San Diego Home Prices Rose 54.6% While Jobs Grew 3.2%: What Happens When Prices Rest on Assets, Not Wages

From late 2019 to September 2026, San Diego's median home value rose from roughly $600,000 to $926,961, a cumulative gain of 54.6%. That is more than the national figure of 48.0%, and more than the other two cities I have examined in this series, Boston (+47.6%) and Dallas (+37.5%) (Zillow ZHVI, September 2026). Over the same period, San Diego employment grew only 3.2%, versus 4.6% nationally (BLS QCEW, 2019–2024). The metro has just 111,000 jobs paying $150,000 or more, less than 60% of Dallas's 194,000 and about a third of Boston's 320,000 (BLS OEWS, May 2025). Of the three cities, the one with the fewest high-wage jobs has the highest prices and the largest gains.

Same soil, yet the price tree exploded while the wage sapling barely grew: the increase wasn't watered by paychecks.

This article is about that contradiction. My core judgment is that San Diego's prices were not pushed up by wages. They were set by households that already hold assets—long-time local owners, employees with equity in biotech firms and Qualcomm, and affluent people arriving from Los Angeles and the Bay Area—bidding against each other in a market with extremely low supply elasticity. Scarcity explains why prices are high; it does not explain the extra 54% since 2019. That increment came from the asset side, which means the market's risk sits on the asset side too, not in the jobs report. The coastal high end that rose the most is precisely the segment that will adjust first and hardest.

The article has eight parts. First, I use defense, biotech, and healthcare to show that wages cannot account for the gains. Second, supply elasticity and Proposition 13 explain why scarcity is an amplifier rather than the gain itself. Parts three and four trace where the money came from and the fingerprint it left on the price structure. Part five uses San Diego's own 1990s history and wildfire insurance to locate the fragility. Part six lays out guidance for buyers, sellers, and investors along with two-year scenario probabilities. I then respond to the objections readers are most likely to raise and distill the method into a checklist anyone can apply. This is the third installment of my ten-city deep-dive series, following Dallas and Boston.

1. Wages Can't Push Prices This Far: Defense Is Ballast, Biotech Is Contracting

San Diego's economy rests on two pillars: defense and biotech. If prices were wage-driven, the incremental money should come from one of these two. Start with defense. San Diego is one of the Pacific Fleet's most important home ports. A November 2025 report by the San Diego Military Advisory Council (SDMAC) and UC San Diego's Rady School of Management estimates that defense spending accounts for 22.2% of the regional economy, supporting 357,000 jobs and $61.3 billion of economic activity. This kind of spending has a distinctive property: it does not move with the business cycle, and because service members rotate duty stations every year, there is always a fresh cohort of families needing to rent or buy. That is why I placed San Diego on the defense-beneficiary list in my piece on the 24 U.S. cities that benefit in the AI era, and I am not changing that long-term view.

Defense is an anchor, not a sail: it keeps San Diego prices from sinking but does nothing to push them up.

But ballast is not an engine. Department of Defense contracts performed in San Diego County totaled roughly $12.8 billion in FY2019 and about $11.7 billion in FY2025 (USAspending). Over six years they did not grow; they drifted lower. Defense gives San Diego prices a relatively solid floor, but it is not pushing them upward. This distinction becomes more important when we get to the 1990s: defense provides "won't fall," not "will rise."

Now biotech. NIH RePORTER data show that NIH funding to San Diego and La Jolla institutions fell from $1.14 billion (2,077 projects) in FY2024 to $1.04 billion (1,691 projects) in FY2026—roughly a tenth less in dollars and nearly a fifth fewer projects. Venture capital contracted faster: San Diego biotech companies raised about $1.4 billion in the first three quarters of 2026, down 34.1% year over year, with just $500 million in the third quarter against $900 million a year earlier; life-science lab vacancy reached 28.5% in the third quarter (Savills data, reported by Commercial Observer, October 2026). As I argued in AI is redistributing high-income jobs, pharma will boom while needing fewer scientists. The current downturn is driven mainly by the funding and financing cycle—AI has not yet shown up in the data—but the direction matches what I said then.

So where is San Diego's job growth coming from? Healthcare. Healthcare employment stands at roughly 257,000, up 34.5% from late 2019, while professional and technical services, government, and manufacturing are flat to down (BLS CES). Nurses and care aides must follow the aging population; the work cannot be outsourced or done remotely, making it among the hardest to replace in the AI era. Partly because of that structure, when BLS OEWS occupation counts are weighted by the AI-exposure estimates in Eloundou et al. (2024, Science), 29.8% of San Diego jobs are highly exposed—the lowest of the three cities. But healthcare wages cannot carry a $927,000 median price.

Lab lights go out one by one while healthcare spreads along the valley of the elderly: jobs grow, but not the kind that lifts prices.

Defense is the floor under San Diego prices, not the engine; biotech is contracting; healthcare is expanding but does not pay enough. Wages cannot produce a 54% gain.

2. Supply Constraint Is an Amplifier: Nothing Gets Built, and Owners Won't Sell

The usual reply to Section 1 is "because there aren't enough homes." That is right, but only half right. Take the right half first. Wharton professor Albert Saiz's 2010 housing-supply elasticity estimates, published in the Quarterly Journal of Economics, run from easy to build (high numbers) to hard (low): Dallas is 2.18, Boston 0.86, and San Diego 0.67, the fifth most constrained of 95 metros. The geography is obvious—the Pacific to the west, the Mexican border to the south, mountains and desert to the east, Camp Pendleton to the north, and a city carved up by dozens of canyons. The developable flat land ran out decades ago. From 2020 through 2025, San Diego County permitted only 63,614 housing units, and on a per-capita basis fewer than half as many per thousand residents as Dallas (Census Building Permits Survey).

The direct consequence of low elasticity is that demand shifts get amplified. In a regression across 73 U.S. metros, each 1% increase in employment leaves Dallas prices nearly unchanged but lifts San Diego prices by 2.9%, the highest of the three cities (my compilation from BLS QCEW, Saiz elasticities, and the FHFA house price index). That coefficient is San Diego's amplifier. In the Dallas installment I showed how supply elasticity can eat an AI-winner city's price gains; San Diego is the mirror image—the same demand impulse is magnified nearly threefold here.

New homes can't be built, and existing homes aren't coming to market either. Over the twelve months through September 2026, San Diego's monthly new listings ran at only 66% of the pre-pandemic pace, versus 80% in Boston and 96% in Dallas (Realtor.com). Owners stay put for two reasons. One is the 3% mortgage they do not want to give up. The other is California's Proposition 13: property is assessed at its purchase price and the assessment can rise at most 2% per year (California Legislative Analyst's Office). A home bought for $500,000 in 2010 is assessed today at roughly $660,000 after applying California's annual inflation factors; sell it to buy a $1 million home locally and the tax bill resets to $1 million immediately. Rate lock-in exists nationwide; Proposition 13 is a California-only layer on top. That is why San Diego's long-time owners are less willing to sell than owners anywhere else.

Cheap mortgages and Proposition 13 act like golden chains, locking owners in place so even existing homes stop flowing.

Yet scarcity only explains why prices are high, not why they are still rising. The supply shortage is a constant—San Diego has looked like this for decades, including before 2019. The additional 54% since 2019 had to be paid for by someone, in real dollars, while local wages did not rise anywhere near that much and people kept leaving. So the question becomes: who paid?

Scarcity is a constant; it sets the water level of San Diego prices but cannot explain the increment since 2019. Someone had to pay that increment in real money.

3. Who Is Paying: Asset Holders, Not Wage Earners

Start by ruling out ordinary wage-earning households. Under Zillow's affordability method (20% down, payment no more than 30% of income), buying a median-priced San Diego home requires household income of $237,000, up from $119,000 in late 2019—exactly double. The metro's median household income is $109,000 (Census ACS 2024 one-year). The monthly payment makes it concrete: in late 2019 the median home cost about $600,000 at a 3.72% mortgage rate, for principal and interest of roughly $2,224; today it is $927,000 at a 30-year fixed rate of 7.24% (Freddie Mac PMMS, week of October 29, 2026), for roughly $5,050—2.3 times the 2019 figure. Add property tax and insurance and the monthly outlay is $6,100 to $6,300, after a down payment of about $190,000. Prices rose 54%, but the payment more than doubled; wage-dependent households have been priced out of marginal pricing altogether.

The income needed to buy a median home doubled in seven years while local median income stayed put: the threshold rose beyond wage earners' reach.

Are wealthy out-of-towners moving in and outbidding locals? The data do not support it. The Census Bureau estimates San Diego loses a net 17,000 to 41,000 residents a year to other parts of the United States (Census Vintage 2025 metro estimates). IRS county-to-county migration data reveal the income structure: in 2022–2023, roughly 32,000 households moved in from other states with an average income of $89,800; roughly 41,000 households moved out to other states averaging $88,900; households that stayed averaged $114,000 (IRS SOI). In-movers and out-movers earn almost the same, and both earn less than those who stayed. People arriving from other states are not richer than locals, and those leaving are largely young families pushed out by prices—San Diego's next cohort of first-time buyers.

So where does the money come from? I see three sources. First, long-time local owners: homes bought years ago have appreciated enormously, and selling one plus savings funds a more expensive purchase—past price gains paying today's prices. Second, equities: employees of biotech firms and companies like Qualcomm hold stock, and when the market rises their wealth and their down-payment capacity rise with it. Third, affluent households and retirees relocating from Los Angeles and the Bay Area: the IRS series tracks only interstate moves, so intra-California relocation—San Diego's most important source of high-net-worth demand—is invisible in it. These three sources share one trait: they rest on assets, not current wages. Those who cannot buy rent: 45.6% of San Diego households rent, 58% of them spending more than 30% of income on rent (Census ACS 2024), and the typical rent of $2,993 is up 44.1% from late 2019 (Zillow ZORI, August 2026)—both figures the highest of the three cities.

Three asset rivers feed this basin: old-home equity, stock wealth, and money moving south; the wage river has run dry.

San Diego's marginal buyer is not a wage earner but someone who already holds property and stock; their purchasing power comes from asset prices and has little to do with current income.

4. The Fingerprint on Prices: Expensive Homes Rise, Cheap Ones Stall

If Section 3 is right, it must leave a fingerprint: expensive and inexpensive homes should move differently. I sorted San Diego's 95 ZIP codes into quintiles by price. The cheapest 20%, with a median value of about $650,000, rose only 3.0% over the past three years; the most expensive 20%, with a median of about $1.8 million, rose 11.3% (Zillow ZHVI by ZIP). At the city level, coastal Solana Beach gained 13.5% over three years while Imperial Beach in the South Bay gained 0.7%.

The mechanism is the buyer's wallet. Entry-level buyers depend on wages and loans: when rates rise from 3% to 7%, the same income borrows about 37% less—close to 40%, and that is arithmetic, not opinion. High-end buyers depend on assets: with large down payments or all cash, rates matter far less, and when stocks and home values rise their purchasing power actually grows. So cheap homes stall not because nobody wants them but because those who want them cannot borrow more; expensive homes keep rising because their buyers are not rate-constrained. Dallas shows the opposite pattern—the low end fell most while the high end barely moved—because builders concentrate new supply at the low end. San Diego has almost no new construction, so the stagnation at the low end is purely a demand-side phenomenon.

Higher rates shorten the loan-buyer's cable so entry-level is out of reach; asset buyers ride a lift pushed up by wealth, so the high end keeps climbing.

Condos tell the story most clearly. San Diego condos are now 7% below their July 2024 peak (Zillow ZHVI condo), and condos are the primary entry point for young first-time buyers. Their decline and the stagnation of cheap ZIP codes are two faces of the same fact: wage-and-loan demand has hit its ceiling. What pushed San Diego prices up is a minority of asset-rich households buying the coastal segment; the segment ordinary families buy has barely moved in three years.

Cheap homes stall not because nobody wants them but because wage-and-loan buyers have hit their limit; expensive homes keep rising because their buyers' purchasing power tracks assets.

5. Where the Fragility Lies: Equities, the 1990s Precedent, and Wildfire Insurance

The amplifier works both ways, and the market is already slowing

Section 2 established that demand shifts in San Diego are magnified nearly threefold. That is true on the way up and on the way down. High-end buyers' money is tied to the stock market and to biotech financing: when equities fall, that cohort retrenches simultaneously, and coastal luxury neighborhoods have almost no alternative buyers to step in. This is why the beachfront homes that rose the most will also be the first to correct. The market is already signaling: San Diego prices peaked in July 2024 and have moved sideways since, up only 0.5% over the past year (Zillow, September 2026). Active inventory is just 88% of the pre-pandemic level—still scarce—yet median days on market is 46, versus 36 before the pandemic, and 20.4% of listings have taken a price cut, versus 18.9% (Realtor.com). Fewer homes, slower sales: the problem is not supply, it is buyers. At today's prices and rates, fewer people can step up.

The 1990s: jobs fell 3.3%, real prices fell 31%

Some will say San Diego has no land left, so even if the rich pull back, how far can prices really fall? San Diego's own history has answered that. In the 1980s a large share of its high-wage jobs depended on aerospace and defense orders. When the Cold War ended, orders collapsed; in 1994 General Dynamics closed its Convair plant in San Diego (UPI, July 1994). Aerospace employment fell from 31,000 in 1988 to about 9,000 in 1998, a 70% decline (California Legislative Analyst's Office, September 1998 report). Yet total San Diego nonfarm employment fell only 3.3%, from a January 1991 peak of 988,000 to a December 1992 trough of 956,000 (BLS CES). That does not sound like much.

The 1990s sample: same land, same walls, yet when the pillar fell, total jobs dipped only slightly and real prices fell by nearly a third.

What happened to prices? By the S&P Case-Shiller San Diego index (via FRED), prices peaked in June 1990 and fell in nominal terms through August 1996, a decline of 16.7%; adjusted for CPI inflation, real prices bottomed in December 1996, down 31.2%. Nominal prices took 8 years and 2 months to regain the peak; real prices took 10 years and 5 months. And mortgage rates? They averaged 10.13% in 1990 and fell to 6.74% in the week of October 22, 1993, the low for the first half of the decade (Freddie Mac via FRED). Rates dropped more than three points, and prices still fell for six years—because lower rates only let an individual buyer borrow a bit more, while the high-wage jobs that had held up prices were gone and the buyer pool had shrunk sharply. San Diego could not build then either; the Pacific was still to the west and the Marine base still to the north. Scarcity is an amplifier: it magnifies the upside and the downside alike.

Stretch the horizon to ten years and I am watching the same thing: the asset base under prices. San Diego is not Boston. Boston's prices rest on the payrolls of 320,000 high-wage jobs; if AI removes those jobs, the floor disappears. San Diego's prices rest on assets—biotech R&D cutbacks are one strand, but the bulk is the stock market and people arriving with money. My judgment: if over the next decade equities and tech valuations go through a downturn comparable to what defense orders did in the 1990s, San Diego's real home prices could run 15% to 30% below trend, with the coastal segment falling first and furthest. Conversely, as long as that asset base holds and nothing gets built, prices will not fall. So for San Diego's next ten years, watch the stock market, not the jobs report.

Insurance: a line item no other city has

Beyond equities, San Diego carries a cost other cities do not: wildfire insurance. In recent years many carriers have cut back underwriting in California, pushing more owners into the state-backed FAIR Plan. San Diego County had about 37,375 FAIR Plan policies two years ago, jumped 58% to 59,063 a year later, and stood at 64,555 as of September 30, 2026, with year-over-year growth slowing to 9%; statewide the count is 698,307, up 8% (California FAIR Plan county data, updated October 2026). The slowdown does not mean risk is receding—it means everyone who could be pushed into the FAIR Plan largely has been, a 1.7x increase in two years. The coast and the urban core remain more or less normal, but in East County mountain communities such as Ramona, Alpine, and Julian, coverage is increasingly hard to find and expensive; in some areas only basic FAIR Plan fire coverage is available, requiring a separate supplemental policy.

As private insurers pull out, more homes crowd under the state's scorched umbrella; the only room to build is where insurance is hardest to get.

Insurance feeds into prices through two channels. The first is the buyer pool: when you sell, the first question will be "can this house be insured?"—and a smaller buyer pool means a lower price. The second is condos: when a building's master policy rises, the cost ends up in your HOA dues, and in severe cases triggers special assessments. The structural issue is that San Diego's only remaining direction for expansion is east into the mountains, which is exactly the high wildfire-risk zone. The land that could still be built on is the land where insurance is hardest to get. That tightens the supply constraint further on the insurance side, while buyers at the low end are the least able to absorb rising insurance costs.

For San Diego's next decade, watch equities, not the jobs report: in the 1990s total employment fell only 3.3% while inflation-adjusted prices fell 31%.

6. How to Buy, Sell, and Invest: Two-Year Scenarios and Practical Guidance

Buyers first. One: confirm insurance before negotiating price. For homes in East County, the mountains, or along canyon edges, have an insurance broker quote the specific address before you write an offer; premiums and insurability determine both your carrying cost and your future buyer pool. Two: this is one of the few windows in recent years when terms are negotiable—median days on market is 46 and 20.4% of listings have cut prices, so you can be more aggressive on homes listed 45 days or longer. But do not expect a big price drop; inventory is only 88% of pre-pandemic levels and long-time owners will not dump homes. Three: first-time buyers should look at condos, now 7% below the July 2024 peak, provided the HOA's finances are sound, the building's insurance is renewable, and no major repairs are imminent. On the question of whether to wait, I laid out my position in whether to time the market: in a market priced by assets, what you are waiting on is not rates but the stock market.

Sellers next. If you own a coastal high-end home and were planning to sell anyway, prices are near record highs and there is no reason to wait—this segment depends most on equities, a variable you do not control. If you own a condo or an entry-level home, price it correctly from day one; overpricing just means sitting on the market, because this segment's buyers are the most rate-constrained. Before listing, complete deferred repairs and fire-hardening so buyers can obtain insurance more easily—in effect, you are widening your buyer pool.

Finally, investors. A $930,000 single-family home renting for $4,136 a month yields a gross 5.3%. Subtract property tax at 1.2% ($11,170 a year), $3,000 of insurance, and roughly $9,930 for vacancy, maintenance, and management, and the net yield is 2.7%, versus 3.3% in Dallas. With the 30-year fixed at 7.24%, the cost of borrowing exceeds the property's net yield by 4.5 percentage points. San Diego rentals therefore suit only all-cash or low-leverage buyers planning to hold long term—Proposition 13 makes property tax cheaper the longer you hold, the one institutional subsidy San Diego offers patient owners. The steadiest rental demand is around UC San Diego and around the naval bases: students and researchers in the first case, rotating military families in the second, neither of which moves with the stock market.

Net rental yield sits far below the cost of borrowing: San Diego only works for all-cash or low-leverage long-term holders.

My two-year scenario probabilities:

These three scenarios, along with my outlook for high-priced single-family homes, ordinary owner-occupied homes, condos, rentals, student housing, and multifamily, are all on the housing map on my site (https://www.seahomepedia.com/en/housing-map/ )—click San Diego to see them.

The likeliest road ahead is flat and slow: small gains, few sales; the one to guard against is the branch that descends toward the cliff.

For the next two years San Diego is "firm but fragile": a 55% chance of a 0% to 3% gain on very thin volume. The scenario to guard against is the 25% downside, and its trigger is the stock market.

Counterarguments and Responses

Objection one: San Diego has no land, owners are locked in by Proposition 13, and supply is rock-hard—so even if the wealthy pull back, prices will plateau, not actually fall. This is the most common and most substantial objection, and I answer it on two levels. The first is history: 1990s San Diego had exactly today's supply constraints—the Pacific, the Marine base, the canyons were all there, and Proposition 13 had been in force for years—yet total employment fell only 3.3% while prices dropped 16.7% nominally and 31.2% in real terms, taking 10 years and 5 months to recover in real terms. Hard supply did not prevent the decline; it concentrated the decline in the segment where demand vanished. The second is mechanism: low supply elasticity means high price sensitivity to demand, and that sensitivity has no direction. The regression coefficient of a 2.9% price gain per 1% job gain is, in reverse, a 2.9% decline per 1% demand loss. A plateau requires a stable count of marginal buyers, and San Diego's marginal buyers are precisely the least stable group—their purchasing power tracks the stock market.

Objection two: defense is 22.2% of the regional economy, healthcare jobs are up 34.5%, AI exposure is the lowest of the three cities—San Diego's fundamentals are clearly steadier than Boston's, so why call it fragile? The answer requires separating the floor from marginal pricing. Defense and healthcare do give San Diego a steadier employment floor than Boston, which is why I count it among defense-beneficiary cities and why my ten-year view differs from Boston's: Boston's risk is that AI removes the high-wage jobs themselves, and San Diego does not carry that risk. But prices are not set by the employment floor; they are set by the marginal buyer. San Diego's employment floor supports entry-level demand, and that segment rose only 3% in three years while condos fell 7%—the floor is already in the price, and what it props up is the cheap segment. The coastal high end that rose 11.3% to 13.5% has no defense or healthcare behind it, only assets. So "steady fundamentals" and "fragile high end" do not conflict: one describes the floor, the other the ceiling. And the fact that defense contracts slipped from $12.8 billion to $11.7 billion is a reminder that even the floor itself is drifting slowly lower, not higher.

Defense and healthcare are solid bedrock, but prices are set by the top floors held up by balloons: a stable base does not mean a stable peak.

Objection three: IRS data cover only interstate moves, and the article's third source of money—wealthy arrivals from Los Angeles and the Bay Area—has no direct data behind it. Isn't that speculation? It is an inference, and I want to be clear about that. I do not have income data on intra-state movers; it is the weakest link in the argument. But it is an inference supported by indirect evidence. First, out-of-state arrivals average only $89,800, below the $114,000 of households that stayed, so if "wealthy outsiders" exist they can only be coming from within California. Second, the price structure—top-quintile ZIPs up 11.3%, bottom-quintile up 3%, condos down 7%—is consistent with asset-holder pricing and inconsistent with both wage pricing and an influx of rich interstate movers. I present the three funding sources together and do not depend on any one of them alone; as long as one accepts that the marginal buyer relies on assets rather than wages, the fragility conclusion that follows stands.

A Framework: How to Tell Whether a City's Prices Rest on Wages or Assets

What I most want readers to take away is not any one San Diego number but a method that can be applied to any city. It has three steps.

Step one: determine whether the fuel is wages or assets. Ask four questions. (1) Do price gains line up with job growth and the count of high-wage jobs? San Diego's 54.6% price gain, 3.2% job growth, and fewest high-wage jobs of the three cities do not line up. (2) Can an ordinary household at the local median income buy a median-priced home? Required income of $237,000 against a median of $109,000—no. (3) Are in-migrants richer than locals? IRS data say no. (4) Is the price structure diverging—expensive rising, cheap stalling, condos slipping? Yes. When all four point to assets, the city is asset-priced.

Diagnose a city by checking its fuel: are prices fed by wages or by assets? Compare growth rates, local affordability, and whether prices are splitting.

Step two: measure the amplifier. Look at Saiz supply elasticity and per-capita building permits, then at new listings relative to pre-pandemic levels and any local lock-in factor such as Proposition 13. The lower the elasticity and the thinner the listings, the larger the multiple by which demand changes pass through to prices. San Diego scores 0.67, permits fewer than half as many units per thousand residents as Dallas, and lists at only 66% of the pre-pandemic pace; its amplifier is roughly 2.9. Remember that the amplifier has no direction.

Step three: identify the variable that drives the asset base, and test it against history. If the fuel is wages, watch the jobs report and AI's effect on occupations. If the fuel is assets, watch equities, tech valuations, venture funding, and the wealth of in-migrants—the jobs report carries almost no information. Then find an episode in the city's own history when the pillar fell but supply did not change, and see how far prices dropped and how long recovery took. San Diego's episode is the 1990s: employment down only 3.3%, real prices down 31%. Finally, add the city's distinctive carrying costs—in San Diego, wildfire insurance and Proposition 13—because they determine which segment's buyer pool contracts first.

Apply these three steps to San Diego and the conclusion is the two sentences this article rests on. A big run-up is not the same as stability: wage-supported prices follow employment, asset-supported prices follow the stock market, and San Diego is the latter. Scarce supply is an amplifier in both directions: in a city whose prices rest on assets, what you must watch is the stock market and the wealth of those asset holders, not the jobs report.

In a city where assets prop up prices, point the beam at the stock market and the wealth of the asset-rich, not at the jobs report.

To judge a city, first ask what fuels its prices, then ask how large the amplifier is, and finally find the episode in its own history when the pillar gave way.