Category Archives: Innovation

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.

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.

Pokémon Go Represents the Best of Capitalism

An article uploaded to Vox.com by Timothy Lee earlier this week, “Pokémon Go is everything that is wrong with late capitalism,”has caused quite a stir, since it was fairly critical of the “Pokémon Go economy.” Given the popularity of the game though (and our concern that some players would be alarmed that their lighthearted entertainment was somehow destroying the economy) we wanted to offer a different perspective to some of the points made in the article.

In fact, we think that Pokémon Go actually represents the best of capitalism. In less than a week the game has topped 15 million downloads and the 21 million active daily users spend an average of 33 minutes a day playing. That amounts to over 11.5 million hours of playing per day, and those numbers only look to increase. The app doesn’t cost anything to download and play, which means that Nintendo and Niantic (the game developer) are essentially giving away tens of millions of dollars of value to the eager players.

We know that’s a bold statement. But this is why it’s true: A person’s time is scarce and valuable. Every moment they spend playing Pokémon Go they could instead be doing something else. The fact that they’re voluntarily choosing to play means that the benefit of playing is more than the cost.

Economists call this “consumer surplus” – the difference between a customer’s willingness to pay for a good or service and the price that it actually costs. It’s a measurement of the dollar value gained by the consumer in the exchange. If a person was to buy a game of bowling for $5 that they value at $7, instead of playing an hour of Pokémon that they value at $3 for free, that person would lose out on value that would have made their life better.

So even if the average consumer surplus is only a measly dollar an hour, consumers are getting $11.5 million dollars of value each day. The fact that customers are buying special items to use in the game, spending upwards of $1.6 million each day, implies that the value players receive from the game is actually higher.

The article laments that local economies are harmed because people are turning toward forms of entertainment that don’t have high production costs, like movie theaters or bowling alleys that need expensive buildings or numerous employees selling buckets of popcorn. What the article misses is that the economic activity associated with traditional entertainment options represent the costs of providing the entertainment. The reality we have now is much better, since we not only gain the value of the entertainment, but we have the money we would have paid for it to purchase other things as well. It’s almost like getting something for nothing, and our lives – and the economy in general – are better as result.

This is the core of economic growth – decreasing the scarcity of goods and services that limits our lives. The article makes it seem as if economic growth comes from simply spending money. This view can lead us astray because it ignores the importance of entrepreneurs, whose role is critical in the creation of new products and services that improve everyone’s well-being.

Pokémon Go is actually a great example of this. The game developers and their investors thought that they could make something that customers might like and they took the entrepreneurial risk to create the game without the certainty that it was going to be a success. Obviously, it was a good gamble, but I’m sure that even they are amazed at the results. Imagine if the game development funds had been used to build a couple of bowling alleys instead. Wow. What fun.

Think of what would have been lost to society if entrepreneurs didn’t have the funds and the freedom to take that gamble. And their success has spawned a sub-industry of “Poképreneurs” who are selling drinks and providing rides to Pokémon players. Economic growth – and our increased social well-being – depends on this kind of permissionless innovation.

In short, Pokémon Go represents the very best of capitalism because it’s premised on voluntary exchange – no one is forced to download the game, players can stop playing at any time they like, and if they value the special items available in the game store they can buy them to enhance their fun. Furthermore, the entrepreneurs who had the foresight and the guts to dare to make the world a better place are being rewarded for their accomplishment. Most importantly, that success only comes about because they have made people’s lives better in the process. That’s something Team Rocket could never learn to do.

About the Authors:

Michael Farren is a Research Fellow in the Study of American Capitalism at the Mercatus Center at George Mason University. He’s a proud member of Team Instinct, because he likes a challenge.

Adam A. Millsap is a Research Fellow in the State and Local Policy Project at the Mercatus Center at George Mason University. No team will allow him to join, because all he can catch is Pidgeys.

*The title and opening sentence of this article has changed since it was originally published.

Northern Cities Need To Be Bold If They Want To Grow

Geography and climate have played a significant role in U.S. population growth since 1970 (see here, here, here, and here). The figure below shows the correlation between county-level natural amenities and county population growth from 1970 – 2013 controlling for other factors including the population of the county in 1970, the average wage of the county in 1970 (a measure of labor productivity), the proportion of adults in the county with a bachelor’s degree or higher in 1970 and region of the country. The county-level natural amenities index is from the U.S. Department of Agriculture and scores the counties in the continental U.S. according to their climate and geographic features. The county with the worst score is Red Lake, MN and the county with the best score is Ventura, CA.

1970-13 pop growth, amenities

As shown in the figure the slope of the best fit line is positive. The coefficient from the regression is also given at the bottom of the figure and is equal to 0.16, meaning a one point increase in the score increased population growth by 16 percentage points on average.

The effect of natural amenities on population growth is much larger than the effect of the proportion of adults with a bachelor’s degree or higher, which is another strong predictor of population growth at the metropolitan (MSA) and city level (see here, here, here, and here). The relationship between county population growth from 1970 – 2013 and human capital is depicted below.

1970-13 pop growth, bachelors or more

Again, the relationship is positive but the effect is smaller. The coefficient is 0.026 which means a 1 percentage point increase in the proportion of adults with a bachelor’s degree or higher in 1970 increased population growth by 2.6 percentage points on average.

An example using some specific counties can help us see the difference between the climate and education effects. In the table below the county where I grew up, Greene County, OH, is the baseline county. I also include five other urban counties from around the country: Charleston County, SC; Dallas County, TX; Eau Claire County, WI; San Diego County, CA; and Sedgwick County, TX.

1970-13 pop chg, amenities table

The first column lists the amenities score for each county. The highest score belongs to San Diego. The second column lists the difference between Green County’s score and the other counties, e.g. 9.78 – (-1.97) = 11.75 which is the difference between Greene County’s score and San Diego’s score. The third column is the difference column multiplied by the 0.16 coefficient from the natural amenity figure e.g. 11.75 x 0.16 = 188% in the San Diego row. What this means is that according to this model, if Greene County had San Diego’s climate and geography it would have grown by an additional 188 percentage points from 1970 – 2013 all else equal.

Finally, the last column is the actual population growth of the county from 1970 – 2013. As shown, San Diego County grew by 135% while Greene County only grew by 30% over this 43 year period. Improving Greene County’s climate to that of any of the other counties except for Eau Claire would have increased its population growth by a substantial yet realistic amount.

Table 2 below is similar to the natural amenities table above only it shows the different effects on Greene County’s population growth due to a change in the proportion of adults with a bachelor’s degree or higher.

1970-13 pop chg, bachelor's table

As shown in the first column, Greene County actually had the largest proportion of adults with bachelor’s degree or higher in 1970 – 14.7% – of the counties listed.

The third column shows how Greene County’s population growth would have changed if it had the same proportion of adults with a bachelor’s degree or higher as the other counties did in 1970. If Greene County had the proportion of Charleston (11.2%) instead of 14.7% in 1970, its population growth is predicted to have been 9 percentage points lower from 1970 – 2013, all else equal. All of the effects in the table are negative since all of the counties had a lower proportion than Greene and population education has a positive effect on population growth.

Several studies have demonstrated the positive impact of an educated population on overall city population growth – often through its impact on entrepreneurial activity – but as shown here the education effect tends to be swamped by geographic and climate features. What this means is that city officials in less desirable areas need to be bold in order to compensate for the poor geography and climate that are out of their control.

A highly educated population combined with a business environment that fosters innovation can create the conditions for city growth. Burdensome land-use regulations, lengthy, confusing permitting processes, and unpredictable rules coupled with inconsistent enforcement increase the costs of doing business and stifle entrepreneurship. When these harmful business-climate factors are coupled with a generally bad climate the result is something like Cleveland, OH.

The reality is that the tax and regulatory environments of declining manufacturing cities remain too similar to those of cities in the Sunbelt while their weather and geography differ dramatically, and not in a good way. Since only relative differences cause people and firms to relocate, the similarity across tax and regulatory environments ensures that weather and climate remain the primary drivers of population change.

To overcome the persistent disadvantage of geography and climate officials in cold-weather cities need to be aggressive in implementing reforms. Fiddling around the edges of tax and regulatory policy in a half-hearted attempt to attract educated people, entrepreneurs and large, high-skill employers is a waste of time and residents’ resources – Florida’s cities have nicer weather and they’re in a state with no income tax. Northern cities like Flint, Cleveland, and Milwaukee that simply match the tax and regulatory environment of Houston, San Diego, or Tampa have done nothing to differentiate themselves along those dimensions and still have far worse weather.

Location choices reveal that people are willing to put up with a lot of negatives to live in places with good weather. California has one of the worst tax and regulatory environments of any state in the country and terrible congestion problems yet its large cities continue to grow. A marginally better business environment is not going to overcome the allure of the sun and beaches.

While a better business environment that is attractive to high-skilled workers and encourages entrepreneurship is unlikely to completely close the gap between a place like San Diego and Dayton when it comes to being a nice place to live and work, it’s a start. And more importantly it’s the only option cities like Dayton, Buffalo, Cleveland, St. Louis and Detroit have.

City population dynamics since 1850

The reason why some cities grow and some cities shrink is a heavily debated topic in economics, sociology, urban planning, and public administration. In truth, there is no single reason why a city declines. Often exogenous factors – new modes of transportation, increased globalization, institutional changes, and federal policies – initiate the decline while subsequent poor political management can exacerbate it. This post focuses on the population trends of America’s largest cities since 1850 and how changes in these factors affected the distribution of people within the US.

When water transportation, water power, and proximity to natural resources such as coal were the most important factors driving industrial productivity, businesses and people congregated in locations near major waterways for power and shipping purposes. The graph below shows the top 10 cities* by population in 1850 and follows them until 1900. The rank of the city is on the left axis.

top cities 1850-1900

 

* The 9th, 11th, and 12th ranked cities in 1850 were all incorporated into Philadelphia by 1860. Pittsburgh was the next highest ranked city (13th) that was not incorporated so I used it in the graph instead.

All of the largest cities were located on heavily traveled rivers (New Orleans, Cincinnati, Pittsburgh, and St. Louis) or on the coast and had busy ports (New York, Boston, Philadelphia, Brooklyn, and Baltimore). Albany, NY may seem like an outlier but it was the starting point of the Erie Canal.

As economist Ed Glaeser (2005) notes “…almost every large northern city in the US as of 1860 became an industrial powerhouse over the next 60 years as factories started in central locations where they could save transport costs and make use of large urban labor forces.”

Along with waterways, railroads were an important mode of transportation from 1850 – 1900 and many of these cities had important railroads running through them, such as the B&O through Balitmore and the Erie Railroad in New York. The increasing importance of railroads impacted the list of top 10 cities in 1900 as shown below.

top cities 1900-1950

A similar but not identical set of cities dominated the urban landscape over the next 50 years. By 1900, New Orleans, Brooklyn (merged with New York) Albany, and Pittsburgh were replaced by Chicago, Cleveland, Buffalo, and San Francisco. Chicago, Cleveland, and Buffalo are all located on the Great Lakes and thus had water access, but it was the increasing importance of railroad shipping and travel that helped their populations grow. Buffalo was on the B&O railroad and was also the terminal point of the Erie Canal. San Francisco became much more accessible after the completion of the Pacific Railroad in 1869, but the California Gold Rush in the late 1840s got its population growth started.

As rail and eventually automobile/truck transportation became more important during the early 1900s, cities that relied on strategic river locations began to decline. New Orleans was already out of the top 10 by 1900 (falling from 5th to 12th) and Cincinnati went from 10th in 1900 to 18th by 1950. Buffalo also fell out of the top 10 during this time period, declining from 8th to 15th. But despite some changes in the rankings, there was only one warm-weather city in the top 10 as late as 1950 (Los Angeles). However, as the next graphs shows there was a surge in the populations of warm-weather cities during the period from 1950 to 2010 that caused many of the older Midwestern cities to fall out of the rankings.

top cities 1950-2010

The largest shakeup in the population rankings occurred during this period. Out of the top 10 cities in 1950, only 4 (Philadelphia, Los Angeles, Chicago, and New York) were still in the top 10 in 2010 (All were in the top 5, with Houston – 4th in 2010 – being the only city not already ranked in the top 10 in 1950, when it was 14th). The cities ranked 6 – 10 fell out of the top 20 while Detroit declined from 5th to 18th. The large change in the rankings during this time period is striking when compared to the relative stability of the earlier time periods.

Economic changes due to globalization and the prevalence of right-to-work laws in the southern states, combined with preferences for warm weather and other factors have resulted in both population and economic decline in many major Midwestern and Northeastern cities. All of the new cities in the top ten in 2010 have relatively warm weather: Phoenix, San Antonio, San Diego, Dallas, and San Jose. Some large cities missing from the 2010 list – particularly San Francisco and perhaps Washington D.C. and Boston as well – would probably be ranked higher if not for restrictive land-use regulations that artificially increase housing prices and limit population growth. In those cities and other smaller cities – primarily located in Southern California – low population growth is a goal rather than a result of outside forces.

The only cold-weather cities that were in the top 15 in 2014 that were not in the top 5 in 1950 were Indianapolis, IN (14th) and Columbus, OH (15th). These two cities not only avoided the fate of nearby Detroit and Cleveland, they thrived. From 1950 to 2014 Columbus’ population grew by 122% and Indianapolis’ grew by 99%. This is striking compared to the 57% decline in Cleveland and the 63% decline in Detroit during the same time period.

So why have Columbus and Indianapolis grown since 1950 while every other large city in the Midwest has declined? There isn’t an obvious answer. One thing among many that both Columbus and Indianapolis have in common is that they are both state capitals. State spending as a percentage of Gross State Product (GSP) has been increasing since 1970 across the country as shown in the graph below.

OH, IN state spending as per GSP

In Ohio state spending growth as a percentage of GSP has outpaced the nation since 1970. It is possible that increased state spending in Ohio and Indiana is crowding out private investment in other parts of those states. And since much of the money collected by the state ends up being spent in the capital via government wages, both Columbus and Indianapolis grow relative to other cities in their respective states.

There has also been an increase in state level regulation over time. As state governments become larger players in the economy business leaders will find it more and more beneficial to be near state legislators and governors in order to lobby for regulations that help their company or for exemptions from rules that harm it. Company executives who fail to get a seat at the table when regulations are being drafted may find that their competitors have helped draft rules that put them at a competitive disadvantage. The decline of manufacturing in the Midwest may have created an urban reset that presented firms and workers with an opportunity to migrate to areas that have a relative abundance of an increasingly important factor of production – government.

Education, Innovation, and Urban Growth

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

BA, city growth 1

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

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

BA, city growth 2

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

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

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

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

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

Embrace Change

Kaiserin_Maria_Theresia_(HRR)Whenever someone suggested a new innovation or an improvement, Empress Maria Theresa had a favorite response: “Leave everything as it is.” As the sovereign of most of central Europe during the 18th Century, the Habsburg Empress epitomized absolutist rule, claiming that her powers had no limit.

But as her statement demonstrates, she clearly understood that her powers were limited by new and disruptive innovations. Her husband, Holy Roman Emperor Francis I understood this as well. Daron Acemoglu and James Robinson relate that when an English philanthropist suggested some social reforms for the benefit of Austria’s poorest, one of Francis’s assistants replied: “We do not desire at all that the great masses shall become well off and independent….How could we otherwise rule over them?” (A&R, 224).

This is why these Habsburg rulers did everything they could to stand athwart innovation. As Acemoglu and Robinson put it:

In addition to serfdom, which completely blocked the emergence of a labor market and removed the economic incentives or initiative from the mass of the rural population, Habsburg absolutism thrived on monopolies and other restrictions on trade. The urban economy was dominated by guilds, which restricted entry into professions. (A&R, 224).

Francis went so far as to block new technologies. For instance, he banned the adoption of new industrial machinery until 1811. He also refused to permit the building of steam railroads. Acemoglu and Robinson inform us that:

[T]he first railway built in the empire had to use horse-drawn carriages. The line…was built with gradients and corners, which meant that it was impossible subsequently to convert it to steam engines. So it continued with horse power until the 1860s. (A&R, 226).

Unfortunately, history is replete with examples of despots who stood in the way of innovation. In Russia, Nicholas I enacted laws restricting the number of factories and “forbade the opening of any new cotton or woolen spinning mills and iron foundries.” (A&R, 229). And in the Ottoman Empire, sultans banned the use of printing. So stultifying was the effect that “well into the second half of the nineteenth century, book production in the Ottoman Empire was still primarily undertaken by scribes hand-copying existing books.” (A&R, 214).

The centuries and the miles that separate us from these episodes give us some objectivity and allow us to see them for what they are: the naked exercise of government force to obstruct innovation for the benefit of a few entrenched interests. But how different are these episodes, really, from the stories we read in today’s newspapers? Are they all that different from New Jersey’s refusal to allow car companies to sell directly to consumers? Are they any less silly than the anti-Uber laws cooked up by a dozen U.S. cities? We like to think that our own political process is more enlightened but right now, federal, state and city policy makers are working to block the development of promising innovations such as wearable technologies, 3D printing, smart cars, and autonomous vehicles.

book-cover-smallFor a thoughtful and forceful discussion of what might be called the anti-Maria Theresa view, everyone should read Permissionless Innovation by my colleague Adam Thierer. It is a well-researched and well-argued defense of the proposition that our default policy should be “innovation allowed.” You can find Kindle and paperback versions on Amazon. Or you can check out the free PDF version at the Mercatus Center. For a nice overview of his book, see Adam’s post (and video) here. Please read it and send (free) copies to any modern-day Maria Theresas you may know.