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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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Economic Impacts of the Culinary Industry in San Antonio in 2019 and 2020

I recently completed an economic impact analysis of the culinary industry in San Antonio in 2019 and 2020 for the San Antonio City of Gastronomy program. A summary of the results is shown in the following table. For the detailed results, please see the full report.

The culinary industry in San Antonio directly employed 125,770 workers and paid wages and benefits of $4,4 billion in 2019. The industry had a direct economic impact as measured by output of about $16.6 billion. The direct contributions to gross regional product (GRP) of the industry totaled $7.1 billion. However, with the impact of the COVID-19 pandemic, these impacts declined in 2020 with direct employment in the industry falling to 110,121 and wages and benefits declining to $4.0 billion. Direct economic impact shrank to about $15.8 billion, while the industry’s contribution to gross regional product fell to $6.5 billion.

When multiplier effects are included, the total employment supported by the culinary industry in San Antonio in 2019 was 227,764 workers who earned wages and benefits of almost $8.0 billion. The total economic impact on the local economy as measured by output amounted to $29.3 billion, and the industry’s contribution to GRP in 2019 was $13.4 billion. Like with the direct impacts, the total impacts declined in 2020. Total employment supported by the culinary industry declined to 208,642 jobs with incomes of $7.3 billion. The total output (i.e., economic impact) fell almost $1.5 billion to about $28.0 billion, and the total contribution to GRP declined 6.9% to $12.5 billion.

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A Brief Look at One Measure of Inequality in San Antonio as of 2015

Income inequality has been a serious issue in the U.S. for many years now. The coronavirus pandemic has not only very clearly exposed the income inequalities across the country, but it has also blatantly displayed the devastating effects of such inequality. For a great exposition of these effects, I encourage you to read Unbound: How Inequality Constricts Our Economy and What We Can Do about it by Heather Boushey. I am starting to research further into the inequality in San Antonio and the other major metropolitan areas across Texas. I will document this research here but thought I would begin by sharing the findings of one study that delves deeply into the issue across states, metropolitan areas, and counties.

One of the first studies I discovered in this research is a report published by the Economic Policy Institute in 2018, “The New Gilded Age: Income Inequality in the U.S. by State, Metropolitan Area, and County,” by Estelle Sommeiller and Mark Price (https://www.epi.org/publication/the-new-gilded-age-income-inequality-in-the-u-s-by-state-metropolitan-area-and-county/#epi-toc-4). They calculate income inequality as the ratio of the average income of the top 1% to the average income of the bottom 99%. In this report, they provide the numbers for 2015. The level of income inequality by this measure in the major metropolitan areas of Texas and the state are provided in the following table.

In the table, a lower ratio indicates a lower level of inequality. Of the major metropolitan areas in Texas, El Paso has the lowest level of inequality with a ratio of 13.6, and it is the only MSA with a ratio below the median of all metropolitan areas in the country. San Antonio has the second lowest ratio at 20.4, which is higher than the median of 15.5. Houston has the highest level of inequality with a ratio of 25.5, but this is just slightly higher than Austin and Dallas-Fort Worth. The ratio of income inequality in Texas is 24.2, which is higher than the ratio of the median state (South Carolina) at 19.7 but lower than inequality in the U.S. with a ratio of 26.3.

These figures only show inequality as of 2015 by this one measure. I will explore the changes in inequality over time, as well as look at it by other measures.

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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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GDP and the Role of Women in the San Antonio Economy

My colleague, Belinda Román and I, have been working on a study of a more accurate measure of the role of women in the San Antonio economy. The results were released this past Wednesday at the San Antonio Hispanic Chamber’s Women’s Award Luncheon. The presentation can be found here.

This is the first study done under our new Women in the Economy Research Program at the SABÉR Institute. There is still much to be researched in this area, but we began by calculating what the gross domestic product of the San Antonio metropolitan economy would be if the non-market household production activities were counted in GDP and if women received equal pay to men.

Household production includes, in part, activities like child care, yard work, preparing meals, house cleaning, maintenance and repairs of the house, and travel time related to such activities.

As of 2016, GDP in San Antonio was $109.3 billion, and with these adjustments, GDP would be about $149.1 billion. We are still working to complete the full report, but it will be released in July.

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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Cost-Benefit Analysis of Excel Beyond the Bell San Antonio Partner Agencies

I had the honor to speak yesterday at the Excel Beyond the Bell San Antonio Annual Summit on the results of a study I did with Eddie Molina on the net benefits or return on investment that this network of out-of-school time agencies contribute to the local community. In short, for every dollar invested in these programs, the valuable services they provide to the youth of San Antonio returns $3.66 in benefits to the community.

These agencies serve 55,000 youth, which is a staggering number in and of itself, and they make a profound impact on many of these kids’ lives. Additionally, while this study did not look directly at their potential impact on economic development, these programs are vital to the future development of San Antonio’s economy, since they are playing such a big role in developing the future workforce and enhancing the quality of life of the community.

The slides I used for my speech can be found here, and the full report can be found here.

Steve

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