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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.

Here is a link to my latest piece on Forbes.com

New research shows that some local economies avoid slumps during national recessions and that an educated population and flexible housing supply can help.

Recessions Don’t Have The Same Impact On Every City

 

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.

Location-based programs that provide tax credits to firms and investors that locate in particular areas are popular among politicians of both parties. Democrats tend to support them because they are meant to revitalize poorer or rural areas. In a recent speech about the economy, presumed Democratic nominee Hillary Clinton spoke favorably about two of them: the New Markets Tax Credit Program and Empowerment Zones.

Some Republicans also support such programs, which they view as being a pro-business way to help low-income communities. However, House Speaker Paul Ryan’s recent tax reform blueprint generally disapproves of tax credit programs.

Due to the volume of location-based programs and their relatively narrow objectives, many taxpayers are unfamiliar with their differences or unaware that they even exist. This is to be expected since most people are never directly affected by one. In this post I explain one that Hillary Clinton recently spoke about, the New Markets Tax Credit (NMTC) program.

The NMTC program was created in 2000 as part of the Community Renewal Tax Relief Act. It is managed by the Community Development Financial Institutions Fund, which is a division of the U.S. Treasury Department.

The NMTC program provides both new and established businesses with a tax credit that can be used to offset the costs of new capital investment or hiring new workers. The goal is to increase investment in low income communities (LIC) in order to improve the economic outcomes of residents.

Even though the program was started in 2000, no funds were issued to investors until 2003 (although some funds were allocated to the program in 2001 and 2002). Since 2001 over $43 billion has been allocated to the program. The figure below shows the allocations by year, amount issued to investors, and the total amount allocated from 2001 – 2014 (orange bar, uses right axis).

NMTC allocations Figure 1

Practically all of the allocated funds from 2001 to 2012 have been issued to investors. A little over $250 million remains from 2013 and $1.3 billion from 2014. As the figure makes clear, this program controls a non-trivial amount of money.

The types of projects funded by the NMTC program can be seen in the figure below. The data for this figure comes from a 2013 Urban Institute report.

NMTC projects funded Figure 2

So what have taxpayers gotten for their money? The program’s ‘fact sheet’ asserts that since 2003 the program has

“…created or retained an estimated 197,585 jobs. It has also supported the construction of 32.4 million square feet of manufacturing space, 74.8 million square feet of office space, and 57.5 million square feet of retail space.”

Like many government program administrators, those running the NMTC program seem to confuse outputs with outcomes. Presumably the goal of the NMTC program is not to build office space, which is a trivial achievement, but to improve the lives of the people living in low income communities. In fact, the program’s fact sheet also states that

“Investments made through the NMTC Program are used to finance businesses, breathing new life into neglected, underserved low-income communities.”

What really matters is whether the program has succeeded at “breathing new life” into LICs. To answer this more complicated question one needs to examine the actual economic outcomes in areas receiving the credits in order to determine whether they have improved relative to areas that haven’t received the credits. Such an exercise is not the same thing as simply reporting the amount of new office space.

That being said, even the simpler task of measuring new office space or counting new jobs is harder than it first appears. It’s important for program evaluators and the taxpayers who fund the program to be aware of the reasons that either result could be speciously assigned to the tax credit.

First, the office space or jobs might have been added regardless of the tax credit. Firms choose locations for a variety of reasons and it’s possible that a particular firm would locate in a particular low income community regardless of the availability of a tax credit. This could happen for economic reasons—the firm is attracted by the low price of space or the location is near an important supplier—or the location has sentimental value e.g. the firm owner is from the neighborhood.

A second reason is that the firms that locate or expand in the community might do so at the expense of other firms that would have located there absent the tax credit. For example, suppose the tax credit attracts a hotel owner who due to the credit finds it worthwhile to build a hotel in the neighborhood, and that this prevents a retail store owner from locating on the same plot of land, even though she would have done so without a credit.

The tax credit may also mistakenly appear to be beneficial if all it does is reallocate investment from one community to another. Not all communities are eligible for these tax credits. If a firm was going to locate in a neighboring community that wasn’t eligible but then switched to the eligible community upon finding out about the tax credit then no new investment was created in the city, it was simply shifted around. In this scenario one community benefits at the expense of another due to the availability of the tax credit.

A new study examines the NMTC program in order to determine whether it has resulted in new employment or new businesses in eligible communities. It uses census tract data from 2002 – 2006. In order to qualify for NMTCs, a census tract’s median family income must be 80% or less of its state’s median family income or the poverty rate of the tract must be over 20%. (There are two other population criteria that were added in 2004, but according to the study 98% qualify due to the income or poverty criterion.)

The authors use the median income ratio of 0.8 to separate census tracts into a qualifying and non-qualifying group, and then compare tracts that are close to and on either side of the 0.8 cutoff. The economic outcomes they examine are employment at new firms, number of new firms, and new employment at existing firms.

They find that there was less new employment at new firms in NMTC eligible tracts in the transportation and wholesale industries but more new employment in the retail industry. Figure 2 shows that retail received a relatively large portion of the tax credits. This result shows that the tax credits helped new retail firms add workers relative to firms in transportation and manufacturing in eligible census tracts.

The authors note that the magnitude of the effects are small—a 0.2% increase in new retail employment and a 0.12% and 0.41% decrease in new transportation and wholesale employment respectively. Thus the program had a limited impact during the 2002 – 2006 period according to this measure, despite the fact that nearly $8 billion was granted to investors from 2002 – 2005.

The authors find a similar result when examining new firms: Retail firms located in the NMTC eligible tracts while services and wholesale firms did not. Together these two results are evidence that the NMTC does not benefit firms in all industries equally since it causes firms in different industries to locate in different tracts. The latter result also supports the idea that firms that benefit most from the tax credit crowd out other types of firms, similar to the earlier hotel and retail store example.

Finally, the authors examined new employment at existing firms. This result is more favorable to the program—an 8.8% increase in new employment at existing manufacturing firms and a 10.4% increase at retail firms. Thus NMTCs appear to have been primarily used to expand existing operations.

But while there is evidence that the tax credit slightly increased employment, the authors note that due to the limitations of their data they are unable to conclude whether the gains in new employment or firms was due to a re-allocation of economic activity from non-eligible to eligible census tracts or to actual new economic activity that only occurred because of the program. Thus even the small effects identified by the authors cannot be conclusively considered net new economic activity generated by the NMTC program. Instead, the NMTC program may have just moved economic activity from one community to another.

The mixed results of this recent study combined with the inability to conclusively assign them to the NMTC program cast doubt on the programs overall effectiveness. Additionally, the size of the effects are quite small. Thus even if the effects are positive once crowding out and reallocation are taken into account, the benefits still may fall short of the $43.5 billion cost of the program (which doesn’t include the program’s administrative costs).

An alternative to location-based tax credit programs is to lower tax rates on businesses and investment across the board. This would remove the distortions that are inherent in location-based programs that favor some areas and businesses over others. It would also reduce the uncertainty that surrounds the renewal and management of the programs. Attempts to help specific places are often unsuccessful and give residents of such places false hope that community revitalization is right around the corner.

Tax credits, despite their good intentions, often fail to deliver the promised benefits. The alternative—low, stable tax rates that apply to all firms—helps create a business climate that is conducive to long-term planning and investment, which leads to better economic outcomes.

Washington’s Legitimacy Crisis Presents an Opportunity for the States

June 28, 2016

You’ve heard it before. Americans are deeply unhappy with Washington, DC. Sixty-five percent say the country is on the wrong track. Confidence in institutions is near all-time lows. Congress’s approval rating is terrible, and the two major presidential candidates are viewed more negatively than any other mainstream presidential candidates in recent memory. Only nineteen percent of the public trust the government to do the right […]

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Does Tax Increment Financing (TIF) generate economic development?

June 20, 2016

Tax increment financing, or TIF, is a method of financing economic development projects first used in California in 1952. Since then, 48 other states have enacted TIF legislation with Arizona being the lone holdout. It was originally conceived as a method for combating urban blight, but over time it has become the go-to tool for […]

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Washington DC is set to become the latest city to make it illegal for low-skill people to work

June 8, 2016

In the latest example of politics trumping economics, Washington DC’s city council voted to increase the city’s minimum wage to $15 per hour by 2020. The economic arguments against a minimum wage are well-known to most people so I won’t rehash them here, but if you want to read more about why the minimum wage […]

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Northern Cities Need To Be Bold If They Want To Grow

May 11, 2016

Geography and climate have played a significant role in U.S. population growth since 1970 (see here, here, here, and here). The figure below shows the correlation between county-level natural amenities and county population growth from 1970 – 2013 controlling for other factors including the population of the county in 1970, the average wage of the […]

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Baltimore’s misguided move to raise its minimum wage will harm its most vulnerable

April 22, 2016

Baltimore’s city council, like others around the country, is considering raising the city’s minimum wage to $15 per hour. This is an ill-advised move that will make it harder for young people and the least skilled to find employment, which is already a difficult task in Baltimore. The figure below shows the age 16 – […]

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States with lower minimum wages will feel the impact of California’s experiment

April 8, 2016

California governor Jerry Brown recently signed a law raising California’s minimum wage to $15/hour by 2022. This ill-advised increase in the minimum wage will banish the least productive workers of California – teens, the less educated, the elderly – from the labor market. It will be especially destructive in the poorer areas of California that […]

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