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.
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.
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).
The unemployment rate in the U.S. was recently reported to be at 14.7% in April. Here is a link to the full report released by the U.S. Bureau of Labor Statistics. It is somewhat lengthy, but as always, it is worth a quick look, especially since this report contains some insightful information beyond the headline unemployment rate.
One insight is the difficulty in being able to correctly capture the data due to the unique situation caused by the pandemic. This is highlighted in the following statement from the report.
However, there was also a large increase in the number of workers who were classified as employed but absent from work. As was the case in March, special instructions sent to household survey interviewers called for all employed persons absent from work due to coronavirus-related business closures to be classified as unemployed on temporary layoff. However, it is apparent that not all such workers were so classified.
If the workers who were recorded as employed but absent from work due to “other reasons” (over and above the number absent for other reasons in a typical April) had been classified as unemployed on temporary layoff, the overall unemployment rate would have been almost 5 percentage points higher than reported (on a not seasonally adjusted basis). However, according to usual practice, the data from the household survey are accepted as recorded. To maintain data integrity, no ad hoc actions are taken to reclassify survey responses (pp. 5-6).
As noted in the statement, they calculate that the unemployment rate would have been close to 20% if this data was accurately reported.
A second data point of note is that when those who are marginally attached to the labor force and the total employed part time for economic reasons are considered, the unemployment rate (technically referred to as U-6), was 22.8% in April (see Table A-15 in the report).
I hate to highlight more bad news, as if 14.7% of the labor force being unemployed was not bad enough, but in order to really understand the depth of the economic recession we are in, I think it is important to consider these figures.
Some definitions: Those marginally attached to the labor force include people who are not currently looking for a job but have indicated they would like to work and have looked for a job in the past 12 months. This also includes discouraged workers who have become discouraged about their prospects of finding a job and have dropped out of the labor force. Those employed part time for economic reasons are the workers who would like to work full time but can only find part time work.
In their article, “The Phantom of the Opera: Cultural Amenities, Human Capital, and Regional Economic Growth,” Falck, Fritsch, and Heblich show that the presence of baroque opera houses in Germany helps attract “high-human-capital employees” to these regions. Upon showing this existence of this effect, they extend their analysis to see if these high-human-capital workers will generate knowledge spillovers. They state that: “Answering this question is of practical relevance for local government because in the absence of positive spillovers, it is difficult to justify using taxpayers’ money to subsidize cultural amenities” (Falck, Fritsch, and Heblish, 2011, p. 761). Their finding that cultural amenities do lead to knowledge spillovers and increases in productivity and economic growth is very interesting and important. While I agree with their statement about this being a justification to subsidize the arts, I think their is a nuance here that also need to be mentioned.
Even if there was no knowledge spillovers as they found, there could still be justification for funding of the arts based on the enhancements to the quality of life it brings to the residents of the community. I just feel the need to mention this because I think economics puts too much emphasis on growth in productivity and GDP. It is often argued that if a policy does not increase productivity or GDP growth then it is just not worth pursuing. I understand that these effects are all interrelated in that cultural amenities help attract and retain labor because it enhances quality of life, which could then drive economic growth higher. But, what if the cultural amenities just enhanced the quality of life of those living in the community without boosting economic growth? Could that value not be enough to justify subsidizing the arts? I argue that it could.
Falck, O., Fritsch, M., & Heblich, S. (2011). The phantom of the opera: Cultural amenities, human capital, and regional economic growth. Labour Economics, 18(6): 755-766.
It is that time of year for economic forecasts, so here is my forecast for the San Antonio economy in 2019. An update of the San Antonio economy through October and more detail on the forecast can be found here.
Like the U.S. and Texas economies, the San Antonio economy continues to show healthy growth. Employment through October grew 2.47% compared to October 2017, which is about at the historical average growth rate for the region. This is not bad given the extraordinary length of this expansion. The unemployment rate in San Antonio was at 3.2%, the second-lowest among the major metropolitan economies in the state. However, growth in San Antonio has been pretty strong across all sectors of the economy up until about six months ago when year-over-year employment growth in many sectors started to slow and even turn negative. These trends are shown in the following graph where it is clear that growth in the information, construction and mining, manufacturing, and professional and business services industries has started to decline.
It is also a sign of economic strength that the unemployment rate in San Antonio is so low. There is mounting anecdotal evidence, though, that the labor market is very tight. There are surely people who are still underemployed or who are not counted as unemployed because they have dropped out of the labor force, but I think we are at the point where growth is going to be driven by growth in the labor force and/or increases in productivity. This is going to be a constraint on growth into the near future.
Similar trends are also occurring at the state level, and the leading index for the Texas economy has been trending down since about May. It is too early to tell if this is an indication that the Texas economy is headed for a downward turn, but it bears watching.
On the national front, one of the best predictors of a downturn in the economy is the yield curve. The yield curve is very close to inverting, and in fact, the yield curve based on the difference between the 5-year and 2-year bond rates has already inverted. Once the yield curve inverts, it is a good bet the economy will move into a recession not too long after the inversion. Relatedly, recessions are typically preceded by the Federal Reserve raising interest rates, which they have been doing and are most likely going to continue to be doing. The housing market nationally and in San Antonio has been strong for a number of years now, but it got a bit frothy, again, and while it remains strong in San Antonio, it is starting to soften in other major metropolitan areas in Texas, particularly Dallas, and other parts of the country.
There are also some worrying trends in the global economy as growth has slowed in China and many countries of the European Union. While there are surely many factors playing into this, the trade war is not helping matters.
The current expansion is now the second-longest in our nation’s history. It is not going to go on forever. Sorry, but if we learned anything from the Great Recession, it is that the business cycle is not dead. There is typically a trigger, though, that turns the economy into a recession. As already mentioned, the inverting of the yield curve, raising of interest rates by the Federal Reserve (which, by the way, is the right thing for them to do, in my opinion), the trade war, Brexit, severe downturn in the housing market, and slowing global growth could each be that trigger. There may also be others not mentioned.
The upshot is that I believe we will continue to see the San Antonio economy grow into 2019, but I predict (as do many other economists) that we will move into a recession toward the end of 2019 or in 2020. It may not be as severe as the Great Recession, but I am very concerned about the federal government’s ability to respond to it. This is due to the fact that the Federal Reserve may not have as much room as they need to lower interest rates, which may mean they have to resort to quantitative easing again. But, there could be pressure not to implement such a policy again. A similar issue concerns me with respect to the ability of the federal government to provide any sort of fiscal stimulus given the increasing federal budget deficit due to the recent tax cuts of the Trump Administration. If the deficit is over $1 trillion by the time the recession hits, are the policymakers going to be willing to provide an economic stimulus large enough to pull the economy out of the recession, since it will make the deficit even worse?
In this environment, I think San Antonio will continue to see growth in 2019, but the growth in employment will likely slow to somewhere in the range of 1.75-2.25%. The unemployment rate is also likely to tick up a bit to about 3.5-4.0%.
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).
Mazzucato, M. (2018). The Value of Everything. New York, NY: PublicAffairs.
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:
Organize for action
Select a priority specialization
Set the goal
Measure global market opportunity within the specialization
Factor in market accessibility
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.