Tag Archives: percent

Economic Freedom, Growth, and What Might Have Been

Economists are obsessed with growth. And for good reason. Greater wealth doesn’t just buy us nicer vacations and fancier gadgets. It also buys longer life spans, better nutrition, and lower infant mortality. It buys more time with family, and less time at work. It buys greater self-reported happiness. And as Harvard economist Benjamin Friedman has argued, wealth even seems to make us better people:

Economic growth—meaning a rising standard of living for the clear majority of citizens—more often than not fosters greater opportunity, tolerance of diversity, social mobility, commitment to fairness, and dedication to democracy.

For much of my lifetime, brisk economic growth was the norm in the United States. From 1983 to 2000, annual growth in real (that is, inflation-adjusted) GDP averaged 3.67 percent. During this period, the U.S. experienced only one (short and mild) recession in the early ‘90s. The era was known among macroeconomists as the “great moderation.”

But starting around the turn of the millennium, things changed. Instead of averaging 3.67 percent growth, the U.S. economy grew at less than half that rate, 1.78 percent on average. To see the effect of this deceleration, consider the chart below (data are from the BEA). The blue line shows actual GDP growth (as measured in billions of chained 2009 dollars).

The red line shows what might have happened if we’d continued to grow at the 3.67 percent rate which prevailed for the two previous decades. At this rate, the economy would have been 30 percent larger in 2015 than it actually was.

This assumes that the Great Recession never happened. So to see what would have happened to GDP if the Great Recession had still occurred but if growth had resumed (as it has in every other post-WWII recession), I calculated a second hypothetical growth path. The green line shows the hypothetical path of GDP had the economy still gone through the Great Recession but then resumed its normal 3.67 percent rate of growth from 2010 onward. Under this scenario, the economy would have been fully 8 percent larger in 2015 than it actually was.

screen-shot-2016-09-16-at-11-31-02-am

(Click to enlarge)

So what happened to growth? One answer is economic freedom—or a lack thereof. Just yesterday, the Fraser Institute released its annual Economic Freedom of the World report. Authored by Professors James Gwartney of Florida State University, Robert Lawson of Southern Methodist University, and Joshua Hall of West Virginia University, the report assesses the degree to which people are free to exchange goods and services with one another without interference. As Adam Smith might have put it, it measures the degree to which we live under “a system of natural liberty.”

As the chart below shows, economic freedom was on the steady rise before 2000. This coincided with modest deregulation of a few industries under Carter and Reagan, tax cuts under Reagan and Clinton, free trade deals, and restrained growth in the size of government. But from 2000 onward, U.S. economic freedom has been in precipitous decline. This coincides with major new financial regulations under both Bush II and Obama, significant growth in government spending, and a steady erosion in measures of the rule of law.

screen-shot-2016-09-16-at-11-33-15-am

(Click to enlarge)

As I’ve noted before, the research on economic freedom is quite extensive (nearly 200 peer-reviewed academic studies use economic freedom as an explanatory variable). Moreover, meta-studies of that literature find “there is a solid finding of a direct positive association between economic freedom and economic growth.”

Perhaps the two charts have something to do with one another?

 

 

Can historic districts dampen urban renewal?

Struggling cities in the Northeast and Midwest have been trying to revitalize their downtown neighborhoods for years. City officials have used taxpayer money to build stadiums, construct river walks, and lure employers with the hope that such actions will attract affluent, tax -paying residents back to the urban core. Often these strategies fail to deliver but that hasn’t deterred other cities from duplicating or even doubling down on the efforts. But if these policies don’t work, what can cities do?

Part of the answer is to allow more building, especially newer housing. One factor that may be hampering the gentrification efforts of many cities is the age of their housing stock. The theory is straightforward and is explained and tested in this 2009 study. From the abstract:

“This paper identifies a new factor, the age of the housing stock, that affects where high- and low-income neighborhoods are located in U.S. cities. High-income households, driven by a high demand for housing services, will tend to locate in areas of the city where the housing stock is relatively young. Because cities develop and redevelop from the center outward over time, the location of these neighborhoods varies over the city’s history. The model predicts a suburban location for the rich in an initial period, when young dwellings are found only in the suburbs, while predicting eventual gentrification once central redevelopment creates a young downtown housing stock.”

In the empirical section of the paper the authors find that:

… a tract’s economic status tends to fall rather than rise as distance increases holding age fixed, suggesting that high-income households would tend to live near city centers were it not for old central housing stocks.” (My bold)

This makes sense. High income people like relatively nicer, newer housing and will purchase housing in neighborhoods where the housing is relatively nicer and newer. In the latter half of the 20th century this meant buying new suburban homes, but as that housing ages and new housing is built to replace the even older housing in the central city high income people will be drawn back to central city neighborhoods. This has the power to reduce the income disparity between the central city and suburbs seen in many metropolitan areas. As the authors note:

Our results show that, if the influence of spatial variation in dwelling ages were eliminated, central city/suburban disparities in neighborhood economic status would be reduced by up to 50 percent within American cities. In other words, if the housing age distribution were made uniform across space, reducing average dwelling ages in the central city and raising them in the suburbs, then neighborhood economic status would shift in response, rising in the center and falling in the suburbs. (My bold)

To get a sense of the age of the housing stock in northern cities, the figure below depicts the proportion of housing in eight different age categories in Ohio’s six major cities as of 2013 (most recent data available, see table B25034 here).

age of ohio's housing stock

The age categories are: built after 2000, from 1990 and 1999, from 1980-89, from 1970-79, from 1960-69, from 1950-59, from 1940-49, and built prior to 1939. As the figure shows most of the housing stock in Ohio’s major cities is quite old. In every city except for Columbus over 30% of the housing stock was built prior to 1939. In Cleveland, over 50% of the housing stock is over 75 years old! In Columbus, which is the largest and fastest growing city in Ohio, the housing stock is fairly evenly distributed across the age categories. Columbus really stands out in the three youngest categories.

In a free market for housing old housing would be torn down and replaced by new housing once the net benefits of demolition and rebuilding exceed the net benefits of renovation. But anyone who studies the housing market knows that it is hardly free, as city ordinances regulate everything from lot sizes to height requirements. While these regulations restrict new housing, they are a larger problem in cities where demand for housing is already high since they artificially restrict supply and drive up prices.

A potentially bigger problem for declining cities that has to do with the age of the housing stock is historic districts. In historic districts the housing is protected by local rules that limit the types of renovations that can be undertaken. Property owners are required to maintain their home’s historical look and it can be difficult to demolish old houses.

For example, in Dayton, OH there are 20 historic districts in a city of only 142,000 people. Dayton’s Landmark Commission is charged with reviewing and approving major modifications to the buildings in historic districts including their demolition.  Many of the districts are located near the center of the city and contain homes built in the late 1800s and early 1900s. Some are also quite large; St. Anne’s Hill contains 315 structures and the South Park historic district covers 24 blocks and contains more than 700 structures. The table below provides a list of Dayton’s historic districts as well as the year they were classified, number of structures, acreage, and whether the district is a locally protected district. Seventy percent of the districts are protected by a local historic designation while 30 percent are only protected by the national designation.

dayton historic districts table

I personally like old houses, but I also recognize that holding on to the past can interfere with revitalization and growth. Older homes, especially those built prior to 1940, are expensive to restore and maintain. They often have old or outdated plumbing systems, electrical systems, and inefficient windows that need to be replaced. They may also contain lead paint or other hazardous materials that were commonly used at the time they were built which may have to be removed. Many people can’t afford these upfront costs and those that can often don’t want to deal with the hassle of a restoration project.

Also, people have different tastes and historic districts make it difficult for some people to live in the house they want in the area they want. As this map shows, many of the Dayton’s historic districts are located near the center of the city in the most walkable, urban neighborhoods. The Oregon district and St. Anne’s Hill are both quite walkable and contain several restaurants, bars, and shops. If a person wants to live in one of these neighborhoods they have to be content with living in an older house. The design restrictions that come standard with historic districts prevent people with certain tastes from locating in these areas.

A 2013 study that examined the Cleveland housing market determined that it is economical to demolish many of the older, vacant homes in declining cities rather than renovate them. This is just as true of older homes that happen to be in historic districts.

Ultimately homeowners should be free to do what they want with their home and the land that it sits on. If a person wants to buy a historic house and renovate it they should be free to do so, but they should also be allowed to build a new structure on the property if they wish. When a city protects large swathes of houses via historic districts they slow down the cycle of housing construction that could draw people back to urban neighborhoods. This is especially true if the historic districts encompass the best areas of the city, such as those closest to downtown amenities and employment opportunities. Living in the city is appealing to many people, but being forced to purchase and live in outdated housing dampens the appeal for some and may be contributing to the inability of cities like Dayton to turn the corner.

Puerto Rico’s labor market woes

Puerto Rico – a U.S. territory – has $72 billion dollars in outstanding debt, which is dangerously high in a country with a Gross Domestic Product (GDP) of only $103.1 billion. The Puerto Rican government failed to pay creditors in August and this was viewed as a default by the credit rating agency Moody’s, which had already downgraded Puerto Rico’s bonds to junk status earlier this year. The Obama administration has proposed allowing Puerto Rico to declare bankruptcy, which would allow it to negotiate with creditors and eliminate some of its debt. Currently only municipalities – not states or territories – are allowed to declare bankruptcy under U.S. law. Several former Obama administration officials have come out in favor of the plan, including former Budget Director Peter Orszag and former Director of the National Economic Council Larry Summers. Others are warning that bankruptcy is not a cure-all and that more structural reforms need to take place. Many of these pundits have pointed out that Puerto Rico’s labor market is a mess and that people are leaving the country in droves. Since 2010 over 200,000 people have migrated from Puerto Rico, decreasing its population to just over 3.5 million. This steady loss of the tax base has increased the debt burden on those remaining and has made it harder for Puerto Rico to get out of debt.

To get a sense of Puerto Rico’s situation, the figure below shows the poverty rate of Puerto Rico along with that of three US states that will be used throughout this post as a means of comparison: California (wealthy state), Ohio (medium-wealth state), and Mississippi (low-wealth state). All the data are 1-year ACS data from American FactFinder.

puerto rico poverty

The poverty rate in Puerto Rico is very high compared to these states. Mississippi’s poverty rate is high by US standards and was approximately 22% in 2014, but Puerto Rico’s dwarfed it at over 45%. Assisting Puerto Rico with their immediate debt problem will do little to fix this issue.

A government requires taxes in order to provide services, and taxes are primarily collected from people who work in the regular economy via income taxes. A small labor force with relatively few employed workers makes it difficult for a county to raises taxes to provide services and pay off debt. Puerto Rico has a very low labor force participation (LFP) rate relative to mainland US states and a very low employment rate. The graphs below plot Puerto Rico’s LFP rate and employment rate along with the rates of California, Mississippi, and Ohio.

puerto rico labor force

puerto rico employ rate

As shown in the figures, Puerto Rico’s employment rate and LFP rate are far below the rates of the US states including one of the poorest states, Mississippi. In 2014 less than 45% of Puerto Rico’s 16 and over population was in the labor force and only about 35% of the 16 and over population was employed. In Mississippi the LFP rate was 58% while the employment rate was 52%. Additionally, the employment rate fell in Puerto Rico from 2010-14 while it rose in each of the other three states. So at a time when the labor market was improving on the mainland things were getting worse in Puerto Rico.

An educated labor force is an important input in the production process and it is especially important for generating innovation and entrepreneurship. The figure below shows the percent of people 25 and over in each area that have a bachelor’s degree or higher.

puerto rico gt 24 education attain

Puerto Rico has a relatively educated labor force compared to Mississippi, though it trails Ohio and California. The percentage also increased over this time period, though it appears to have stabilized after 2012 while continuing to grow in the other states.

Puerto Rico has nice beaches and weather, so a high percentage of educated people over the age of 25 may simply be due to a high percentage of educated retirees residing in Puerto Rico to take advantage of its geographic amenities. The next figure shows the percentage of 25 to 44 year olds with a bachelor’s degree or higher. I examined this age group to see if the somewhat surprising percentage of people with a bachelor’s degree or higher in Puerto Rico is being driven by educated older workers and retirees who are less likely to help reinvigorate the Puerto Rican economy going forward.

puerto rico 25to44 educ attain

As shown in the graph, Puerto Rico actually fares better when looking at the 25 – 44 age group, especially from 2010-12. In 2012 Puerto Rico had a higher percentage of educated people in this age group than Ohio.

Since then, however, Puerto Rico’s percentage declined slightly while Ohio’s rose, along with Mississippi’s and California’s. The decline in Puerto Rico was driven by a decline in the percentage of people 35 to 44 with a bachelor’s or higher as shown in the next figure below.

puerto rico 35to44 educ attain

The percentage of 35 to 44 year olds with a bachelor’s or advanced degree fell from 32% in 2012 to 29.4% in 2014 while it rose in the other three states. This is evidence that educated people in their prime earning years left the territory during this period, most likely to work in the US where there are more opportunities and wages are higher. This “bright flight” is a bad sign for Puerto Rico’s economy.

One of the reforms that many believe will help Puerto Rico is an exemption from compliance with federal minimum wage laws. Workers in Puerto Rico are far less productive than in the US, and thus a $7.25 minimum wage has a large effect on employment. Businesses cannot afford to pay low-skill workers in Puerto Rico such a high wage because the workers simply do not produce enough value to justify it. The graph below shows the median individual yearly income in each area divided by the full time federal minimum wage income of $15,080.

puerto rico min wage ratio

As shown in the graph, Puerto Rico’s ratio was the highest by a substantial amount. The yearly income from earning the minimum wage was about 80% of the yearly median income in Puerto Rico over this period, while it was only about 40% in Mississippi and less in Ohio and California. By this measure, California’s minimum wage would need to be $23.82 – which is equal to $49,546 per year – to equal the ratio in Puerto Rico. California’s actual minimum wage is $9 and it’s scheduled to increase to $10 in 2016. I don’t think there’s a single economist who would argue that more than doubling the minimum wage in California would have no effect on employment.

The preceding figures do not paint a rosy picture of Puerto Rico: Its poverty rate is high and trending up, less than half of the people over 16 are in the labor force and only about a third are actually employed, educated people appear to be leaving the country, and the minimum wage is a severe hindrance on hiring. Any effort by the federal government to help Puerto Rico needs to take these problems into account. Ultimately the Puerto Rican government needs to be enabled and encouraged to institute reforms that will help grow Puerto Rico’s economy. Without fundamental reforms that increase economic opportunity in Puerto Rico people will continue to leave, further weakening the commonwealth’s economy and making additional defaults more likely.

 

 

Banking on risky investments is no way to guarantee a public pension

Over the past several years I’ve spent a lot of time studying public pension systems. That’s involved diving into the economics and actuarial literature, reading through many individual plan reports, and analyzing the trends in those systems in the context of the principles of financial economics. Why do this? It isn’t just a public finance problem. Twenty million Americans participate in these plans. If research points to systematic structural weaknesses in public sector plans, that under the right conditions, can lead to plan failure, then it is an imperative to point it out and recommend solutions to ensure that retirees receive the pensions they’ve been promised without placing unnecessary burdens on taxpayers or forcing painful budget tradeoffs at the worst possible time: during a recession.

The only way to protect pensions is to accurately assess their true value and funded status and then contribute what is needed to pay out those benefits. Unfortunately, the story of US public sector pension is that they are built on investment risk and accounting illusions.

Pension finance is not without controversy. Misunderstandings can arise in part due to the very different approaches taken by financial economists and traditionally trained actuaries over how to most appropriately value pension liabilities and assets, as well as the nature of investment risk.

However, some of the conflict is due to the implications of the pension literature. Applying the economic approach to valuing pension fund liabilities reveals trillions more in obligations and far bigger funding gaps for states and cities. It shows how public sector plans have exposed themselves to an unwise amount of investment risk effectively linking guaranteed pension payments to market volatility and putting taxpayers on the hook for losses. Some state and local governments have responded to this debate either through small accounting reforms or policy changes meant to shore up pension systems. These reforms are not necessarily sufficient but it’s a tacit recognition that the math really matters.

There are some plans that continue to staunchly defend a “More investment risk = safe and guaranteed pension with no downsides” approach. And at least one system has gone on the offense against any suggestion that increasing investment risk in a government-guaranteed pension system amounts to gambling with employees’ pension benefits.

In May 2014 I authored a paper that made the case for economic accounting and better funding for Alabama’s three state-run pension plans.[1] My study was featured in The Advisor in July 2014, the newsletter the Retirement Systems of Alabama (RSA) provides to its members.[2] One article written by “RSA staff” purports to debunk my paper, but ends up missing the implications of both the literature and my analysis.

The RSA staff’s main complaint revolves around one sentence in which I cite a peer-reviewed 2010 study in the National Tax Journal by Joshua Rauh entitled, “Are State Public Pension Plans Sustainable?[3] Rauh finds that, without policy changes, Alabama might run out of assets to pay benefits by 2023, necessitating the move to a pay as you go system. To be sure, that is a sobering claim.

The RSA staff argues that the runout date calculated by Rauh is based on “bad data” from 2006, when Alabama offered a 3.5 percent ad hoc Cost of Living Adjustment (COLA). It further contends the runout date is based on the assumption of a risk-free discount rate and asset values from 2009, and this all unfairly inflates liabilities and cherry-picks a low-point for asset values. In addition, Rauh assumes that the plan only pays for normal costs going forward (not for past benefits), in keeping with the contribution behavior of most plans at the time of the study.

The first two claims by the RSA staff are incorrect. In the “run-out dates” paper, Rauh’s data is assembled from, “the individual plans and the Center for Retirement Research on a plan-by-plan basis.”[4] This dataset was originally developed for a previous peer-reviewed paper with Robert Novy-Marx entitled, “Public Pension Promises: How Big Are They and What Are They Worth?” which drew from the individual Comprehensive Annual Financial Reports (CAFRs) of 116 state-sponsored pension plans.[5] Nine data items were taken from the pension plan CAFRs that were available as of December 31, 2008. (The FY 2008 CAFR contains data for 2007 that the authors project to 2009). These CAFR-derived items are:

  • the plans’ stated liability
  • its state-chosen discount rate
  • the actuarial method (EAN or PUC)
  • a benefit factor
  • a Cost of Living Adjustment
  • an inflation assumption
  • the share of active workers in the plan;
  • the share of retired workers in the plan; and
  • the dollar amount of benefits paid in the most recent year.

The third item – the actuarial method – was drawn from both the CAFR and information from the Center for Retirement Research at Boston College as of 2006.[6]

Novy-Marx and Rauh estimated a total of $42 billion projected liabilities as of June 2009 for all three of Alabama’s plans. [7] The authors’ estimate closely matches the reported value of $41.6 billion in September 30, 2009 in RSA’s FY 2010 CAFR. Novy-Marx and Rauh re-calculate the value of state promised pension liabilities when valued based on risk-free Treasury bonds. They find that Alabama’s total liabilities of $42 billion increase to $61.8 billion when discounted using the risk-free Treasury rate.

Their paper triggered a lot of attention. Clearly, the finding that GASB 25 was leading state plans to obscure the true size of their pension liabilities generates a lot of follow-up questions, such as, “When will they run out of money?”

In a subsequent paper Rauh (2010) tackles this very question. His assumptions are key to interpreting the run out date. Beginning with the data that he and Novy-Marx assembled, Rauh models the cash flows of these pension plans under the rate of return assumed by the plan itself, in the case of Alabama: 8 percent. A further assumption is made that future contributions to the plan will be equal in value to the benefits earned by employees in that year, “an assumption broadly in keeping with states’ recent contribution behavior.”[8] If the state fully funds benefits as they are accrued how long will the assets last under the assumption that the plans earn 8 percent each year?

Under an 8 percent discount rate with no COLA, and only funding the normal cost, Rauh projects that the RSA will run out of assets in 2023. The implication is that state contributions will have to increase, placing a greater demand on state budgets, necessitating increased taxes or cuts to spending. One thing going in Alabama’s favor is that they have a history of making the full contribution each year. However, this contribution amount is calculated under optimistic assumptions that I demonstrate in the paper are based on assuming a large amount of investment risk. And that is where the danger lies.

Contrary to the RSA staff’s claim:

  • There is no COLA assumption in Rauh’s 2010 run-out date study
  • The run out date of 2023 is based on a discount rate of 8 percent.

The RSA staff is correct to note that Rauh’s calculation is based on only paying the normal cost. Since Alabama has a history of making the full annual contribution this will help the system to forestall a run-out. The question is by how much, by how many years? As long as the RSA assumes an 8 percent discount rate and embraces a risky investment strategy they are operating under an accounting illusion that leads them to low-ball the annual contribution needed to fund the system.

If the market has a great run over the next decade with returns exceeding 8 percent per year and the RSA continues to to pay 100 percent of the ARC under these conditions it would stay solvent. The RSA points to the fact that between 2009 and today its assets have grown by 46 percent, or $35 billion. [9]

But there’s another problem. The RSA’s funded status continues its decade-long drop. Let’s look at Alabama’s assets, liabilities, and funded status of the plan between 2008 and 2013 (the most recent data available) taken from the plan CAFRs, with no adjustments to the data. The trend is clear. Liabilities are growing faster than the assets. Funding ratios are falling.

For Teachers’ Retirement System (TRS) over the period the total actuarial value of assets fell by six percent from $20.8 billion to $19.6 billion, while total liabilities grew from $26 billion to $29 billion (11 percent), leaving the system with a funded ratio of 66 percent.

Table 1. Teachers Retirement System Actuarial Accrued Liability and Actuarial Assets (2008-2013) Adjusted for Inflation

($ mil) 2008 2009 2010 2011 2012 2013 % change 2008-2014
TRS Liabilities $26,804 $27,537 $28,299 $28,776 $28,251 $29,665 11%
TRS Assets  $20,812 $20,582 $20,132 $19,430 $18,786 $19,629 -6%

Source: Comprehensive Annual Financial Report (CAFR) for Retirement System of Alabama (RSA) FY 2009-2014.

The same story can be told of the Employees Retirement System (ERS). Assets fell by 4 percent as liabilities grew by 11 percent over the period. The ERS is currently funded at 65 percent, down from 77 percent in 2009. Four years of increased returns have not reversed the decline.

Table 2. Employees’ Retirement System Actuarial Accrued Liabilities and Actuarial Assets 2008-2013

($ mil) 2008 2009 2010 2011 2012 2013 % change 2008-2014
ERS Liabilities $13,078 $13,756 $14,248 $14,366 $13,884 $14,536 11%
ERS Assets $9,905 $9,928 $9,739 $9,456 $9,116 $9,546 -4%

Source: Comprehensive Annual Financial Report (CAFR) for Retirement System of Alabama (RSA) FY 2009-2014

The Judicial Retirement Fund (JRF) had the steepest increase in liabilities. Assets fell by 6 percent and liabilities grew by 28 percent. JRF is the most weakly funded at 58 percent.

Table 1. Judicial Retirement System Actuarial Accrued Liability and Actuarial Assets (2008-2013) Adjusted for Inflation

($ mil) 2008 2009 2010 2011 2012 2013 % change 2008-2014
JRF Liabilities $323 $340 $358 $393 $380 $414 28%
JRF Assets $259 $252 $246 $235 $234 $243 -6%

Source: Comprehensive Annual Financial Report (CAFR) for Retirement System of Alabama (RSA) FY 2009-2014

Looking back at the decade shows an even more dramatic trend. These systems began 2003 with funding levels of 90 percent. They have fallen every year since to their current levels of between 66 percent and 58 percent.

The RSA has stated in the past that 80 percent funding is good enough and that investing assets in a risky portfolio currently comprised of 70 percent equities will enable the system to comfortably meet its obligations. But as these funding trends show a volatile portfolio comes with a downside. The assets may be back to where they were five years ago, but in the meantime, liabilities continue their steady growth.

The next observation the RSA staff makes is that these numbers are too bleak since they are based on 2009 asset values. Since then the assets have grown by 11 percent on average over the period. To be sure, once you exclude 2008, things look better. But that’s a bit like excluding the F when you calculate your average grade for the semester. Ignoring the downturn doesn’t mean it didn’t happen or that it didn’t erode the assets. It takes exceptional and sustained performance to make up for it.

The five and 10-year period tell a less bullish story.

Annualized returns for the RSA for the Fiscal Year ended September 30, 2013. (p. 60)

Total Portfolio 1 year Last 3 Years Last 5 Years Last 10 Years
TRS 14.93% 11.45% 6.68% 6.29%
ERS 14.6% 11.4% 6.17% 5.97%
JFR 14.05% 10.89% 8.74% 7.06%

While investments have rebounded for the RSA, plan funding status is falling despite increased contributions. Since 2012 employers and most employees are making bigger contributions to these plans. Alabama now operates a Two-tiered pension system. Tier 1 TRS and ERS employees (those hired before January 1, 2013) saw their individual contributions rates increase from 5 percent of pay in 2011 to 7.5 percent of pay in 2013. JRF members, firefighters, police officers and correctional officers contribution rates increased from 6 percent in 2011 to 8.25 percent of pay in 2013. Tier II members (those hired after January 1, 2013) will have lower contribution rates and diminished benefits. Both tiers will give something up.

Employers are also contributing more. The state’s contributions have increased. For the TRS (Tier 1 employees), the state’s contribution has risen from 6.3 percent of payroll in 2000 to 11.7 percent in 2014. Employer contributions for the ERS (Tier 1) rose from 4 percent to 12 percent of payroll over the same period. JRF has the largest employer contribution “In 2000, the state contribution to the JRF was 21 percent of payroll. It reached 35% by 2014.”

Rauh’s 2010 study points to a trend worth monitoring. Funding levels are dropping. Assets are not growing fast enough to keep up with the growth in liabilities necessitating more revenues, higher contributions or some other action. Yet the RSA staff points to its recent returns of 11%, as if that is something the RSA can sustain. The stock market does reward risk-taking with high returns in bull markets, but at a cost of negative returns in recession years like 2008. Increasing the risk of RSA assets to chase high stock market returns is banking on something neither the RSA nor anyone else can guarantee.

Valuing a guaranteed pension based on the expected returns of risky and volatile assets increases the chance of a funding shortfall. It is likely that Alabama will find it will need more revenue to fund the RSA. Already inadequate funding levels are falling. The investment portfolio is heavily exposed to market risk. And contribution rates are rising.

The RSA staff’s response to my research is part of a more general problem. Many of those responsible for public sector pensions think that investment risk can be ignored or it can just be passed on to taxpayers. The point of this entire body of literature drives home one theme consistently: public sector pension accounting flaunts the established principles of finance by claiming that there is no price for assuming investment risk. Financial theory can be abstract. But recent history gives us a demonstration of these core principles. Many pensions systems, the RSA included, have ignored the lessons of the Great Recession and are exposing pensions to even more investment risk.

[1] Eileen Norcross, “Pension Reform in Alabama: A Case for Economic Accounting,” in Improving Lives in Alabama: A Vision for Economic Freedom and Prosperity, The Johnson Center at Troy University, May 2014 (https://nebula.wsimg.com/35b439dc51fd0dae2bd46e38024dadd2?AccessKeyId=F0B126F45D4E1A4094F7&disposition=0&alloworigin=1)

[2] “Troy University Report on RSA has Erroneous Assumptions,” by RSA Staff, The Advisor, July 2014 (http://www.rsa-al.gov/uploads/files/Advisor_July2014.pdf)

[3] Joshua Rauh, “Are State Public Pension Plans Sustainable? Why the Federal Government Should Worry about State Pension Liabilities,” National Tax Journal 63(3) p. 585-601, May 2010. (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1596679)

[4] Ibid, p. 6 and p. 9.

[5] Robert Novy-Marx and Joshua Rauh, “Public Pension Promises: How Big Are They and What Are They Worth?” Journal of Finance 66 (4), 1211-1249, 2011 (http://www.jstor.org/stable/29789814?seq=1#page_scan_tab_contents)

[6] Ibid p. 1224, “The actuarial method (item 3) combines our own data collection with information from the state and local pension data made available by the Center for Retirement Research (2006.)

[7] Ibid, p. 1239

[8] Rauh, (2010) “Are Public Pensions Sustainable?” p. 2.

 

An interesting development in state regulation of wine shipment

Can one state enforce another state’s laws that prohibit direct-to-consumer wine shipment from out-of-state retailers while allowing it by in-state retailers?  That’s the question posed in a recent New York case.

The New York State Liquor Authority has a rule that prohibits licensees from engaging in “improper conduct.”  The liquor regulator argues that direct shipments by retailers that violate other states’ laws constitute improper conduct.  It has fined, revoked licenses, and filed charges against New York retailers that it believes have shipped wine illegally to customers in other states. One retailer, Empire Wine, refused to settle and has sued the liquor authority in state court, claiming that the “improper conduct” rule is unconstitutionally vague and that the liquor authority cannot enforce other states’ laws that discriminate against interstate commerce.

Many states continue to prohibit direct shipment from out-of-state retailers. For example, 40 states do not allow New York retailers to ship directly to consumers.  This harms consumers, because it is usually out-of state-retailers, rather than wineries, that offer significant savings compared to in-state retailers. In a 2013 article published in the Journal of Empirical Legal Studies, Alan Wiseman and I identified two different anti-consumer effects of laws that allow out-of-state wineries to ship direct to consumer but prohibit out-of-state retailers from doing so. First, these laws deprive consumers of price savings from buying many bottles online: “Online retailers consistently offered price savings on much higher percentages of the bottles in each year—between 57 and 81 percent of the bottles when shipped via ground and between 32 and 48 percent when shipped via air. Excluding retailers from direct shipment thus substantially reduces—but does not completely eliminate—the price savings available from purchasing wine online.” Second, these laws reduce competitive pressure on bricks-and-mortar wine stores, since they exclude lower-priced out-of-state retailers from the local market. Thus, the laws likely harm consumers who buy from their local wine shops, not just consumers who want to buy online. (The published version of the paper is behind a paywall, but you can read the working paper version at SSRN.)

(Photo credit: http://srxawordonhealth.com/2011/07/11/exercise-in-a-bottle/)

 

How Complete Are Federal Agencies’ Regulatory Analyses?

A report released yesterday by the Government Accountability Office will likely get spun to imply that federal agencies are doing a pretty good job of assessing the benefits and costs of their proposed regulations. The subtitle of the report reads in part, “Agencies Included Key Elements of Cost-Benefit Analysis…” Unfortunately, agency analyses of regulations are less complete than this subtitle suggests.

The GAO report defined four major elements of regulatory analysis: discussion of the need for the regulatory action, analysis of alternatives, and assessment of the benefits and costs of the regulation. These crucial features have been required in executive orders on regulatory analysis and OMB guidance for decades. For the largest regulations with economic effects exceeding $100 million annually (“economically significant” regulations), GAO found that agencies always included a statement of the regulation’s purpose, discussed alternatives 81 percent of the time, always discussed benefits and costs, provided a monetized estimate of costs 97 percent of the time, and provided a monetized estimate of benefits 76 percent of the time.

A deeper dive into the report, however, reveals that GAO did not evaluate the quality of any of these aspects of agencies’ analysis. Page 4 of the report notes, “[O]ur analysis was not designed to evaluate the quality of the cost-benefit analysis in the rules. The presence of all key elements does not provide information regarding the quality of the analysis, nor does the absence of a key element necessarily imply a deficiency in a cost-benefit analysis.”

For example, GAO checked to see if the agency include a statement of the purpose of the regulation, but it apparently accepted a statement that the regulation is required by law as a sufficient statement of purpose (p. 22). Citing a statute is not the same thing as articulating a goal or identifying the root cause of the problem an agency seeks to solve.

Similarly, an agency can provide a monetary estimate of some benefits or costs without necessarily addressing all major benefits or costs the regulation is likely to create. GAO notes that it did not ascertain whether agencies addressed all relevant benefits or costs (p. 23).

For an assessment of the quality of agencies’ regulatory analysis, check out the Mercatus Center’s Regulatory Report Card. The Report Card evaluation method explicitly assesses the quality of the agency’s analysis, rather than just checking to see if the agency discussed the topics. For example, to assess how well the agency analyzed the problem it is trying to solve, the evaluators ask five questions:

1. Does the analysis identify a market failure or other systemic problem?

2. Does the analysis outline a coherent and testable theory that explains why the problem is systemic rather than anecdotal?

3. Does the analysis present credible empirical support for the theory?

4. Does the analysis adequately address the baseline — that is, what the state of the world is likely to be in the absence of federal intervention not just now but in the future?

5. Does the analysis adequately assess uncertainty about the existence or size of the problem?

These questions are intended to ascertain whether the agency identified a real, significant problem and identified its likely cause. On a scoring scale ranging from 0 points (no relevant content) to 5 points (substantial analysis), economically significant regulations proposed between 2008 and 2012 scored an average of just 2.2 points for their analysis of the systemic problem. This score indicates that many regulations are accompanied by very little evidence-based analysis of the underlying problem the regulation is supposed to solve. Scores for assessment of alternatives, benefits, and costs are only slightly better, which suggests that these aspects of the analysis are often seriously incomplete.

These results are consistent with the findings of other scholars who have evaluated the quality of agency Regulatory Impact Analyses during the past several decades. (Check pp. 7-10 of this paper for citations.)

The Report Card results are also consistent with the findings in the GAO report. GAO assessed whether agencies are turning in their assigned homework; the Report Card assesses how well they did the work.

The GAO report contains a lot of useful information, and the authors are forthright about its limitations. GAO combed through 203 final regulations to figure out what parts of the analysis the agencies did and did not do — an impressive accomplishment by any measure!

I’m more concerned that some participants in the political debate over regulatory reform will claim that the report shows regulatory agencies are doing a great job of analysis, and no reforms to improve the quality of analysis are needed. The Regulatory Report Card results clearly demonstrate otherwise.

North Carolina Reconsiders its Rejection of Corporate Welfare

A couple of weeks ago, something surprising happened in North Carolina. As the Carolina Journal explained:

RALEIGH — Twenty-eight House Republicans bolted party ranks Tuesday, joining 26 Democrats to defeat an economic incentives program that some labeled “corporate welfare.” It was a rebuke to House Speaker Thom Tillis, R-Mecklenburg, Senate leader Phil Berger, R-Rockingham, and Gov. Pat McCrory, all of whom championed the legislation.

The 47-54 vote against House Bill 1224 signaled that the end of the meandering 2014 “short session” of the General Assembly could be nigh, arriving perhaps as early as today.

The move marked an unusual triumph of economic rationality over special-interest politics. As Brian Balfour explained it in the Civitas Review, the bill combined two unrelated policies: it capped local sales tax rates while expanding the state’s corporate welfare efforts. Now, however, the Washington Post is reporting that the governor is under intense pressure to call a special session so the legislature can reconsider the legislation.

If they do come back into session, legislators would be wise to study up on the issue before they reconsider their votes. A good place to start would be a recent Mercatus working paper by George Mason University Professor Christopher Coyne and GMU Ph.D. candidate Lotta Moberg. The paper explores the effects of targeted economic development incentives, stressing two under-appreciated downsides to the policies:

(1) they lead to a misallocation of resources, and (2) they encourage rent-seeking and thus cronyism. We argue that these costs, which are often longer-term and not readily observable at the time the targeted benefits are granted, may very well outweigh any possible short-term economic benefits.

To gain a better understanding of the effects of these policies, my colleague Olivia Gonzalez and I have begun looking at the empirical literature. While our results are still preliminary, what we have found so far should give Tar Heel legislators pause in re-thinking their decision. We found 26 peer-reviewed papers that assess the effect of targeted incentives on the broader economy (a surprisingly large number of studies only look at whether incentives help the privileged firms and sectors, ignoring how they affect the broader economy).

The pie chart below shows what we’ve found. Just 2 studies, constituting 8 percent of the sample, found that targeted incentives positively affect the economy-at-large. Four studies (15 percent of the sample) found that targeted incentives negatively affect the broader economy. Another 6 studies found that they produce some positive effects (such as higher employment) but also some negative effects (such as lower labor force participation). One study in the sample found a distinct group (manufacturers) benefited while others (finance, insurance, and real estate) lost. Thirteen studies (half the sample), simply found no statistically significant effect of targeted incentives.

Targeted incentives research pie chartOn balance, this is not a strong case for the effectiveness of targeted economic development incentives. It suggests that when states privilege particular firms or industries, they are wasting taxpayer resources, benefiting some at the expense of others, and potentially harming the broader economy. Of course, some pathologies of privilege such as long-term resource misallocation, rent-seeking waste, and corruption may not manifest themselves for years and are not likely to be picked up by these studies.

Paving over pension liabilities, again

Public sector pensions are subject to a variety of accounting and actuarial manipulations. A lot of the reason for the lack of funding discipline, I’ve argued, is in part due to the mal-incentives in the public sector to fully fund employee pensions. Discount rate assumptions, asset smoothing, and altering amortization schedules are three of the most common kinds of maneuvers used to make pension payments easier on the sponsor. Short-sighted politicians don’t always want to pay the full bill when they can use revenues for other things. The problem with these tactics is they can also lead to underfunding, basically kicking the can down the road.

Private sector plans are not immune to government-sanctioned accounting subterfuges. Last week’s Wall Street Journal reported on just one such technique.

President Obama recently signed a $10.8 billion transportation bill that also included a provision to allow companies to continue “pension smoothing” for 10 more months. The result is to lower the companies’ contribution to employee pension plans. It’s also a federal revenue device. Since pension payments are tax-deductible these companies will have slightly higher tax bills this year. Those taxes go to help fund federal transportation per the recently signed legislation.

A little bit less is put into private-sector pension plans and a little bit more is put into the government’s coffers.

The WSJ notes that the top 100 private pension plans could see their $44 billion required pension contribution reduced by 30 percent, adding an estimated $2.3 billion deficit to private pension plans. It’s poor discipline considering the variable condition of a lot of private plans which are backed by the Pension Benefit Guaranty Corporation (PBGC).

My colleague Jason Fichtner and I drew attention to these subtle accounting dodges triggered by last year’s transportation bill. In “Paving over Pension Liabilities,” we call out discount rate manipulation used by corporations and encouraged by Congress that basically has the same effect: redirecting a portion of the companies’ reduced pension payments to the federal government in order to finance transportation spending. The small reduction in corporate plans’ discount rate translates into an extra $8.8 billion for the federal government over 10 years.

The AFL-CIO isn’t worried about these gimmicks. They argue that pension smoothing makes life easier for the sponsor, and thus makes offering a defined benefit plan, “less daunting.” But such, “politically-opportunistic accounting,” (a term defined by economist Odd Stalebrink) is basically a means of covering up reality, like only paying a portion of your credit card bill or mortgage. Do it long enough and you’ll eventually forget how much those shopping sprees and your house actually cost.

Ex-Im’s Deadweight Loss

To hear defenders of Ex-Im talk, you’d think that export subsidies are ALL upside and no downside. Economic theory suggests otherwise.

Clearly, some benefit from export subsidies. The most-obvious beneficiaries are the 10 or so U.S. manufacturers whose products capture the bulk of Ex-Im’s privileges (if they didn’t benefit, their “all hands on deck” public relations campaign to save the bank wouldn’t make a lot of sense).

Foreign purchasers who receive loans and loan guarantees from the bank in exchange for buying these products also clearly benefit.

The least-conspicuous beneficiaries are the private banks who finance these deals and get to offload up to 85 percent of the risk on to U.S. taxpayers. But they too clearly benefit.

Those are the upsides. But as economists are wont to say, “there is no such thing as a free lunch.”

Behind each of these beneficiaries is someone left holding the bag: there are taxpayers who bear risks that private lenders are unable or unwilling to bear. There are consumers who must pay higher prices for products that are made artificially expensive by Ex-Im subsidies. And there are other borrowers who lose out on capital because they aren’t lucky enough to have the full faith and credit of the U.S. taxpayer standing behind them.

One might be tempted to think that gains of the winners roughly offset the losses of the losers. But basic economic analysis suggests that the losses exceed the gains.

A few simple diagrams illustrate this point.

First consider any subsidy of a private (that is, excludable and rivalrous) good. Perhaps the most relevant example is a subsidy to private lenders. This is shown in the familiar supply and demand diagram shown below. The quantity of loanable funds is displayed along the horizontal axis and the price of a loan—the interest rate—is shown on the vertical axis.

People want loans to invest in their projects. We call this the “Demand for Investment.” It is shown as the blue, downward-sloping line. It is downward sloping because there are diminishing marginal returns to investment and because if you have to pay a higher interest rate, you will borrow less.

Other people have money to lend. We call this the “Supply of Savings.” It is depicted below as the solid red, upward-sloping line. It is upward sloping because there are increasing opportunity costs to lending out money and lenders must be enticed with higher and higher interest rates to lend more and more money.

The key to understanding this diagram—and this is a point that non-economists tend to find unintuitive—is that there is an optimal quantity of loans and it is not infinity. There is some point beyond which the marginal opportunity cost of further lending exceeds the marginal expected benefit from these investments.

Now consider what happens when the government guarantees the loans. Knowing that taxpayers will cover up to 85 percent of their losses, rational lenders will be willing to supply any given quantity of loans at a lower interest rate. Thus, the supply of savings shifts to the lower, dashed red line. But just because loan guarantees shield lenders from the true opportunity cost of these funds, it does not mean that the true opportunity cost goes away. In this case, taxpayers wear the risk. (For a dated but lucid explanation of the true opportunity cost associated with Ex-Im, see this Minneapolis Fed paper).

Society as a whole is made poorer because scarce resources are redirected from higher-valued uses toward lower-valued uses. In other words, those who lose end up losing more than the winners win. Economists call this “dead weight loss” (DWL). It is represented by the red triangle in the diagram below (click to enlarge).

DWL of a Subsidy

So far, this is the basic economic theory of a subsidy. But economists have developed more-specific models to understand subsidies in the context of international trade.

To get a handle on this, check out some videos by Professor Michael Moore of George Washington University. If international trade diagrams are new to you, I’d recommend looking at these diagrams before watching his videos. Then watch Professor Moore’s excellent illustration of an export subsidy in a small country, followed by the slightly more-complicated—but more relevant—case of export subsidies in a large country.

Small country case:

Large country case:

This is the basic case for free trade and it is widely accepted by economists. Some astute readers may know that there are some interesting theoretical exceptions to this rule. These exceptions derive from what are known as “strategic trade” models. They posit that in some situations—such as oligopolistic industries—governments can theoretically manage to use subsidies to make domestic firms win more than domestic consumers lose. The world is still poorer, but domestic winnings outweigh domestic losses.

These models are worth understanding. But the truth is they have not—and should not—undermine the basic economic case for free trade. The best exposition of this point is a classic piece by Paul Krugman called “Is Free Trade Passe?” In it, Krugman carefully walks the reader through the logic of these models. He then notes, quite rightly, that:

The normative conclusion that this justifies a greater degree of government intervention in trade, however, has met with sharp criticism and opposition—not least from some of the creators of the new theory themselves.

Krugman then ticks through the reasons why free trade should still be the reasonable rule of thumb. For one thing, since the strategic trade models seem to only work in oligopolistic industries, policy makers would need to know exactly how oligopolists will respond to these subsidies and the fact is “economists do not have reliable models of how oligopolists behave.” Then there is the problem of entry. Even if a government does solve the empirical problem of anticipating and accurately responding to oligopolists, it “may still not be able to raise national income if the benefits of its intervention are dissipated by entry of additional firms.”

Krugman’s final two critiques are fascinating because they are precisely the sorts of concerns a George Mason economist might raise. First, there is what Hayek might call the information problem:

[T]o pursue a strategic trade policy successfully, a government must not only understand the effects of its policy on the targeted industry, which is difficult enough, but must also understand all the industries in the economy well enough that it can judge that an advantage gained here is worth advantage lost elsewhere. Therefore, the information burden is increased even further.

And finally, there is the public choice problem. At the international level, “In many (though not all) cases, a trade war between two interventionist governments will leave both countries worse off than if a hands-off approach were adopted by both.” And at the domestic level:

Governments do not necessarily act in the national interest, especially when making detailed microeconomic interventions. Instead, they are influenced by interest group pressures. The kinds of interventions that new trade theory suggests can raise national income will typically raise the welfare of small, fortunate groups by large amounts, while imposing costs on larger, more diffuse groups. The result, as with any microeconomic policy, can easily be that excessive or misguided intervention takes place because the beneficiaries have more knowledge and influence than the losers.

To this, one could add a host of problems that arise when governments privilege particular firms or industries.

Which (finally) brings me to the bottom line: the economic case remains strong that export subsidies to domestic firms like Boeing and GE end up costing American consumers, borrowers, and taxpayers more than they end up benefiting the privileged firms.

Delaware Senate votes to bail out three casinos

Delaware’s state senate has voted to redirect $10 billion in economic development funding to bail out three gambling casinos. The measure now goes to the House. Two reasons the casinos are failing: increased competition from Maryland and Pennsylvania and having to share a large chuck of revenue with the state. Lawmakers admit the bailout is only a “Band Aid,” and not enough to salvage the operations.

Supporters defend SB 220 as a jobs protection measure. But the real incentive is more likely the revenues involved. Lottery receipts are the fourth largest source of Delaware’s revenues at about 7 percent of the total bringing in $277 billion in 2013, right behind Income taxes, Franchise taxes, and Abandoned Property.

The casinos are certainly in trouble. According to Delaware Newszap.com Dover Downs Gaming & Entertainment saw a $1 million loss in Q1 2014 and is $46 million in debt. During that same first quarter the casino paid the state $16 million in revenue.

Revenue sharing between the state and the casinos has grown more onerous over the past 20 years. In 1997, the casino claimed 50.2 percent of the revenue and the state took 25.2 percent. In 2009, that split reversed, with the state claiming 43.5 percent of revenues and the casino keeping 37.8 percent.

The incentive for the bailout is fairly clear though the economic thinking is convoluted. Why not reduce the tax rate instead? Economist James Butkiewicz at the University of Delaware notes that as a voluntary tax it’s easy revenue and the state doesn’t have to raise taxes elsewhere.

But do casinos deliver for state coffers and economies?  Economists Douglas Walker (whose field is casino economics) and John Jackson find that while lotteries and horse racing tend to increase state revenues, casinos and greyhound racing tend to decrease it. Using recent data, Walker and Jackson find casinos have a positive economic impact. There are many other things to consider when thinking about the effects of casinos. As state creations there is ample opportunity for corruption and regulatory capture. Walker and Calcagno find just such a link in their paper in the journal Applied Economics (Dec 2013), “Casinos and Political Corruption in the United States: A Granger Causality Analysis.” And as a recent article by the WSJ notes oversaturation of casinos on the East Coast has also triggered an interstate “war” for revenues. Delaware’s gaming revenues are down 29 percent since 2011. A Delaware Casino Executive laments that the business model they are using is simply, “unworkable.”