Airbnb’s Hidden Costs: How short-term lets create long-term problems

 Airbnb looks like a win-win, and the numbers back up its popularity, growing from 2.1 million listings in 2016 to over 8 million in 2024 (Kumar, 2025). Homeowners make extra money, and travellers get somewhere to stay cheaper and more flexible than a hotel. But in the cities where Airbnb has grown fastest, rents have gone up, long-term housing has become harder to find, and neighbourhoods have changed alongside the sound of rolling suitcases. The backlash makes sense once you see what's actually going on. This is not really a tourism problem, it's a textbook negative externality. The guest pays, the host earns, but neither of them pays for the costs imposed upon everyone else. This blog explains how that happens, shows the evidence, and asks whether current policy can actually fix it.

Source: (BBC, 2022)

 

Negative externality in Airbnb market

Hosts have strong incentives to use Airbnb because short-term letting is flexible, can adjust prices in peak tourist seasons and offers higher returns than long-term tenancies. Tourists have more choices of accommodation and sometimes offer cheaper prices than hotels. Therefore, both hosts and tourists benefit from the transaction and it seems like a win-win exchange. However, not all people gain from this transaction. When more properties are shifted from long-term to short-term use, the supply of long-term housing falls, pushing up rents for local residents.

 

Therefore, the short-term market price only reflects private benefits but not full social costs. As a result, the level of output for short-term lets exceeds the socially efficient level, resulting in overproduction and negative externality in production. The negative externality in consumption cannot be ignored as well. Locals may face problems such as noise, overcrowding and safety concerns. Together, these effects show how externalities can distort market outcomes.

 

Figure 1 below illustrates how Airbnb can create hidden costs in the housing market. In the private market, the equilibrium point is Q_pc, which shows that hosts only consider their own private costs and expected returns. However, this equilibrium point does not include some external costs imposed on local residents. Once these external costs are taken into account, the social optimal point falls to Q*.

Figure 1: Without regulation, the Airbnb Market produces a deadweight loss

 

Real Life Externalities

There is growing evidence that the theory plays out in reality. A study of Portugal found that a 1 percentage point increase in Airbnb's market share was associated with roughly a 3.7% increase in housing prices (Franco and Santos, 2021). In Barcelona, between 2009 and 2016, Airbnb was found to be responsible for a 4% increase in rents (Garcia-López et al., 2018), and in New York City, when Airbnb listings doubled, property values increased by 6% to 11% (Sheppard and Udell, 2016). The pattern is clear: in high-demand areas where housing supply is already tight, Airbnb places upward pressure on costs, and those costs land on locals who take no part in any booking transaction - exactly the hidden cost to third parties shown as MEC_p in Figure 1. It is a cost Airbnb hosts and guests don’t pay, but neighbours do.

 

Policy Solutions

So why doesn’t the market sort this out on its own? The Coase theorem suggests that if property rights are clear and bargaining is cheap, the people affected by an externality can negotiate their way to an efficient outcome without the government getting involved. The problem is neither condition works here. No one has the right to a quiet street or affordable local rents, and even if they did, it would be near impossible to get every resident to bargain with every Airbnb host in their respective area. The transaction costs are simply too high, so the external costs stay invisible to the hosts and the market keeps overproducing short-term lets, which is why government intervention is required.

 

Governments have two main levers for dealing with this kind of negative externality: cap it or tax it. A correctly set tax works by raising the cost of operating a short-term let by exactly the marginal external cost (MEC_p). This lifts the private cost curve (S=MPC) up until it rests on top of the social cost curve (MSC), which collapses the deadweight loss triangle (DWL) to zero in Figure 1 and shrinks the market quantity from Q_pc to the socially efficient quantity Q*. An example of this is in Edinburgh, where from 24 July 2026 there will be a 5% tourist tax added on to the cost of short-term accommodation (BBC, 2026). Although the tax is legally paid by guests, the burden is shared with hosts through lower nightly revenue, opening a wedge between what guests pay and hosts receive, which nudges the market down toward Q*.

 

A cap instead restricts quantity rather than price, pushing the market quantity (Q_pc) down toward the socially efficient quantity (Q*). Caps target commercial-style lets that do the most damage to long-term housing supply (london.gov, 2025). An example of this is London, where there is a cap of 90 nights per year for a listing without needing planning permission (Ucha Vekua, 2025).

 

Both policies are better than a blanket ban. A ban wipes out the externality, but also wipes out every short-term let a tourist would have valued and every extra pound a host would have earned above what they would receive from long-term letting. The aim of good policy is not to eliminate short-term lets, but to move the market quantity under perfect competition(Q_pc) toward the socially efficient level (Q*), where there is no longer any deadweight loss. The harder question to answer is whether Edinburgh's 5% tourist tax or London's 90 night cap actually match the marginal external cost (MEC_p) they are attempting to offset. Both policies were produced through political negotiation rather than by calculating the externality, so while each moves the market in the direction of the socially efficient quantity, there is no guarantee that either policy lands perfectly on Q*.

References:

BBC (2022). Green light for Edinburgh short-term lets controls. BBC News. [online] 24 Feb. Available at: https://www.bbc.co.uk/news/uk-scotland-edinburgh-east-fife-60478178.

BBC (2026). Councils given power to charge ‘flat fee’ tourist tax. BBC News. [online] 24 Mar. Available at: https://www.bbc.co.uk/news/articles/c1w4qjlzxgjo.

Franco, S.F. and Santos, C.D. (2021). The Impact of Airbnb on Residential Property Values and Rents: Evidence from Portugal. Regional Science and Urban Economics, 88, p.22. doi:https://doi.org/10.1016/j.regsciurbeco.2021.103667.

Garcia-López, M.-À., Jofre-Monseny, J., Martínez Mazza, R. and Segú, M. (2018). Do Short-Term Rental Platforms Affect Housing Markets? Evidence From Airbnb in Barcelona. SSRN Electronic Journal, 119. doi:https://doi.org/10.2139/ssrn.3428237.

Kumar, N. (2025). Airbnb Statistics 2025: Users & Revenue Data. [online] Demand Sage. Available at: https://www.demandsage.com/airbnb-statistics/.

london.gov (2025). Guidance on short term and holiday lets in London. [online] London City Hall. Available at: https://www.london.gov.uk/programmes-strategies/housing-and-land/buying-and-owning-home/guidance-short-term-and-holiday-lets-london.

Sheppard, S. and Udell, A. (2016). Do Airbnb properties affect house prices? [online] Available at: https://web.williams.edu/Economics/wp/SheppardUdellAirbnbAffectHousePrices.pdf.

Ucha Vekua (2025). What is the 90 day rule on Airbnb? [online] Wise. Available at: https://wise.com/us/blog/what-is-the-90-day-rule-on-airbnb.