Tag Archives: Washington

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

We don’t need more federal infrastructure spending

Many of the presidential candidates on both sides of the aisle have expressed interest in fixing America’s infrastructure, including Donald Trump, Hilary Clinton, and Bernie Sanders. All of them claim that America’s roads and bridges are crumbling and that more money, often in the form of tax increases, is needed before they fall into further disrepair.

The provision of basic infrastructure is one of the most economically sound purposes of government. Good roads, bridges, and ports facilitate economic transactions and the exchange of ideas which helps foster innovation and economic growth. There is certainly room to debate which level of government – federal, state, or local – should provide which type of infrastructure, but I want to start by examining US infrastructure spending over time. To hear the candidates talk one would think that infrastructure spending has fallen of a cliff. What else could explain the current derelict state?

A quick look at the data shows that this simply isn’t true. A 2015 CBO report on public spending on transportation and water infrastructure provides the following figure.

CBO us infrastructure spending

In inflation adjusted dollars (the top panel) infrastructure spending has exhibited a positive trend and was higher on average post 1992 after the completion of the interstate highway system. (By the way, the original estimate for the interstate system was $25 billion over 12 years and it ended up costing $114 billion over 35 years.)

The bottom panel shows that spending as a % of GDP has declined since the early 80s, but it has never been very high, topping out at approximately 6% in 1965. Since the top panel shows an increase in the level of spending, the decline relative to GDP is due to the government increasing spending in other areas over this time period, not cutting spending on infrastructure.

The increase in the level of spending over time is further revealed when looking at per capita spending. Using the data from the CBO report and US population data I created the following figure (dollars are adjusted for inflation and are in 2014 dollars).

infrastructure spend per cap

The top green line is total spending per capita, the middle red line is state and local spending with federal grants and loan subsidies subtracted out, and the bottom blue line is federal spending. Federal spending per capita has remained relatively flat while state and local spending experienced a big jump in the late 80s, which increased the total as well. This graph shows that the amount of infrastructure spending has largely increased when adjusted for inflation and population. It’s true that spending is down since the early 2000s but it’s still higher than at any point prior to the early 90s and higher than it was during the 35-year-construction of the interstate highway system.

Another interesting thing that jumps out is that state and local governments provide the bulk of infrastructure spending. The graph below depicts the percentage of total infrastructure spending that is done by state and local governments.

infrastructure spend state, local as percent of total

As shown in the graph state and local spending on infrastructure has accounted for roughly 75% of total infrastructure spending since the late 80s. Prior to that it averaged about 70% except for a dip to around 65% in the late 70s.

All of this data shows that the federal government – at least in terms of spending – has not ignored the country’s infrastructure over the last 50 plus years, despite the rhetoric one hears from the campaign trail. In fact, on a per capita basis total infrastructure spending has increased since the early 1980s, driven primarily by state and local governments.

And this brings up a second important point: state and local governments are and have always been the primary source of infrastructure spending. The federal government has historically played a small role in building and maintaining roads, bridges, and water infrastructure. And for good reason. As my colleague Veronique de Rugy has pointed out :

“…infrastructure spending by the federal government tends to suffer from massive cost overruns, waste, fraud, and abuse. As a result, many projects that look good on paper turn out to have much lower return on investments than planned.”

As evidence she notes that:

“According to the Danish researchers, American cost overruns reached on average $55 billion per year. This figure includes famous disasters like the Central Artery/Tunnel Project (CA/T), better known as the Boston Big Dig.22 By the time the Beantown highway project—the most expensive in American history—was completed in 2008 its price tag was a staggering $22 billion. The estimated cost in 1985 was $2.8 billion. The Big Dig also wrapped up 7 years behind schedule.”

Since state and local governments are doing the bulk of the financing anyway and most infrastructure is local in nature it is best to keep the federal government out as much as possible. States are also more likely to experiment with private methods of infrastructure funding. As de Rugy points out:

“…a number of states have started to finance and operate highways privately. In 1995, Virginia opened the Dulles Greenway, a 14-mile highway, paid for by private bond and equity issues. Similar private highway projects have been completed, or are being pursued, in California, Maryland, Minnesota, North Carolina, South Carolina, and Texas. In Indiana, Governor Mitch Daniels leased the highways and made a $4 billion profit for the state’s taxpayers. Consumers in Indiana were better off: the deal not only saved money, but the quality of the roads improved as they were run more efficiently.”

It remains an open question as to exactly how much more money should be devoted to America’s infrastructure. But even if the amount is substantial it’s not clear that the federal government needs to get any more involved than they already are. Infrastructure is largely a state and local issue and that is where the taxing and spending should take place, not in Washington D.C.

 

 

Fixing municipal finances in Pennsylvania

Last week I was a panelist at the Keystone Conference on Business and Policy. The panel was titled Fixing Municipal Finances and myself and the other panelists explained the current state of municipal finances in Pennsylvania, how the municipalities got into their present situation, and what they can do to turn things around. I think it was a productive discussion. To get a sense of what was discussed my opening remarks are below.

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Pennsylvania is the 6th most populous state in the US – just behind IL and in front of OH – and its population is growing.

PA population

But though Pennsylvania is growing, southern and western states are growing faster. According to the US census, from 2013 to 2014 seven of the ten fastest growing states were west of the Mississippi, and two of the remaining three were in the South (FL and SC). Only Washington D.C. at #5 was in the Northeast quadrant. Every state with the largest numeric increase was also in the west or the south. This is the latest evidence that the US population is shifting westward and southward, which has been a long term trend.

Urbanization is slowing down in the US as well. In 1950 only about 60% of the population lived in an urban area. In 2010 a little over 80% did. The 1 to 4 ratio appears to be close to the equilibrium, which means that city growth can no longer come at the expense of rural areas like it did throughout most of the 20th century.

urban, rural proportion

2012 census projections predict only 0.66% annual population growth for the US until 2043. The birth rate among white Americans is already below the replacement rate. Without immigration and the higher birth rates among recent immigrants the US population would be growing even slower, if not shrinking. This means that Pennsylvania cities that are losing population – Erie, Scranton, Altoona, Harrisburg and others – are going to have to attract residents from other cities in order to achieve any meaningful level of growth.

PA city populations

Fixing municipal finances ultimately means aligning costs with revenue. Thus a city that consistently runs a deficit has two options:

  1. Increase revenue
  2. Decrease costs

Municipalities must be vigilant in monitoring their costs since the revenue side is more difficult to control, much like with firms in the private sector. A city’s revenue base – taxpayers – is mobile. Taxpayers can leave if they feel like they are not getting value for their tax dollars, an issue that is largely endogenous to the city itself, or they can leave if another jurisdiction becomes relatively more attractive, which may be exogenous and out of the city’s control (e.g. air conditioning and the South, state policy, the decline of U.S. manufacturing/the economic growth of China, Japan, India, etc.). The aforementioned low natural population growth in the US precludes cities from increasing their tax base without significant levels of intercity migration.

What are the factors that affect location choice? Economist Ed Glaeser has stated that:

“In a service economy where transport costs are small and natural productive resources nearly irrelevant, weather and government stand as the features which should increasingly determine the location of people.” (Glaeser and Kohlhase (2004) p. 212.)

Pennsylvania’s weather is not the worst in the US, but it I don’t think anyone would argue that it’s the best either. The continued migration of people to the south and west reveal that many Americans like sunnier climates. And since PA municipalities cannot alter their weather, they will have to create an attractive fiscal and business environment in order to induce firms and residents to locate within their borders. Comparatively good government is a necessity for Pennsylvania municipalities that want to increase – or simply stabilize – their tax base. Local governments must also strictly monitor their costs, since mobile residents and firms who perceive that a government is being careless with their money can and will leave for greener – and sunnier – pastures.

Fixing municipal finances in Pennsylvania will involve more than just pension reform. Act 47 was passed by the general assembly in 1987 and created a framework for assisting distressed municipalities. Unfortunately, its effectiveness is questionable. Since 1987, 29 municipalities have been placed under Act 47, but only 10 have recovered and each took an average of 9.3 years to do so. Currently 19 municipalities are designated as distressed under Act 47 and 13 of the 19 are cities. Only one city has recovered in the history of Act 47 – the city of Nanticoke. The average duration of the municipalities currently under Act 47 is 16.5 years. The city of Aliquippa has been an Act 47 city since 1987 and is on its 6th recovery plan.

Act 47 bar graphAct 47 under pie chartAct 47 recovered pie chart

The majority of municipalities that have recovered from Act 47 status have been smaller boroughs (8 of 10). The average population of the recovered communities using the most recent data is 5,569 while the average population of the currently-under communities is 37,106. The population distribution for the under municipalities is skewed due to the presence of Pittsburgh, but even the median of the under cities is nearly double that of the recovered at 9,317 compared to 4,669.

Act 47 avg, med. population

This raises the question of whether Act 47 is an effective tool for dealing with larger municipalities that have comparatively larger problems and perhaps a more difficult time reaching a political/community consensus concerning what to do.

To attract new residents and increase revenue, local governments must give taxpayers/voters/residents a reason for choosing their city over the alternatives available. Economist Richard Wagner argues that governments are a lot like businesses. He states:

“In order to attract investors [residents, voters], politicians develop new programs and revise old programs in a continuing search to meet the competition, just as ordinary businesspeople do in ordinary commercial activity.” (American Federalism – How well does it support liberty? (2014))

Ultimately, local governments in Pennsylvania must provide exceptional long-term value for residents in order to make up for the place-specific amenities they lack. This is easier said than done, but I think it’s necessary to ensure the long-run solvency of Pennsylvania’s municipalities.

Scranton, PA and the failures of top-down planning

City officials in Scranton, PA are concerned that a recently released U.S. census map used as a basis for distributing federal grant money doesn’t reflect reality. The map was created using 2010 census data and identifies which neighborhoods meet the U.S. government’s criteria for low-to-moderate-income classification. Such neighborhoods are eligible to receive Community Development Block grant (CDBG) funding.

Scranton Councilman Wayne Evans stated that:

“A lot of us feel that the map is inaccurate, knowing the neighborhoods like we do,”

The city is hoping to conduct their own survey of the area and then use the results to petition the federal government to change the designations of the areas city officials believe are misclassified so they can receive funding.

This situation is a great example of the importance of local knowledge. Economist F.A. Hayek wrote the seminal paper on the importance of local knowledge in 1945. In his book Doing Bad by Doing Good, economist Chris Coyne builds on Hayek’s idea and defines the “planner’s problem” as “the inability of nonmarket participants to access relevant knowledge regarding how to allocate resources in a welfare-maximizing way in the face of a variety of competing, feasible alternatives.” The primary goal of the CDBG program is to create viable urban communities. In order to accomplish this a top-down planner needs to take certain steps: 1) the place to be developed needs to be identified and the goals of the development need to be established; 2) the availability of the resources needed for the development project needs to be confirmed and the resources need to be allocated; and 3) a feedback mechanism needs to be identified that can confirm that the goals are met. If any of these steps are not taken effective economic development will not occur.

As the example from Scranton shows, sometimes the planner – in this case the Department of Housing and Urban Development – fails to carry out step 1 effectively: Scranton officials and HUD can’t even agree on the place to be developed. Instead of letting the local officials who are knowledgeable about the area allocate the CDBGs, HUD officials in Washington bypass them by identifying the areas that need help via census data. Sometimes this approach might work, but when it doesn’t resources will be given to relatively prosperous areas while poorer areas are ignored.

The misallocation of resources will be an issue as long as the ability to allocate the funds is severed from the people with local knowledge of the communities. Cities and municipalities are receiving more and more of their revenues from the state and federal government, as seen in the graph below for Pennsylvania, and this contributes to situations like the one in Scranton.

PA intergov grants

As shown in the graph, total intergovernmental revenue and state intergovernmental to local governments in Pennsylvania increased in real terms from 1992 to 2012 (measured on the left vertical axis). In 1992, total intergovernmental revenue to local governments was equal to 59% of the revenue that local governments raised on their own (the orange line measured on the right vertical axis). In 2012 it was equal to 69%, an increase of 10 percentage points. This means that local governments became more dependent on higher-level governments for funding.

Funding from higher-level governments usually comes with restrictions and conditions that must be met, which prevents local citizens from using their local knowledge to alleviate the problems in their community. The further away decisions makers are from the region, the more likely they are to misidentify the problem areas. In Scranton’s case, city officials now have to expend scarce resources conducting their own survey and petitioning the federal government to change the neighborhood classifications.

Local knowledge is important and it should be utilized by decision makers. State and federal governments should limit intergovernmental transfers and allow local communities to keep more of their own tax dollars, which they can then use to address their own local issues.

State government spending hits new heights

There is a large literature in macroeconomics that examines the extent to which federal spending “crowds out” investment in the private sector. Basic theory and common sense lead to the conclusion that government spending must replace some private sector spending. After all, dollars are scarce – if the government taxes Paul and uses his money to build a road Paul necessarily has less money to invest in his landscaping business. In theory government spending on public goods like roads could be a net gain. This would occur if the additional value produced by spending one more dollar on roads was greater than the additional value produced by investing one more dollar in Paul’s landscaping business. But even in this scenario, Paul himself may be worse off – he’s one dollar poorer and he may not use the new road – and there is still a dead-weight loss due to the tax.

In reality, the federal government does a lot more than build roads, especially productive ones. In 2014, only 1.9% of federal income tax revenue was spent on transportation. And most of the other stuff that the government does is way less productive, like shuffling money around via entitlement programs – Medicare, Medicaid, and Social Security – and investing in businesses that later go bankrupt like Solyndra. So while it is possible that a dollar spent by the government is more productive than a dollar spent by a guy like Paul, in a country with America’s spending habits it’s unlikely to be the case.

The same crowding out that occurs at the federal level can occur at the state level. In fact, in many states state spending as a percentage of gross state product (GSP) exceeds federal spending as a percentage of GDP. The graph below shows state spending as a percentage of GSP for all 50 states and Washington D.C. in 1970, 1990, and 2012 (data). The red, dashed line is federal spending as a percentage of GDP in 2012 (21.9%).

state spending gsp graph

As shown in the graph, nearly every state increased their spending relative to GSP from 1970 – 2012 (triangles are above the X’s). Only one state, South Dakota, had lower spending relative to GSP in 2012 than in 1970. In 2012, 15 of the 50 states spent more as a percentage of GSP than the federal government spent as a percentage of GDP (states where the triangle is above the red, dashed line). In 1990 only two states, Arizona and Montana, spent at that level.

It used to be the case that state and local spending was primarily focused on classic government services like roads, water/sewer systems, police officers, firemen, and K-12 education. But state spending is increasingly looking similar to federal spending. Redistributive public welfare expenditures and pension expenditures have increased substantially since 1992. As an example, the tables below provide a breakdown of some key spending areas for two states, Ohio and Pennsylvania, in 1992 and 2012 (1992 data here, 2012 data here). The dollar per capita amounts are adjusted for inflation and are in 2009 dollars.

ohio spending table

penn spending table

As the tables show, spending on public welfare, hospitals, and health increased by 120% in Ohio and 86% in Pennsylvania from 1992 to 2012. Pension expenditures increased by 83% and 125% respectively. And contrary to what many politicians and media types say, funding for higher education – the large majority of state education spending is on higher education – increased dramatically during this time period; up 250% in Ohio and 199% in Pennsylvania. Meanwhile, funding for highways – the classic public good that politicians everywhere insist wouldn’t exist without them – has increased by a much smaller amount in both states.

The state spending increases of the recent past are being driven in large part by public welfare programs that redistribute money, pensions for government employees, and higher education. While one could argue that higher education spending is a productive public investment (Milton Friedman didn’t think so and I agree) it is hard to make a case that public welfare and pension payments are good investments. This alone doesn’t mean that society shouldn’t provide those things. Other factors like equity and economic security might be more important to some people than economic productivity. But this does make it unlikely that the marginal dollar spent by a state government today is as economically productive as that dollar spent in the private sector. Like federal spending, state spending is likely crowding out productive private investment, which will ultimately lower output and economic growth in the long run.

Education, Innovation, and Urban Growth

One of the strongest predictors of urban growth since the start of the 20th century is the skill level of a city’s population. Cities that have a highly skilled population, usually measured as the share of the population with a bachelor’s degree or more, tend to grow faster than similar cities with less educated populations. This is true at both the metropolitan level and the city level. The figure below plots the population growth of 30 large U.S. cities from 1970 – 2013 on the vertical axis and the share of the city’s 25 and over population that had at least a bachelor’s degree in 1967 on the horizontal axis. (The education data for the cities are here. I am using the political city’s population growth and the share of the central city population with a bachelor’s degree or more from the census data linked to above.)

BA, city growth 1

As shown in the figure there is a strong, positive relationship between the two variables: The correlation coefficient is 0.61. It is well known that over the last 50 years cities in warmer areas have been growing while cities in colder areas have been shrinking, but in this sample the cities in warmer areas also tended to have a better educated population in 1967. Many of the cities known today for their highly educated populations, such as Seattle, San Francisco, and Washington D.C., also had highly educated populations in 1967. Colder manufacturing cities such as Detroit, Buffalo, and Newark had less educated workforces in 1967 and subsequently less population growth.

The above figure uses data on both warm and cold cities, but the relationship holds for only cold cities as well. Below is the same graph but only depicts cities that have a January mean temperature below 40°F. Twenty out of the 30 cities fit this criteria.

BA, city growth 2

Again, there is a strong, positive relationship. In fact it is even stronger; the correlation coefficient is 0.68. Most of the cities in the graph lost population from 1970 – 2013, but the cities that did grow, such as Columbus, Seattle, and Denver, all had relatively educated populations in 1967.

There are several reasons why an educated population and urban population growth are correlated. One is that a faster accumulation of skills and human capital spillovers in cities increase wages which attracts workers. Also, the large number of specialized employers located in cities makes it easier for workers, especially high-skill workers, to find employment. Cities are also home to a range of consumption amenities that attract educated people, such as a wide variety of shops, restaurants, museums, and sporting events.

Another reason why an educated workforce may actually cause city growth has to do with its ability to adjust and innovate. On average, educated workers tend to be more innovative and better able to learn new skills. When there is an negative, exogenous shock to an industry, such as the decline of the automobile industry or the steel industry, educated workers can learn new skills and create new industries to replace the old ones. Many of the mid-20th century workers in Detroit and other Midwestern cities decided to forego higher education because good paying factory jobs were plentiful. When manufacturing declined those workers had a difficult time learning new skills. Also, the large firms that dominated the economic landscape, such as Ford, did not support entrepreneurial thinking. This meant that even the educated workers were not prepared to create new businesses.

Local politicians often want to protect local firms in certain industries through favorable treatment and regulation. But often this protection harms newer, innovative firms since they are forced to compete with the older firms on an uneven playing field. Political favoritism fosters a stagnant economy since in the short-run established firms thrive at the expense of newer, more innovative startups. Famous political statements such as “What’s good for General Motors is good for the country” helped mislead workers into thinking that government was willing and able to protect their employers. But governments at all levels were unable to stop the economic forces that battered U.S. manufacturing.

To thrive in the 21st century local politicians need to foster economic environments that encourage innovation and ingenuity. The successful cities of the future will be those that are best able to innovate and to adapt in an increasingly complex world. History has shown us that an educated and entrepreneurial workforce is capable of overcoming economic challenges, but to do this people need to be free to innovate and create. Stringent land-use regulations, overly-burdensome occupational licensing, certificate-of-need laws, and other unnecessary regulations create barriers to innovation and make it more difficult for entrepreneurs to create the firms and industries of the future.

Local land-use restrictions harm everyone

In a recent NBER working paper, authors Enrico Moretti and Chang-Tai Hsieh analyze how the growth of cities determines the growth of nations. They use data on 220 MSAs from 1964 – 2009 to estimate the contribution of each city to US national GDP growth. They compare what they call the accounting estimate to the model-driven estimate. The accounting estimate is the simple way of attributing city nominal GDP growth to national GDP growth in that it doesn’t account for whether the increase in city GDP is due to higher nominal wages or increased output caused by an increase in local employment. The model-driven estimate that they compare it to distinguishes between these two factors.

Before I go any further it is important to explain the theory behind the author’s empirical findings. Suppose there is a productivity shock to City A such that workers in City A are more productive than they were previously. This productivity shock could be the result of a new method of production or a newly invented piece of equipment (capital) that helps workers make more stuff with a given amount of labor. This productivity shock will increase the local demand for labor which will increase the wage.

Now one of two things can happen and the diagram below depicts the two scenarios. The supply and demand lines are those for workers, with the wage on the Y-axis and the amount of workers on the X-axis. Since more workers lead to more output I also labeled labor as L = αY, where α is some fraction less than 1 to signify that each additional unit of labor doesn’t lead to a one unit increase in output, but rather some fraction of 1 unit (capital is needed too).

moretti, land use pic

City A can have a highly elastic supply of housing, meaning that it is easy to expand the number of housing units in that city and thus it is relatively easy for people to move there. This would mean that the supply of labor is like S-elastic in the diagram. Thus the number of workers that are able to migrate to City A after labor demand increases (D1 to D2) is large, local employment increases (Le > L*), and total output (GDP) increases. Wages only increase a little bit (We > W*). In this situation the productivity shock would have a relatively large effect on national GDP since it resulted in a large increase in local output as workers moved from relatively low-productivity cities to the relatively high-productivity City A.

Alternatively, the supply of housing in City A could be very inelastic; this would be like S-inelastic. If that is the case, then the productivity shock would still increase the wage in City A (Wi > W*), but it will be more difficult for new workers to move in since new housing cannot be built to shelter them. In this case wages increase but since total local employment stays fairly constant due to the restriction on available housing the increase in output is not as large (Li > L* but < Le). If City A output stays relatively constant and instead the productivity shock is expressed in higher nominal wages, then the resulting growth in City A nominal GDP will not have as large of an effect on national output growth.

As an example, Moretti and Hsieh calculate that the growth of New York City’s GDP was 12% of national GDP growth from 1964-2009. But when accounting for the change in wages, New York’s contribution to national output growth was only 5%: Most of New York’s GDP growth was manifested in higher nominal wages. This is not surprising as it is well known that New York has strict housing regulations that make it difficult to build new housing units (the recent extension of NYC rent-control laws won’t help). This makes it difficult for people to relocate from relatively low-productivity places to a high-productivity New York.

In three of the most intensely land-regulated cities: New York, San Francisco, and San Jose, the accounting contribution to national GDP growth was 19.3%. But these cities actual contribution to national output as estimated by the authors was only 6.1%. Contrast that with the Rust Belt cities (e.g. Detroit, Pittsburgh, Cleveland, etc.) which contributed -28.5% according to the accounting method but +6.1% according to the author’s model.

The authors conclude that less onerous land-use restrictions in high-productivity cities New York, Washington D.C., Boston, San Francisco, San Jose, and the rest of Silicon Valley could increase the nation’s output growth rate by making it easier for workers to migrate from low to high-productivity areas. In an extreme migration scenario where 52% of American workers in 2009 lived in a different city than they actually did, the author’s calculate that GDP per worker would have been $8,775 higher in 2009, or $6,345 per person. In a more realistic scenario (only 20% of workers lived in a different city) it would have been $3,055 more per person: That is a substantial increase.

While I agree with the author’s conclusion that less land-use restrictions would result in a more productive allocation of labor and thus more stuff for all of us, the author’s policy prescriptions at the end of the paper leave much to be desired.  They propose that the federal government constrain the ability of municipalities to set land-use restrictions since these restrictions impose negative externalities on the rest of the country if the form of lowering national output growth. They also support the use of government funded high-speed rail to link  low-productivity labor markets to high-productivity labor markets e.g. the current high-speed rail construction project taking place in California could help workers get form low productivity areas like Stockton, Fresno, and Modesto, to high productivity areas in Silicon Valley.

Land-use restrictions are a problem in many areas, but not a problem that warrants arbitrary federal involvement. If federal involvement simply meant the Supreme Court ruling that land-use regulations (or at least most of them) are unconstitutional then I think that would be beneficial; a broad removal of land-use restrictions would go a long way towards reinstituting the institution of private property. Unfortunately, I don’t think that is what Moretti and Hsieh had in mind.

Arbitrary federal involvement in striking down local land-use regulations would further infringe on federalism and create opportunities for political cronyism. Whatever federal bureaucracy was put in charge of monitoring land-use restrictions would have little local knowledge of the situation. The Environmental Protection Agency (EPA) already monitors some local land use and faulty information along with an expensive appeals process creates problems for residents simply trying to use their own property. Creating a whole federal bureaucracy tasked with picking and choosing which land-use restrictions are acceptable and which aren’t would no doubt lead to more of these types of situations as well as increase the opportunities for regulatory activism. Also, federal land-use regulators may target certain areas that have governors or mayors who don’t agree with them on other issues.

As for more public transportation spending, I think the record speaks for itself – see here, here, and here.

No, bailouts are not something to celebrate

Robert Samuelson at the Washington Post is celebrating the auto bailout.

Last December I had a piece in the Post in which I argued that “pro-business” policies like bailouts are actually bad for business. I offered five reasons:

  1. Pro-business policies undermine competition.
  2. They retard innovation
  3. They sucker workers into unsustainable careers.
  4. They encourage wasteful privilege seeking.
  5. They undermine the legitimacy of government and business.

Read my piece for the full argument.

But aren’t things different in the midst of a major economic and financial crisis? Shouldn’t we have more leeway for bailouts in exigent circumstances?

No. Here is why:

First, we should always remember that the concentrated beneficiaries of a bailout have every incentive to overstate its necessity while the diffuse interests that pay for it (other borrowers, taxpayers, un-favored competitors, and the future inheritors of a less dynamic and less competitive economy) have almost no incentive or ability to get organized and lobby against it.

Bailout proponents talk as if they know bailouts avert certain calamity. But the truth is that we can never know exactly what would have happened without a bailout. We can, however, draw on both economic theory and past experience. And both suggest that the macroeconomy of a world without bailouts is actually more stable than one with bailouts. This is because bailouts incentivize excessive risk (and, importantly, correlated risk taking). Moreover, because the bailout vs. no bailout call is inherently arbitrary, bailouts generate uncertainty.

Todd Zywicki at GMU law argues convincingly that normal bankruptcy proceedings would have worked just fine in the case of the autos.

Moreover, as Garett Jones and Katelyn Christ explain, alternative options like “speed bankruptcy” (aka debt-to-equity swaps) offer better ways to improve the health of institutions without completely letting creditors off the hook. This isn’t just blind speculation. The EU used this approach in its “bail in” of Cyprus and it seems to have worked pretty well.

Ironically, one can make a reasonable case that many (most?) bailouts are themselves the result of previous bailouts. The 1979 bailout of Chrysler taught a valuable lesson to the big 3 automakers and their creditors. It showed them that Washington would do whatever it took to save them. That, and decades of other privileges allowed the auto makers to ignore both customers and market realities.

Indeed, at least some of the blame for the entire 2008 debacle falls on the ‘too big to fail’ expectation that systematically encouraged most large financial firms to leverage up. While it was hardly the only factor, the successive bailouts of Continental Illinois (1984), the S&Ls (1990s), the implicit guarantee of the GSEs, etc., likely exacerbated the severity of the 2008 financial crisis. So a good cost-benefit analysis of any bailout should include some probability that it will encourage future excessive risk taking, and future calls for more bailouts. Once these additional costs are accounted for, bailouts look like significantly worse deals.

Adherence to the “rule of law” is more important in a crisis than it is in normal times. Constitutional prohibitions, statutory limits, and even political taboos are typically not needed in “easy cases.” It is the hard cases that make for bad precedent.

The Sharing Economy and Consumer Protection

(It has been a busy few weeks and I haven’t had much time for blogging).

In early December, my colleagues Chris Koopman, Adam Thierer, and I published a piece on the sharing economy and consumer protection regulation. Here is a summary.

A few days later, I was on the Diane Rehm Show talking about the sharing economy with Alvaro Bedoya (@alvarombedoya) and Nancy Scola (@nancyscola). Alvaro is the executive director of the Center on Privacy and Technology at Georgetown University Law School and Nancy is a reporter covering the intersections of technology and public policy, politics, and governance for The Washington Post.

During the course of our conversation, Diane also spoke with Sunil Paul, the co-founder and CEO of Sidecar and with Donna Blythe-Shaw, the spokesperson for the Boston Taxi Drivers’ Association.

It was a great conversation and I very much enjoyed meeting Diane, Alvaro and Nancy.

You can listen to it here.

Also check out Adam’s comments on the sharing economy at a Congressional Internet Caucus Advisory Committee here.

What to expect from a lame duck

Two weeks ago, I sat down with CSPAN’s Greta Wodele Brawner to talk about “lame duck” sessions of Congress. Drawing on my research with colleagues Chris Koopman and Emily Washington, we discussed the ways in which roll call voting patterns differ during lame duck sessions compared with ordinary sessions.

A few times I struck a relatively upbeat tone about what might get accomplished in the next two years. Only two weeks old, I worry that some of these comments already seem wildly optimistic. Let me know what you think.