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Guy
Sacramento (DRU) projections for the Bay Area are still much too high
The Department of Finance Demographic Research Unit (DRU) recently revised its California population projections. Now, the DRU projects that California's population will remain flat till 2060. However, when you focus on the Bay Area (9 counties), the DRU projections are still too high.
From 2020 to 2022, DRU developed early estimates of populations using the 2019 population figure and adding early estimates for births, deaths, and migrants. I included those in history (2000 - 2022).
During the data history (2000 - 2022), shown in the above left-hand graph, we observe that California, excluding the Bay Area (California - Other), grew much faster than the Bay Area. But, during the forecast period ( 2022 - 2060, right-hand graph), DRU has the Bay Area growing quite rapidly while other California regions' populations are contracting by 2060.
The Bay Area is a bit older than other California regions. Even before COVID and Work From Home (WFH), its migration rate had slowed down. And, with WFH, the Bay Area's migration rate turned more negative than for the other regions that were less affected by WFH (you can see that on the left-hand graph).
It makes no sense that the Bay Area would grow so much faster than other California regions as it grew much slower during the data history (2000 - 2022). AI is not going to change that. Just as Socia Media, Cloud Computing, Machine Learning, the Metaverse, and Blockchain have not left a footprint in the history of the data (2000 - 2022).
So, why is the DRU's Bay Area forecast off?
The reason is the same as for other DRU forecasts I have analyzed so far. Their migration assumptions are much too high. I'll review this situation shortly.
On a positive note, the DRU always generates reasonable natural growth rates as shown below.
Natural growth rate is calculated as:
(# births - # deaths)/population within a year.
As mentioned, the DRU's natural growth rate projections are very realistic. They show a rapid downward trend. This is a common pattern for the entire developed World. It reflects aging demographics with low fertility rates. Notice that by 2030, fairly early in the forecast 7 out of the 9 counties already have a negative natural growth rate. Much before 2040, all counties experience a negative natural growth rate.
Migration assumptions are a chronic issue with many DRU projections
You can readily see that on the graph below. Contrast the history of the data (2009 - 2022) with the projections (2023 - 2060). Even before COVID & WFH, the counties experienced a rapid downward trend in migration rates. During early COVID & WFH, all migration rates took a deep dive into record negative territory. In 2022, migration rates were still markedly negative. However, during the projections, DRU forecasts that all migration rates would rebound as quickly as they dropped and reach a very high and sustained level through the end of the forecast period (2060).
If we look at the median (50th percentile), you can see that the medians during the projections are way higher. That is where DRU's projections for the Bay Area went off the road.
The one exception to this overestimating migration rate was San Francisco where the median migration rate during the projection is in line with the history of the data. Notice that if I had focused on the average instead of the median, San Francisco's average is way lower at 0.2%.
Building an adjusted Bay Area population forecast
I did this in a very simple way.
- I used the DRU natural growth rates (as mentioned they were very reasonable).
- I used the DRU migration rates only up to 2026. And, from 2027 to 2060 I used the median migration rates during history. But, I used a floor of 0%. So, I would not project negative migration rates from 2027 to 2060, which I viewed as too punitive. And, I did this for 8 of the 9 counties as I viewed the San Francisco migration rates to be reasonable; so, I kept them unchanged.
By doing so, I got very different results.
My adjusted forecast (Bay Area2) is respectful of the historical demographic trends where the Bay Area's population growth is expected to be much lower than for the other California regions. The DRU projections do not respect such demographic trends, as they expect the Bay Area to grow a lot faster than the other regions. That is most unlikely. As stated, all the hype around AI will most probably not change that.
The tables below disclose the huge difference between the DRU forecast and the adjusted forecast. The highlighted Bay Area forecast is the only one I changed. While DRU expects the Bay Area population would grow by 10.8% by 2060, I expect instead that it would contract by - 4.2%. This has a profound impact on the overall California forecast. DRU projects California's population to increase by 1.2%. Meanwhile, I anticipate it will contract by - 1.7%. The difference between the two forecasts is 1.1 million for the whole State and the Bay Area. At the Bay Area level, this is a gigantic difference.
The graphs below visualize the above data. They illustrate what a drastic difference using more reasonable migration assumptions makes for the Bay Area and the impact it has on the overall California forecast.
The above right-hand graph shows that after using reasonable migration assumptions for the Bay Area, the whole State's population is explicitly expected to contract by 2060 instead of remaining stable.
The tables below disclose the huge differences between the DRU forecast and the adjusted forecast at the county level.
Notice the very large contraction in population for Marin, Napa, San Mateo, and Sonoma ranging from - 13% to - 25%. How can one explain that? Very easily...
Just revisit the natural growth rates for these four counties. You can see on the graph below that 3 out of the 4 counties already experienced negative natural growth rates very early into the forecast. And, the fourth county, San Mateo, experienced a negative growth rate just a few years later still during the 2020s. Also, these negative rates reach record low levels often in the -0.6% range, even -0.8% range (for Marin & Sonoma). Such negative rates result in material population contractions by 2060 when factoring that none of those counties had compensating positive median migration rates during history that I used to build my adjusted forecast (I used a floor of 0% to not use negative migration rates over a long period).
