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The use of locally-imposed selective taxes to fund public pension liabilities

Many eyes are on Kentucky policymakers as they grapple with finding a solution to their $40 billion state-reported unfunded public pension liability. As talks of a potential pension bill surface, various proposals have been made by legislators, but very few have gained traction. One such proposal stands out from the rest. A proposal that has since been shut down suggested imposing selective taxes on tobacco, prescription opiates, and outsourced labor to generate revenue to direct towards paying down the state’s pension debt. Despite its short-lived tenure, this selective tax proposal reflects a recent trend in pension funding reform; a trend that policymakers should be wary of. Implementing new taxes on select goods or services may seem like a good idea as it could, in theory, potentially raise additional revenues, but experience at the local level suggests otherwise.

In chapter 12 of a new Mercatus book on sin taxes, NYU professor Thad Calabrese examines the practice of locally-imposed selective taxes that are used to fund public pension liabilities and doesn’t find much evidence to support their continued usage.

Selective taxes are sales taxes that target specific goods and are also known as ‘sin taxes’ because of their popular usage in taxing less healthy goods such as cigarettes, junk food, or alcohol. In the examples that Calabrese examines, selective taxes are used to target insurance premiums as revenue sources for pensions.

Only a select few states have begun this practice – including Illinois, Pennsylvania, as well as municipalities in West Virginia and Missouri – but it may become more popular if courts begin to restrict the way in which current pension benefits can be modified. Once benefits are taken off the table as an avenue for reform, like in Illinois, policymakers will feel more pressure to find new revenue sources.

The proposal in Kentucky may seem appealing to policymakers, especially because of its potential to raise $600 million a year, but this estimate overlooks the unintended effects that such new taxes could facilitate. Thankfully, the proposal did not go through, but I think some time should be spent looking at what similar proposals have looked like at the local level, so that other states do not get tempted pick up where Kentucky left off.

Calabrese draws on the experiences in Pennsylvania and Illinois to examine how these taxes have operated, how the decoupling of setting and financing employee benefits tends to lead to these taxes, and how the use of these taxes is associated with significantly underfunded pension systems. Below I highlight Pennsylvania’s experience and caution against further usage of this mechanism for pension funding.

How it works (or doesn’t)

In 1895, Pennsylvania implemented a 2 percent tax on out-of-state fire and casualty insurance companies’ premiums on in-state property and then earmarked this for distribution to local governments to pay for pensions. Act 205 of 1984 replaced the original act in which the state of Pennsylvania allocated pension aid based on where the insured property was located and instead the new allocation was based on the number of public employees in a locality.

Calabrese explains how the funds were distributed:

“Each public employee was considered a ‘unit,’ and uniformed employees (such as police and fire) each represented two units. The pool of insurance tax revenue collected by the state was then divided by the sum of municipal units to arrive at a unit value. This distribution could subsidize local governments’ pension expenditures up to 100 percent of the annual cost. In 1985, this tax generated $62.3 million in revenues; as a result, each unit value was worth $1,146 – meaning that local governments received $1,146 for pension funding for each public employee and an additional $1,146 for pension funding for each uniformed public employee. Importantly, 75 percent of municipalities received enough funding from this revenue in 1985 to fully offset their pension costs.”

The new mechanism raised more funds, but it also unexpectedly raised costs. If a municipality had to contribute less than the $1,146 annually for a regular employee or $2,292 for a uniformed employee, for example, the municipality was essentially incentivized to increase benefits to public employees up to this limit, because local public employees would receive increased benefits at no direct budgetary cost to the municipality.

“…the tax likely increased insurance costs for residents and businesses (and then only a small fraction of the cost), but not directly for the government employer. Further, this system privileged benefits relative to other compensation, because these payments (borne at least statutorily by out-of-state companies) could only be used for financing pensions and not other forms of compensation.”

A tax originally implemented to fund pension costs statewide resulted in a system that encouraged more generous benefits.

Despite increased subsidies from the state, only 38 percent of municipalities received sufficient allocated funds from the pool to fully offset the costs of pensions. This was because annual pension contributions were growing at a faster rate than the rate at which the subsidy from the state insurance tax was growing.

To highlight a city with severely distressed pension plans, Philadelphia continued to struggle even following the implementation of the state insurance tax. The police pension plan, nonuniformed plan, and firefighter pension plan were all only 49, 47, and 45 percent funded, respectively. In 2009, the City Council passed a temporary 1 percentage point increase in their sales tax and when the temporary rate was renewed in 2014, any revenue in excess of $120 million was dedicated to the city’s pension plans. Additionally, the state permitted the city to pass a $2 per pack cigarette tax to fund a planned budget deficit for the school system; likely because its income tax capacity was largely exhausted.

Philadelphia’s new taxes technically generated new revenues, but they did little to improve the funding of the city’s pension plans.

The selective taxes implemented to fund pension liabilities in Pennsylvania were effectively a Band-Aid that was two small for the state’s pension funding problem, which in turn required the addition of more, insufficient pension Band-Aids. It merely created a public financing system that encouraged pension benefit growth which led to the passage of additional laws requiring certain pension funding levels. And when these funding levels were not met, even more laws were passed that provided temporary pension funding relief, which further grew liabilities for distressed municipalities.

Act 44 became law in 1993 and provided plan sponsors pension funding relief, but primarily by allowing sponsors to alter actuarial assumptions and thereby reduce required pension contributions. Another law delayed funding by manipulating how the required contribution was calculated, rather than providing any permanent fix.

Moving forward

Selective taxes for the purpose of funding pensions are still a relatively rare practice, but as pension liabilities grow and the landscape of reform options changes, it may become increasingly attractive to policymakers. As Calabrese has demonstrated in his book chapter, however, we should be wary of this avenue as it may only encourage the growth of pension liabilities without addressing the problem in any meaningful way. Reforming the structure of the pension plan or the level of benefits provided to current or future employees would provide the most long-term solution.

A solution with the long-term in mind and that doesn’t involve touching current beneficiaries includes moving future workers to defined contribution plans; plans that are better suited to keeping costs contained. The ballooning costs aren’t stemming solely from overly generous plan benefits, but more seriously are the result of their poor management and incentives for funding, only exacerbated by poor accounting practices. The problem is certainly complicated and moving towards the use of defined contribution plans wouldn’t eliminate all issues, but it would at least set governments on a more sustainable path.

At the very least, policymakers interested in long-term solutions should be cautioned against using selective taxes to fund pensions.

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.

A public sector retirement plan for Millennials

According to the Center for Retirement Research, about 52 percent of households are “at risk of not having enough to maintain their living standards in retirement” and that the retirement landscape is making “the outlook for retiring Baby Boomers and Generation Xers far less sanguine than for current retirees.” This growing problem for younger generations is highlighted by the Economic Policy Institute’s finding that almost half of households headed by someone between the ages of 32 and 61 have nothing saved for retirement. A confluence of factors has led to a predicament for millennials as they try to prepare for retirement in a drastically changing job market.

The millennial generation has grown to be an integral part of the workforce, and private sector companies are increasing their efforts to understand what they value most a job. A Deloitte survey reveals that a good work/life balance, opportunities to progress/be leaders, flexibility, and a sense of meaning emerge as the most important factors when evaluating job opportunities. What’s more, millennials are not likely to stick around for a job that doesn’t meet this criteria. The same survey found that if given the choice during the next year, one in four millennials would quit his or her current employer to join a new organization or to do something different.

This flightiness appears to be a characteristic of many young people and to be happening in tandem with, if not contributing to, an increasingly transient job market. This phenomenon, corroborated by other surveys, demonstrates that more and more millennial workers are changing jobs at a higher rate than previous generations. It is not as common to stick with your first or second job until retirement, as it once was for Baby Boomers. The “loyalty challenge” facing companies, paired with changes in technology and culture, has in turn been transforming the landscape of retirement options.

As workers become more transient, companies are forced to provide more portable retirement plan options. During the past two decades, the private sector has done just that by transitioning from offering primarily defined benefit retirement plans to offering more defined contribution plans. This change is to be expected in part because of the flexibility it provides for beneficiaries. Defined contribution plans allow for workers to take their benefits more easily with them from job to job.

The public sector has not quite caught up to this trend. Public sector plans have had much more difficulty staying solvent and much of this is because of the prevalence of defined benefit plans. Mercatus scholars, along with many economists, have long criticized the poor incentive structure of these plans. If these aren’t reason enough for policymakers to offer defined contribution plans in their place, then maybe their changing workforces will.

Much of the debate over growing pension liabilities has focused on whether public sector compensation costs are fair either in comparison to other states or to the private sector. But much less has been said about what is fair across generations.

Most pension reform efforts at the state level target changes in benefits for younger employees while preserving the benefits of older workers. Although this is largely the result of legal and political constraints, such changes have the potential to force younger generations of public-sector workers to shoulder a disproportionate share of the cost of reforms, as their retirement benefits become more uncertain, thus violating a crucial criterion of “intergenerational equity” for pension reform.

Pension experts Robert Novy-Marx and Joshua Rauh reveal in a 2008 study that the intergenerational transfer of pension debt could be quite large. They predict a 50 percent chance of underfunding across the states amounting to more than $750 billion, even before adjusting for risk. In other words, if left alone, the pension bills of today are going to be handed to the generations of tomorrow.

A new Mercatus paper uncovers how similar intergenerational equity issues have developed in the state of Oregon. The author, legal scholar Scott Shepard, writes:

“…the system radically favors (generally older) workers who started before 1996 and 2003, respectively – not just in expected ways, like seniority pay bumps, but in deeply structural ways; earlier-hired employees simply get a significantly better pay-and-benefit package for every minute of their climb up the seniority ladder.”

Oregon’s pension system, along with many other states’ plans, started out offering extremely generous benefits, but as this has grown increasingly unsustainable, the state is being forced to deal with reality and reign in benefits for newer workers.

The unfair retirement landscape that this creates is largely the result of many past poor policy decisions and although this difference in benefits between age groups is far from intentional, how Oregon – and other states in similar positions – responds can be. Changing demographic trends may lend reason for public pension officials to consider moving towards defined contribution plan structures, or at least providing the option.

Shepard strongly urges Oregon to make this shift. He describes a number of benefits; from the perspective of the state, taxpayers, and future generations:

“First, payments must be made when due, rather than being shifted off to future generations. This may seem painful to present taxpayers, but the long-term effect is to ensure a more honest government, in that politicians cannot make promises that their (unrepresented) descendants end up paying for generations later, long after the promisors have reaped the political benefits of making unfunded promises, only to have retired from the scene when payment comes due. This inability to promise now and pay later has a corollary benefit of thwarting the impulse to make extravagant pension promises, as the payments come due immediately, rather than being foisted off on future generations.”

Offering defined contribution plans for workers can provide a more sustainable option that would prevent this equity issue from worsening.

In addition to the accountability and savings that offering a defined contribution option provides, like we have seen demonstrated in Utah and Michigan, this also has the potential to lead to higher worker satisfaction.

With millennials looking to save money for retirement through more portable means, policymakers will want to offer benefits packages that match these preferences. Private sector workers and some public – including Federal and public university – workers lie at the forefront of those benefiting from the defined contribution trend. Most state public plans, however, still fall behind, which has continuing implications for public plan solvency and intergenerational equity.

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

Innovation and economic growth in the early 20th century and lessons for today

Economic growth is vital for improving our lives and the primary long-run determinant of economic growth is innovation. More innovation means better products, more choices for consumers and a higher standard of living. Worldwide, hundreds of millions of people have been lifted out of poverty due to the economic growth that has occurred in many countries since the 1970s.

The effect of innovation on economic growth has been heavily analyzed using data from the post-WWII period, but there is considerably less work that examines the relationship between innovation and economic growth during earlier time periods. An interesting new working paper by Ufuk Akcigit, John Grigsby and Tom Nicholas that examines innovation across America during the late 19th and early 20th century helps fill in this gap.

The authors examine innovation and inventors in the U.S. during this period using U.S. patent data and census data from 1880 to 1940. The figure below shows the geographic distribution of inventiveness in 1940. Darker colors mean higher rates of inventive activity.

geography of inventiveness 1940

Most of the inventive activity in 1940 was in the industrial Midwest and Northeast, with California being the most notable western exception.

The next figure depicts the relationship between the log of the total number of patents granted to inventors in each state from 1900 to 2000 (x-axis) and annualized GDP growth (y-axis) over the same period for the 48 contiguous states.

innovation, long run growth US states

As shown there is a strong positive relationship between this measure of innovation and economic growth. The authors also conduct multi-variable regression analyses, including an instrumental variable analysis, and find the same positive relationship.

The better understand why certain states had more inventive activity than others in the early 20th century, the authors analyze several factors: 1) urbanization, 2) access to capital, 3) geographic connectedness and 4) openness to new ideas.

The figures below show the more urbanization was associated with more innovation from 1940 to 1960. The left figure plots the percent of people in each state living in an urban area in 1940 on the x-axis while the right has the percent living on a farm on the x-axis. Both figures tell the same story—rural states were less innovative.

pop density, innovation 1940-1960

Next, the authors look at the financial health of each state using deposits per capita as their measure. A stable, well-funded banking system makes it easier for inventors to get the capital they need to innovate. The figure below shows the positive relationship between deposits per capita in 1920 and patent production from 1920 to 1930.

innovation, bank deposits 1920-1940

The size of the market should also matter to inventors, since greater access to consumers means more sales and profits from successful inventions. The figures below show the relationship between a state’s transport cost advantage (x-axis) and innovation. The left figure depicts all of the states while the right omits the less populated, more geographically isolated Western states.

innovation, transport costs 1920-1940

States with a greater transport cost advantage in 1920—i.e. less economically isolated—were more innovative from 1920 to 1940, and this relationship is stronger when states in the far West are removed.

The last relationship the authors examine is that between innovation and openness to new, potentially disruptive ideas. One of their proxies for openness is the percent of families who owned slaves in a state, with more slave ownership being a sign of less openness to change and innovation.

innovation, slavery 1880-1940

The figures show that more slave ownership in 1860 was associated with less innovation at the state-level from 1880 to 1940. This negative relationship holds when all states are included (left figure) and when states with no slave ownership in 1860—which includes many Northern states—are omitted (right figure).

The authors also analyze individual-level data and find that inventors of the early 20th century were more likely to migrate across state lines than the rest of the population. Additionally, they find that conditional on moving, inventors tended to migrate to states that were more urbanized, had higher bank deposits per capita and had lower rates of historical slave ownership.

Next, the relationship between innovation and inequality is examined. Inequality has been a hot topic the last several years, with many people citing research by economists Thomas Piketty and Emmanuel Saez that argues that inequality has increased in the U.S. since the 1970s. The methods and data used to construct some of the most notable evidence of increasing inequality has been criticized, but this has not made the topic any less popular.

In theory, innovation has an ambiguous effect on inequality. If there is a lot of regulation and high barriers to entry, the profits from innovation may primarily accrue to large established companies, which would tend to increase inequality.

On the other hand, new firms that create innovative new products can erode the market share and profits of larger, richer firms, and this would tend to decrease inequality. This idea of innovation aligns with economist Joseph Schumpeter’s “creative destruction”.

So what was going on in the early 20th century? The figure below shows the relationship between innovation and two measures of state-level inequality: the ratio of the 90th percentile wage over the 10th percentile wage in 1940 and the wage income Gini coefficient in 1940. For each measure, a smaller value means less inequality.

innovation, inc inequality 1920-1940

As shown in the figures above, a higher patent rate is correlated with less inequality. However, only the result using 90-10 ratio remains statistically significant when each state’s occupation mix is controlled for in a multi-variable regression.

The authors also find that when the share of income controlled by the top 1% of earners is used as the measure of inequality, the relationship between innovation and inequality makes a U shape. That is, innovation decreases inequality up to a point, but after that point it’s associated with more inequality.

Thus when using the broader measures of inequality (90-10 ratio, Gini coeffecieint) innovation is negatively correlated with inequality, but when using a measure of top-end inequality (income controlled by top 1%) the relationship is less clear. This shows that inequality results are sensitive to the measurement of inequality used.

Social mobility is an important measure of economic opportunity within a society and the figure below shows that innovation is positively correlated with greater social mobility.

innovation, social mobility 1940

The measure of social mobility used is the percentage of people who have a high-skill occupation in 1940 given that they had a low-skill father (y-axis). States with more innovation from 1920 to 1940 had more social mobility according to this measure.

In the early 20th century it appears that innovation improved social mobility and decreased inequality, though the latter result is sensitive to the measurement of inequality. However, the two concepts are not equally important: Economic and social mobility are worthy societal ideals that require opportunity to be available to all, while static income or wealth inequality is largely a red herring that distracts us from more important issues. And once you take into account the consumer-benefits of innovation during this period—electricity, the automobile, refrigeration etc.—it is clear that innovation does far more good than harm.

This paper is interesting and useful for several reasons. First, it shows that innovation is important for economic growth over a long time period for one country. It also shows that more innovation occurred in denser, urbanized states that provided better access to capital, were more interconnected and were more open to new, disruptive ideas. These results are consistent with what economists have found using more recent data, but this research provides evidence that these relationships have existed over a much longer time period.

The positive relationships between innovation and income equality/social mobility in the early 20th century should also help alleviate the fears some people have about the negative effects of creative destruction. Innovation inevitably creates adjustment costs that harm some people, but during this period it doesn’t appear that it caused widespread harm to workers.

If we reduce regulation today in order to encourage more innovation and competition we will likely experience similar results, along with more economic growth and all of the consumer benefits.

High-speed rail: is this year different?

Many U.S. cities are racing to develop high speed rail systems that shorten commute times and develop the economy for residents. These trains are able to reach speeds over 124 mph, sometimes even as high as 374 mph as in the case of Japan’s record-breaking trains. Despite this potential, American cities haven’t quite had the success of other countries. In 2009, the Obama administration awarded almost a billion dollars of stimulus money to Wisconsin to build a high-speed rail line connection between Milwaukee and Madison, and possibly to the Twin Cities, but that project was derailed. Now, the Trump administration has plans to support a high-speed rail project in Texas. Given so many failed attempts in the U.S., it’s fair to ask if this time is different. And if it is, will high-speed rail bring the benefits that proponents claim it to have?

The argument for building high-speed rail lines usually entails promises of faster trips, better connections between major cities, and economic growth as a result. It almost seems like a no-brainer – why would any city not want to pursue something like this? The answer, like with most public policy questions, depends on the costs, and whether the benefits actually realize.

In a forthcoming paper for the Mercatus Center, transportation scholar Kenneth Button explores these questions by studying the high-speed rail experiences of Spain, Japan, and China; the countries with the three largest systems (measured by network length). Although there are benefits to these rail systems, Button cautions against focusing too narrowly on them as models, primarily because what works in one area can’t necessarily be easily replicated in another.

Most major systems in other countries have been the result of large public investment and built with each area’s unique geography and political environment kept in mind. Taking their approaches and trying to apply them to American cities not only ignores how these factors can differ, but also how much costs can differ. For example, the average infrastructure unit price of high-speed rail in Europe is between $17 and $24 million per mile and the estimated cost for proposals in California is conservatively estimated at $35 million per mile.

The cost side of the equation is often overlooked, and more attention is given to the benefit side. Button explains that the main potential benefit – generating economic growth – doesn’t always live up to expectations. The realized growth effects are usually minimal, and sometimes even negative. Despite this, proponents of high-speed rail oversell them. The process of thinking through high-speed rail as a sound public investment is often short-lived.

The goal is to generate new economic activity, not merely replace or divert it from elsewhere. In Japan, for example, only six percent of the traffic on the Sanyo Shinkansen line was newly generated, while 55 percent came from other rail lines, 23 percent from air, and 16 percent from inter-city bus. In China, after the Nanguang and Guiguang lines began operating in 2014, a World Bank survey found that many of the passengers would have made the journey along these commutes through some other form of transportation if the high-speed rail option wasn’t there. The passengers who chose this new transport method surely benefited from shorter travel times, but this should not be confused with net growth across the economy.

Even if diverted away from other transport modes, the amount of high-speed rail traffic Japan and China have generated is commendable. Spain’s system, however, has not been as successful. Its network has only generated about 5 percent of Japan’s passenger volume. A line between Perpignan, France and Figueres, Spain that began services in 2009 severely fell short of projected traffic. Originally, it was expected to run 19,000 trains per year, but has only reached 800 trains by 2015.

There is also evidence that high speed rail systems poorly re-distribute activity geographically. This is especially concerning given the fact that projects are often sold on a promise of promoting regional equity and reducing congestion in over-heating areas. You can plan a track between well-developed and less-developed regions, but this does not guarantee that growth for both will follow. The Shinkansen system delivers much of Japan’s workforce to Tokyo, for example, but does not spread much employment away from the capital. In fact, faster growth happened where it was already expected, even before the high-speed rail was planned or built. Additionally, the Tokyo-Osaka Shinkansan line in particular has strengthened the relative economic position of Tokyo and Osaka while weakening those of cities not served.

Passenger volume and line access are not – and should not be – the only metrics of success. Academics have exhibited a fair amount of skepticism regarding high-speed rail’s ability to meet other objectives. When it comes to investment value, many cases have resulted in much lower returns than expected. A recent, extreme example of this is California’s bullet train that is 50 percent over its planned budget; not to mention being seven years behind in its building schedule.

The project in California has been deemed a lost cause by many, but other projects have gained more momentum in the past year. North American High Speed Rail Group has proposed a rail line between Rochester and the Twin Cities, and if it gets approval from city officials, it plans to finance entirely with private money. The main drawback of the project is that it would require the use of eminent domain to take the property of existing businesses that are in the way of the planned line path. Private companies trying to use eminent domain to get past a roadblock like this often do so claiming that it is for the “public benefit.” Given that many residents have resisted the North American High Speed Rail Group’s plans, trying to force the use of eminent domain would likely only destroy value; reallocating property from a higher-value to a lower-value use.

Past Mercatus research has found that using eminent domain powers for redevelopment purposes – i.e. by taking from one private company and giving to another – can cause the tax base to shrink as a result of decreases in private investment. Or in other words, when entrepreneurs see that the projects that they invest in could easily be taken if another business owner makes the case to city officials, it would in turn discourage future investors from moving into the same area. This ironically discourages development and the government’s revenues suffer as a result.

Florida’s Brightline might have found a way around this. Instead of trying to take the property of other businesses and homes in its way, the company has raised money to re-purpose existing tracks already between Miami and West Palm Beach. If implemented successfully, this will be the first privately run and operated rail service launched in the U.S. in over 100 years. And it doesn’t require using eminent domain or the use of taxpayer dollars to jump-start that, like any investment, has risk of being a failure; factors that reduce the cost side of the equation from the public’s perspective.

Which brings us back to the Houston-to-Dallas line that Trump appears to be getting behind. How does that plan stack up to these other projects? For one, it would require eminent domain to take from rural landowners in order to build a line that would primarily benefit city residents. Federal intervention would require picking a winner and loser at the offset. Additionally, there is no guarantee that building of the line would bring about the economic development that many proponents promise. Button’s new paper suggests that it’s fair to be skeptical.

I’m not making the argument that high-speed rail in America should be abandoned altogether. Progress in Florida demonstrates that maybe in the right conditions and with the right timing, it could be cost-effective. The authors of a 2013 study echo this by writing:

“In the end, HSR’s effect on economic and urban development can be characterized as analogous to a fertilizer’s effect on crop growth: it is one ingredient that could stimulate economic growth, but other ingredients must be present.”

For cities that can’t seem to mix up the right ingredients, they can look to other options for reaching the same goals. In fact, a review of the economic literature finds that investing in road infrastructure is a much better investment than other transportation methods like airports, railways, or ports. Or like I’ve discussed previously, being more welcoming to new technologies like driver-less cars has the potential to both reduce congestion and generate significant economic gains.

Pension funding practices and investment risk

A recent paper by Donald J. Boyd and Yimeng Yin of The Nelson A. Rockefeller Institute of Government at SUNY  investigates how public pension funding practices contribute to big funding gaps and the need for sudden contribution increases. This is a situation public sector plans find themselves in due to three reasons 1) muddling the valuation of debt-like pension liabilities with the plan’s investment strategy (i.e. using discount rates basked on risky asset portfolios to measure pension liabilities) 2) amortization methods and 3) asset smoothing.

To find out the impact of these assumptions the authors build a stochastic simulation model for public sector plans that allows them to look at how different funding policies affect plan funding. They find that the funding polices and practices of most plans reduce the volatility of contributions and increase the risk of severe underfunding. And “even if investment return assumptions (7.5 percent annually) are met every single year and employers make the full actuarially determined contributions” they would only reach 85 percent funding after 30 years.

Now consider that it’s unlikely that plans will meet the 7.5 percent annual return each year. If investment returns vary – as they do –  the same plan faces a one-in-six chance of falling below 40 percent funding.

The authors have an interesting chart from a recent presentation highlighting what happens when returns vary each year. In reality, a plan with a portfolio made up of a mix of stocks and bonds is likely to achieve greater than 7.5 percent return in some years and less than 7.5 percent returns in other years). Current plan assumptions project steady and gradually increasing funding ratios and completely flat contribution levels. But in reality, it is all over the map: a roller coaster for funding levels levels and the potential for a huge ramp up in contributions.

Source: Boyd and Yin, 2016 "Standards and Metrics for Public Retirement Systems" The Nelson A. Rockefeller Institute at SUNY

source: Boyd and Yin, 2016, “Standards and Metrics for Public Retirement Systems” The Nelson A. Rockefeller Institute at SUNY