Author Archives: Adam Millsap

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.

What else can the government do for America’s poor?

This year marks the 20th anniversary of the 1996 welfare reforms, which has generated some discussion about poverty in the U.S. I recently spoke to a group of high school students on this topic and about what reforms, if any, should be made to our means-tested welfare programs.

After reading several papers (e.g. here, here and here), the book Hillbilly Elegy, and reflecting on my own experiences I am not convinced the government is capable of doing much more.

History

President Lyndon Johnson declared “War on Poverty” in his 1964 state of the union address. Over the last 50 years there has been some progress but there are still approximately 43 million Americans living in poverty as defined by the U.S. Census Bureau.

Early on it looked as if poverty would be eradicated fairly quickly. In 1964, prior to the “War on Poverty”, the official poverty rate was 20%. It declined rapidly from 1965 to 1972, especially for the most impoverished groups as shown in the figure below (data from Table 1 in Haveman et al. , 2015). (Click to enlarge)

poverty-rate-1965-72

Since 1972 the poverty rate has remained fairly constant. It reached its lowest point in 1973—11.1%—but has since fluctuated between roughly 11% and 15%, largely in accordance with the business cycle. The number of people in poverty has increased, but that is unsurprising considering the relatively flat poverty rate coupled with a growing population.

census-poverty-rate-time-series-2015

Meanwhile, an alternative measure called the supplemental poverty measure (SPM) has declined, but it was still over 15% as of 2013, as shown below.

poverty-rate-time-series

The official poverty measure (OPM) only includes cash and cash benefits in its measure of a person’s resources, while the SPM includes tax credits and non-cash transfers (e.g. food stamps) as part of someone’s resources when determining their poverty status. The SPM also makes adjustments for local cost of living.

For example, the official poverty threshold for a single person under the age of 65 was $12,331 in 2015. But $12,331 can buy more in rural South Carolina than it can in Manhattan, primarily because of housing costs. The SPM takes these differences into account, although I am not sure it should for reasons I won’t get into here.

Regardless of the measure we look at, poverty is still higher than most people would probably expect considering the time and resources that have been expended trying to reduce it. This is especially true in high-poverty areas where poverty rates still exceed 33%.

A county-level map from the Census that uses the official poverty measure shows the distribution of poverty across the 48 contiguous states in 2014. White represents the least amount of poverty (3.2% to 11.4%) and dark pink the most (32.7% to 52.2%).

us-county-poverty-map

The most impoverished counties are in the south, Appalachia and rural west, though there are pockets of high-poverty counties in the plains states, central Michigan and northern Maine.

Why haven’t we made more progress on poverty? And is there more that government can do? I think these questions are intertwined. My answer to the first is it’s complicated and to the second I don’t think so.

Past efforts

The inability to reduce the official poverty rate below 10% doesn’t appear to be due to a lack of money. The figure below shows real per capita expenditures—sum of federal, state and local—on the top 84 (top line) and the top 10 (bottom line) means-tested welfare poverty programs since 1970. It is from Haveman et al. (2015).

real-expend-per-capita-on-poverty-programs

There has been substantial growth in both since the largest drop in poverty occurred in the late 1960s. If money was the primary issue one would expect better results over time.

So if the amount of money is not the issue what is? It could be that even though we are spending money, we aren’t spending it on the right things. The chart below shows real per capita spending on several different programs and is also from Haveman et al. (2015).

expend-per-cap-non-medicaid-pov-programs

Spending on direct cash-assistance programs—Aid for Families with Dependent Children (AFDC) and Temporary Assistance for Needy Families (TANF)—has fallen over time, while spending on programs designed to encourage work—Earned Income Tax Credit (EITC)—and on non-cash benefits like food stamps and housing aid increased.

In the mid-1970s welfare programs began shifting from primarily cash aid (AFDC, TANF) to work-based aid (EITC). Today the EITC and food stamps are the core programs of the anti-poverty effort.

It’s impossible to know whether this shift has resulted in more or less poverty than what would have occurred without it. We cannot reconstruct the counterfactual without going back in time. But many people think that more direct cash aid, in the spirit of AFDC, is what’s needed.

The difference today is that instead of means-tested direct cash aid, many are calling for a universal basic income or UBI. A UBI would provide each citizen, from Bill Gates to the poorest single mother, with a monthly cash payment, no strings attached. Prominent supporters of a UBI include libertarian-leaning Charles Murray and people on the left such as Matt Bruenig and Elizabeth Stoker.

Universal Basic Income?

The details of each UBI plan vary, but the basic appeal is the same: It would reduce the welfare bureaucracy, simplify the process for receiving aid, increase the incentive to work at the margin since it doesn’t phase out, treat low-income people like adults capable of making their own decisions and mechanically decrease poverty by giving people extra cash.

A similar proposal is a negative income tax (NIT), first popularized by Milton Friedman. The current EITC is a negative income tax conditional on work, since it is refundable i.e. eligible people receive the difference between their EITC and the taxes they owe. The NIT has its own problems, discussed in the link above, but it still has its supporters.

In theory I like a UBI. Economists in general tend to favor cash benefits over in-kind programs like vouchers and food stamps due to their simplicity and larger effects on recipient satisfaction or utility. In reality, however, a UBI of even $5,000 is very expensive and there are public choice considerations that many UBI supporters ignore, or at least downplay, that are real problems.

The political process can quickly turn an affordable UBI into an unaffordable one. It seems reasonable to expect that politicians trying to win elections will make UBI increases part of their platform, with each trying to outdo the other. There is little that can be done, short of a constitutional amendment (and even those can be changed), to ensure that political forces don’t alter the amount, recipient criteria or add additional programs on top of the UBI.

I think the history of the income tax demonstrates that a relatively low, simple UBI would quickly morph into a monstrosity. In 1913 there were 7 income tax brackets that applied to all taxpayers, and a worker needed to make more than $20K (equivalent to $487,733 in 2016) before he reached the second bracket of 2% (!). By 1927 there were 23 brackets and the second one, at 3%, kicked in at $4K ($55,500 in 2016) instead of $20K. And of course we are all aware of the current tax code’s problems. To chart a different course for the UBI is, in my opinion, a work of fantasy.

Final thoughts

Because of politics, I think an increase in the EITC (and reducing its error rate), for both working parents and single adults, coupled with criminal justice reform that reduces the number of non-violent felons—who have a hard time finding employment upon release—are preferable to a UBI.

I also support the abolition of the minimum wage, which harms the job prospects of low-skilled workers. If we are going to tie anti-poverty programs to work in order to encourage movement towards self-sufficiency, then we should make it as easy as possible to obtain paid employment. Eliminating the minimum wage and subsidizing income through the EITC is a fairer, more efficient way to reduce poverty.

Additionally, if a minimum standard of living is something that is supported by society than all of society should share the burden via tax-funded welfare programs. It is not philanthropic to force business owners to help the poor on behalf of the rest of us.

More economic growth would also help. Capitalism is responsible for lifting billions of people out of dire poverty in developing countries and the poverty rate in the U.S. falls during economic expansions (see previous poverty rate figures). Unfortunately, growth has been slow over the last 8 years and neither presidential candidate’s policies inspire much hope.

In fact, a good way for the government to help the poor is to reduce regulation and lower the corporate tax rate, which would help economic growth and increase wages.

Despite the relatively high official poverty rate in the U.S., poor people here live better than just about anywhere else in the world. Extreme poverty—think Haiti—doesn’t exist in the U.S. On a consumption rather than income basis, there’s evidence that the absolute poverty rate has fallen to about 4%.

Given the way government functions I don’t think there is much left for it to do. Its lack of local knowledge and resulting blunt, one size fits all solutions, coupled with its general inefficiency, makes it incapable of helping the unique cases that fall through the current social safety net.

Any additional progress will need to come from the bottom up and I will discuss this more in a future post.

Women are driving recent increase in age 25-54 labor force participation

Josh Zumbrun from the WSJ posted some interesting labor market charts that use data from today’s September jobs report. The one that jumped out at me was the one below, which shows the prime-age (age 25-54) employment and labor force participation (LFP) rate.

wsj-prime-age-sept-16-prime-age-lfp

In a related tweet he notes that the 25 – 54 LFP rate is up nearly 1 percentage point in the last year. The exact number is 0.9 from Sept. 2015 to Sept. 2016, and in the figure above you can clearly see an increase in the blue line at the end. So does this mean we are finally seeing a recovery in the prime age LFP rate? Yes and no.

I dug a little deeper and females appear to be driving most of the trend. The figure below shows the prime age male and female LFP rates from Jan. 2006 to the Sept. 2016. (Female data series LNS11300062 and male series LNS11300061)

oct-female-male-lfp-rate-1-06-9-16

As shown in the figure, the female LFP rate (orange line) appears to be steadily increasing since September of last year while the male LFP rate (blue line) is flatter. To get a better look, the following figure zooms in on the period January 2015 to September 2016 and adds a linear trend line.

oct-male-female-lfp-rate-1-15-9-16

The female LFP rate does appear to be trending up since the beginning of last year, but the male line is essentially flat.

Much has been made about the short-term and long-term decline of the prime-age male LFP rate. President Obama’s Council of Economic Advisors wrote an entire report about it, and economists such as Larry Summers have recently said that figuring out why males are dropping out of the labor force and what to do about it is “vital to our future”.

The recent uptick in the overall prime-age LFP rate is a good sign, but it appears to be largely driven by women. I think it’s still too early to say that the LFP rate of prime-age men has started to improve, and what this means for the future is still unknown.

Privatizing Water Facilities Can Help Cash-Strapped Municipalities

In my latest Forbes piece I discuss water privatization in the U.S. and why it is often a good idea.

“A public-private partnership has several benefits versus a completely public system. First, private firms often operate in many different jurisdictions, which means they have more experience and are able to institute best practices based on their accumulated knowledge.

Second, there is more oversight. The firm has an incentive to provide the specified water quality in order to maintain their business with the city and to avoid being sued for breach of contract. Local government officials can easily monitor the firm since they only need to focus on water quality and availability. If either the government or the firm fail to do their job, the other entity can alert residents.

Third, private companies are often better situated to maintain the infrastructure than public ownership, and public choice analysis helps explain why. Under complete government ownership, rate increases are a political decision rather than a business decision. There is a strong incentive for government officials to keep rates low, especially during election years, since rate increases rarely lead to votes.

Moreover, it’s difficult for politicians to commit to making necessary infrastructure improvements since the deterioration of a city’s water infrastructure is a long process that’s hard for the average voter to notice. A politician can get more votes by allocating tax dollars to conspicuous things like additional policemen or shiny, new fire trucks—it’s hard to trot out a new water main at a campaign rally.”

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.

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.

Congestion taxes can make society worse off

A new paper by Jeffrey Brinkman in the Journal of Urban Economics (working version here) analyzes two phenomena that are pervasive in urban economics—congestion costs and agglomeration economies. What’s interesting about this paper is that it formalizes the tradeoff that exists between the two. As stated in the abstract:

“Congestion costs in urban areas are significant and clearly represent a negative externality. Nonetheless, economists also recognize the production advantages of urban density in the form of positive agglomeration externalities.”

Agglomeration economies is a term used to describe the benefits that occur when firms and workers are in proximity to one another. This behavior results in firm clusters and cities. In regard to the existence of agglomeration economies, economist Ed Glaeser writes:

“The concentration of people and industries has long been seen by economists as evidence for the existence of agglomeration economies. After all, why would so many people suffer the inconvenience of crowding into the island of Manhattan if there weren’t also advantages from being close to so much economic activity?”

Since congestion is a result of the high population density that is also associated with agglomeration economies, there is tradeoff between the two. Decreasing congestion costs ultimately means spreading out people and firms so that both are more equally distributed across space. Using other modes of transportation such as buses, bikes and subways may alleviate some congestion without changing the location of firms, but the examples of London and New York City, which have robust public transportation systems and a large amount of congestion, show that such a strategy has its limits.

The typical congestion analysis correctly states that workers not only face a private cost from commuting into the city, but that they impose a cost on others in the form of more traffic that slows everyone down. Since they do not consider this cost when deciding whether or not to commute the result is too much traffic.

In economic jargon, the cost to society due to an additional commuter—the marginal social cost (MSC)—is greater than the private cost to the individual—the marginal private cost (MPC). The result is that too many people commute, traffic is too high and society experiences a deadweight loss (DWL). We can depict this analysis using the basic marginal benefit/cost framework.

congestion diagram 1

In this diagram the MSC is higher than the MPC line, and so the traffic that results from equating the driver’s marginal benefit (MB) to her MPC, CH, is too high. The result is the red deadweight loss triangle which reduces society’s welfare. The correct amount is C*, which is the amount that results when the MB intersects the MSC.

The economist’s solution to this problem is to levy a tax equal to the difference between the MSC and the MPC. This difference is sometimes referred to as the marginal damage cost (MDC) and it’s equal to the external cost imposed on society from an additional commuter. The tax aligns the MPC with the MSC and induces the correct amount of traffic, C*. London is one of the few cities that has a congestion charge intended to alleviate inner-city congestion.

But this analysis gets more complicated if an activity has external benefits along with external costs. In that case the diagram would look like this:

congestion diagram 2

Now there is a marginal social benefit associated with traffic—agglomeration economies—that causes the marginal benefit of traffic to diverge from the benefits to society. In this case the efficient amount of traffic is C**, which is where the MSC line intersects the MSB line. Imposing a congestion tax equal to the MDC still eliminates the red DWL, but it creates the smaller blue DWL since it reduces too much traffic. This occurs because the congestion tax does not take into account the positive effects of agglomeration economies.

One solution would be to impose a congestion tax equal to the MDC and then pay a subsidy equal to the distance between the MSB and the MB lines. This would align the private benefits and costs with the social benefits and costs and lead to C**. Alternatively, since in this example the cost gap is greater than the benefit gap, the government could levy a smaller tax. This is shown below.

congestion diagram 3

In this case the tax is decreased to the gap between the dotted red line and the MPC curve, and this tax leads to the correct amount of traffic since it raises the private cost just enough to get the traffic level down from CH to C**, which is the efficient amount (associated with the point where the MSB intersects the MSC).

If city officials ignore the positive effect of agglomeration economies on productivity when calculating their congestion taxes they may set the tax too high. Overall welfare may improve even if the tax is too high (it depends on the size of the DWL when no tax is implemented) but society will not be as well off as it would be if the positive agglomeration effects were taken into account. Alternatively, if the gap between the MSB and the MB is greater than the cost gap, any positive tax would reduce welfare since the correct policy would be a subsidy.

This paper reminds me that the world is complicated. While taxing activities that generate negative externalities and subsidizing activities that generate positive externalities is economically sound, calculating the appropriate tax or subsidy is often difficult in practice. And, as the preceding analysis demonstrated, sometimes both need to be calculated in order to implement the appropriate policy.

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.