Interesting Changes in Industry Concentration in San Antonio

One common indicator used to get a sense of the structure of a local economy is the location quotient. Specifically, it measures the concentration of an industry in a local economy, such as a metropolitan area economy or a state economy, relative to the concentration of the same industry in some base area, typically the national economy. The most often used data to calculate the location quotient is employment, but income or wages is also used. The location quotient for industry i in region r is calculated using the following formula:

LQir = (Employmentir/Total Employmentir)/(EmploymentUS/Total EmploymentUS)

I did these calculations for the San Antonio metropolitan area economy using this formula. I calculated the location quotients for the NAICS 2-digit level industries. The names of these industries and the location quotients as of January 1990 and April 2017 are shown in the following table. April 2017 was used because it was the most current data available at the time I made the calculations.

Four industries in San Antonio have seen increases in their concentration levels since January 1990 (highlighted in yellow). The construction, mining, and logging industry saw the largest increase in relative concentration followed by financial activities, professional and business services, and manufacturing.

The largest declines in the location quotients were in the government sector followed by other services. The hospitality and education and health industries also saw smaller declines in their relative concentrations, and while the trade, transportation, and utilities and the information industries both saw declines so small one should probably just treat these as being inconsequential.

It is also interesting to note that a location quotient greater than 1.00 indicates that the concentration of the industry in the region is greater than the concentration at the level of the national economy.

As of April 2017, the industries with such location quotients were construction, mining, and logging; information; financial activities; education and health; hospitality; and government. The highest location quotient as of April 2017 was the financial activities industry; it had the second highest location quotient in January 1990. The industry with the highest location quotient in January 1990 was government.


These changes highlight two interesting characteristics of the San Antonio economy.

First, it is an economy with a broad base of industries with relatively high concentration levels. Second, the relative base of employment has shifted away from government. This is not to say that government activities and funding are not still a vital component of the San Antonio economy because they are. The military has a big impact on the local economy, and it is worth noting that the military does not have to report employment levels, so I do not believe they are captured in these calculations.

Additionally, government funding of healthcare is very important to the San Antonio economy due to the size of the healthcare industry in the region. That said, the government sector still has a location quotient of 1.08. This fact combined with the diversity of the industry base in San Antonio is why the economy also tends to be somewhat stable relative to regional economies with more focused industry bases.



Accounting for the Ocean Economy

The oceans are an important part of any economy, even those economies that are landlocked. The obvious importance comes from the food and entertainment options the oceans provide, but the oceans also provide invaluable environmental and ecosystem services that certainly have profound economic effects. Maintaining healthy oceans that are sustainable for future generations is vital for continued economic success, but accurately accounting for the ocean or “blue” economy is vital to accomplishing this. The immediacy of achieving this accurate measurement of the ocean economy, including the environmental and ecosystem services the oceans provide, must also be recognized as the effects of climate change are upon us. If we don’t create these measures as accurately and completely as possible, I don’t see how we can fully understand the economic importance of the oceans and move forward with policies and initiatives that will improve their health and sustainability.

This is why I think the special edition recently published by the Journal of Ocean and Coastal Economics is so important. The journal is published by the Center for the Blue Economy at the Middlebury Institute of International Studies at Monterey, California. This special edition, titled Oceans and National Income Accounts: An International Perspective, is a publication of the papers presented at a meeting hosted by the Center for the Blue Economy in October 2015 “to explore ways in which the economic values of oceans and marine resources can be incorporated into national income accounts.”¹

If you are reading this blog, you obviously have an interest in economics, and I highly recommend you read this special edition because if you truly want to understand how the economy functions, you have to understand how it is measured, or not measured. This is especially true for the oceans and the important contributions they make to all economies. As you get into the articles, you will get a deeper understanding of these contributions and the complexities involved in measuring them. It may not seem like the most interesting reading, but given your interest in economics, I think you will find it more engaging than you might think after you start reading the article. The Center for the Blue Economy is a leader in conducting research on the blue economy, disseminating that information through this journal, conferences, and other means, educating future researchers, and raising awareness about the importance of the blue economy, so I also encourage you to follow their other activities. Their website is a treasure trove of information.


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¹Colgan, Charles S. (2016) “Introduction to Special Edition: The Oceans and National Income Accounts: An International Perspective,” Journal of Ocean and Coastal Economics: Vol. 2, Article 1.

San Antonio Economic Forecast Update

I recently presented an update to my 2016 forecast for the San Antonio economy.

Please find the full presentation slides here.

In short, the growth in the San Antonio economy has slowed this year as anticipated. As shown in the following two graphs, through July, employment had grown 2.15% compared to July of 2015 and unemployment was at 2.8% (seasonally adjusted). My forecast for San Antonio this year was for employment growth between 2.25-2.75% and an unemployment rate in the range of 3.5-3.7%. While the July figures are slightly outside these ranges, I am leaving my forecast as is with the recognition that employment growth may end the year a bit lower than 2.25% and unemployment may come in at a rate slightly above 3.7%.

Unemployment rate as of July 2016Employment growth through July 2016

Please feel free to contact me with any questions regarding the report.


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Blind Pursuit of the Free Market Does not Lead to Prosperity

While I think the perfectly competitive model as it is presented in economics has some uses in helping us understand economic behavior, I believe the way it is presented in economics classes has lead to a vast misunderstanding of the workings of the economy. The presentation typically gives the impression that government intervention in the economy is only bad, except for instances where market failures exist. The problem, in my opinion, is that very little attention is given to the assumptions necessary to make the model work. Sure, these are most often covered quickly at the beginning of the presentation of the model, but the rest of the course or discussion of this model is spent showing who this leads to equilibrium in the markets and how government intervention pulls the market away from this equilibrium and leads to a loss of welfare. However, if one stops and thinks about it, the assumptions of the model (e.g., economic agents act rationally, perfect information, perfectly mobile resources) mean that the free market really never exists. By its very inherent nature, market failure is always present, and because of this and the fact that markets and the economy are huge complex systems, not the isolated static mechanisms of the perfectly competitive model, they are rarely, if ever, in equilibrium.

I want to stress again that there are still some valuable lessons that can be taken from the perfectly competitive model. It is an elegant model that lead to some intoxicating conclusions, but because of this and the lack of emphasis of the assumptions underlying the model, it has lead to a lot of misguided economic policy. This is especially the case with respect to macroeconomic policy, which has been misguided by the absurd dynamic stochastic general equilibrium model. This has lead to the belief by many that all regulations and government intervention are bad and that if we would only get rid of almost all regulations, cut taxes, and minimize the size of government, markets would be able to operate freely leading to more prosperity and a better society.

To be clear, I am not arguing that government is the answer to everything, nor am I arguing that we should raise taxes to exorbitant levels. But, this blind pursuit of the free market based on the misapplication of economic theory or just bad economic theory does not lead to prosperity either. There has to be a balance between the two. Even Adam Smith (one of the greatest, if not the greatest, political economists, to have ever lived), whose Wealth of Nations is the standard bearer for all those in blind pursuit of the free market, recognized the need for balance, as he thoroughly discussed in his Theory of Moral Sentiments.

This has lead to the belief that the ideas of cutting taxes (mostly for those in the upper income strata and the wealthy) and shrinking the government will lead to prosperity and improved social outcomes. Two articles recently published in the New York Times provide even more evidence that this is not the case. One of the articles was written by two political science professors, Jacob S. Hacker of Yale University and Paul Pierson at the University of California, Berkeley. The article, “The Path to Prosperity Is Blue,” is a brief summary of their book, American Amnesia: How the War on Government Led Us to Forget What Made America ProsperI think the following quote from the article summarizes their argument.

Mr. Trump and House Speaker Paul Ryan are united by the conviction that cutting taxes – especially on corporations and the wealthy – is what drives growth.

A look at the states, however, suggests that they’re wrong. Red states dominated by Republicans embrace cut and extract. Blue states dominated by Democrats do much more to maintain their investments in education, infrastructure, urban quality of life and human services – investments typically financed through more progressive state and local taxes. And despite what you have heard, blue states are generally doing better.

Work by Jon Bakija, Lane Kenworthy, Peter Lindert, and Jeff Madrick in their book, How Big Should Our Government Be?provides some evidence against the argument that small government facilitates economic growth. They show evidence that there is a direct relationship between the growth of government and economic growth. Over the past fifty years, those countries where governments have grown the largest over the  past fifty years have also experienced some of the fastest economic growth (see the chart here).

While governments are certainly not perfect, and as I have already mentioned, government is not the answer to every issue or problem, but it seems clear to me that government has an important role to play in the proper functioning of an economy and society. Blind pursuit of the neoclassical notion of the free market with the wildly unrealistic assumptions at its foundation can be very appealing, but it leads to bad economic policy in many cases.

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