APDEM804 ePortfolio

The 2020 forecast for Los Angeles County showed that the United States’ most populous county was undergoing significant growth, but was also aging substantially (El Nasser, 2017, para. 3). From a hiring perspective, business planning would likely need to consider a more mature labor force that would likely be less interested in entry-level roles. From a demand perspective, a large rise in mean household income was projected, signaling a rise in consumption for progressive commodities such as recreation and transportation. However, an increasingly senior population would be less socially and economically active, with a more significant home orientation, indicating that at-home recreation would be the specific sector most buoyed by demographic trends. Examples of at-home recreation business opportunities include pool maintenance, entertainment systems, and perhaps pet care; furthermore, in non-recreation sectors, a more senior population tends to demand more healthcare services.

Population changes by age group, from 2010 to 2020

The only age groups projected to decrease between 2010 and 2020 were ages 15 to 24, 35 to 44, and 45 to 54. This illustrates an aging population with lowering fertility, where teenagers came of age (and young professionals move into the county), thereby causing a jump in the 25 to 34 year old age group while the 35 to 44 and 45 to 54 year old age groups both dip. However, as middle-aged residents grew older, the 55 to 64 year old age group rose sharply, as did the 65+ year old age group.

The primary business insight for an aging population structure was that there would be decreases in certain types of demand (alcohol, tobacco, and fashion related consumption) and increases in other types of demand (medical and utilities related consumption). Los Angeles County is famous for its urban sprawl, so a greater home orientation may have a particularly notable impact as the population commutes less and consumption becomes more local or delivery-based. Roughly 75% of L.A. city is zoned for single-family homes, explained Skelton (2020, para. 13), conveying the quantifiable spread-outedness of Los Angeles County. Especially with shifting behaviors as a result of the coronavirus pandemic, businesses focusing on healthcare and at-home recreation and which also go directly to the consumer’s home may have the sharpest competitive advantages.

Labor force changes by age group, from 2010 to 2020

As the population aged going into 2020, there was stagnation (3% increase) in the number of 20 to 24 years olds in the labor force, but notable increases were observed for 25 to 54 year olds (12%), 55 to 64 year olds (13%), and 65+ year olds (23%). This suggested a more skilled, experienced, and perhaps selective labor force, which would make it increasingly challenging to staff entry-level positions. This suggests that businesses relying on large numbers of entry-level employees, contractors, or gig workers such as Uber, Lyft, and Amazon may face issues with hiring or recruiting.

The growing number of 65+ year olds in the labor force (the sharpest increase of all age groups) may not have necessarily been highly skilled workers at the peaks of their careers, or may be very poor and forced to work just to survive (including exiting out of retirement) (Yee, 2022, para. 5). Too poor to retire and too young to die, read one particular grim headline from the LA Times (Glionna, 2016). Such seniors may pick up some of the entry-level jobs that would previously have gone to 15 to 24 year olds. Especially for physically demanding entry-level roles, though — for example, at a Starbucks location, or at a grocery store — an older employee may make firmer demands than a younger employee on safety regulations and labor rights. However, relatively sedentary businesses with many entry-level positions such as call centers may find an abundant pool of potential hires, and may even benefit from a wiser workforce with more life experience. From a policy perspective, upskilling these employees with certifications would create opportunities for businesses and employees alike.

It is worth noting that the growing number of older employees (55 to 64, and 65+ years old) may also have surged in highly skilled positions as people perhaps chose to extend already successful careers. There may also have been a growth in demand for experienced, well-connected professionals due to the explosion of the digital media industry,

Much of the [job] growth [expected through 2021] is being fueled by streaming companies like Amazon and Netflix, which have large and expanding operations in Los Angeles County, Rico said. Netflix, for instance, expanded its Hollywood presence with a new office building lease last year. Apple Inc. is also diving into streaming services and opened a film studio in Culver City in January. … With thousands of internet stars, all with their own brands, there’s a higher demand for managers, agents and publicists who work locally. (Reyes-Velarde, 2018, para. 7-8)

However, an increasingly crowded field of highly-qualified, older candidates would potentially cause salaries for more senior and executive roles to stagnate, even while mean household income rose overall and new jobs were created. If that were the case, it would worsen the already weakening consumption patterns of an increasingly older population. In addition, executive roles may be more remote or hybrid oriented (as opposed to purely office-based), which would add even more downward pressure on consumption in addition to an even stronger home orientation among seniors. For this reason, businesses that would seem to thrive with an aging workforce — e.g. casual work fashion, or office-oriented status symbols such as ties, handbags, and briefcases — may instead face a worsening outlook. Policy considerations would potentially focus on facilitating the transition to retirement.

Household changes by age of householder, from 2010 to 2020

Trends conveyed by overall population totals became even more striking when looking at households by the age of the householder. In these projections, there were massive drops in numbers of householders among all age groups under 55 years old. Even though 25 to 34 year olds grew in overall population, the number of households in this age group plummeted, indicating a strong tendency to cohabitate. From a business perspective, there were some obvious takeaways, such as younger age groups having lower demand for furniture (especially family-oriented furniture like large dining tables) as well as lower demand for utilities and appliances (as people living together will not need to independently heat and cool shared areas, and can share major appliances such as ovens). These same business concerns would perhaps be exacerbated by the overall lower fertility rate, as fewer people would be cooking big dinners at home.

There are two very speculative and possibly conflicting possibilities to consider for 25 to 44 year olds. One is that the coronavirus pandemic perhaps would cause people to stock up on more appliances, or perhaps bigger appliances, with more people eating at home. On the other hand, greater cohabitation may ultimately force younger adults to spend more time outside when gathering with friends, finding it easier to enjoy a glass of wine at a wine bar than inviting guests over to increasingly crowded households.

An increase in older age groups being heads of household, despite having a greater home orientation, would not necessarily compensate for the lower demand for furniture and appliances among younger age groups, as older adults would likely already have purchased many of their larger and more expensive home goods earlier in life.

From a business perspective, the household data reinforced the previous takeaway that businesses catering towards a more sedentary, older population would likely have greater durability going into 2020 and beyond. The only additional insight offered by the households data was that with more seniors being heads of household, demand for utilities would likely grow disproportionately. Also, solar panels, home batteries, and other 21st century infrastructure upgrades would perhaps be key areas of growth because these represent growing industries with many first-time buyers. While almost every householder already has a stove, few have battery systems to power their house.

Changes in mean household income, from 2010 to 2020

Growth in mean household income may have added some buoyancy for consumer demand. However, the drastically shifting age structures for overall population, labor force participation, and householder status meant that this shift was not necessarily equally distributed. Focusing on luxury goods and services that are appealing to older adults may be a successful business strategy, capitalizing on a silver rush of more affluent seniors (Atwal, 2021, para. 6). Especially in Los Angeles County, demand for plastic surgery and skin care may rise, in particular.

However, even youth-obsessed brands may find opportunities by recruiting older brand ambassadors, such as Helen Mirren’s relationship with L’Oréal (Atwal, 2021, Conclusion). In addition, gift-oriented items may be favored by seniors seeking to treat children or grandchildren, as well as one another. According to Socio-emotional Selectivity Theory (SST), as soon as older adults perceive that the time left is limited, explained Kazeminia (2017, Abstract), their high-end purchasing may shift the locus of luxury from symbolic and functional aspects to a more experiential and emotional aspect that supports drawing meaning from life. Importantly, the high diversity of climates and cultures in Los Angeles County means that there is a particularly robust range of opportunities for brands seeking to offer experiential luxury.

Summary

Looking at the changes from 2010 to 2020, and anticipating what lies ahead for the future, investment opportunities seem to orbit around people 35 years old and above, with a dip for the 45 to 54 year old age group. On the other hand, the greatest investment risk seemed to focus around younger age groups, which were dropping in population size and cohabiting in increasingly crowded households, exposing progressive commodities targeting these age groups (tobacco, alcohol, nightlife, etc) to potentially soft demand.

With an increasingly older population and a growing mean household income, businesses that focus at-home recreation and experiences will have greater access to a more sedentary consumer segment. Brands perceived as luxury may be able to cultivate demand if they focus on providing unique, memorable experiences that enrich their customers’ sense of living their life to the fullest. On the service side, at-home chefs who communicate personally with their clients may find more growth than conventional culinary experiences. On the consumer goods side, advertising that includes senior models and goods that are available for subscription delivery may be able to present themselves as part of a lifestyle that is interesting for seniors. Especially due to open cannabis policies in Los Angeles County, a range of cannabis products may intersect the axes of both luxury- and wellness-related consumption. In addition, home upgrades such as solar panels and battery systems may generate growing interest and rising business opportunities.

References

Atwal, Glyn. (2021, July 21). Luxury Brands Should Not Forget The ‘Silver Yuan’. Jing Daily. Retrieved from https://jingdaily.com/luxury-brands-silver-yuan-china-seniors/

El Nasser, H. (2021, October 24). More than half of U.S. population in 4.6 percent of counties. United States Census Bureau. Retrieved from https://www.census.gov/library/stories/2017/10/big- and-small-counties.html

Glionna, J. (2016, January 29). Too poor to retire and too young to die. Los Angeles Times. Retrieved from https://graphics.latimes.com/retirement-nomads/

Kazeminia, A., Bäckstrom, L., Pitt, L. (2017). Enjoy now or Later: An Explanation of Elderly Recipients’ Preferences Regarding Luxury Gifts. In: Campbell, C.L. (eds) The Customer is NOT Always Right? Marketing Orientations in a Dynamic Business World. Developments in Marketing Science: Proceedings of the Academy of Marketing Science. Springer, Cham. https://doi.org/10.1007/978-3-319-50008-9_115

Reyes-Velarde, A. (2018, February 9). Digital media is driving job growth in L.A region, report finds. Los Angeles Times. Retrieved from https://www.latimes.com/business/la-fi- digital-media-growth-20180209-story.html

Skelton, G. (2020, February 3). Column: Suburban sprawl wins again in the battle against California’s housing crisis. Los Angeles Times. Retrieved from https://www.latimes.com/ california/story/2020-02-03/skelton-sb50-housing-california-legislation-fails-los-angeles-county

United States Census Bureau. (n.d.) Decennial Census of 2000, Table PCT035. [Data file]. Retrieved from https://data.census.gov/cedsci/table?q=labor%20force%20by%20age &g=0500000US06037&tid=DECENNIALSF32000.PCT035

United States Census Bureau. (n.d.) Decennial Census of 2000, Table P012. [Data file]. Retrieved from https://data.census.gov

United States Census Bureau. (n.d.) Decennial Census of 2010, Table P12. [Data file]. Retrieved from https://data.census.gov

United States Census Bureau. (n.d.) American Community Survey of 2010, Table B23001. [Data file]. Retrieved from https://data.census.gov/cedsci/table?q=labor%20force%20by%20 age&g=0500000US06037&y=2010&tid=ACSDT1Y2010.B23001

Yee, A. (2022, July 22). Inflation is driving older Americans back to work. Los Angeles Times. Retrieved from https://www.latimes.com/business/story/2022-07-22/inflation- drives-older-americans-back-to-work

Appendix 1: Challenges with projections for Los Angeles County

As of 2017, more than half of the United States population was in less than 5% of counties (El Nasser, 2017, para. 3). More than half of all residents live in just 143 big counties (in terms of the number of residents), stated El Nasser. That means less than half of the population is spread out across the remaining 2,999 small counties. Of the most populated counties, Los Angeles County had the largest population of all: at over 10,000,000 residents, it had double the population of second-place runner-up Cook County, Illinois. From a business perspective, overall conclusions for such a large population would be difficult to act upon without further analysis as some population groups or areas could in fact defy the County-wide trend.

Another major caveat when conducting projections about Los Angeles County was that geographically, there were several distinct climates. In the county’s southwestern corner, the business considerations for the lush Mediterranean coastline (part of the Los Angeles Basin) would be different than for the harsh Mojave Desert of its northeastern corner. A business idea which could thrive in one of Los Angeles County’s moderate climates would perhaps not even be practical (or safe) in one of its hotter climates, or at least would potentially have drastically different resource demands.
To illustrate the previous point, rust and pest mitigation could be a serious concern in the damp, salty air of Santa Monica, while indoor humidifiers and patio misters could be necessary in Palmdale, which is two mountain ranges away. Clearly, a County-level projection model could be a guiding North Star for macro-level business planning trends, but ultimately a deep knowledge of ground-level variation would be needed to actually implement any business decisions.

Appendix 2: Advantages with projections for Los Angeles County

On the other hand, Los Angeles County’s large population and diverse geographic area did lend itself well to projection models in one key way: while smaller, more homogenous counties with several thousands (or millions) of residents may have significant shifts in population size due to one-time events (e.g. development of a new parcel of land), the sheer scale of Los Angeles County meant that such events were unlikely to cause integer-level percentage changes that threw off the project model on their own.

In other words, a projection model’s agnosticism to these types of events — especially with the minimal inputs used in the cohort change ratio (CCR) method — was perfect for Los Angeles County, where its scale and variation would possibly blur out the impact of singular and/or local events on the overall population. Similarly, the range of city governments in Los Angeles County may have had a similar blurring effect even for the impacts of County-wide policies.

Appendix 3: Child to Adult Ratio (CAR)

Since there were ten years (k = 10) between 2010 (t = 2010) and 2020 (t + k = 2020), the only requirements for the cohort change ratio (CCR) method were population counts (according to matching age groups) from 2000 (t - k = 2000). One of the main advantages of a cohort change ratio was that fewer inputs of historical data were required as opposed to other methods, which would require data on births, deaths, inmigration, and outmigration.

However, a CCR could not be calculated for age groups under k (10) years old. For these younger age groups — in this case, ages under 5, and from 5 to 9 — child to adult ratios (CARs) were used instead. In the case of this report: for children under five years old, the CAR’s denominator was the total number of adults aged 20 to 34; and for children aged five to nine years old, the CAR’s denominator was the total number of adults aged 25 to 39. (Other reports may use wider definitions for the age ranges of childbearing adults.).