THE AGING OF THE BAY AREA, 2000 – 2040
Be Sure to Wear Some Flowers in Your Hair… If You Have Any Left
The most lasting effect of the collapse of the tech bubble in 2001 has been demographic. From 2001 to 2005, approximately 250,000 residents moved out of the six county area defined by the San Francisco MSA and Santa Clara County (i.e. Marin, San Francisco, Alameda, Contra Costa, San Mateo, and Santa Clara Counties).* While natural increase of the population and foreign immigration were able to offset some of this exodus, this wave of out-migration slowed population growth in all the counties in this area to below 1% for several years, and has quashed any hope of a quick recovery to pre-recession employment levels. The good news is that the tide has finally turned. Net migration (foreign plus domestic) is now positive for all counties in this six county region, and is rising for all the counties except Contra Costa.
Figure 11: July to July Percentage Change in Population
Source: CA Dept. of Finance, UCLA Anderson Forecast
Figure 12: Net Migration by County
Source: CA Dept. of Finance, UCLA Anderson Forecast
The 2007 population projections recently released by the
California Dept. of Finance (DOF) temper this optimism somewhat. They predict
that population growth in the larger 11-county Consolidated Metropolitan
Statistical Area, or CMSA, (which includes the San Francisco MSA plus Napa,
Sonoma, Solano, Santa Clara, Santa Cruz and San Benito counties) will average
below 1% from now through 2040. The projected differences between growth in
the Bay Area and the rest of California mean that the 11-county CMSA’s share of
California’s population will decline from 20% in 2006 to 18.3% in 2040.
Within the CMSA, most of the changes in the distribution of the population will
occur in the counties bordering the Bay. The shares of the Bay Area’s
population in Marin, San Francisco, and San Mateo counties are all expected to
decline, while the shares in Santa Clara and Contra Costa county increase and
the balance of the counties essentially hold steady.
Figure 13: Projected Average Annual Population Growth in San
Francisco CMSA
Source: CA Dept. of Finance, UCLA Anderson Forecast
Figure 14: County’s Projected Population Share in San
Francisco CMSA
Source: CA Dept. of Finance, UCLA Anderson Forecast
These next 35 years will present an additional challenge for
the Bay Area because of the age distribution of the local population. The Bay
Area has the highest median ages of any region of California, and the highest
share of residents 65 years and older. The oldest of the baby boom generation
is in their early sixties, and as this largest cohort of the population moves
from working age into retirement, the Bay Area’s population will get increasingly
older relative to the rest of California. To take the most extreme example, by
2040, the DOF’s projections expect that 30% of San Francisco County’s population will be over 65, compared to 19% for the state as a whole. Most of the
difference in age profile comes from the peninsula: the East Bay’s age profile is only slightly older than California as a whole, and these differences stay
essentially constant through 2040.
Figure 15: Projected Age Distribution in Alameda County
Source: CA Dept. of Finance, UCLA Anderson Forecast
Source: CA Dept. of Finance, UCLA Anderson Forecast
Figure 16: Projected Age Distribution in Contra Costa County
Source: CA Dept. of Finance, UCLA Anderson Forecast
Figure 17: Projected Share of Population Over 65
The retirement of the baby boomers will lead to substantial
economic changes. This section of the report will focus on two issues that can
be quantified and studied at the level of the local economy. First, we will
explore the effects that the coming changes in the ratio between working and
retired residents could have on economic growth in the Bay Area. Second, we
look at how the spending habits of the 65 and over age group compare with the
population as a whole, and speculate on what effects that may have on the
composition of the Bay Area economy over the next 35 years.
More Retirees = Slower Job Growth
The aging of the Bay Area holds a potential double whammy
for the economy. A higher share of residents over 65 means labor force
participation will most likely fall in the coming years. Coupled to the projected
slowdown in population growth, this means that growth in the local labor force
may slow dramatically in the next 35 years. Since in the long run local
employment can grow no faster than the local labor force grows, this
combination of factors could lead to a long-term slowdown of the Bay Area
economy. Like many things in economics, this story is grossly oversimplified,
yet retains a central kernel of truth. To get a better sense of the subtleties
involved, we’ll proceed in several steps.
First, to establish a baseline, we’ll examine what would
happen to overall growth of the labor force if there’s no change in retirement
behavior. Specifically, let’s assume that labor force participation rates by
age group stay the same as they are today, so that any changes in overall labor
force participation are solely driven by the changing age distribution of the
population.
Figure 18: Average Estimated CA Labor Force Participation
Rates by Age Group, 2000-2006
Source: CA EDD, BLS, UCLA Anderson Forecast
Figure 19: Projected Overall Labor Force Participation
Rates, Assuming Constant Labor Force Participation Rates by Age Group
Source: CA Dept. of Finance, CA EDD, BLS, UCLA Anderson Forecast
Figure 20: Projected Average Annual Labor Force Growth by
Decade, Assuming Constant Labor Force Participation Rates by Age Group
Source: CA Dept. of Finance, CA EDD, BLS, UCLA Anderson Forecast
This simple assumption yields some stark conclusions. Given
the projected changes in local age distributions, overall labor force
participation rates are projected to fall throughout the six county area,
though still remaining higher than the California average. However, in San Francisco and San Mateo, the share of older residents is so high that these
assumptions actually predict a contracting labor force. With the exception of Contra Costa County, the rest of the six county area’s projected labor force growth lags the California average.
There are a number of reasons to question this assumption.
Better health care, less retirement savings, the uncertainty around Social
Security, etc. all suggest that the baby boomers will retire later than
previous generations, implying that labor force participation among older
residents will probably rise over the next 35 years. Our next experiment is to
look at whether this increase in the number of older workers will be enough to
offset the slower labor force growth projected from the shifting age
distribution. We have taken a decidedly “back of the envelope” approach to keep
things simple: rather than allowing participation rates to increases steadily,
we instead chose to apply higher average rates over the entire projected
period.
Figure 21: Labor Force Participation Rate by Age Group, Base
vs. Hypothetical
Source: UCLA Anderson Forecast
Figure 22: Projected Average Annual Labor Force Growth by
Decade, Assuming Hypothetical Higher Labor Force Participation Rates by Age
Group
Source: CA Dept. of Finance, CA EDD, BLS, UCLA Anderson Forecast
We’ve omitted the growth from 2000 to 2010 in this
alternative scenario since the baseline numbers are based on most of this
period. Through 2020, the increased labor force participation of the older
workers does indeed raise local labor force growth, thanks mostly to that fact that
55-64 year olds are now working as much as 45-54 year olds. The Bay Area
counties benefit disproportionately from this hypothetical increase precisely
because they have a bigger share in this age group. But even the ludicrously
high labor force participation rates we’ve examined here don’t help much past
2020: by that point, the boomers are mostly past 75, and we still see the same
slowdown as the baseline scenario.
Thus, boomers delaying retirement is of limited help in
bridging the gap. There are two other potential ways to offset this
demographic drag on labor force growth. If the projected growth in Bay Area
labor supply falls short of future labor demand at the prevailing wage, wages
will obviously rise. Not only will this act to further increase labor force
participation across all age groups, but it will also induce migration – both
foreign and domestic. While in-migration represents the most likely mechanism
for offsetting the demographic drag on labor supply growth, there are several
factors that potentially limit the inflow of new workers.
The DOF’s population projections have already built in the
assumption that foreign migration will continue at roughly the same levels we
see today. Thus, if foreign immigration is to mitigate the slowdown in labor
force growth we’ve projected, it would have to significantly exceed the levels
we’ve seen recently. Consider how contentious the issues of immigration are
today. Is there currently a shortage of high skilled workers that needs to be
filled by foreigners with H1-B visas, or is this simply a source of cheaper
labor? Are low skilled immigrants a net positive for the economy? Is
outsourcing a win-win reorganization of inputs to minimize costs, or a
wholesale betrayal of the American worker? Now consider how much more heated
this debate will become as these demographic shifts slow growth of the native
born workforce. While the incentives for foreigners to immigrate to the Bay
Area will be bigger than ever before, today’s experience suggests that we
should not look for substantial increases in the inflow of foreign workers to
fill the gap.
For domestic migrants, the Bay Area’s obvious attractions
are offset by one of the highest costs of living in the country. Ironically,
the very counties where the slowdown in labor supply growth will be most severe
(San Francisco and San Mateo) are also the most expensive counties. Like so
many places in California, this lack of affordability in areas of high
employment suggests the acceleration of two trends we’re already seeing: the
commutes of tomorrow will make today’s look breezy, and, as a result, this will
eventually cause some redistribution of economic activity to the lower cost
areas where people live.
Changes in Spending Patterns
It probably comes as no surprise that spending habits of
older Americans are somewhat different than the national average. As a larger
share of the population moves into these older age groups, we should expect to
see buying patterns of the population as a whole change. The BLS’ Consumer
Expenditure Survey offers some insight into what we might expect, assuming that
the 65-year olds in 2040 have the same consumption habits as 65-year olds
today. The data is primarily available for Census Regions, which lumps the Bay
Area in with most of the western U.S. However, the limited data that is
available for the San Francisco MSA suggests that aside from spending a higher
share on Shelter and lower share on Transportation, the expenditure shares of
Bay Area residents aren’t that different from the rest of the West.
The most obvious feature of the data is that both the
average annual income and expenditures of residents of the West region decrease
as they get older: the average 75 year old spends almost $20,000 a year less
than the average for all consumers. Moreover, they spend their money
differently. Most of the differences in expenditure share aren’t surprising.
Older consumers spend a significantly higher share of their income on health
care, and spend less on cars and transportation. They spend more on food at
home than they spend on meals out. They spend less on clothes and
entertainment, and more on books (in the Other category).
Figure 23: Average Annual Expenditures in West Region
Figure 24: Share of Total Expenditures in West Region by Age
of Consumer Unit
Source: BLS, UCLA Anderson Forecast
Figure 25: Change in Share of MSA Population 65+ versus
Change in Share of MSA Employment in Education and Health Care
Source: US Census, BLS, UCLA Anderson Forecast
While there’s some room to argue that the retirees of the
future may very well be playing Playstation 10 at the retirement home, most of
these changes in expenditure patterns are likely to persist over the next 35
years. These demographics-driven shifts in the overall patterns of local
consumption have significant implications for the local economy. Looking
across all of the major MSAs in the country, we see that the higher the growth
in the share of residents over 65 from 1996 to 2006, the larger the increase in
the share of local employment in the Education and Health Care super-sector –
which is hardly a surprise given the expenditure data. The Bay Area already has an above average
concentration of health care related employment, and this data argues that this
concentration will surely rise over the foreseeable future.
While the shift towards more health care services will be
the biggest demographics-driven shift in the composition of the economy, the
expenditure data suggests that we should see other shifts as well. Clothes
stores, car dealerships, restaurants, and entertainment venues may all see
local demand for their services drop as a larger share of the population spends
a smaller share of their smaller incomes on these services.
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