San Francisco Bay Area Real Estate Markets Since 1990

The early 1990's recession, the dot-com boom, the subprime bubble and crash, market recovery and high-tech boom, and the pandemic.

From 1990 — following the late 1980's stock market peak, the S&L/junk bond crisis, and the 1989 earthquake — through the recession to the mid-1990s, Bay Area real estate markets generally remained weak, with prices typically declining 5% to 11% within the period. In the middle of the decade, markets began to recover, with home prices subsequently accelerating rapidly during the dot-com boom.

Once the dot-com boom got going, San Francisco and Santa Clara Counties, the centers of the phenomenon, saw the highest appreciation rates. Adjacent counties saw lower, though still substantial increases, with rates in the next circle of counties stepping down further. The Bay Area generally saw appreciation percentages peak dramatically in the year 2000, the height of the dot-com bubble. National home-price appreciation during this period was considerably lower than in the Bay Area.

When dotcom hysteria collapsed and the Nasdaq crashed, only the inner Bay Area Counties — SF and Santa Clara, and those adjacent to them — saw significant (though relatively short-lived) median price declines, while outer counties were generally unaffected. According to the Case-Shiller Home Price Index for the multi-county San Francisco Metro Area, the dot-com collapse affected high-price home markets the most, low-priced homes not at all, and the mid-price segment somewhere in between. More affluent homeowners — also tending to be concentrated in inner Bay Area Counties — were most affected. This is a relatively consistent trend historically: Higher-price home markets are much more sensitive to negative changes or simply uncertainty in financial markets.

The subprime bubble and crash was an anomalous situation caused by predatory lending practices, the abandonment of underwriting standards, dishonest financial engineering on Wall Street, and irrational exuberance in financial markets. This led millions of borrowers to take on purchase and refinance loans unaffordable from the moment deceptive "teaser rates" expired. (We believe giving vast numbers of loans to unqualified borrowers, then using these junk loans to create the "A" rated securities which almost caused a worldwide depression to be anomalous. Perhaps we're being naive.) When the music stopped, a crash in financial markets and a flood of foreclosure and short sales created a fast, deep spiral of home-price declines.

The crisis resulted in large numbers of homes being sold for well below fair market value, which distorts the meaningfulness of median sales price changes during this period. Enormous median price declines occurred, sometimes exceeding 45% (see following charts). "Distressed" homes sold at unnaturally depressed prices, as these transactions often entailed desperate sellers; more hassle, time, uncertainty, and risk for buyers; and the homes were often in significantly poorer condition than the norm.

Part of the definition of "fair market value" is that the seller is not in a situation of being forced to sell quickly. Sellers of foreclosures and short sales — whether homeowners or banks — were usually in urgent distress: This undermined fair market value and provided excellent deals for buyers and hedge funds.

Less expensive, less affluent, less financially sophisticated markets were hammered worst by predatory lending and subprime loans, seeing the largest bubbles and crashes. The most expensive/affluent markets saw much smaller bubbles, and smaller, but still significant price declines, probably caused more by the financial markets crash than by a relatively low number of distressed-home sales. Effects varied greatly by community within counties, generally correlating to cost/affluence: Prices in less expensive markets often dropped twice as much as in more affluent communities within the same county.

Recovery From The Subprime/Financial Markets Crash

Generally speaking, Bay Area real estate markets began their sustained recovery from the effects of the subprime-loan bubble/financial market crash/distressed-property crisis in 2012. An unusual mix of factors subsequently came into play behind the highest rates of appreciation:

1. Whether the county was one of the three at the very heart of the high-tech, venture capital/start-up, and IPO booms: San Francisco, San Mateo amd Santa Clara.
2. Whether the county was adjacent to (or across a bridge from) the 3 central counties but offered significantly more affordable home prices: Alameda was the prime example.
3. Whether the county was rebounding from a distinctly outsized crash following the subprime bubble when their overall markets were utterly dominated by foreclosure and short sales: For example, Contra Costa (especially north county markets); Napa; Alameda (especially Oakland); and Sonoma.

Marin County is an interesting case during this period from the 2012 recovery to the pandemic striking: An affluent, highly desirable market, it saw substantial appreciation, but 1) was not one of the counties at the very heart of the high-tech boom, 2) though close to San Francisco, its housing wasn't enormously more affordable (as was the case in Alameda County), and 3) Marin was one of the very affluent counties least affected by subprime loans. Thus, its appreciation rate during this period lagged other Bay Area Counties, which were boosted by 1 or more of the 3 factors listed above. But Marin's appreciation dynamics would change dramatically with the onset of the pandemic.

Since the pandemic struck in Spring 2020, Bay Area real estate markets have been affected by many diverse and shifting factors, some of them unique to the period. These include population-density and contagion issues; shelter-in-place and its varying effects on urban, suburban, and rural environments; work-from-home upending the relationship between home location and workplace; trillions of dollars of free money issuing from state and federal governments; the historic plunge in interest rates; a remarkable, renewed boom in high-tech (especially affecting local giants like Apple, Facebook, Google); an astounding surge in stock markets (creating enormous amounts of new wealth); the rollout of vaccines; as well as other ecological, political, economic and social factors (fires, taxes, unemployment, family care, etc.).

These factors, as they applied in their various combinations to millions of households, prompted big changes in county-to-county migration; the comparative appeal of urban, suburban, and rural locations; the desirability of different property types (houses, condos, apartments), and amenities (pools; yards, gardens, and decks; home and lot size); heightened attention to housing affordability between regions (now that many could work from anywhere); and surging luxury home and second-home sales (as many households were more affluent than ever).

All this brought about striking changes in market dynamics and appreciation rates. Some of the larger trends were significant population movements from expensive, urban markets to suburban and rural areas. In the immediate aftermath of the pandemic, this migration precipitated a distinct weakening of rental and condo markets (which subsequently saw recoveries in 2021, with the vaccine rollout). Some counties saw disproportionate increases in sales of larger, more expensive homes, a big factor in boosting median sales prices: This affects apples-to-apples comparisons of appreciation rates between counties.

All these recent changes will be subject to future changes, pursuant to factors listed above, some of which may shift or reverse, as well as to brand new and possibly surprising factors as well.

All Bay Area markets experienced extremely high home-price appreciation rates over the past 30 years, but the 3 counties with the highest were San Francisco, Santa Clara, and San Mateo — unsurprisingly, the counties at the very heart of the high-tech booms over these decades. Each had an appreciation rate of over 500% at their median house sales prices.

Next in line was Alameda County, adjacent to or across a bridge from the central three, but generally offering substantially more affordable home prices: Alameda County's 30-year appreciation rate was over 465%.

Other Bay Area Counties saw median house sales price appreciation rates between 330% and 420%.

As a point of comparison, the CoreLogic S&P Case-Shiller Home Price Index — which does not use median sales prices in its calculations, but instead employs its own proprietary algorithm — calculates a national home-price appreciation rate of approximately 250% since 1990, though it should be noted that Case-Shiller Index calculations often run somewhat lower than those based on median sales prices.

It is extremely difficult, if not impossible, to predict the timing of the almost infinite variety of economic, political, and ecological events — occurring locally, nationally, or internationally—that can affect financial and real estate markets.

Compass Bay Area market reports: https://www.bayareamarketreports.com/

Context, methodology, and caveats: Median sales prices are not perfect reflections of changes in fair market values: Indeed, they are relatively blunt measurements, which can be affected by a variety of factors — including seasonality, natural disasters, and large fluctuations in a luxury home, new home, and distressed-property sales. Different analytics programs use varying methodologies, can define property types slightly differently, use different data sets, and generate somewhat varying conclusions as to price changes: Though trends are typically similar, judgment calls were made as to which data set best-reflected appreciation in specific markets.

Appreciation rates will vary based on the exact period they're measured from and to, and even a few months one way or the other can significantly alter calculations. Large anomalies in short-term data were adjusted when identified. The percentage increases and declines in the analyses herein should be considered approximate good-faith estimates: Indicators, rather than exact measurements. They are provided only to illustrate the general scale of changes in different markets within different economic periods. Every home is a relatively unique basket of conditions and circumstances as situated in the exact period of time in which it is being sold. How this report applies to any particular property is unknown without a specific comparative market analysis.

This analysis generally uses 6-month rolling data of county median house sales prices as published by the CA Association of Realtors® and/or the NorCal Regional MLS through September 2021, and CoreLogic S&P Case-Shiller Home Price Index data through August 2021 as published in late October 2021. Generally speaking, the Case-Shiller algorithm often calculates lower appreciation rates than estimates using changes in median sales prices.

Median Sales Price is the price at which half the properties sold for more and half for less. It may be affected by seasonality, "unusual" events, or changes in inventory and buying trends, as well as by changes in fair market value. The median sales price for an area will typically conceal an enormous variety of sales prices within communities and in the underlying individual sales.

Compass is a real estate Broker licensed by the State of California, DRE 01527235. Equal Housing Opportunity. This report has been prepared solely for information purposes. The information herein is based on or derived from information generally available to the public and/or from sources believed to be reliable. No representation or warranty can be given with respect to the accuracy or completeness of the information. Compass disclaims any and all liability relating to this report, including without limitation any express or implied representations or warranties for statements contained in, and omissions from, the report. Nothing contained herein is intended to be or should be read as any regulatory, legal, tax, accounting or other advice and Compass does not provide such advice. All opinions are subject to change without notice. Compass makes no representation regarding the accuracy of any statements regarding references to the laws, statutes, or regulations of any state are those of the author(s). Past performance is no guarantee of future results. Compass.

View More