New York City vs San Diego Airbnb: Which Market Actually Pays

San Diego's median listing earns £13.6K more per year than New York's, but the occupancy gap and brutal seasonality swing mean the right answer depends on how you plan to operate.

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The number that settles most of these arguments before they start is median annual revenue, and here it isn't close. San Diego listings are generating $37.0K a year against New York's $23.4K — a $13.6K gap that compounds across a portfolio. If you stopped reading there, you'd back San Diego and be roughly right.

But the shape of those earnings matters as much as the size. New York runs at 60% occupancy year-round; San Diego hits 68% in July and 31% in December. One of these markets lets you underwrite to a fairly predictable monthly income. The other hands you a bonfire summer and asks you to survive the winter. This piece works through what that difference actually costs you, where the regulations sit, and which investor profile each city is actually suited to.

Where the money actually is

The $166 gap in nightly rate is the headline, and it's real. San Diego's $348 ADR against New York's $182 means a single additional booking in San Diego outearns nearly two nights in New York. That gap alone covers most mortgage differentials between comparable properties in the two markets, assuming you're financing at similar LTVs — though purchase prices are something this data can't tell you, and street-level variance in both cities is enormous.

What complicates the San Diego story is that a 65% rate increase year-on-year is almost certainly not a run-rate you can project forward. Rates that move that fast are either catching up after a suppressed period or riding a demand spike that corrects. New York's 21.9% increase is aggressive too, but against a lower base it's a different kind of signal. The occupancy figures are where New York quietly earns respect: 60% flat year-on-year, with no movement, suggests a market that has found its equilibrium. San Diego at 48% average is being dragged down by those winter months, and the annual median reflects it less than you'd expect because the summer peak is so high.

The entire-home share tells you something about the competitive set. At 88%, San Diego is almost exclusively whole-property listings — you're not competing with hosts renting a spare room, you're competing with other investors running proper STL operations. New York's 55% means a more mixed field, which can work in your favour if you're offering a well-managed entire home into a market that still has a lot of shared-space supply.

The cashflow shape

New York's swing from a 63% June peak to a 42% November trough is a 21-point spread. That's a meaningful seasonal dip, but it's the kind of variance most operators can absorb — you're never empty, you're just quieter. San Diego's 37-point spread from 68% in July to 31% in December is a different animal. A 31% occupancy month on a property with a mortgage means you are almost certainly cashflow negative in December, and probably November and January too.

For a seasonal operator who plans to block the property for personal use in winter anyway, San Diego's pattern is close to ideal — you give up the months you weren't selling, and you maximise the months everyone wants to be there. For a year-round operator who needs consistent income to service debt, New York's flatter curve is genuinely worth more than the raw revenue gap suggests. The $13.6K annual advantage in San Diego can evaporate fast if you're covering carrying costs through three slow months rather than one.

Where the rules bite

Neither city has a night cap in the current data, which removes the most common regulatory kill-switch for STL investors. New York is a city that has historically been aggressive about short-term rental enforcement — Local Law 18, which came into force in 2023, requires hosts to register and be present during guest stays for listings under 30 days. That effectively bans unhosted entire-home rentals in most of the city. The 55% entire-home share in the active listings data suggests operators are finding ways to work within or around this, but any buyer needs to go in clear-eyed: if you're buying to run an unhosted entire-home STL in New York, the legal footing is genuinely precarious and the enforcement risk is real.

San Diego's regulatory environment is materially more permissive. The city introduced a tiered licensing system that allows whole-home STLs with the appropriate permit, and the 88% entire-home share confirms that the market is operating largely as intended. There are permit caps in some tiers, and the process has a waitlist, so this isn't frictionless — but it's a solvable operational problem rather than an existential legal one. For a buyer whose model depends on running an unhosted entire property, San Diego is the only city on this shortlist where that model is straightforwardly legal.

The call

San Diego is the better investment for most buyers on this shortlist. The revenue advantage is substantial, the regulatory framework actually supports the most profitable operating model, and the nightly rate trajectory — even discounting the 65% YoY spike as unsustainable — points to a market where pricing power exists. The seasonality risk is real but manageable with adequate reserves and realistic underwriting.

New York makes sense for one specific buyer: someone who wants urban exposure, accepts lower returns in exchange for flatter cashflow, and has a legal structure that works within the city's strict hosting rules — most likely a hosted model or 30-day-plus stays that fall outside the short-term definition. That's a narrower pitch, and the $23.4K median revenue means the numbers have to work on a lower purchase price to generate any meaningful yield. For most investors looking at a straightforward STL operation, San Diego wins and it isn't particularly close.

Frequently asked questions

Methodology. Figures are medians across active listings from Inside Airbnb's 2026-06-14 snapshot, refreshed automatically as new snapshots land. The table and chart above always show the latest data; the commentary is re-written when the numbers move materially.