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San Antonio Economic Forecast 2022

The San Antonio economy has bounced back from the pandemic-induced recession quite nicely, and I believe the economy will likely continue to show growth at or slightly above its long-term trend in 2022. I project employment growth this year to be in the range of 2.2-2.7%, and the unemployment rate will continue to decline to about 3.5-4.0%. The data, trends, and potential factors that I am seeing in my crystal ball that form the basis for this forecast are discussed in the rest of this post.

After a quick rebound from the pandemic-induced recession, the San Antonio economy has moved toward its more long-term average growth rate in employment. This is somewhat against the pattern seen in the other major metropolitan economies across Texas, as they have continued to maintain historically strong growth. This is especially the case for the Austin economy. These patterns are evident in the following chart showing the year-over-year employment growth. Even though many of these areas have continued to experience such strong growth, it is clear that there is a sizable gap between them and the Austin economy.

As shown in Chart 2, the Austin economy grew 8.11% percent in December, which was still substantially larger than the second-fastest growing region – Dallas – at 5.82% and Fort Worth, the third fastest growing region at 5.02%. The San Antonio economy grew 2.87% in December – the slowest among the major metropolitan regions and below the growth rate across the state of 5.08% and the U.S. at 4.52%.

The large disparities in the growth of the Austin economy relative to San Antonio, and the other major metropolitan economies in Texas for that matter, is worth exploring, and I will have a post on that soon. For now, I want to focus on San Antonio.

Chart 3 shows the year-over-year employment growth by month across broadly-defined industries from January 2019 through December 2021 for San Antonio. As expected, the hospitality industry took the largest dive during the lock down followed by the professional services industry. These two industries have also had the largest immediate recoveries, along with the other services industry.

Chart 4 and Table 1 show the employment growth by industry from the depth of the pandemic-induced recession in April 2020 to a year later in April 2021, i.e., from trough to peak, and then for the remainder of 2021. It needs to be kept in mind that these are similar lengths of time, but it is clear from these numbers that the growth rates across almost all of the industries in San Antonio have slowed considerably. The manufacturing, construction and mining, and education and health industries have seen their growth basically stall or even turn slightly negative in the last three quarters of 2021. The one exception is the hospitality industry that not surprisingly continues to experience growth far above average.

Table 2 compares employment growth in San Antonio over its history leading up to the pandemic (Jan. 1991-Dec. 2019) to the growth rates across industries over the past year. Overall employment growth in 2021 was 2.87%, a bit above the historical average of 2.37% growth. Five of the ten industries – manufacturing; trade transportation, and utilities (TTU); professional services; hospitality; and other services – continued to grow at above average rates in 2021. Not too surprisingly, the hospitality industry continues to lead the growth with a rate of 10.87% in 2021 – far above the industry’s historical average. Only two industries experienced declining growth in 2021 – construction and mining and information. As shown in Chart 3, the declining growth in the information industry is a regression back to the mean based on recent history. Not to give away too much of the punch line for my next post, but this explains, in part, the difference in growth rates between Austin and San Antonio.

I expect these overall slowing trends in employment growth to continue through 2022 in San Antonio. Some of this is just going to be a regression back to the mean from the large growth rates as the economy recovered from the pandemic-induced recession. The structure of the San Antonio economy is an additional reason, and the potential effects of growth in the global and national economies will also play a role, as discussed below.

Similar to the pattern in the other major metropolitan Texas economies and across the state and U.S, the unemployment rate in San Antonio has steadily declined after the precipitous fall following the re-opening of the economy ending 2021 at a rate of 4.2% (see Chart 5). As shown in Chart 6, San Antonio had one of the lowest unemployment rates among the major metropolitan economies in Texas before the pandemic at 3.0%. However, San Antonio experienced one of the largest surges in its unemployment as it climbed to 14.1% in April 2020 at the depth of the recession, but as noted, unemployment has been consistently declining and is similar to the rate in Dallas (4.1%) and Fort Worth (4.2%). The unemployment rate in San Antonio is also lower than the statewide rate at 5.0%, but it is a bit higher than the U.S. unemployment rate at 3.9%. Compared to San Antonio, the unemployment rate in Austin was 0.9 percentage point lower at the end of 2021 at 3.3%. The strong economic growth since April 2020 has surely been the main driver pushing unemployment rates down, but it should be kept in mind that at least part of this decline may be due to the decline in the labor force participation rate due to the Great Resignation phenomenon. In fact, while the labor force participation has been increasing, it is still below the pre-pandemic rate of 63.4% in February 2020 for the U.S.

These structural changes in the labor market are one of the risk factors to this forecast. I can see these changes potentially having both positive and negative effects on economic growth. If the labor market adjusts to these changes fairly quickly and workers fill the jobs at higher pay and with enhanced benefits, this could serve as a boost to overall economic growth. However, if the current trend continues for an extended period of time, this could continue to exacerbate the shortages in many markets and serve to dampen economic growth. These adjustments in the labor market may be forestalled in industries where there is a relative paucity of benefits, such as paid sick leave. If the shortages causing the rapid increase in the inflation rate do not diminish in the near future, the persistent inflation at relatively high rates will also likely be a deterrent to growth in and of itself. In response to this, the Federal Reserve has sent strong signals that it will most likely be raising interest rates several times this year, which will also serve to slow the economy some. There could also be bubbles in many asset markets, such as the stock and housing markets, and if one or more of those bubbles burst, they might also cause the economy to pause a bit, even if it does not push it into a recession. The strong economic growth was, at least in part, driven by the federal government stimulus, and with that coming to an end, consumer spending is likely to move back into a more typical pattern over time causing a moderation in U.S. economic growth. It is also likely that growth in the global economy will also slow this year because of similar trends, and the economic effects of the war in Ukraine may also slow global economic growth a bit. Overall, it seems these various factors combined with the structure of the San Antonio will mean the local economy will continue to grow fairly strongly in 2022 but at a slower rate than in 2021.

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Government Debt and Its Effects on Growth

As the government debt is swelling dramatically in the U.S. and other countries, there is concern that such high levels of debt will depress economic growth in the future. Research by Reinhart and Rogoff (2010) and Reinhart, Reinhart, and Rogoff (2012) indicate the threshold in which the level of debt as a proportion of GDP where growth rates start to decline is ninety percent. Others have argued that such a threshold does not exist because it is not the high debt that is causing growth to slow, but rather, it is slow growth that is causing the level of debt to escalate (Panizza and Presbitero, 2012; Herndon, Ash, and Pollin, 2013).

Pescatori, Sandri, and Simon (2014) take a little different look at the possibility of the existence of such a threshold and contribute some interesting insights. They look at different thresholds instead of focusing on just one, such as ninety percent, and they analyze growth performance over longer periods of time (5, 10, and 15 years) instead of just during the year after which a country’s debt level cross a threshold. This allows them to analyze the effects of changes in debt levels on growth and the longer-term effects. It also accounts for the potential reverse causality effects and the outlier periods of growth. Additionally, it mitigates some of the effects of omitted variables, such as automatic stabilizers (e.g., unemployment insurance).

Their findings are quite interesting.

…The sharp reduction in the following year’s growth that we observed in countries whose debt rose above 90 percent is no longer present for countries that have high but declining debt. In fact, even countries with debt ratios of 130 to 140 percent that are on a declining path have experienced solid growth. This suggests that high debt itself is not causing the low growth in these episodes. Furthermore,…the initial debt trajectory remains important event after 15 years, with falling debt associated with higher growth. That is, the trajectory of debt appears to be an important predictor of subsequent growth, buttressing the idea that the level of debt alone is an inadequate predictor of future growth [emphasis mine] (Pescatori, Sandri, and Simon, 2014, p. 41).

The data they analyzed covered the period from 1875 through the end of the last century. Recognizing that the wide variability in growth rates over some periods of this history (e.g., Great Depression, period following World War II) might distort their results, they “compared an economy’s average growth rate during an episode with the simple average of growth rates for all economies over the same period” (p. 41). Even after this adjustment, they still found

“that, in general, the growth performance of economies with high debt is fairly close to that of their peers with lower debt…Furthermore, we found that an economy’s debt trajectory still matters. Among economies with the same debt levels, the growth performance over the next 15 years in countries in which debt is initially decreasing is better than in countries where it is initially increasing…It is particularly striking for debt levels between 90 and 115 percent of GDP (for which average growth is 1/2 percentage point higher). Furthermore, there is no unique threshold that is consistently followed by a subpar growth performance…Economies with a debt level between 90 and 110 percent of GDP outperform their peers when debt is on a declining trajectory. At the least, this suggests that the debt level alone is insufficient to explain the growth potential of an economy. It also suggests that countries that have dealt with their budget deficits (as indicated by a declining debt level) may be well placed to growth in the future despite high debt levels” (Pescatori, Sandri, and Simon, 2014, p. 41).

They develop a few policy implications from this research. One is that since there does not appear to be any threshold effect, governments can engage in short-term fiscal stimulus, such as is being done in many countries in response to the pandemic, without being concerned that once they cross a certain threshold with debt, economic growth will slow. It is the trend in the debt to GDP ratio that matters, so what has the trend been in the U.S.?

The chart above shows the debt to GDP ratio in the U.S. The data only go through Q4 2019, so it does not include the current stimulus in response to the coronavirus pandemic. Once that is taken into account, this ratio will move even higher. It does not appear that the trajectory of the level of U.S. is moving in the right direction over the past decade. This is clearly due in part to the response to the Great Recession, but even during the historically long growth period following that recession, the level of debt compared to GDP continued to grow. This does not mean we should not be pursuing a stimulus in response to the pandemic, but as noted by the authors, the U.S. will need to reverse this trend once the economy gets back on track if the high level of debt is not going to have deleterious effects on the future growth rate of the U.S. economy.

References:

Herndon, T., Ash, M., and Pollin, R. (2013). Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Political Economy Institute Working Paper No. 322 (Amherst, Massachusetts).

Panizza, U., & Presbitero, A.F. (2012). Public debt and economic growth: Is there a causal effect? MoFIR Working Paper No. 65 (Ancoma, Italy: Money and Finance Research Group).

Pescatori, A., Sandri, D., & Simon, J. (2014). No magic threshold. Finance and Development, 51(2), 39-42. Retrieved from: https://www.imf.org/external/pubs/ft/fandd/2014/06/pescatori.htm.

Reinhart, C.M., & Rogoff, K.S. (2010). Growth in a time of debt. American Economic Review, 100(2), 573-78.

Reinhart, C.M., Reinhart, V.R., & Rogoff, K.S. (2012). Public debt overhangs: Advanced economy episodes since 1800. Journal of Economic Perspectives, 26(3), 69-86.

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Insights #2: Innovation is a Collective Process.

I am currently reading The Value of Everything by Mariana Mazzucato, and one of the great insights she provides in the book is the key role that the public sector plays in innovation. It busts the stereotype of innovation being driven by the lone inventor toiling away in his or her garage or dorm room. I believe she has written a book on this very topic, which I have not read, yet, but it is high on the reading list. I think the following passages summarize this insight pretty well.

Understanding both the role of the public sector in providing strategic finance, and the contribution of employees inside companies, means understanding that innovation is collective: the interactions between different people in different roles and sectors (private, public, third sectors) are a critical part of the process. Those who might otherwise be seen as lone entrepreneurs in fact benefit from such collectivity; moreover, they stand on the shoulders of both previous entrepreneurs and taxpayers who, as we will see, often contribute to the underlying infrastructure and technologies on which innovation builds (p.194).

Examples she provides include:

  • The smartphones many of us depend on these days are driven by technologies created with public funding.
    • The internet and SIRI were developed with funding from the U.S. Department of Defense.
    • Touchscreen display was developed with funding from the CIA.
    • GPS was developed with funding from the U.S. Navy.
  • The U.S. National Institutes of Health has funded the research supporting the development of two-thirds of the most innovative pharmaceuticals.
  • U.S. Department of Energy has funded many of the greatest breakthroughs in energy (p. 194).

As she then goes on to point out, “In the very early days it is often public R&D agencies or universities that fund the science base, and only when innovation is close to having a commercial application do private actors enter” (p. 195).

 

Source:

Mazzucato, M. (2018). The Value of Everything. New York, NY: PublicAffairs.

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Using Data to Foster International Trade, Foreign Direct Investment, and Collaborations Among Metropolitan Areas

The City of San Antonio has been engaged in a six-year process to identify opportunities in foreign markets for international trade, foreign direct investment, and institutional collaborations. The effort was lead by The Brookings Institution, and with the support of JPMorgan Chase, the final portion of the process, called the Global Cities Initiative, was recently completed. In this stage of the process, each of the nine cities involved in the process selected an industry or two on which to focus their efforts in determining these global opportunities. In the case of San Antonio, our specific focus was on the cybersecurity industry. The culmination of the work was the release of the report by The Brookings Institution, Six Steps for Metro Areas to Prioritize Global Markets.

The six steps include:

  1. Organize for action
  2. Select a priority specialization
  3. Set the goal
  4. Measure global market opportunity within the specialization
  5. Factor in market accessibility
  6. Combine and synthesize data

As they are listed, these steps are rather generic and do not say much. I was fortunate and honored to be a part of the San Antonio team working on the project, so I can say with first-hand knowledge, it is quite a thorough process that has educated and enriched the knowledge of the communities involved about the opportunities in cities around the world for particular industries. I am sure it can do the same for other cities that want to engage in the process. If you want to get into the detail, I highly recommend you read through the report authored by Max Bouchet, Marek Gootman, and Joseph Parilla of The Brookings Institution. It can be found here.

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Forecast of the San Antonio Economy as Presented to the GFOAT

I gave a speech today to the San Antonio chapter of the Government Finance Officers Association of Texas on the San Antonio economy. I will pull out specific charts and talk about them in detail over the next couple of weeks, but here is the entire speech for now. In short, the economy looks strong and should continue to be strong for the next year or so, but I think the probability of another recession starting within the next couple of years is pretty high.

Steve

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“Inextricable Connections” Are Important for Economic Development

As an economist whose research focuses on regional economies, I have often wondered about the economic and social impacts of the movement to online retail and social engagement in general through online means and away from interactions among physical persons. As one whose graduate degrees are in political economy, I am aware of the close connections between politics, a well-functioning government, and the functioning of the economy. Like many U.S. citizens, I am also increasingly concerned about the acrimony of our political environment in the U.S., especially, but also around the world.

I am reading Brene Brown’s, Braving the Wilderness, and among the many great insights in the book, she makes the point that we have a human need for “inextricable connection.”

All of these examples of collective joy and pain are sacred experiences. They are so deeply human that they cut through our differences and tap into our hardwired nature. These experiences tell us what is true and possible about the human spirit. We need these moments with strangers as reminders that despite how much we might dislike someone on Facebook or even in person, we are still inextricably connected. And it doesn’t have to be a big moment with thousands of strangers. We can be reminded of our inextricable connection after talking with a seatmate on a two-hour flight.

The problem is that we don’t show up for enough of these experiences. We clearly need them. But it’s vulnerable to lean in to that kind of shared joy and pain. We armor up. We shove our hands into our pockets during the concert or we roll our eyes at the dance or put our headphones on rather than get to know someone on the train (Brown, 2017, pp. 128-129).

The disrupting or tearing apart of these connections not only has social ramifications, but it also has economic effects that are not good. One of the key lessons I took away from the book is that it is easy to hate and spread nonsense when you can hide behind email and social media. One of her chapter titles summarizes it perfectly: “People Are Hard to Hate Close Up. Move In” (p. 63).

Reading the book highlighted one of the concerns I have been thinking about with respect to the effects of moving our everyday economic transactions and engagement with others both socially and economically to the online world. I took from Dr. Brown’s discussion that as this social disruption continues, the lack of personal engagement will decline as brick and mortar stores go out of business. Even though the interactions we have as we shop at one of these stores might be brief, it seems to me that they are very important per the points Dr. Brown makes as previously highlighted. As we lose these physical in-person interactions, it seems to me that it only exacerbates our vitriolic political climate, which is not good for our economic future.

Additionally, we may also lose the benefits and efficiencies that come from clusters of people (be they large or small numbers) engaging with one another in person. These are called agglomerations economies in economics. One of the biggest benefits that comes from these interactions are the transmission of ideas that lead to innovations that facilitate business growth, new business creation, and ultimately, economic development. Some argue that these can occur just as well in an online environment, and to some extent they do. What gets missed is the richness of the discussions that occur when in the physical presence of others that do not occur in an online environment. Sometimes (often times?), this just happens serendipitously as we wander the streets or engage in our daily activities – including our consumer activities at physical stores.

As usual, Dr. Brown states the importance of the physical interactions much more eloquently than I do.

As I started digging into this question [i.e., Is social media a toll to achieve collective joy and pain or more for the spreading of hate, unfounded statements, and picture of cute animals?] with research participants, there was very little ambiguity It became clear that face-to-face connection is imperative in our true belonging practice. Not only did face-to-face contact emerge as essential from the participant data in my research, but studies across the world confirm those findings. Social media are helpful in cultivating connection only to the extent that they’re used to create real community where there is structure, purpose, and meaning, and some face-to-face contact.

One of the most well-respected researchers in this area is Susan Pinker. In her book The Village Effect: How Face-to-Face Contact Can Make Us Healthier and Happier, Pinker writes, “In a short evolutionary time, we have changed from group-living primates skilled at reading each other’s every gesture and intention to a solitary species, each one of us preoccupied with our own screen.” Based on studies across diverse fields, Pinker concludes that there is no substitute for in-person interactions. They are proven to bolster our immune system, send positive hormones surging through our bloodstream and brain, and help us live longer. Pinker adds, “I call this building your village, and building it as a matter of life or death.”

…Social media are great for developing community, but for true belonging, real connection and real empathy require meeting real people in a real space in real time (Brown, 2017, pp. 140-141).

To be clear, I am not against shopping online or the internet or social media. I do my share of shopping online and certainly use the internet and social media, but I do think there are negative consequences for the economy that we need to keep in mind. One of these negative consequences is that it reduces our physical interactions with others, which reduces our understanding and tolerance of others. This leads to an inability to have reasonable and productive public debates and a dysfunctional democracy. Whether you love or dislike the government, a poorly functioning government has serious negative consequences for economic development. This lack of face-to-face interaction may also stifle the benefits of agglomerations economies, which could also slow economic development. In other words, the demise of online retail seems to be more than just structural changes happening in the economy. The reduction in face-to-face interactions leads to destructive social problems and slower development of the economy.

Just something to keep in mind as many of us consider where to shop at the end of the holiday season and spend all of those gift cards afterwards. Now, out the door I go to finish my last minute holiday shopping.

May you enjoy the season with those you love.

Steve

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References

Brown, B. (2017). Braving the Wilderness: The Quest for True Belonging and the Courage to Stand Alone. New York: Random House.

 

 

 

 

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The Imperative of Understanding the Role of Institutions, Culture, and History in Economics

I recently read an article by Dr. Avner Greif of Stanford University titled, “Cultural Beliefs and the Organization of Society: A Historical and Theoretical Reflection on Collectivist and individualist Societies.” While it is a somewhat dated article being published in 1994 (see citation below), Dr. Greif’s conclusion struck me as being very important and still applicable to understanding economic development and economics in general today. I think his concluding remarks are also important to take into consideration when one is attempting to apply economics in the making of public policy or just trying to understand a certain issue or event.

Here are the highlights I took from Dr. Greif’s conclusion.

…This paper points to factors that make trajectories of societal organization – and hence economic growth – path dependent. Given the technologically determined rules of the game, institutions – the nontechnological constraints on human interactions – are composed of two interrelated elements: cultural beliefs (how individuals expect others to act in various contingencies) and organizations (the endogenous human constructs that alter the rules of the game…). Thus the capacity of societal organizations to change is a function of its history, since institutions are combined of organizations and cultural beliefs, cultural beliefs are uncoordinated expectations, organizations reinforce the cultural beliefs that led to their adoption, and past organizations and cultural beliefs influence historically subsequent games, organizations, and equilibria.

Understanding the sources of institutional path dependence indicates the factors that forestall successful intersociety adoption of institutions for which there are many historical and contemporary examples…The view of institutions developed in this paper indicates why it is misleading to expect that a beneficial organization of one society will yield the same results in another. The effect of organizations is a function of their impact on the rules of the game and the cultural beliefs of the society within which this game is embedded. Analyzing economic and political institutions and the impact of organizational modifications requires the examination of the historical development and implications of the related cultural beliefs.

Past, present, and future economic growth is not a mere function of endowment, technology, and preferences. It is a complex process in which the organization of society plays a significant role. The organization of society itself, however, reflects historical, cultural, social, political, and economic processes. Comparative historical analysis is likely to enhance our comprehension of the evolution of diverse societal organization, since this process is historical in nature. Furthermore, such an analysis provides the historical perspective and diversity required to examine institutional evolution and the interrelations between culture, the organization of society, and economic growth (Greif 1994, 943-944).

What this means to me is that if we are truly going to understand economics, the process of economic development, and the functioning of economies, we have to also understand the related historical, political, social, cultural, and institutional elements. We can’t only rely on mainstream economic theory. The culture and institutions that are embedded within an economic system are vitally important to fully understanding how that economy functions at a macro level, as well as gaining a full understanding of the economic behavior at the micro level.

Furthermore, since history (along with culture) plays a key role in determining the path dependence of the economy’s institutions, it is imperative to understand the historical context of an economy in order to be able to appropriately apply economic theory to the development and implementation of effective policy. Institutions, culture, and history matter, but yet, we ignore them, for the most part, in mainstream economics…much to the detriment of society.

Reference

Greif, A. (1994). Cultural beliefs and the organization of society: A historical and theoretical reflection on collectivist and individualist societies. Journal of Political Economy, 102, 5, 912-950.

 

Steve

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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.

Slide1

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.

Steve

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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.

Enjoy.

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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.

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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.

Steve

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