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Housing and tourism analysis

Is Airbnb emptying the city?

2026 Airbnb listings compared with the emptying city, the appreciating city and the city of second homes: Cancún's Airbnb follows price, not emptying.

In one sentenceOrients short-term-rental regulation toward where it concentrates — second homes and appreciating areas — rather than emptying areas.

Spanish original: ¿El Airbnb vacía la ciudad?

Is Airbnb emptying the city?

A common hypothesis is that vacation rentals displace residents.

This atlas sets 2026 Airbnb listings next to the city that is emptying, the one that is appreciating and the one of second homes, to see which it matches.

Key findings

  • It does not follow emptying

    Blocks losing population have almost the same Airbnb intensity as those gaining (0.38 and 0.37 listings per 100 dwellings, excluding second homes).

  • It follows price

    Appreciating superblocks have 6.7 times more listings per dwelling than depreciating ones; 49% of all listings are there.

  • New housing oriented to rental

    31% of listings are in blocks that had no housing in 2020, and where second homes predominate intensity is 11 times higher.

The interactive atlas below is in Spanish. Numbers, maps and controls are the same as described on this page.Open it full screen ↗

Anuncios de Airbnb 2026 por manzana · Censo 2010 y 2020 · precios de mercado por supermanzana 2016–2023 · Base cartográfica: Esri World Light Gray

Approach

  1. Step 1

    Assign 2026 Airbnb listings to the series' 12,639 blocks.

  2. Step 2

    Compare intensity (listings per 100 dwellings) between blocks losing, gaining or keeping population, and between appreciating and depreciating areas.

  3. Step 3

    Repeat the comparisons without occasional-use housing to separate the second-home effect.

How to read it

  • Listings are from 2026 and housing from 2020: a six-year lag.
  • A listing is not a dwelling; the layer does not show accommodation type or availability.
  • This is a territorial association: it does not rule out individual displacement, which would require household data.

Data

  • Airbnb 2026

    Listings by block.

  • 2010 and 2020 Censuses

    Population and private housing (occupied, vacant, occasional use).

  • Market prices

    Dynamics by superblock 2016–2023.

What you just saw

Hypothesis test between listings, population change and land value, with controls.

What else this method can answer

  • Where do short-term rentals concentrate?
  • Which areas should be monitored?
  • What about new housing the census did not see?

In other places

Needs listings, two censuses and land values.

Line of work

D · Territorial diagnosis and monitoring →

Do you have a similar question in your city?

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Next in Land, housing and zoningThe appreciation frontier