135% while Greene County only grew by 30% over this 43 year period. Improving Greene County’s climate to that of any of the other counties except for Eau Claire would have increased its population growth by a substantial yet realistic amount.

Table 2 below is similar to the natural amenities table above only it shows the different effects on Greene County’s population growth due to a change in the proportion of adults with a bachelor’s degree or higher.

1970-13 pop chg, bachelor's table

As shown in the first column, Greene County actually had the largest proportion of adults with bachelor’s degree or higher in 1970 – 14.7% – of the counties listed.

The third column shows how Greene County’s population growth would have changed if it had the same proportion of adults with a bachelor’s degree or higher as the other counties did in 1970. If Greene County had the proportion of Charleston (11.2%) instead of 14.7% in 1970, its population growth is predicted to have been 9 percentage points lower from 1970 – 2013, all else equal. All of the effects in the table are negative since all of the counties had a lower proportion than Greene and population education has a positive effect on population growth.

Several studies have demonstrated the positive impact of an educated population on overall city population growth – often through its impact on entrepreneurial activity – but as shown here the education effect tends to be swamped by geographic and climate features. What this means is that city officials in less desirable areas need to be bold in order to compensate for the poor geography and climate that are out of their control.

A highly educated population combined with a business environment that fosters innovation can create the conditions for city growth. Burdensome land-use regulations, lengthy, confusing permitting processes, and unpredictable rules coupled with inconsistent enforcement increase the costs of doing business and stifle entrepreneurship. When these harmful business-climate factors are coupled with a generally bad climate the result is something like Cleveland, OH.

The reality is that the tax and regulatory environments of declining manufacturing cities remain too similar to those of cities in the Sunbelt while their weather and geography differ dramatically, and not in a good way. Since only relative differences cause people and firms to relocate, the similarity across tax and regulatory environments ensures that weather and climate remain the primary drivers of population change.

To overcome the persistent disadvantage of geography and climate officials in cold-weather cities need to be aggressive in implementing reforms. Fiddling around the edges of tax and regulatory policy in a half-hearted attempt to attract educated people, entrepreneurs and large, high-skill employers is a waste of time and residents’ resources – Florida’s cities have nicer weather and they’re in a state with no income tax. Northern cities like Flint, Cleveland, and Milwaukee that simply match the tax and regulatory environment of Houston, San Diego, or Tampa have done nothing to differentiate themselves along those dimensions and still have far worse weather.

Location choices reveal that people are willing to put up with a lot of negatives to live in places with good weather. California has one of the worst tax and regulatory environments of any state in the country and terrible congestion problems yet its large cities continue to grow. A marginally better business environment is not going to overcome the allure of the sun and beaches.

While a better business environment that is attractive to high-skilled workers and encourages entrepreneurship is unlikely to completely close the gap between a place like San Diego and Dayton when it comes to being a nice place to live and work, it’s a start. And more importantly it’s the only option cities like Dayton, Buffalo, Cleveland, St. Louis and Detroit have.