Tag Archives: research

The unseen costs of Amazon’s HQ2 Site Selection

Earlier this year Amazon narrowed down the list of potential cities to site its second headquarters. Applicants are now waiting out the selection process. It’s unclear when Amazon will make its choice, but that hasn’t stopped many from speculating who the likely contenders are. Varying sources report Atlanta, Boston, and Washington D.C. at the top of the list. The cities that didn’t make the cut are no doubt envious of the finalists, having just missed out on the potential for a $5 billion facility and 50,000 jobs. The second HQ is supposed to be as significant for economic growth as the company’s first site, which according to Amazon’s calculations contributed an additional $38 billion to Seattle’s economy between 2010 and 2016. There is clearly a lot to be gained by the winner.  But there are also many costs. Whichever city ends up winning the bid will be changed forever. What’s left out of the discussion is how the bidding process and corporate incentives affect the country.

Although the details of the proposals are not made public, each finalist is likely offering some combination of tax breaks, subsidies, and other incentives in return for the company’s choice to locate in their city. The very bidding process necessitates a lot of time and effort by many parties. It will certainly seem “worth it” to the winning party, but the losers aren’t getting back the time and effort they spent.

This practice of offering incentives for businesses has been employed by states and localities for decades, with increased usage over time. Targeted economic development incentives can take the form of tax exemptions, abatements, regulatory relief, and taxpayer assistance. They are but one explicit cost paid by states and cities looking to secure business, and there is a growing literature that suggests these policies are more costly than meets the eye.

First, there’s the issue of economic freedom. Recent Mercatus research suggests that there may be a tradeoff to offering economic development incentives like the ones that Amazon is receiving. Economists John Dove and Daniel Sutter find that states that spend more on targeted development incentives as a percentage of gross state product also have less overall economic freedom. The theoretical reasoning behind this is not very clear, but Dove and Sutter propose that it could be because state governments that use more subsidies or tax breaks to attract businesses will also spend more or raise taxes for everyone else in their state, resulting in less equitable treatment of their citizens and reducing overall economic freedom.

The authors define an area as having more economic freedom if it has lower levels of government spending, taxation, and labor market restrictions. They use the Fraser Institute’s Economic Freedom of North America Index (EFNA) to measure this. Of the three areas within the EFNA index, labor market freedom is the most affected by targeted economic development incentives. This means that labor market regulation such as the minimum wage, government employment, and union density are all significantly related to the use of targeted incentives.

Economic freedom can be ambiguous, however, and it’s sometimes hard to really grasp its impact on our lives. It sounds nice in theory, but because of its vagueness, it may not seem as appealing as a tangible economic development incentive package and the corresponding business attached to it. Economic freedom is associated with a series of other, more tangible benefits, including higher levels of income and faster economic growth. There’s also evidence that greater economic freedom is associated with urban development.

Not only is the practice of offering targeted incentives associated with lower economic freedom, but it is also indicative of other issues. Economists Peter Calcagno and Frank Hefner have found that states with budget issues, high tax and regulatory burdens, and poorly trained labor forces are also more likely to offer targeted incentives as a way to offset costly economic conditions. Or, in other words, targeted development incentives can be – and often are – used to compensate for a less than ideal business climate. Rather than reform preexisting fiscal or regulatory issues within a state, the status quo and the use of targeted incentives is the more politically feasible option.

Perhaps the most concerning aspect of Amazon’s bidding process is the effect it has on our culture. Ideally, economic development policy should be determined by healthy economic competition between states. In practice, it has evolved into more of an unhealthy interaction between private interests and political favor. Economists Joshua Jansa and Virginia Gray refer to this as cultural capture. They find increases in business political contributions to be positively correlated with state subsidy spending. Additionally, they express concern over the types of firms that these subsidies attract. There is a selection bias for targeted incentives to systematically favor “flighty firms” or firms that will simply relocate if better subsidies are offered by another state, or potentially threaten to leave in an effort to extract more subsidies.

None of these concerns even address the question of whether targeted incentives actually achieve their intended goals.  The evidence does not look good. In a review of the literature by my colleague Matthew Mitchell, and me, we found that of the studies that evaluate the effect of targeted incentives on the broader economy, only one study found a positive effect, whereas four studies found unanimously negative effects. Thirteen studies (half of the sample) found no statistically significant effect, and the remaining papers found mixed results in which some companies or industries won, but at the expense of others.

In addition to these unseen costs on the economy, some critics are beginning to question whether being chosen by Amazon is even worth it. Amazon’s first headquarters has been considered a catalyst for the city’s tech industry, but local government and business leaders have raised concerns about other possibly related issues such as gentrification, rising housing prices, and persistent construction and traffic congestion. There is less research on this, but it is worth considering.

It is up to each city’s policymakers to decide whether these trade-offs are worth it. I would argue, however, that much of the evidence points to targeted incentives – like the ones that cities are using to attract Amazon’s business – as having more costs than benefits. Targeted economic development incentives may seem to offer a lot of tangible benefits, but their unseen costs should not be overlooked. From the perspective of how they benefit each state’s economy as a whole, targeted incentives are detrimental to economic freedom as well as our culture surrounding corporate handouts. Last but not least, they may often be an attempt to cover up other issues that are unattractive to businesses.

Graduate School Opportunities Available Through Mercatus

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

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

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

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Mercatus PhD Fellowship

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

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

Mercatus MA Fellowship

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

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

Mercatus Adam Smith Fellowship

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

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

Mercatus Frédéric Bastiat Fellowship

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

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

 

 

What’s going on with Alaska’s budget?

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

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

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

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

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

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

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

alaska-revenues-exp4.5.17

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

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

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

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

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

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

alaska-spendinggrowth4.5.17

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

What should Alaska do?

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

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

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

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

An Overview of the Virginia State Budget and Economy

By Adam Millsap and Thomas Savidge

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

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

Government Overview: Expenditures and Revenue

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

VA expend and rev 2006-16

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

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

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

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

VA expend by category 2006-16

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

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

Virginia Economic Growth & County Personal Income

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

VA GDP 2006-15

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

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

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

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

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

VA county pers. inc. map

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

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

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

US county pers. inc. map

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

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

Conclusion:

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

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


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

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

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

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

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

geography of inventiveness 1940

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

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

innovation, long run growth US states

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

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

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

pop density, innovation 1940-1960

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

innovation, bank deposits 1920-1940

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

innovation, transport costs 1920-1940

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

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

innovation, slavery 1880-1940

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

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

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

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

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

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

innovation, inc inequality 1920-1940

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

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

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

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

innovation, social mobility 1940

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

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

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

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

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

Decreasing congestion with driverless cars

Traffic is aggravating. Especially for San Francisco residents. According to Texas A&M Transportation Institute, traffic congestion in the San Francisco-Oakland CA area costs the average auto commuter 78 hours per year in extra travel time, $1,675 for their travel time delays, and an extra 33 gallons of gas compared to free-flow traffic conditions. That means the average commuter spends more than three full days stuck in traffic each year. Unfortunately for these commuters, a potential solution to their problems just left town.

Last month, after California officials told Uber to stop its pilot self-driving car program because it lacked the necessary state permits for autonomous driving, Uber decided to relocate the program from San Francisco to Phoenix, Arizona. In an attempt to alleviate safety concerns, these self-driving cars are not yet driverless, but they do have the potential to reduce the number of cars on the road. Other companies like Google, Tesla, and Ford have expressed plans to develop similar technologies, and some experts predict that completely driverless cars will be on the road by 2021.

Until then, however, cities like San Francisco will continue to suffer from the most severe congestion in the country. Commuters in these cities experience serious delays, higher gasoline usage, and lost time behind the wheel. If you live in any of these areas, you are probably very familiar with the mind-numbing effect of sitting through sluggish traffic.

It shouldn’t be surprising then that these costs could culminate into a larger problem for economic growth. New Mercatus research finds that traffic congestion can significantly harm economic growth and concludes with optimistic predictions for how autonomous vehicle usage could help.

Brookings Senior Fellow Clifford Winston and Yale JD candidate Quentin Karpilow find significant negative effects of traffic congestion on the growth rates of California counties’ gross domestic product (GDP), employment, wages, and commodity freight flows. They find that a 10% reduction in congestion in a California urban area increases both job and GDP growth by roughly 0.25% and wage growth to increase by approximately 0.18%.

This is the first comprehensive model built to understand how traffic harms the economy, and it builds on past research that has found that highway congestion leads to slower job growth. Similarly, congestion in West Coast ports, which occurs while dockworkers and marine terminal employers negotiate contracts, has caused perishable commodities to go bad, resulting in a 0.2 percentage point reduction in GDP during the first quarter of 2015.

There are two main ways to solve the congestion problem; either by reducing the number of cars on the road or by increasing road capacity. Economists have found that the “build more roads” method in application has actually been quite wasteful and usually only induces additional highway traffic that quickly fills the new road capacity.

A common proposal for the alternative method of reducing the number of cars on the road is to implement congestion pricing, or highway tolls that change based on the number of drivers using the road. Increasing the cost of travel during peak travel times incentivizes drivers to think more strategically about when they plan their trips; usually shifting less essential trips to a different time or by carpooling. Another Mercatus study finds that different forms of congestion pricing have been effective at reducing traffic congestion internationally in London and Stockholm as well as for cities in Southern California.

The main drawback of this proposal, however, is the political difficulty of implementation, especially with interstate highways that involve more than one jurisdiction to approve it. Even though surveys show that drivers generally change their mind towards supporting congestion pricing after they experience the lower congestion that results from tolling, getting them on board in the first place can be difficult.

Those skeptical of congestion pricing, or merely looking for a less challenging policy to implement, should look forward to the new growing technology of driverless cars. The authors of the recent Mercatus study, Winston and Karpilow, find that the adoption of autonomous vehicles could have large macroeconomic stimulative effects.

For California specifically, even if just half of vehicles became driverless, this would create nearly 350,000 additional jobs, increase the state’s GDP by $35 billion, and raise workers’ earnings nearly $15 billion. Extrapolating this to the whole country, this could add at least 3 million jobs, raise the nation’s annual growth rate 1.8 percentage points, and raise annual labor earnings more than $100 billion.

What would this mean for the most congested cities? Using Winston and Karpilow’s estimates, I calculated how reduced congestion from increased autonomous car usage could affect Metropolitan Statistical Areas (MSAs) that include New York City, Los Angeles, Boston, San Francisco, and the DC area. The first chart shows the number of jobs that would have been added in 2011 if 50% of motor vehicles had been driverless. The second chart shows how this would affect real GDP per capita, revealing that the San Francisco MSA would have the most to gain, but with the others following close behind.

jobsadd_autonomousvehicles realgdp_autonomousvehicles

As with any new technology, there is uncertainty with how exactly autonomous cars will be fully developed and integrated into cities. But with pilot programs already being implemented by Uber in Pittsburgh and nuTonomy in Singapore, it is becoming clear that the technology’s efficacy is growing.

With approximately $1,332 GDP per capita and 45,318 potential jobs on the table for the San Francisco Metropolitan Statistical Area, it is a shame that San Francisco just missed a chance to realize some of these gains and to be at the forefront of driving progress in autonomous vehicle implementation.

Eight years after the financial crisis: lessons from the most fiscally distressed cities

You’d think that eight years after the financial crisis, cities would have recovered. Instead, declining tax revenues following the economic downturn paired with growing liabilities have slowed recovery. Some cities exacerbated their situations with poor policy choices. Much could be learned by studying how city officials manage their finances in response to fiscal crises.

Detroit made history in 2013 when it became the largest city to declare bankruptcy after decades of financial struggle. Other cities like Stockton and San Bernardino in California had their own financial battles that also resulted in bankruptcy. Their policy decisions reflect the most extreme responses to fiscal crises.

You could probably count on both hands how many cities file for bankruptcy each year, but this is not an extremely telling statistic as cities often take many other steps to alleviate budget problems and view bankruptcy as a last resort. When times get tough, city officials often reduce payments into their pension systems, raise taxes – or when that doesn’t seem adequate – find themselves cutting services or laying off public workers.

It turns out that many municipalities weathered the 2008 recession without needing to take such extreme actions. Studying how these cities managed to recover more quickly than cities like Stockton provides interesting insight on what courses of action can help city officials better respond to fiscal distress.

A new Mercatus study examines the types of actions that public officials have taken under fiscal distress and then concludes with recommendations that could help future crises from occurring. Their empirical model finds that increased reserves, lower debt, and better tax structures all significantly improve a city’s fiscal health.

The authors, researchers Evgenia Gorina and Craig Maher, define fiscal distress as:

“the condition of local finances that does not permit the government to provide public services and meet its own operating needs to the extent to which these have been provided and met previously.”

In order to determine whether a city or county government is under fiscal distress, the authors study the actual actions taken by city officials between 2007 and 2012. Their approach is unique because it stands in contrast with previous literature that primarily looks to poorly performing financial indicators to measure fiscal distress. An example of such an indicator would be how much cash a government has on hand relative to its liabilities.

Although financial indicators can tell someone a lot about the fiscal condition of their locality, they are only a snapshot of financial resources on hand and don’t provide information on how previous policy choices got them to their current state. A robust analysis of a city’s financial health would require a deeper look. Looking at policy decisions as well as financial indicators can paint a more complete picture of just how financial resources are being managed.

The figure here displays the types of actions, or “fiscal distress episodes”, that the authors of the study found were the most common among cities in California, Michigan, and Pennsylvania. As expected, you’ll see that bankruptcy occurs much less frequently than other courses of action. The top three most common attempts to meet fundamental operating needs and service requirements during times of fiscal distress include (1) large across-the-board budget cuts or cuts in services, (2) blanket reduction in employee salaries, and (3) unusual tax rate or fee increases.

fiscal-distress-episodes

Another thing that becomes clear from this figure is that public workers and taxpayers appear to be adversely affected by the most common fiscal episodes. Cuts in services, reductions in employee salaries, large tax increases, and layoffs all place much of the distress on these groups. By contrast, actions like fund transfers, deferring capital projects, or late budget enactment don’t directly affect public workers or taxpayers (at least in the short term).

I decided to break down how episodes affected public workers and taxpayers for each state examined in the sample. 91% of California’s municipal fiscal distress episodes directly affected public employees or the provision of public services, while the remaining 9% indirectly affected them. Michigan and Pennsylvania followed with 85% and 66% of episodes, respectively, directly affecting public workers or taxpayers through cuts in services, tax increases, or layoffs.

Many of these actions surely happen in tandem with each other in more distressed cities, but it seems that more often than not, the burden falls heavily on public workers and taxpayers.

The city officials who had to make these hard decisions obviously did so under financially and politically intense circumstances; what many, including researchers like Gorina and Maher, consider to be a fiscal crisis. In fact, 32 percent of the communities across the three states in their sample experienced fiscal distress which, on its own, sheds light on the magnitude of the 2007-2009 recession. A large motivator of Gorina and Maher’s research is to understand what characteristics of the cities who more quickly rebounded from the Great Recession allowed them to prevent hitting fiscal crisis stage in the first place.

They do so by testing the effect of a city’s pre-existing fiscal condition on their likelihood to undergo fiscal distress. After controlling for things like government type, size, and local economic factors, they found that cities that had larger reserves and lower debt tended to weather the recession better relative to other cities. More specifically, declining general revenue balance as a percent of general expenditures and increases in debt as a share of total revenue both increase the odds of fiscal distress for a city.

Additionally, the authors found that cities with a greater reliance on property taxes managed to weather the recession better than governments reliant on other revenue sources. This suggests that revenue structure, not just the amount of revenue raised, is an important determinant of fiscal health.

No city wants to end up like Detroit or Scranton. Policymakers in these cities were forced to make hard choices that were politically unpopular; often harming public employees and taxpayers. Officials can look to Gorina and Maher’s research to understand how they can prevent ending up in such dire situations.

When approaching municipal finances, each city’s unique situation should of course be taken into consideration. This requires looking at each city’s economic history and financial practices, similar to what my colleagues have done for Scranton. Combining each city’s financial context with principles of sound financial management can surely help more cities find and maintain a healthy fiscal path.

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?

 

 

Does Tax Increment Financing (TIF) generate economic development?

Tax increment financing, or TIF, is a method of financing economic development projects first used in California in 1952. Since then, 48 other states have enacted TIF legislation with Arizona being the lone holdout. It was originally conceived as a method for combating urban blight, but over time it has become the go-to tool for local politicians pushing economic development in general. For example, Baltimore is considering using TIF to raise $535 million to help Under Armor founder Kevin Plank develop Port Covington.

So how does TIF work? Though the particulars can vary by state, the basic mechanism is usually similar. First, an area is designated as a TIF district. TIF districts are mostly industrial or commercial areas rather than residential areas since the goal is to encourage economic development.

Usually, in an effort to ensure that TIF is used appropriately, the municipal government that designates the area as a TIF has to assert that economic development would not take place absent the TIF designation and subsequent investment. This is known as the ‘but-for’ test, since the argument is that development would not occur but for the TIF. Though the ‘but-for’ test is still applied, some argue that it is largely pro forma.

Once an area has been designated as a TIF district, the property values in the area are assessed in order to create a baseline value. The current property tax rate is applied to the baseline assessed value to determine the amount of revenue that is used for the provision of local government goods and services (roads, police, fire, water etc.). This value will then be frozen for a set period of time (e.g. up to 30 years in North Carolina), and any increase in assessed property values that occurs after this time and the subsequent revenue generated will be used to pay for the economic development project(s) in the TIF district.

The key idea is that municipalities can borrow against the projected property value increases in order to pay for current economic development projects. A simple numerical example will help clarify how TIF works.

In the table below there are five years. In year 1 the assessed value of the property in the TIF district is $20 million and it is determined that it takes $1 million per year to provide the government goods and services needed in the area (road maintenance, sewage lines, police/fire protection, etc.). A tax rate of 5% is applied to the $20 million of assessed value to raise the necessary $1 million (Tax revenue column).

TIF example table

The municipality issues bonds totaling $1 million to invest in an economic development project in the TIF district. As an example, let’s say the project is renovating an old business park in order to make it more attractive to 21st century startups. The plan is that improving the business park will make the area more desirable and increase the property values in the TIF district. As the assessed value increases the extra tax revenue raised by applying the 5% rate to the incremental value of the property will be used to pay off the bonds (incremental revenue column).

Meanwhile, the $1 million required for providing the government goods and services will remain intact, since only the incremental increase in assessed value is used to pay for the business park improvements. Hence the term Tax Increment Financing.

As shown in the table, if the assessed value of the property increases by $2 million per year for 4 years the municipality will recoup the $1 million required to amortize the bond (I’m omitting interest to keep it simple). Each $1 million dollars of increased value increase tax revenue by $50,000 without increasing the tax rate, which is what allows the municipality to pay for the economic development without raising property tax rates. For many city officials this is an attractive feature since property owners usually don’t like tax rate increases.

City officials may also prefer TIF to the issuance of general obligation bonds since the latter often require voter approval while TIF does not. This is the case in North Carolina. TIF supporters claim that this gives city officials more flexibility in dealing with the particular needs of development projects. However, it also allows influential individuals to push TIF through for projects that a majority of voters may not support.

While TIF can be used for traditional government goods like roads, sewer systems, water systems, and public transportation, it can also be used for private goods like business parks and sports facilities. The former arguably provide direct benefits to all firms in the TIF district since better roads, streetscapes and water systems can be used by any firm in the area. The latter projects, though they may provide indirect benefits to nearby firms in the form of more attractive surroundings and increased property values, mostly benefit the owners of entity receiving the development funding. Like other development incentives, TIF can be used to subsidize private businesses with taxpayer dollars.

Projects that use TIF are often described as ‘self-financing’ since the project itself is supposedly what creates the higher property values that pay for it. Additionally, TIF is often sold to voters as a way to create jobs or spur additional private investment in blighted areas. But there is no guarantee that the development project will lead to increased private sector investment, more jobs or higher property values. Researchers at the UNC School of Government explain the risks of TIF in a 2008 Economic Bulletin:

“Tax increment financing is not a silver bullet solution to development problems. There is no guarantee that the initial public investment will spur sufficient private investment, over time, that creates enough increment to pay back the bonds. Moreover, even if the investment succeeds on paper, it may do so by “capturing” growth that would have occurred even without the investment. Successful TIF districts can place an additional strain on existing public resources like schools and parks, whose funding is frozen at base valuation levels while growth in the district increases demand for their services.”

The researchers also note that it’s often larger corporations that municipalities are trying to attract with TIF dollars, and any subsidies via TIF that the municipality provides to the larger firm gives it an advantage over its already-established, local competitors. This is even more unfair when the local competitor is a small, mom-and-pop business that already faces a difficult challenge due to economies of scale.

There is also little evidence that TIF regularly provides the job or private sector investment that its supporters promise. Chicago is one of the largest users of TIF for economic development and its program has been one of the most widely studied. Research on Chicago’s TIF program found that “Overall, TIF failed to produce the promise of jobs, business development or real estate activity at the neighborhood level beyond what would have occurred without TIF.”

If economic development projects that rely on TIF do not generate additional development above and beyond what would have occurred anyway, then the additional tax revenue due to the higher assessed values is used to pay for an economic development project that didn’t really add anything. Without TIF, that revenue could have been used for providing other government goods and services such as infrastructure or better police and fire protection. Once TIF is used, the additional revenue must be used to pay for the economic development project: it cannot be spent on other services that residents might prefer.

Another study, also looking at the Chicago metro area, found that cities that adopt TIF experience slower property value growth than those that do not. The authors suggest that this is due to a reallocation of resources to TIF districts from other areas of the city. The result is that the TIF districts grow at the expense of the municipality as a whole. This is an example of the TIF working on paper, but only because it is pilfering growth that would have occurred in other areas of the city.

Local politicians often like tax increment financing because it is relatively flexible and enables them to be entrepreneurial in some sense: local officials as venture capitalists. It’s also an easier sell than a tax rate increase or general obligation bonds that require a voter referendum.

But politicians tend to make bad venture capitalists for several reasons. First, it’s usually not their area of expertise and it’s hard: even the professionals occasionally lose money. Second, as Milton Friedman pointed out, people tend to be more careless when spending other people’s money. Local officials aren’t investing their own money in these projects, and when people invest or spend other people’s money they tend to emphasize the positive outcomes and downplay the negative ones since they aren’t directly affected. Third, pecuniary factors don’t always drive the decision. Different politicians like different industries and businesses – green energy, biotech, advanced manufacturing, etc. – for various reasons and their subjective, non-pecuniary preferences may cause them to ignore the underlying financials of a project and support a bad investment.

If TIF is going to be used it should be used on things like public infrastructure – roads, sewer/water lines, sidewalks – rather than specific private businesses. This makes it harder to get distracted by non-pecuniary factors and does a better – though not perfect – job of directly helping development in general rather than a specific company or private developer. But taxpayers should be aware of the dangers of TIF and politicians and developers should not tout it as a panacea for jump-starting an area’s economy.

Economic freedom matters at the local level too

Since 1996 the Fraser Institute has published an annual economic freedom of the world index that ranks countries according to their level of economic freedom. They also publish an economic freedom of North America Index that ranks the US states, Canadian provinces, and Mexican provinces using similar data.

Both of these studies have been used to show that countries and states/provinces with relatively high levels of economic freedom tend to be better off in several ways, including higher GDP per capita, longer life expectancy, and greater economic growth. Countries with higher levels of economic freedom tend to have higher quality democracies as well.

A quick google search reveals that there has been a lot of other research that looks at the relationship between economic freedom and various outcomes at the country and state level. However, substantially less research has been done at the local level and there are two main reasons for this.

First, it’s hard to gather data at the local level. There are thousands of municipalities in the US and not all of them make their data easily available. This makes gathering data very costly in terms of time and resources. Second, a lot of policies that impact economic freedom are enacted at the federal and state level. Because of this many people probably don’t think about the considerable effects that local policy can have on local economies.

There has been one study that I know of that attempts to create an economic freedom index for metropolitan areas (MSAs). This study is by Dr. Dean Stansel of SMU, a coauthor of the economic freedom of North America index. The MSA economic freedom index runs from 0 (not free) to 10 (very free) and was created with 2002 data. I am currently working on a paper with Dean that uses this index, but I was recently inspired to use the index in a different way. I wanted to see if economic freedom at the MSA level impacted subsequent employment and population growth, so I gathered BEA data on employment and population and ran a few simple regressions. The dependent variables are at the top of each column in the table below and are private, non-farm employment growth from 2003 – 2014, proprietor employment growth from 2003 – 2014, and population growth from 2003 – 2014.

MSA econ freedom regressions

I also included a quality of life index independent variable from another study in order to control for the place-specific amenities of each MSA like weather and location. This variable measures how much people would be willing to pay to live in a particular MSA; a positive number means a person would pay to live in an area, while a negative number means a person would have to be paid to live in an area. Thus larger, positive numbers indicate more attractive areas. The index is constructed with 2000 data.

As shown in the table, economic freedom has a positive and significant effect on both measures of employment and population growth. The quality of life index is also positive and significant for private employment growth (column 1) and population growth (column 3, only at the 10% level). We can calculate the magnitude of the effects using the standard deviations from the table below.

MSA econ freedom sum stats

Using the standard deviation from column 1 (0.84) we can calculate that a one standard deviation increase in economic freedom would generate a 2 percentage point increase in private employment growth from 2003 – 2014 (0.84 x 0.024), a 4.5 percentage point increase in proprietor employment growth, and a 2.9 percentage point increase in population growth.  A one standard deviation change would be like increasing San Francisco’s level of economic freedom (6.70) to that of San Antonio’s (7.53).

Similarly, a one standard deviation increase in the quality of life index would lead to a 2.1 percentage point increase in private employment growth from 2003 – 2014 (0.000011 x 1912.86) and a 1.9 percentage point increase in population growth. A one standard deviation change would be like increasing the quality of life of Montgomery, AL (-21) to that of Myrtle Beach, SC (1643).

I think the most interesting finding is that quality of life does not affect proprietor employment while economic freedom’s largest effect is on proprietor employment (column 2). According to the BEA proprietor employment consists of the number of sole proprietorships and the number of general partners. Thus it can act as a proxy for the level of entrepreneurship in an MSA. This result implies that economic freedom is more important than things like weather and geographic location when it comes to promoting small business formation and entrepreneurship. This is a good sign for cities located in colder regions of the country like the Midwest and Northeast that can’t do much about their weather or location but can increase their level of economic freedom.

Of course, correlation does not mean causation and these simple regressions omit other factors that likely impact employment and population growth. But you have to start somewhere. And given what we know about the positive effects of economic freedom at the country and state level it seems reasonable to believe that it matters at the local level as well.