Author Archives: Adam Millsap

Smart rule-breakers make the best entrepreneurs

A new paper in the Quarterly Journal of Economics (working version here) finds that the combination of intelligence and a willingness to break the rules as a youth is associated with a greater tendency to operate a high-earning incorporated business as an adult i.e. be an entrepreneur.

Previous work examining entrepreneurship that categorizes all self-employed persons as entrepreneurs has often found that entrepreneurs earn less than similar salaried workers. But this contradicts the important role entrepreneurs are presumed to play in generating economic growth. As the authors of the new QJE paper remark:

“If the self-employed are a good proxy for risk-taking, growth-creating entrepreneurs, it is puzzling that their human capital traits are similar to those of salaried workers and that they earn less.”

So instead of looking at the self-employed as one group, the authors separate them into two groups: those who operate unincorporated businesses and those who operate incorporated businesses. They argue that incorporation is important for risk-taking entrepreneurs due to the limited liability and separate legal identity it provides, and they find that those who choose incorporation are more likely to engage in tasks that require creativity, analytical flexibility and complex interpersonal communications; all tasks that are closely identified with the concept of entrepreneurship.

People who operate unincorporated businesses, on the other hand, are more likely to engage in activities that require high levels of hand, eye and foot coordination, such as landscaping or truck driving.

Once the self-employed are separated into incorporated and unincorporated, the puzzling finding of entrepreneurs earning less than similar salaried workers disappears. The statistics in the table below taken from the paper show that on average incorporated business owners (last column) earn more, work more hours, have more years of schooling and are more likely to be a college graduate than both unincorporated business owners and salaried workers based on two different data sets (Current Population Survey (CPS) and National Longitudinal Survey of Youth (NLSY)).

(click table to enlarge)

The authors then examine the individual characteristics of incorporated and unincorporated business owners. They find that people with high self-esteem, a strong sense of controlling one’s future, high Armed Forces Qualifications Test scores (AFQT)—which is a measure of intelligence and trainability—and a greater propensity for engaging in illicit activity as a youth are more likely to be incorporated self-employed.

Moreover, it’s the combination of intelligence and risk-taking that turns a young person into a high-earning owner of an incorporated business. As the authors state, “The mixture of high learning aptitude and disruptive, “break-the-rules” behavior is tightly linked with entrepreneurship.”

These findings fit nicely with some notable recent examples of entrepreneurship—Uber and Airbnb. Both companies are regularly sued for violating state and local ordinances, but this hasn’t stopped them from becoming popular providers of transportation and short-term housing.

If the founders of Uber and Airbnb always obtained approval before operating the companies would be hindered by all sorts of special interests, including taxi commissions, hotel industry groups and nosy neighbors. Seeking everyone’s approval—including the government’s—before operating likely would have meant never getting off the ground and the companies know this. It’s interesting to see evidence that many other, less well-known entrepreneurs share a similar willingness to violate the rules if necessary in order to provide their goods and services to customers.

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

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

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

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

country 25-54 LFP rate, manuf table

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

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

country 25-54 LFP rate, manuf scatter plot

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

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

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

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

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

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

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

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

25-54 males NILF by state 2016

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

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

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

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

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

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

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

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

25-54 native, foreign NILF diff

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

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

25-54 native, foreign males NILF by educ

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

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

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

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

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

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

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

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

Mutant Capitalism rears its ugly head in Arlington

Confectionery-giant Nestlé plans to move its U.S. headquarters from California to 1812 North Moore in the Rosslyn area of Arlington in the next few years. This should be great news for the people of Arlington—a world-famous company has decided that Arlington County is the best place to be in the U.S. This must be due to our educated workforce and high quality of life, right?

Maybe. The real attraction might also be the $6 million of state handouts to Nestlé, along with an additional $6 million from Arlington County. Government handouts like these have become a way of life in the U.S. even though the results are often underwhelming.

Federal programs such as the New Markets Tax Credit Program have had at best small effects on economic development, and there is a good chance they just reallocate economic activity from one place to another rather than generate new economic activity. Local programs like Tax Increment Financing appear to largely reallocate economic activity as well. These programs might be good for the neighborhood or city that gets the handout, but it doesn’t help the residents of nearby places who are forced to contribute via their tax dollars.

In the Nestlé case, all of Virginia’s taxpayers are paying for Nestlé to locate in Arlington, which already has a relatively strong economy and is one of the wealthiest counties in Virginia. Why should taxpayers in struggling counties such as Buchanan or Dickenson County be forced to subsidize a company in Arlington? Government handouts to firms are often regressive since companies rarely want to locate in areas with a low-skill—and thus low-income—workforce. Everyone pays, but the most economically successful areas get the benefits.

Government officials often praise the jobs that these deals create and the Nestlé deal is no different: According to the performance agreement, Nestlé must create and maintain 748 new full-time jobs. And even if we ignore the fact that jobs are an economic cost, not a benefit, a closer look reveals that projections and reality usually diverge. For example, Buffalo awarded hundreds of millions of dollars to SolarCity, which promised to create 5,000 jobs. They have since revised that number down to 1,460. There are numerous other examples where the cost per job turned out to be higher than initially projected.

The grant performance agreement also estimates that Nestlé will provide $18.2 million in taxes to the county over the next 10 years, more than enough to offset the grant expenditure. But this doesn’t take into account what would have happened absent the handout. Perhaps some other company would have relocated here for free. Or a local company, or collection of companies, would have eventually rented out the space.

Government grants may also distort the real estate market: There’s a good chance no company had occupied 1812 North Moore because the rent was too high. If so, part of this grant is a handout to the owners of the building, Monday Properties, since now it does not have to lower its rent to attract a tenant. This may lead other property companies to lobby for and expect government handouts to help them find tenants.

Government grants often distort the economy by treating out-of-state companies differently than in-state companies. They encourage relocation by subsidizing it, which discourages expansion. A better strategy is to create a simple, non-intrusive business environment that treats all businesses equally.

Government grants are a characteristic of what my colleague Chris Koopman calls Mutant Capitalism and are antithetical to real capitalism and free enterprise. Capitalism involves businesses competing for consumers on an even playing field—there is no room for government favors that tilt the playing field towards one business or another.

Government Spending and Economic Growth in Nebraska since 1997

Mercatus recently released a study that examines Nebraska’s budget, budgetary rules and economy. As the study points out, Nebraska, like many other states, consistently faces budgeting problems. State officials are confronted by a variety of competing interests looking for more state funding—schools, health services and public pensions to name a few—and attempts to placate each of them often leave officials scrambling to avoid budget shortfalls in the short term.

Money spent by state and local governments is collected from taxpayers who earn money in the labor market and through investments. The money earned by taxpayers is the result of producing goods and services that people want and the total is essentially captured in a state’s Gross Domestic Product (GSP).

State GSP is a good measure of the amount of money available for a state to tax, and if state and local government spending is growing faster than GSP, state and local governments will be controlling a larger and larger portion of their state’s output over time. This is unsustainable in the long run, and in the short run more state and local government spending can reduce the dynamism of a state’s economy as resources are taken from risk-taking entrepreneurs in the private sector and given to government bureaucrats.

The charts below use data from the BEA to depict the growth of state and local government spending and private industry GSP in Nebraska (click on charts to enlarge). The first shows the annual growth rates in private industry GSP and state and local government GSP from 1997 to 2014. The data is adjusted for inflation (2009 dollars) and the year depicted is the ending year (e.g. 1998 is growth from 1997 – 1998).

NE GSP annual growth rates 1997-14

In Nebraska, real private industry GSP growth has been positive every year except for 2012. There is some volatility consistent with the business cycles over this time period, but Nebraska’s economy has regularly grown over this period.

On the other hand, state and local GSP growth was negative 10 of the 17 years depicted. It grew rapidly during recession periods (2000 – 2002 and 2009 – 2010), but it appears that state and local officials were somewhat successful in reducing spending once economic conditions improved.

The next chart shows how much private industry and state and local GSP grew over the entire period for both Nebraska and the U.S. as a whole. The 1997 value of each category is used as the base year and the yearly ratio is plotted in the figure. The data is adjusted for inflation (2009 dollars).

NE, US GSP growth since 1997

In 2014, Nebraska’s private industry GSP (red line) was nearly 1.6 times larger than its value in 1997. On the other hand, state and local spending (light red line) was only about 1.1 times larger. Nebraska’s private industry GSP grew more than the country’s as a whole over this period (57% vs 46%) while its state and local government spending grew less (11% vs. 15%).

State and local government spending in Nebraska spiked from 2009 to 2010 but has come down slightly since then. Meanwhile, the state’s private sector has experienced relatively strong growth since 2009 compared to the country as a whole, though it was lagging the country prior to the recession.

Compared to the country overall, Nebraska’s private sector economy has been doing well since 2008 and state and local spending, while growing, appears to be largely under control. If you would like to learn more about Nebraska’s economy and the policies responsible for the information presented here, I encourage you to read Governing Nebraska’s Fiscal Commons: Addressing the Budgetary Squeeze, by Creighton University Professor Michael Thomas.

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.

Economic policies and institutions matter

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

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

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

US city productivity

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

 

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

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

german city size, product graph

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

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

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

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

Why the lack of labor mobility in the U.S. is a problem and how we can fix it

Many researchers have found evidence that mobility in the U.S. is declining. More specifically, it doesn’t appear that people move from places with weaker economies to places with stronger economies as consistently as they did in the past. Two sets of figures from a paper by Peter Ganong and Daniel Shoag succinctly show this decline over time.

The first, shown below, has log income per capita by state on the x-axis for two different years, 1940 (left) and 1990 (right). On the vertical axis of each graph is the annual population growth rate by state for two periods, 1940 – 1960 (left) and 1990 – 2010 (right).

directed migration ganong, shoag

In the 1940 – 1960 period, the graph depicts a strong positive relationship: States with higher per capita incomes in 1940 experienced more population growth over the next 20 years than states with lower per capita incomes. This relationship disappears and actually reverses in the 1990 – 2010 period: States with higher per capita incomes actually grew slower on average. So in general people became less likely to move to states with higher incomes between the middle and end of the 20th century. Other researchers have also found that people are not moving to areas with better economies.

This had an effect on income convergence, as shown in the next set of figures. In the 1940 – 1960 period (left), states with higher per capita incomes experienced less income growth than states with lower per capita incomes, as shown by the negative relationship. This negative relationship existed in the 1990 – 2010 period as well, but it was much weaker.

income convergence ganong, shoag

We would expect income convergence when workers leave low income states for high income states, since that increases the labor supply in high-income states and pushes down wages. Meanwhile, the labor supply decreases in low-income states which increases wages. Overall, this leads to per capita incomes converging across states.

Why labor mobility matters

As law professor David Schleicher points out in a recent paper, the current lack of labor mobility can reduce the ability of the federal government to manage the U.S. economy. In the U.S. we have a common currency—every state uses the U.S. dollar. This means that if a state is hit by an economic shock, e.g. low energy prices harm Texas, Alaska and North Dakota but help other states, that state’s currency cannot adjust to cushion the blow.

For example, if the UK goes into a recession, the Bank of England can print more money so that the pound will depreciate relative to other currencies, making goods produced in the UK relatively cheap. This will decrease the UK’s imports and increase economic activity and exports, which will help it emerge from the recession. If the U.S. as a whole suffered a negative economic shock, a similar process would take place.

However, within a country this adjustment mechanism is unavailable: Texas can’t devalue its dollar relative to Ohio’s dollar. There is no within-country monetary policy that can help particular states or regions. Instead, the movement of capital and labor from weak areas to strong areas is the primary mechanism available for restoring full employment within the U.S. If capital and labor mobility are low it will take longer for the U.S. to recover from area-specific negative economic shocks.

State or area-specific economic shocks are more likely in large countries like the U.S. that have very diverse local economies. This makes labor and capital mobility more important in the U.S. than in smaller, less economically diverse countries such as Denmark or Switzerland, since those countries are less susceptible to area-specific economic shocks.

Why labor mobility is low

There is some consensus about policies that can increase labor mobility. Many people, including former President Barack Obama, my colleagues at the Mercatus Center and others, have pointed out that state occupational licensing makes it harder for workers in licensed professions to move across state borders. There is similar agreement that land-use regulations increase housing prices which makes it harder for people to move to areas with the strongest economies.

Reducing occupational licensing and land-use regulations would increase labor mobility, but actually doing these things is not easy. Occupational licensing and land-use regulations are controlled at the state and local level, so currently there is little that the federal government can do.

Moreover, as Mr. Schleicher points out in his paper, state and local governments created these regulations for a reason and it’s not clear that they have any incentive to change them. Like all politicians, state and local ones care about being re-elected and that means, at least to some extent, listening to their constituents. These residents usually value stability, so politicians who advocate too strongly for growth may find themselves out of office. Mr. Schleicher also notes that incumbent politicians often prefer a stable, immobile electorate because it means that the voters who elected them in the first place will be there next election cycle.

Occupational licensing and land-use regulations make it harder for people to enter thriving local economies, but other policies make it harder to leave areas with poor economies. Nearly 13% of Americans work for state and local governments and 92% of them have a defined-benefit pension plan. Defined-benefit plans have long vesting periods and benefits can be significantly smaller if employees split their career between multiple employers rather than remain at one employer. Thus over 10% of the workforce has a strong retirement-based incentive to stay where they are.

Eligibility standards for public benefits and their amounts also vary by state, and this discourages people who receive benefits such as Temporary Assistance for Needy Families (TANF) from moving to states that may have a stronger economy but less benefits. Even when eligibility standards and benefits are similar, the paperwork and time burden of enrolling in a new state can discourage mobility.

The federal government subsidizes home ownership as well, and homeownership is correlated with less labor mobility over time. Place-based subsidies to declining cities also artificially support areas that should have less people. As long as state and federal governments subsidize government services in cities like Atlantic City and Detroit people will be less inclined to leave them. People-based subsidies that incentivize people to move to thriving areas are an alternative that is likely better for the taxpayer, the recipient and the country in the long run.

How to increase labor mobility

Since state and local governments are unlikely to directly address the impediments to labor mobility that they have created, Mr. Schleicher argues for more federal involvement. Some of his suggestions don’t interfere with local control, such as a federal clearinghouse for coordinated occupational-licensing rules across states. This is not a bad idea but I am not sure how effective it would be.

Other suggestions are more intrusive and range from complete federal preemption of state and local rules to federal grants that encourage more housing construction or suspension of the mortgage-interest deduction in places that restrict housing construction.

Local control is important due to the presence of local knowledge and the beneficial effects that arise from interjurisdictional competition, so I don’t support complete federal preemption of local rules. Economist William Fischel also thinks the mortgage interest deduction is largely responsible for excessive local land-use regulation, so eliminating it altogether or suspending it in places that don’t allow enough new housing seems like a good idea.

I also support more people-based subsidies that incentivize moving to areas with better economies and less place-based subsidies. These subsidies could target people living in specific places and the amounts could be based on the economic characteristics of the destination, with larger amounts given to people who are willing to move to areas with the most employment opportunities and/or highest wages.

Making it easier for people to retain any state-based government benefits across state lines would also help improve labor mobility. I support reforms that reduce the paperwork and time requirements for transferring benefits or for simply understanding what steps need to be taken to do so.

Several policy changes will need to occur before we can expect to see significant changes in labor mobility. There is broad agreement around some of them, such as occupational licensing and land-use regulation reform, but bringing them to fruition will take time. As for the less popular ideas, it will be interesting to see which, if any, are tried.

Today’s public policies exacerbate our differences

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

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

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

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

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

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

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