CSG: Technology and Demographics: A Follow-Up to the MAGNY Demographics Meeting
By CSG Managing Partner, George Friedlander
On Friday, January 11, the Municipal Analysts Group of NY held a very impressive luncheon talking about demographic shifts and implications for state and local governments. The session was in two parts: First, Dr. Olu Sonola, Group Credit Officer for U.S. Public Finance and Global Infrastructure for Fitch Ratings, discussed recent U.S. aging patterns and their long-term economic and credit implications, particularly for state governments. Also on the panel was Timothy Little, Associate Director in the U.S. States Team at S&P Global Ratings, who discussed the use of demographics in the rating process and the rating implications of recent and projected U.S. demographic and population trends. Then, Richard Prisinzano, Senior Economist and Tax Division Head with the Penn-Wharton Budget Model, discussed his view that high tax rates on millionaires have not led to significant interstate migration by high-income individuals, and Nicole Kaeding, Director of Federal Projects at the Tax Foundation, presented a contrasting viewpoint, discussing the impact of high tax rates on corporate location decisions and interstate migration by residents in locations with high tax brackets.
The Panel’s description is up at the MAGNY site here.
The event highlighted a lot of what we at CSG have been reporting and we continue our discussion of some of the demographic patterns that will link up with technological change, in ways that ultimately affect credit strength, mostly (but not exclusively) at the local level. We will cite four patterns at this point, with many more to come:
A continued move toward urban/suburban centers—the world isn’t so flat;
Economic and demographic advantages of tech-oriented cities—Brookings’ smart industry cities;
Continued extension of post-retirement life expectancies; and,
Ultimately, changes related to automated transportation.
And, we note two demographic patterns that aren’t so tech-oriented, but are crucial: 1) the recent continuation of news on declining fertility rates, and related implications of immigration; and 2) climate change-related patterns and uncertainties for demographics.
Final note, for now: The following is by no means intended to be comprehensive. We are merely suggesting that the factors affecting demographics are changing rapidly, and technology, climate change and politics are all playing a key role in these changes. Credit implications: It seems clear that pressures on rural credits will continue, including especially healthcare and weaker local tax-supported debt. Pressures are likely to be particularly significant in rural areas that overlap with weather-related implications of climate change.
I. A move away from rural growth continues
According to a report from Pew Research from May 2018, growth in suburban population continues to lead, while rural growth to lag behind, with urban in the middle.
As the tables indicate, population growth is largely concentrated in urban/suburban complexes—SMSA’s—while rural growth lags far behind. This includes population aging over 65, which we will discuss additionally below.
II. The world isn’t flat—tech cities continue to lead in economic and population growth
In his book from 2005, “The World Is Flat: A Brief History of the Twenty-first Century” Thomas Friedman suggested that technology was going to flatten out population distributions due to factors such as telecommuting. In his subsequent book, from 2016, entitled “Thank you for Being Late: an Optimist's Guide to Thriving in the Age of Accelerations,” Friedman basically said “never mind,” and the evidence for the latter is strong.
As noted in a report by Citilab, “High-tech talent is a key driver of the wealth and competitiveness of cities. But it’s highly concentrated in places across the United States and the world, following a winner-take-all pattern and reinforcing the geographic inequality that underpins our broader economic and political divides.” From the vantage point of mid-2017, the top 5 cities for tech growth were San Jose, San Francisco, Washington DC, Boston/Cambridge, and Raleigh/Durham/Chapel Hill. Some key patterns show up in all discussion we have seen on concentrated tech growth:
Tech-oriented individuals want to be with other tech-oriented individuals;
The big 10 technology companies are major drivers of growth (see: Amazon in Long Island City); and,
Having high-level tech-oriented educational facilities is a major plus (see: Boston) As noted from Citilab, “ the ranking skews to knowledge hubs and college towns and away from larger, more socio-economically diverse places.” That said, the location of Cornell Tech on Roosevelt Island in NYC may have been a major net positive for the city—See the Amazon location.
In a series of articles in 2016 on “Advances Industry Cities,” Brookings noted some similar patterns. (America’s advanced industries: New trends.” Mark Muro, Siddharth Kulkarni, and David M. Hart August 4, 2016).
Credit implications: Over time we expect more pressures on local governments from a variety of sources, including among other factors, pensions, changing labor conditions related to technological change and weather-related issues (in some cases). These effects will be far from uniform, however, with clear “winners and losers.” A key component of the winner/loser pattern, in our view, is likely to be continued clustering of economic activity into SMSA’s with strong connections to technology-supported economic growth.
III. A Continuation in lengthening of post-retirement life expectancies
As was discussed very briefly at MAGNY, adult life expectancies have not been growing much—but the data is tricky. Pre-65 deaths have increased as a result of factors such as opioid dependency. And, census data shows post-65 life expectancies growing fairly modestly. However, we believe that the outlook for post-65 life expectancies is like to take off in ways that are not yet in the data.
The reasons: 1) dramatic improvement in the treatment of illnesses that hit the elderly particularly hard, and, 2) better control of the aging process.
In the former case, according to an article by VeryWell Health, the top 10 causes of death in the elderly are heart disease, cancer, Chronic Obstructive Pulmonary Disease (COPD), Cerebrovascular Disease (Stroke), Alzheimers, Diabetes, Pneumonia and Influenza, Accidents, Nephritis and Septicemia. It seems highly likely that many of these factors will be better controlled by advancing medical technology—cancer from better diagnosis, revolutionary advances in treatments that are still in the early stages, and far less smoking. According to a study by the American Cancer Society, deaths from cancer have dropped steadily for 25 straight years. The study shows the nationwide death rate from cancer fell 27% between 1991 and 2016—and the most important advances in diagnosis and treatment are happening after that time period. Diabetes seems likely to also be more effectively treated in the near future, from wearable monitors and dispensers of medication. Other conditions on that top 10 list also seem likely to come under control from technological advances that are not yet included in census or actuarial data—Alzheimers, for example.
With respect to mechanisms of aging Peter Diamandis of Singularity Hub/Singularity University came out with a note on Sunday, January 12, which observed that “Now, exponential technologies like artificial intelligence, 3D printing and sensors, as well as tremendous advancements in genomics, stem cell research, chemistry and many other fields, are beginning to tackle the fundamental issues of why we age.” We expect these technologies will lead to substantial expansions of post-65 life expectancies.
The implications of demographic changes related to longer post-65 life expectancies are pretty clear, in our view: a higher proportion of retired individuals to work-age population, more pressure on pensions, and other related factors. This patterns will not happen overnight but are worth following in terms of the impact on demographic trends and credits.
Credit implications: The implications of demographic changes related to longer post-65 life expectancies are pretty clear, in our view: a higher proportion of retired individuals to work-age population, more pressure on pensions, and other related factors. These patterns will not happen overnight but are worth following in terms of the impact on demographic trends and credits. In the meantime, significantly longer post-retirement age life expectancies will increase governmental costs for caring for the elderly, while also providing additional jobs in this sector.
IV. Declining fertility rates
In a new report last week from the Centers for Disease Control and Prevention, it was made clear that U.S. fertility rates are now well below the break-even level that, ex-immigration, would keep US population levels steady.
According to the report, “The 2017 TFR for the United States of 1,765.5 was 16% below what is considered the level for a population to replace itself (2,100.0). For overall population, only two states, South Dakota and Utah, had TFRs above replacement level. Among non-Hispanic white women, no states had a TFR above the replacement level (Utah was 2,099.5); among non-Hispanic black women, 12 states had TFRs above replacement; and among Hispanic women, 29 states had TFRs above 2,100.0. Although nearly all states lack a TFR that indicates their total population will increase due to births, these results demonstrate that there is variation in fertility patterns within states among groups according to race and Hispanic origin.”
This study shows the importance of continued reliance on immigration, particularly when considered in conjunction with the extension of post-retirement life expectancies discussed above.
Credit implications: As was discussed in some detail at the MAGNY meeting, state and local governments will come under continued pressure as the ratio of working-age individuals to retirees continues to decline. This is a very long-term trend, but one with likely considerable implications. On the other hand, a reduction in working age individuals is likely to offset some of the potential pressures on jobs related to technological change.
V. Two other factors for future discussion
We intend to return to two other major factors that are, in our view, going to affect demographic patterns. The first is climate change, which will, we expect lead to significant changes in where people live and economies flourish, on a state and local basis.
The second is impending changes in the role and functioning of automotive transportation, including:
A transition to electric automated vehicles (EAVs);
More use of shared and leased vehicles that reduce the needed number of vehicles and vehicle manufacturing; and,
Less use of carbon-based fuels.
These transitions will not happen overnight, of course, but we suspect that the recent bad news on climate change will, over time, lead to policy disruptions that create policy incentives for acceleration of the move toward EAVs. Demographically, of course, climate change, pressure on fossil fuel use and possible reduction in new auto manufacturing count will all affect regions, states and cities. More about this in the future.
We believe that the demographic changes we discuss are a) going to happen, and b) going to affect federal, state, and local governmental policies, and, c) going to affect credit strength and weakness of various state and local governments. We will be back with further discussion of these factors.