Category Archives: Economic Freedom

The unseen costs of Amazon’s HQ2 Site Selection

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

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

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

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

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

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

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

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

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

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

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

Why Do We Get So Much Regulation?

Over the past 60 or 70 years, levels of regulation in the United States have been on the rise by almost any measure. As evidence, in the year 1950 there were only 9,745 pages in the US Code of Federal Regulations. Today that number is over 178,000 pages. There is less information about regulation at the state level, but anecdotal evidence suggests regulation is on the rise there too. For example, the Commonwealth of Kentucky publishes its regulatory code each year in a series of volumes known as the Kentucky Administrative Regulations Service (KARS). These volumes consist of books, each roughly 400 or 500 pages or so in length. In 1975, there were 4 books in the KARS. By 2015, that number had risen to 14 books. There are many different theories as to why so much regulation gets produced, so it makes sense to review some of those theories in order to explain the phenomenon of regulatory accumulation.

Perhaps the most popular theory of regulation is that it exists to advance the public interest. According to this view, well-intended regulators intervene in the marketplace due to “market failures”, which are situations where the market fails to allocate resources optimally. Some common examples of market failures include externalities (cases where third parties are impacted by the transactions involving others), asymmetric information (cases where buyers and sellers possess different levels of information about products being sold), public goods problems (whereby certain items are under-provided or not provided at all by the market), and concentration of industry in the form of monopoly power. When market failure occurs, the idea is that regulators intervene in order to make imperfect markets behave more like theoretically perfect markets.

Other theories of regulation are less optimistic about the motivations of the different participants in the rulemaking process. One popular theory suggests regulators work primarily to help powerful special interest groups, a phenomenon known as regulatory capture. Under this view—commonly associated with the writings of University of Chicago economist George Stigler—regulators fix prices and limit entry into an industry because it benefits the industry being regulated. An example would be how regulators, up until the late 1970s, fixed airline prices above what they would have been in a competitive market.

The interest groups that “capture” regulatory agencies are most often thought to be businesses, but it’s important to remember that agencies can also be captured by other groups. The revolving door between the government and the private sector doesn’t end with large banks. It also extends to nonprofit groups, labor unions, and activist groups of various kinds that also wield significant resources and power.

The “public choice theory” of regulation posits that public officials are primarily self-interested, rather than being focused on advancing the public interest. Under this view, regulators may be most concerned with increasing their own salaries or budgets. Or, they may be focused primarily on concentrating their own power.

It’s also possible that regulators are not nearly so calculating and rational as this. The behavioral public choice theory of regulation suggests regulators behave irrationally in many cases, due to the cognitive limitations inherent in all human beings. A case in point is how regulatory agencies routinely overestimate risks, or try to regulate already very low risks down to zero. There is significant evidence that people, including regulators, tend to overestimate small probability risks, leading to responses that are disproportionate to the expected harm. For example, the Environmental Protection Agency’s evaluations of sites related to the Superfund clean-up project routinely overestimated risks by orders of magnitude. Such overreactions might also be a response to public perceptions, for example in response to high-profile media events, such as following acts of terrorism. If the public’s reactions carry over into the voting booth, then legislation and regulation may be enacted soon after.

One of the more interesting and novel theories as to why we see regulation relates to public trust in institutions. A 2010 paper in the Quarterly Journal of Economics noted that there is a strong correlation between trust in various social institutions and some measures of regulation. The figure below is an example of this relationship, found in the paper.

QJE trust

Trust can relate to public institutions, such as the government, but it also extends to trust in corporations and in our fellow citizens. Interestingly, the authors of the QJE article argue that an environment of low trust and high regulation can be a self-fulfilling prophecy. Low levels of trust, ironically, can lead to more demand for regulation, even when there is little trust in the government. One reason for this might be that people think that giving an untrustworthy government control over private affairs is still superior to allowing unscrupulous businesses to have free rein.

The flip-side of this situation is that in high-trust countries, such as Sweden, the public demands lower levels of regulation and this can breed more trust. So an environment of free-market policies combined with trustworthy businesses can produce good market outcomes, more trust, and this too can be a self-fulfilling, allowing some countries to maintain a “good” equilibrium.

This is concerning for the United States because trust has been on the decline in a whole host of areas. A Gallop survey has been asking questions related to trust in public institutions for several decades. There is a long-term secular decline in Gallup’s broad measure of trust, as evidenced by the figure below, although periodically there are upswings in the measure.

gallup trust

Pew has a similar survey that looks at public trust in the government. Here the decline is even more evident.

pew trust

Given that regulation has been on the rise for decades, a decline in trust in the government, in corporations, and in each other, may be a key reason this is occurring. Of course, it’s possible that these groups are simply dishonest and do not merit public trust. Nonetheless, the US might find itself stuck in a self-fulfilling situation, whereby distrust breeds more government intervention in the economy, worse market outcomes, and even more distrust in the future. Getting out of that kind of situation is not easy. One way might be through education about the institutions that lead to free and prosperous societies, as well as to create a culture whereby corruption and unscrupulous behavior are discouraged.

There are a number of theories that seek to explain why regulation comes about. No theory is perfect, and some theories explain certain situations better than others. Nonetheless, the theories presented here go a long way towards laying out the forces that lead to regulation, even if no one theory can explain all regulation at all times.

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.

More labor market freedom means more labor force participation

The U.S. labor force participation (LFP) rate has yet to bounce back to its pre-recession level. Some of the decline is due to retiring baby-boomers but even the prime-age LFP rate, which only counts people age 25 – 54 and thus less affected by retirement, has not recovered.

Economists and government officials are concerned about the weak recovery in labor force participation. A high LFP rate is usually a sign of a strong economy—people are either working or optimistic about their chances of finding a job. A low LFP rate is often a sign of little economic opportunity or disappointment with the employment options available.

The U.S. is a large, diverse country so the national LFP rate obscures substantial state variation in LFP rates. The figure below shows the age 16 and up LFP rates for the 50 states and the U.S. as a whole (black bar) in 2014. (data)

2014-state-lfp-rates

The rates range from a high of 72.6% in North Dakota to a low of 53.1% in West Virginia. The U.S. rate was 62.9%. Several of the states with relatively low rates are in the south, including Mississippi, Alabama and Arkansas. Florida and Arizona also had relatively low labor force participation, which is not surprising considering their reputations as retirement destinations.

There are several reasons why some states have more labor force participation than others. Demographics is one: states with a higher percentage of people over age 65 and between 16 and 22 will have lower rates on average since people in these age groups are often retired or in school full time. States also have different economies made up of different industries and at any given time some industries are thriving while others are struggling.

Federal and state regulation also play a role. Federal regulation disparately impacts different states because of the different industrial compositions of state economies. For example, states with large energy industries tend to be more affected by federal regulation than other states.

States also tax and regulate their labor markets differently. States have different occupational licensing standards, different minimum wages and different levels of payroll and income taxes among other things. Each of these things alters the incentive for businesses to hire or for people to join the labor market and thus affects states’ LFP rates.

We can see the relationship between labor market freedom and labor force participation in the figure below. The figure shows the relationship between the Economic Freedom of North America’s 2013 labor market freedom score (x-axis) and the 2014 labor force participation rate for each state (y-axis).

lab-mkt-freed-and-lfp-rate

As shown in the figure there is a positive relationship—more labor market freedom is associated with a higher LFP rate on average. States with lower freedom scores such as Mississippi, Kentucky and Alabama also had low LFP rates while states with higher freedom scores such as North Dakota, South Dakota and Virginia had higher LFP rates.

This is not an all-else-equal analysis and other variables—such as demographics and industry composition which I mentioned earlier—also play a role. That being said, state officials concerned about their state’s labor market should think about what they can do to increase labor market freedom—and economic freedom more broadly—in their state.

New York’s Buffalo Billion initiative has been underwhelming

New York’s Buffalo Billion plan has come under fire amidst an ongoing corruption probe looking into whether some contracts were inappropriately awarded to political donors. The investigation has led to funding delays and there are reports of some contractors and companies rethinking their investments. But even without these legal problems, it is unlikely that the Buffalo Billion initiative will remake Buffalo’s economy.

Buffalo, NY has been one of America’s struggling cities since the 1950s, but before then it had a long history of growth. After it became the terminal point of the Erie Canal in 1825 it grew rapidly; over the next 100 years the city’s population went from just under 9,000 to over 570,000. Growth slowed down from 1930 to 1950, and between 1950 and 1960 the city lost nearly 50,000 people. It has been losing population ever since. The Metropolitan Area (MSA), which is the economic city, continued to grow until the 1970s as people left the central city for the surrounding suburbs, but it has also been losing population since then. (click to enlarge figure)

buffalo-population

Buffalo’s population decline has not escaped the notice of local, state and federal officials, and billions of dollars in government aid have been given to the area in an effort to halt or reverse its population and economic slide. The newest attempt is Governor Andrew Cuomo’s Buffalo Billion, which promises to give $1 billion of state funds to the region. The investment began in 2013 and as of January 2016, $870.5 million worth of projects have been announced. The table below lists some of the projects, the amount of the investment, and the number of jobs each investment is supposed to create, retain, or induce (includes indirect jobs due to construction and jobs created by subsequent private investment). This information is from the Buffalo Billion Process and Implementation plan (henceforth Buffalo Billion Plan).

buffalo-billion-projects

The projects listed have been awarded $727 million in direct investment, $150 million in tax breaks and $250 million in other state funds. The total number of jobs related to these investments is 9,900 according to the documentation, for an average cost of $113,859 per job (last column).

However, these jobs numbers are projections, not actual counts. This is one of the main criticisms of investment efforts like Buffalo Billion—a lot of money is spent and a lot of jobs are promised, but rarely does anyone follow up to see if the jobs were actually created. In this case it remains to be seen whether reality will match the promises, but the early signs are not encouraging.

Executives of the first project, SolarCity, which received $750 million of benefits and promised 5,000 jobs in western New York, appear to have already scaled back their promise. One company official recently said that 1,460 jobs will be created in Buffalo, including 500 manufacturing jobs. This is down from 2,000 in the Buffalo Billion Plan, a 27% decrease.

The SolarCity factory is not scheduled to open until June 2017 so there is still time for hiring plans to change. But even if the company eventually creates 5,000 jobs in the area, it is hard to see how that will drastically improve the economy of an MSA of over 1.1 million people. Moreover, page eight of the Buffalo Billion Plan reports that the entire $1 billion is only projected to create 14,000 jobs over the course of 5 years, which is again a relatively small amount for such a large area.

Contrary to the local anecdotes that say otherwise, so far there is little evidence that Buffalo Billion has significantly impacted the local economy. Since the recession, employment in Buffalo and its MSA has barely improved, as shown below (data are from the BLS). There has also been little improvement since 2013 when the Buffalo Billion development plan was released. (City data plotted on the right axis, MSA on the left axis.)

buffalo-employment

Real wages in both Erie and Niagara County, the two counties that make up the Buffalo MSA, have also been fairly stagnant since the recession, though there is evidence of some improvement since 2013, particularly in Erie County (data are from the BLS). Still, it is hard to separate these small increases in employment and wages from the general recovery that typically occurs after a deep recession.

buffalo-county-wages

The goal of the Buffalo Billion is to create a “Big Push” that leads to new industry clusters, such as a green energy cluster anchored by SolarCity and an advanced manufacturing cluster. Unfortunately, grandiose plans to artificially create clusters in older manufacturing cities rarely succeed.

As economist Enrico Moretti notes in his book, The New Geography of Jobs, in order for Big Push policies to succeed they need to attract both workers and firms at the same time. This is hard to do since either workers or firms need to be convinced that the other group will eventually arrive if they make the first move.

If firms relocate but high-skill workers stay away, then the firm has spent scarce resources locating in an area that doesn’t have the workforce it needs. If workers move but firms stay away, then the high-skill workers are left with few employment opportunities. Neither situation is sustainable in the long-run.

The use of targeted incentives to attract firms, as in the aforementioned SolarCity project, has been shown to be an ineffective way to grow a regional economy. While such incentives often help some firms at the expense of others, they do not provide broader benefits to the economy as a whole. The mobile firms attracted by such incentives, called footloose firms, are also likely to leave once the incentives expire, meaning that even if there is a short term boost it will be expensive to maintain since the incentives will have to be renewed.

Also, in order for any business to succeed state and local policies need to support, rather than inhibit, economic growth. New York has one of the worst economic environments according to several different measures: It’s 50th in overall state freedom, 50th in economic freedom, and 49th in state business tax climate. New York does well on some other measures, such as Kauffman’s entrepreneurship rankings, but such results are usually driven by the New York City area, which is an economically vibrant area largely due to historical path dependencies and agglomeration economies. Buffalo, and western New York in general, lacks the same innate and historical advantages and thus has a harder time overcoming the burdensome tax and regulatory policies of state government, which are particularly harmful to the local economies located near state borders.

Buffalo officials can control some things at the local level that will improve their economic environment, such as zoning, business licensing, and local taxes, but in order to achieve robust economic growth the city will likely need better cooperation from state officials.

State and local policy makers often refuse to acknowledge the harm that relatively high-tax, high-regulation environments have on economic growth, and this prevents them from making policy changes that would foster more economic activity. Instead, politicians invest billions of dollars of taxpayer money, often in the form of ineffective targeted incentives to favored firms or industries, with the hope that this time will be different.

Discovering an areas comparative advantage and creating a sustainable industry cluster or clusters requires experimentation, which will likely result in some failures. Local and state governments should create an environment that encourages entrepreneurs to experiment with new products and services in their region, but they shouldn’t be risking taxpayer money picking winners and losers. Creating a low-tax, low-regulation environment that treats all businesses—established and start-up, large and small—the same is a better way to grow an economy than government subsidies to favored firms. Unfortunately the Buffalo Billion project looks like another example of the latter futile strategy.

Economic Freedom, Growth, and What Might Have Been

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

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

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

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

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

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

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

(Click to enlarge)

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

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

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

(Click to enlarge)

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

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

 

 

More competition can lead to less inequality

Wealth inequality in the United States and many European countries, especially between the richest and the rest, has been a popular topic since Thomas Piketty’s Capital in the 21st Century was published. Piketty and others argue that tax data shows that wealth inequality has increased in the U.S. since the late 1970s, as seen in the figure below from a paper by Emmanuel Saez—Picketty’s frequent co-author— and Gabriel Zucman.

top-0-1-income-inequ

The figure shows the percentage of all U.S. household wealth that is owned by the top 0.1% of households, which as the note explains consists of about 160,000 families. The percentage fell from 25% in the late 1920s to about 7% in the late 1970s and then began to rise. Many people have used this and similar data to argue for higher marginal taxes on the rich and more income redistribution in order to close the wealth gap between the richest and the rest.

While politicians and pundits continue debating what should be done, if anything, about taxes and redistribution, many economists are trying to understand what factors can affect wealth and thus the wealth distribution over time. An important one that is not talked about enough is competition, specifically Joseph Schumpeter’s idea of creative destruction.

Charles Jones, a professor at Stanford, has discussed the connection between profits and creative destruction and their link with inequality. To help illustrate the connection, Mr. Jones uses the example of an entrepreneur who creates a new phone app. The app’s creator will earn profits over time as the app’s popularity and sales increase. However, her profits will eventually decline due to the process of creative destruction: a newer, better app will hit the market that pulls her customers away from her product, erodes her sales and forces her to adapt or fail. The longer she is able to differentiate her product from others, the longer she will be in business and the more money she will earn. This process is stylized in the figure below.

firm-life-and-profit2

If the app maintains its popularity for the duration of firm life 1, the entrepreneur will earn profits P1. After that the firm is replaced by a new firm that also exists for firm life 1 and earns profit P1. The longer a firm is able to maintain its product’s uniqueness, the more profit it will earn, as shown by firm life 2: In this case the firm earns profit P2. A lack of competition stretches out a firm’s life cycle since the paucity of substitutes makes it costlier for consumers to switch products if the value of the firm’s product declines.

Higher profits can translate into greater inequality as well, especially if we broaden the discussion to include wages and sole-proprietor income. Maintaining market power for a long period of time by restricting entry not only increases corporate profits, it also allows doctors, lawyers, opticians, and a host of other workers who operate under a licensing regime that restricts entry to earn higher wages than they otherwise would. The higher wages obtained due to state restrictions on healthcare provision, restrictions on providing legal services and state-level occupational licensing can exacerbate inequality at the lower levels of the income distribution as well as the higher levels.

Workers and sole proprietors in the U.S. have been using government to restrict entry into occupations since the country was founded. In the past such restrictions were often drawn on racial or ethnic lines. In their Pulitzer Prize-winning history of New York City, Gotham, historians Edwin G. Burrows and Mike Wallace write about New York City cartmen in the 1820s:

American-born carters complained to the city fathers that Irish immigrants, who had been licensed during the war [of 1812] while Anglo-Dutchmen were off soldiering, were undercutting established rates and stealing customers. Mayor Colden limited future alien licensing to dirt carting, a field the Irish quickly dominated. When they continued to challenge the Anglo-Americans in other areas, the Society of Cartmen petitioned the Common Council to reaffirm their “ancient privileges”. The municipal government agreed, rejecting calls for the decontrol of carting, as the business and trade of the city depended on in it, and in 1826 the council banned aliens from carting, pawnbroking, and hackney-coach driving; soon all licensed trades were closed to them.

Modern occupational licensing is the legacy of these earlier, successful efforts to protect profits by limiting entry, often of “undesirables”. Today’s occupational licensing is no longer a response to racial or ethnic prejudices, but it has similar results: It protects the earning power of established providers.

Throughout America’s history the economy has been relatively dynamic, and this dynamism has made it difficult for businesses to earn profits for long periods of time; only 12% of the companies on the Fortune 500 in 1955 were still on the list in 2015. In a properly functioning capitalist economy, newer, poorer firms will regularly supplant older, richer firms and this economic churn tempers inequality.

The same churn occurs among the highest echelon of individuals as well. An increasing number of the Forbes 400 are self-made, often from humble beginnings. In 1984, 99 people on the list inherited their fortune and were not actively growing it. By 2014 only 28 people were in the same position. Meanwhile, the percentage of the Forbes 400 who are largely self-made increased from 43% to 69% over the same period.

But this dynamism may be abating and excessive regulation is likely a factor. For example, the rate of new-bank formation from 1990 – 2010 was about 100 banks per year. Since 2010, the rate has fallen to about three per year. Researchers have attributed some of the decline of small banks to the Dodd-Frank Wall Street Reform Act, which increased compliance costs that disproportionately harm small banks. Fewer banks means less competition and higher prices.

Another recent example of how a lack of competition can increase profits and inequality is EpiPen. The price of EpiPen—a medicine used to treat severe allergic reactions to things like peanuts—has increased dramatically since 2011. This price increase was possible because there are almost no good substitutes for EpiPen, and the lack of substitutes can be attributed to the FDA and other government policies that have insulated EpiPen’s maker, Mylan, from market competition. Meanwhile, the compensation of Mylan’s CEO Heather Bresch increased by 671% from 2007 to 2015. I doubt that Bresch’s compensation would have increased by such a large amount without the profits of EpiPen.

Letting firms and workers compete in the marketplace fosters economic growth and can help dampen inequality. To the extent that wealth inequality is an issue we don’t need more regulation and redistribution to fix it: We need more competition.

Economic freedom matters at the local level too

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

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

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

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

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

MSA econ freedom regressions

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

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

MSA econ freedom sum stats

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

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

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

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

Berkeley, CA and the $15 – oops – $19 living wage

Berkeley, CA’s labor commission – in what should be an unsurprising move at this point in Berkeley’s history – has proposed raising the city’s minimum wage to an astounding $19 per hour by 2020! The labor commission’s argument in a nutshell is that Berkeley is an expensive place to live so worker’s need more money. And while Berkeley may be an expensive place to live, mandating that employers pay a certain wage doesn’t necessarily mean that the workers will get that money. As one Berkeley restaurant owner noted:

“We can raise our prices. But you can’t charge $25 for a sandwich,” said Dorothee Mitrani, who owns La Note. “A lot of mom-and-pop delis and cafes may disappear.”

The article states that Ms. Mitrani’s

…. full-service restaurant now subsidizes her take-out shop, which she said is running in the red as a result of the increases already in place. If the minimum rose to $19, she expects she would have to shut it down.

Of course, there are some politicians – and unfortunately some economists – who insist that raising the minimum wage doesn’t have adverse effects on employment, despite sound theoretical reasoning and empirical evidence to the contrary. My Mercatus center colleague Don Boudreaux has compiled an extensive collection of blog posts at Café Hayek debunking and refuting every pro-minimum wage argument out there, and I encourage interested readers to check them out.

The minimum wage most adversely effects low-skill, inexperienced workers, such as those without a high school degree, below the poverty level, between the ages of 16 – 19, and with some type of disability. So how do the people who fit into those categories currently fare in Berkeley’s labor market?

The table below shows the labor force rate and percentage employed for people 16 and over in each of those categories in the city of Berkeley in 2013 and 2014. The data is from the ACS 1-year survey. (American FactFinder table S2301)

berkely min wage employment 2013-14

As the table shows the labor force rate and the employment rate for each of those categories is already low compared to the overall labor force rate in Berkeley of 67% and employment rate of 62%. From 2013 to 2014 both the labor force rate and the employment rate declined for people without a high school degree, while the employment rate increased in the other categories. Nothing in this table leads me to believe that it would be a good idea to make the workers in these categories more expensive to hire, as it seems it is already difficult for them to find employment and it’s getting more difficult for some.

The table below compares Berkeley to the surrounding San Francisco MSA using only 2014 data.

berkeley min wage emp vs SF MSA

This table reveals that compared to the surrounding area, workers in these categories fare worse in Berkeley. The percentage of people with less than a high school degree who are employed was 11 percentage points lower in Berkeley, while the percentage with a disability was 0.8 points lower and the percentage below the poverty level was 1.5 points lower. Out of the four categories only 16 – 19 year olds had a better chance of being employed in Berkeley than in the surrounding MSA.

Hopefully Berkeley’s city council reviews the labor market reality in their city and thinks about actual consequences vs. intentions before deciding to increase the price that low-skill workers are allowed to charge for their labor. It’s already difficult for low-skill, inexperienced workers to find a job in Berkeley and making it harder won’t help them.

When new ideas meet old regulatory solutions

With the Pennsylvania Public Utility Commission recently issuing cease-and-desist letters to ride-share services Lyft and Uber, Pittsburgh Mayor Bill Peduto invoked the Age of Reptiles to describe the decision:

“Technologies like ride-sharing evolve with the times and state regulators must, too,” said Mayor Peduto in a prepared statement. “While the commission may wish for Pennsylvania to cling to a Jurassic Age of transportation options, people in Pittsburgh and other communities know our state must adapt or die in the global marketplace.”

That is Christopher Koopman and me, writing in the Pittsburgh Post-Gazette. Click here to read the rest.