Decision-maker brief

Bringing short-term rental in Budapest above board

The situation, measurement results and seven policy proposals

GuestGuru Kft.August 2026

Contents

---

1. Executive summary

Budapest has 15,125 short-term rental listings on Airbnb and Booking.com. Of these, 4,952 are unlicensed: the mandatory NTAK identifier is missing, the number given does not exist, or it belongs to someone else. That is 32.7 per cent of the supply, and it is a conservative figure.

This third pays no tourist tax, no tourism development contribution, typically issues no invoice, and offers no one to turn to if there is a problem in the building. Counting only the Airbnb side and only two taxes, the council and the state lose HUF 1.3 billion of revenue a year, and that figure comes entirely from measured data. Counting the whole market and the further taxes, the shortfall is above HUF 3 billion.

Meanwhile the inner districts are introducing restrictions or bans on short-term letting one after another. Structurally, these affect only those who registered in the first place. They push the legal operator out of the market, leave the non-compliant one in place, and even hand them a competitive advantage.

Terézváros is living proof. After the total ban that entered into force on 1 January 2026, three-quarters of the listings still running in the district are unlicensed. Meanwhile 72 thousand guest nights disappeared in a single quarter, HUF 280 million of tourist tax in six months, and hospitality turnover fell by 30 per cent. The guests did not move to hotels: hotels absorbed less than a quarter of the loss.

We also measured the housing argument. Of Budapest's 961,061 homes, 10,703 go to short-term rental (1.1 per cent), while 95,320 homes stand genuinely empty: nearly nine times as many. The explanation for the housing crisis, and its solution, are not to be found in this segment (3.6); cleaning up the market, however, is due regardless, because that is about competition and tax.

The essence of our proposal in a single sentence: let us reverse the order. First uncover and wind up the unlawful operations, then measure how much of a problem is left. This does not require district clerks but a single Budapest enforcement point able to negotiate with the platforms (Airbnb, Booking), and a uniform tax base that allows the platform itself to collect the tourist tax.

---

2. What we measured and how

BPDB (Budapest Database) is a system we built ourselves, merging three public data sources:¹

1. The district councils' accommodation registers. Public data, but available with differing content and interfaces in each district. Some districts already display the NTAK identifier, most do not.
2. The NTAK and accommodation classification register. Public. It shows whether a given identifier exists, which address it belongs to, its category, and whether it has a valid classification.
3. Airbnb and Booking.com listings. Public, since guests book on them. Since 2023 the NTAK identifier must be displayed in them.

The system checks the identifier given in the listing against the register, and compares the listing's geographic location with the registered address. This yields six statuses. Of these, the following are non-compliant:

• non-existent identifier: the number in the listing does not appear in the register
• missing identifier: the listing does not display one at all, although it has been mandatory for two and a half years
• foreign identifier: the number exists but demonstrably belongs to another property, typically several hundred or several thousand metres away
• contradictory data

A separate category is where there is an identifier but no valid classification. We deliberately do not count these among the unlicensed, because they may include properties with an expired classification or awaiting one. There are 1,402 such listings. If we counted them, the share of unlicensed would be 42 per cent instead of 34.

What the system cannot do. It cannot say who the advertiser is, because Airbnb hides the exact address until booking and gives the location to an accuracy of about 150 metres. It cannot look into bookings or revenue. It is not a regulatory tool: it can show where to look, not who is guilty. This is why we emphasise the presumption of innocence throughout.

What an authority could do and we cannot. Request data from Airbnb and Booking. That is the difference between our list and actual proceedings.

---

3. The state of the market in numbers

3.1 Overview

(measurement of September 1, 2026)¹

Districts affected: all 23. Identified operators affected: 59.

3.2 The type of non-compliance

The largest item is the non-existent identifier. This is the category where a good-faith explanation is hardest to find: mistyping happens, but not in nearly three thousand cases.

Most of the missing identifiers are on Booking. This suggests that the two platforms treat the field with differing strictness.

The penultimate row is a separate category: here the identifier is in order, but the operation itself is prohibited, because since 1 January 2026 no private or other accommodation may be let in Terézváros for even a single night. We include it here because it is equally operation without a permit, only for a different reason.

3.3 Breakdown by district

Two districts stand out. In Terézváros because of the ban (chapter 4 covers this), but in District V not: there, quite simply, every second listing is unlicensed.

3.4 Who operates these properties

One of the main arguments of those opposed to short-term letting is that it is the terrain of big investors. The district councils' own registers show otherwise. 15,062 permits are spread across 9,495 named providers.²

1 property2-34-1011-50Above 50

97.5 per cent of operators have at most three properties, and they provide 73.6 per cent of all properties. Every second property belongs to an operator who has exactly one. This is a market of families and one-person businesses, not of big investors.

One limitation must be stated: the aggregation groups by the provider name in the register and does not see ownership links. Actual concentration may therefore be higher than this, not lower.

Why does this matter for regulation? Because the burden and the benefit of a restriction are not symmetrical. Those who lose from a ban are several thousand small players with no connection to one another, no common representation and no lobbying power. The winner is a concentrated, organised industry. The peer-reviewed study of the New York ban documents this too: the hotel industry spent an order of magnitude more on political contributions than the platforms, especially in the period before the ban.³ The ownership background of the Hungarian hotel market is tracked by the civic database nerhotel.hu: it collects owners linked to the governing circle between 2010 and 2026, and lists 32 hotels in Budapest.⁴

The literature review describes the same mechanism: restriction "primarily redistributes surplus from consumers to the firms present in the market".⁵

3.5 The order of magnitude of the tax shortfall

According to AirDNA's estimate, the last twelve months' revenue of active Airbnb listings flagged as unlicensed is EUR 45.25 million, that is, roughly HUF 16.5 billion (HUF 364.64/EUR, National Bank of Hungary, 12 August 2026).⁶⁷

This is the measured base: every element of it traces back to data. It does not include the Booking side, VAT, the itemised flat-rate tax, building tax, or the 1,402 listings without classification.

The full order of magnitude

The measured base is deliberately narrow. If we also count those missing items for which we have enough data, the picture is considerably larger.

The Booking side, without double counting. We have no revenue data for Booking listings, but their number is measured, and the system's cross-platform matching tells us which Booking listing is the same home as an active Airbnb listing.

Of the unlicensed Booking listings, 2,276 have an invalid, missing or foreign identifier. The remaining 80 are in District VI with a valid NTAK number but operate despite the ban; they presumably pay tax, so they are left out of the shortfall estimate. The same on the Airbnb side is 169 listings; together the two make up the 249 Terézváros item.

Of the 2,276, 295 have a match with an active Airbnb listing, and these we do not count again. That leaves 1,981 stand-alone listings.

These are on average smaller than the Airbnb ones: 1.35 bedrooms and 2.93 places, against Airbnb's 1.63 bedrooms and 4.28 places. So we do not apply the Airbnb average to them, but the average of Airbnb's unlicensed one-bedroom listings, EUR 12,132.⁶

Itemised flat-rate tax. HUF 150,000 per habitable room per year where the number of guest nights exceeded 2 million; Budapest is such a place.⁸ The unlicensed Airbnb listings account for 4,662 bedrooms and the stand-alone Booking listings for 2,354, a total of 7,016.

Over three years that is roughly HUF 9 billion, over four about HUF 12 billion, on top of the fines.

What has to be stated about the extended estimate:

1. The Booking side is an estimate, not a measurement. The number is measured; the per-listing revenue is a value projected from the Airbnb data.
2. Airbnb's bedroom count is not the same as NAV's concept of a habitable room. The definition of a room differs between NAV, NTAK and some councils; that in itself is one item on the map of problems. The room count is therefore an approximation.
3. A private individual may elect the itemised flat-rate tax for at most three properties, and companies are taxed differently. The figure shows what the most common form of taxation would have yielded, not that the shortfall is exactly this.
4. Where the bedroom count was missing, we counted one. This biases downwards.
5. It still does not include VAT, building tax, fines, or the 1,402 listings without classification.

Internal consistency. Unlicensed Airbnb listings account for 32 per cent of the listing count and 29 per cent of the estimated revenue. The ratio holds: unlicensed listings on average earn somewhat less than legal ones (median EUR 13,051 against EUR 17,080). This also indicates that we are not dealing with a few large players but with a broad, scattered phenomenon.

---

3.6 Weight in the housing market: empty homes versus short-term rental

This question requires dwelling-level, not listing-level figures. In the measurement deduplicated to unique NTAK identifiers, the 14,602 dwelling-type listings map to 9,415 unique properties (on average 1.55 listings per dwelling); at dwelling level there are 10,703 units let short-term, of which 6,703 are compliant and about 4,000 unlicensed.⁹

That is 1.1 per cent of Budapest's 961,061 homes. According to the HCSO's 2022 census, 160,723 homes in the capital are unoccupied;¹⁰ according to the breakdown derived from measured and official sources, of these 95,320 stand genuinely empty and unused (including 3,698 council-owned homes).¹¹¹²¹³ In other words, there are nearly nine times as many genuinely empty homes as there are short-let ones.

Two comparisons for a sense of proportion:

• Offices. 13,000 homes operate as offices, surgeries or shops, nearly twice the 6,703 lawfully let short-term. The vacant modern office space (557,710 m²) is equivalent to about 8,400 homes: 65 per cent of the home offices would fit into the office buildings that are empty today.¹¹¹⁴
• Prices. According to the HCSO house price index, in Q4 2025 the annual increase was lowest in Budapest (21 per cent; county seats 24, smaller towns 23, villages 37), even though short-term supply is concentrated practically in the inner city of Budapest.¹⁵

The concentration must be stated: in Erzsébetváros 9.1 per cent of homes go to short-term letting (a third of Budapest's supply), in the Inner City 7.2; in eleven outer districts, however, it is one home in two thousand. In District VII short-term letting is a real factor, but even there the number of empty, non-short-let homes is double that of the short-let ones.

This chapter is not the dossier's main claim but a sense of proportion: the causes of the housing crisis and its reserves are not to be sought in this 1.1 per cent. Nor are our proposals about housing: they are about fair competition and tax.

---

4. Terézváros: what the total ban delivered

4.1 Background

In September 2024 Terézváros held a binding local referendum on banning Airbnb-type accommodation. The majority voted for the ban. On 31 October 2024 the council prohibited short-term letting by decree

1. with effect from 1 January, limiting the number of lettable nights to zero.¹⁶

The Government Office challenged the legislation; the Curia rejected the motion. In March 2026 a constitutional complaint was filed against the decree, and the Constitutional Court has not yet ruled.

4.2 What is left

(BPDB, September 1, 2026, seven months after entry into force)

After the ban, three-quarters of the accommodation still available in the district is unlicensed.

Those who followed the rules closed. Those who did not are still open. And since they pay no tourist tax, they now also have a tax advantage over the host in the neighbouring district who operates legally.

The Infojegyzet separately notes that "apartment operating companies were able to circumvent the Terézváros decree, for example by converting several adjacent flats into a guesthouse or hotel". In other words, the decree could be avoided by the larger, well-capitalised player, but not by the family letting one flat.

4.3 Guest nights

Source: Office of the National Assembly, Information Service for Members of Parliament, Infojegyzet 2026/6,

1. figure. Data source: HCSO Dissemination database.¹⁶ District VI,

January–March, thousand guest nights.

HotelsPrivate and other accommodation

Hotels grew by 22.7 thousand nights. 94.9 thousand were lost from private accommodation. Hotels absorbed 23.9 per cent of the loss.

This refutes the most common argument for the ban. It is not that the guest comes to the same place and merely sleeps somewhere else. Three-quarters of the demand simply vanished from the district.

The Infojegyzet publishes the figure but does not link it to the ban and does not draw this conclusion. The data belongs to Parliament; the interpretation is ours.

4.4 Tourist tax¹⁷

20252026

Actual shortfall: HUF 279.7 million in six months.

Measured against the trend it is larger still. The first half of 2025 grew by 19.6 per cent on 2024. Had that continued, about HUF 1,470 million would have come in during the first half of 2026. Against the actual HUF 949 million, that is roughly HUF 520 million of shortfall.

Important: this is the district's entire tourist tax, hotels included. The tax from private and other accommodation has effectively fallen to zero, that from hotels has grown, and the net result of the two is this minus 22.8 per cent.

4.5 What 72,200 lost guest nights take away

According to the HCSO's quarterly data, foreign visitors to Hungary on multi-day trips spend an average of HUF 32,600 a day (Q1 2026: 1,492 thousand trips, 4,496 thousand days spent, HUF 146,787 million of expenditure).¹⁸

Applied to the Terézváros loss:

72,200 lost guest nights × HUF 32,600 = roughly HUF 2.35 billion of visitor spending, in a single quarter, in a single district.

This is an order-of-magnitude estimate, and four things must be said about it. The HCSO figure is a national average across all foreign multi-day visitors, not Budapest city-break tourists. It also includes the accommodation charge, so it is total visitor spending, not the part on top of accommodation. A visitor day and a guest night in commercial accommodation are not the same concept. And the first quarter is the weakest season, so the annual loss is larger than this; we do not publish an annual figure, however, because we only have first-quarter guest-night data.

Where would this money land? Two peer-reviewed studies answer this, and they are stronger than a spending average because they measure a causal effect. In Madrid, fourteen additional Airbnb rooms in a census tract mean roughly one more restaurant or hospitality venue, and eleven new tourism-related jobs at district level; the authors interpret this explicitly as market expansion, not diversion.¹⁹ In New York, a one percentage point increase in Airbnb activity brings about a 1.7 per cent rise in restaurant employment in tracts that were previously not tourist destinations.²⁰

And it matters where that money is spent. A significant part of a hotel guest's spending stays inside the hotel: according to the HCSO, 23.7 per cent of Hungarian hotels' gross revenue is food and drink, and more than 40 per cent of revenue is not room revenue at all.²¹ That is food and drink not bought in the shops and hospitality venues of the neighbourhood.

For a short-term rental guest it is the other way round. There is a Hungarian peer-reviewed study on this, with a Budapest sample: of Airbnb guests' non-accommodation spending, 74.08 per cent goes on local goods and services, against 47.41 per cent for hotel guests.²² And according to a study from Granada, someone staying in a short-term rental (that is, not in a hotel but in a flat booked on Airbnb or a similar platform) spends 29 per cent more per day on food and drink, while their total daily spending is practically identical to a hotel guest's: the difference is in the composition, not the amount.²³

Two limitations must be stated. The Hungarian study measures a proportion, not an amount, and its sample is 103 people. The Granada one is 2018 data from a single city. So we are not claiming that a short-term rental guest spends more; we are claiming that a larger share of their spending stays with the small businesses of the neighbourhood.

This is exactly the mechanism the Hungarian Hospitality Employers' Association is measuring in Terézváros, only in reverse.

4.6 Hospitality and the related sectors

According to the Hungarian Hospitality Employers' Association's June 2026 statement, turnover at District VI restaurants, cafés and bars fell by an average of 30 per cent in the first half of the year.²⁴

The owner of a local restaurant: "Nearly a third of our turnover has gone, but the bills and the district taxes have not fallen by 30%. They expect us to earn the building tax and the local business tax just the same, while with their decree they drove away precisely the guests we lived on."

The association wrote to the mayor asking for a review of the economic effects of the restriction and for consideration of tax compensation.

Short-term letting is not a standalone sector. It provides work for cleaners, laundries, transfer services and maintenance staff, and brings custom to the shops nearby. When a district phases it out, these lose too. The ban therefore hit not one sector but several.

4.7 What the ban did not deliver

The purpose of the decree was to improve the housing situation. No 864 tenants moved into the place of the 864 listings still operating in the district. At dwelling level, short-term letting affects 1.1 per cent of Budapest's housing stock, while according to the HCSO's 2022 census 160,723 homes in the capital are unoccupied, of which 95,320 stand genuinely empty (3.6). The orders of magnitude do not meet.

---

5. International experience

5.1 Airbnb and hotels are not the same market

Our Terézváros measurement is telling in itself: hotels absorbed 23.9 per cent of the loss. That means 76 per cent of guests did not move to a hotel. There is now international, peer-reviewed backing for this too.

Farronato and Fradkin's 2022 study in the American Economic Review measures, with a structural model that also accounts for hotel capacity constraints and hotels' price response, what share of Airbnb guests would have booked a hotel had Airbnb not existed.²⁵

Verbatim: "The share of Airbnb travelers who would not, in fact, have booked a hotel room increases across all cities, from 49 percent in Austin and Portland to 70 percent in New York, all the way up to 87 percent during compression nights."

The 76 per cent in Terézváros falls exactly within that range, indeed in its upper half. Two independent measurements, in two countries, by two methods, with the same result.

Two further findings of the study bear directly on the Hungarian debate:

• In peak season the number of room nights sold by hotels is unchanged without Airbnb. At such times practically zero per cent of the displaced guests move to a hotel, because hotels are full. A "compression night" means that at least one hotel category has reached 95 per cent occupancy.
• Under a complete Airbnb ban, hotels' room nights sold would rise by a mere 1.4 per cent, and their revenue by 1.6 per cent.

From the other direction, the same is reinforced by Zervas, Proserpio and Byers' 2017 study in the Journal of Marketing Research.²⁶ In Austin, where Airbnb supply was largest, the effect on hotel revenue is 8–10 per cent. But the effect is concentrated on lower-priced hotels and those not serving business travellers; for the Upscale and Luxury segment it is small and not statistically significant. And the effect operates through price, not occupancy.

In Chicago, after short-term rental was regulated, "we do not find any significant increase in hotel revenues": the coefficients are indistinguishable from zero.²⁷

The literature review concludes that "structural estimates suggest that between one half and two thirds of bookings would not have resulted in a hotel stay absent the platform, and this share rises steeply in peak periods". The same review says of restrictions that they "benefit hotels substantially, but through higher prices rather than greater volume: regulation primarily redistributes surplus from consumers to the firms present in the market".⁵

5.2 New York: the largest-scale experiment

On 5 September 2023, with Local Law 18 (formally the Short-Term Rental Registration Law), New York effectively banned short-term letting: letting an entire home for less than 30 days is prohibited, the registered resident must be present, and there may be at most two guests.²⁸

Supply fell by more than 90 per cent. About 38,500 units disappeared; some 3,000 legal short-term rentals remained. In the outer boroughs, from 17,000 to 1,400.²⁹

Rents did not fall. Median rent in Manhattan was a record USD 4,700 in July 2025, with vacancy at 2.45 per cent, close to an all-time low. According to the available market data, rents grew faster in the neighbourhoods that previously had the most Airbnbs. A significant part of the withdrawn homes did not enter the classic long-term rental market either: owners typically switched to medium-term letting just over 30 days — the lower threshold of the ban in New York — or took the flat into their own use.³⁰

Hotel prices rose. There is a peer-reviewed study on this: Anastasi, Marsella, Melo, Stephenson and Wagner (2025), Short-term rental bans and the hotel industry: Evidence from New York city, European Journal of Political Economy, vol. 89.³ Hotels' average daily rate rose by USD 14–19 per night, and hotel industry revenue in the first 18 months after the ban by USD 2.1–2.9 billion. The effect on the number of room nights sold is small and imprecisely estimated: the additional revenue is almost entirely a price effect.

The same study documents that the hotel industry spent an order of magnitude more on political contributions than the platforms, especially in the period preceding the ban. This is not a conspiracy theory but one of the study's findings.

Restaurant turnover fell. According to a working paper by researchers at Emory and USC (Zhao and Shoshani, When Airbnb Leaves Town), restaurant spending fell by about 10 per cent relative to the matched control group, with a trough of 12 per cent. The decline was strongest at higher-priced restaurants and those serving a non-local clientele. Implied annual revenue loss: about USD 2.99 billion.³¹

It was not eased. The only substantive reform proposal (Int. 1107-2024) stalled at committee stage and died at the end of the session, on 31 December 2025.³²

Worth noting: short-term letting accounted for 1.4 per cent of New York's housing stock.³³ In Budapest, at dwelling level, the share is about 1.1 per cent (3.6). The two situations are comparable in order of magnitude.

5.3 Where rules were withdrawn or eased

Berlin, 2018. After the 2016 tightening, in March 2018 the state parliament adopted an easing amendment. Letting a main residence to tourists during the owner's absence is permitted as a general rule, and a secondary dwelling may be let for 90 days a year. In exchange, from 1 August 2018 displaying the registration number became mandatory.³⁴ This is precisely the logic of our proposal: identifiability instead of quantitative prohibition.

Amsterdam, 2023. In 2020 the city completely banned holiday letting in three inner-city neighbourhoods. In March 2021 the Amsterdam court declared it unlawful, and on 31 May 2023 the Raad van State upheld this: the housing act does not authorise such a ban. The city withdrew EUR 400,000 in fines.³⁵

Lisbon, December 2025. The earlier containment-zone system was replaced by a neighbourhood-based system driven by ratios.³⁶

Edinburgh, January 2025. A lower licence fee for home-sharers, and easier temporary exemption for the festival period.³⁷ Meanwhile rents rose by 13.9 per cent and hotel prices by 11.5 per cent.

Counter-examples, in fairness. Santa Monica's 2015 ordinance is in force, and the court ruled in the city's favour.³⁸ Barcelona is phasing out all of its roughly 10,000 licences by 2028, and in March 2025 the Spanish Constitutional Court rejected the owners' appeals.³⁹

5.4 What the research says about the effect on rents

The picture is mixed, but the order of magnitude is clear.

Where no effect could be shown:

• Santa Monica. Chaves-Fonseca (2024), International Journal of Housing Markets and Analysis, using the synthetic control method. The number of Airbnb listings fell by 60 per cent within two years, but the effect on rents was not significant, in any breakdown.⁴⁰
• Chicago. Jin, Wagman and Zhong (2024), NBER Working Paper 32537. Active listings fell by 16.4 per cent, but the average price, revenue and number of bookings per listing did not change significantly.²⁷

Where there was an effect:

• San Francisco. Bibler, Teltser et al. (2025), Real Estate Economics. The 2017 registration requirement reduced supply by 20–27 per cent, and long-term house prices fell as well.⁴¹
• Irvine, California. A 3 per cent fall in contracted rents within about two years.

The order of magnitude, from two measurements. According to the peer-reviewed study by Barron, Kung and Proserpio (Marketing Science, 2021), a 1 per cent increase in the number of listings raises rents by 0.018 per cent and house prices by 0.026 per cent.⁴² According to Calder-Wang's structural model for New York, Airbnb took 0.68 per cent of the rental stock, and the total rent effect is 0.71 per cent, USD 125 a year for the median tenant; this is a working paper, under review at the American Economic Review.⁴³

The lesson. The effect is typically between zero and a few per cent, and never approaches the order of magnitude of the housing crisis. What is noteworthy, however: in San Francisco it was not a ban but a registration requirement. That is, precisely what we propose. Where the intervention targeted identifiability, there was an effect. Where it targeted quantity, there was none.

5.5 Tax collection by the platform: the uniform tax base is the key

This is the most important lesson of international experience for our proposal 4.

France. Airbnb began collecting the tourist tax in two cities in 2015, and by 2017 was up to fifty, each under a separate agreement. On 1 July 2018, however, it extended in one step to about 23,000 municipalities.⁴⁴ Two things made this possible:

1. Article 44 of the amended 2017 Finance Act made it mandatory from 1 January 2019 that the tax on unclassified accommodation be set uniformly at 1–5 per cent of the accommodation charge, proportionally, instead of the previous arbitrary fixed amounts set municipality by municipality.⁴⁵
2. The state operates a single, national, machine-readable tariff register (DELTA). Municipalities enter their tariffs by 15 September, and the state publishes them in October as open data, in XML format.

The statutory obligation entered into force on 1 January 2019 (Article 162 of the 2019 Finance Act, which rewrote Article L. 2333-34 of the Code général des collectivités territoriales). If the platform fails to comply, it is itself liable for paying the tax.⁴⁶

The single strongest data point: from 2018 to 2019, across an unchanged set of municipalities, the tax collected rose from EUR 24 million to EUR 58 million. That is the additional yield of mandatory platform collection on its own.

In 2025 one third of the total went to municipalities with fewer than 4,500 inhabitants, and more than 900 municipalities received such revenue for the first time. In other words, the mechanism does not favour only large cities.

These are figures published by Airbnb, and the absolute growth partly reflects the expansion of the platform's own business. The 2018–2019 jump, however, is a clean signal, because the set of municipalities did not change.

Italy. The 2024 budget act made collection mandatory from 1 January 2024. In Airbnb's own words, the tool "consolidates more than 1,000 different tourist tax rules into a single digital solution".⁴⁹ Result: about EUR 100 million in 2024, more than EUR 110 million in 2025.⁵⁰

Where there is no uniform rule, there is no collection. Germany has no national tourist tax act: every municipality works with its own decree, its own rate, its own exemptions and its own deadline. Airbnb therefore collects in four German cities: Dresden, Dortmund, Frankfurt and Wiesbaden. Berlin, Hamburg, Munich and Cologne are not among them, even though these are the largest markets.⁵¹⁵² Switzerland is in the same position, concluding agreements canton by canton.⁵³ In the United States, where there is a uniform rule at state level, collection is automatic; jurisdictions that create their own, differing rules — Chicago, for example — drop out.⁵⁴

Bratislava: the closest analogy. Bratislava has 17 boroughs. Yet the tourist tax is set by a single city decree, with two bands: €3.50 in the Old Town and €3.00 in the other boroughs, per person per night. Airbnb has collected it automatically since 1 July 2021.⁵⁵ It was the first such agreement in the Visegrád Four.⁵⁶

From this follows the most important detail: it is not the rate that needs to be unified, but the tax base and the filing regime. The districts may keep their own band, as long as the legal framework and the register are one.

---

6. Why the authorities do not act: a documented case

The following chronology is our own case; the complete correspondence is available.⁵⁷

In May 2026 it emerged that four listings by strangers were running under a client's NTAK number, deleted in January 2025 — one on Airbnb and three on Booking. (The Airbnb one later turned out to be a typing error, not an abuse; the three Booking listings did not.) We approached four authorities with the same questions.

On 10 June we handed the four listings to the clerk's office with links, identifiers, addresses and screenshots. The reply of 17 June was a single sentence. Not a word about whether proceedings had been opened, or whether the advertisers had been able to swap the false number for a real one without consequences. The next day we asked formally, in a submission through the Company Gateway, whether anyone had been penalised. We have had no substantive answer since.

NTAK's detailed opinion of 25 June states that the clerk "may impose an administrative fine and order the temporary — or in serious cases even immediate — closure of the accommodation", and that "the legislation does not prescribe a separate form or mandatory content for reports of this kind". The same letter also states the system's fundamental problem: "the clerk has no power to have listings removed directly from online platforms".

On 24 July we reported the two Booking listings on the platform's own form. Six days later both were removed: "the property you reported is in breach of our Terms and Conditions and has been removed from Booking.com".

Three months, five authorities, and to this day we do not know whether proceedings were opened. In the end the listings were removed by the platform, in six days.

6.1 What we learn from this

None of the offices made a mistake. Each did exactly what the rules empower it to do. The trouble is that the powers do not meet anywhere.

Whoever can remove has no power to penalise. The platform acts fast under its own terms of business, but cannot collect tax and cannot impose fines.

Whoever can penalise has no means to remove. The district clerk is the only authority, but cannot have the listing taken down, and does not know the advertiser's identity, because Airbnb hides the address.

And it is not worth their while either. A council can document an irregularity through a test purchase. That establishes the tourist tax on a single booking, a few thousand forints, and it cannot levy tax retrospectively. The maximum fine is HUF 200,000 for private accommodation and HUF 400,000 for other accommodation.⁵⁸ The cost in working hours of an inspection is often more than that. Inspection is today an economically loss-making activity.

The tax authority and the council do not cooperate. If a council reports an unlicensed property to NAV, it receives no feedback on whether an inspection or a finding took place. Yet both have lost revenue from the same case.

No single district clerk is a large enough counterpart for a platform. Terézváros tried. The talks stalled because the council asked for a very broad data disclosure, which Airbnb refused, and after that there was no one to narrow the request and reach agreement.

---

7. The seven proposals

0. The order: unlicensed hosts first, restrictions afterwards

What we propose. Let policy state that before any quantitative restriction is introduced, unlawful operation must be surveyed and wound up, and the problem then measured again.

Why. As long as a third of the supply is invisible, every percentage cap hits the wrong half. Both Terézváros and New York show this. It is conceivable that most of the problems attributed to short-term letting are caused by the non-compliant minority, and that once they are dealt with, no problem remains that would have to be handled by a ban.

Its cost. Zero. This is a decision about sequence, not a demand for resources.

1. One Budapest enforcement point instead of 23 clerks

What we propose. A unit of two or three people holding the data, the platform relationship and the initiation of proceedings in one place. It does not take away the districts' powers; it does for them what they have no capacity to do separately.

Why. Today one or two people in each of 23 clerks' offices deal with the question, and none of them is a large enough counterpart for Airbnb or Booking. A capital city or a national body is.

Its cost. The salaries of two or three people and a data system. Against the tax shortfall in section 3.4, this is negligible.

2. Retrospective data reporting from the platforms

What we propose. Let the enforcement point request from Airbnb and Booking the booking and revenue data of identified unlicensed properties for the past three to four years. In matters of the tourist tax the council counts as a tax authority, so it has a legal basis to request data.

Why. This is what reverses the economics of enforcement. A test purchase brings in a few thousand forints. On the basis of three to four years of booking data, the unpaid tourist tax, tourism development contribution, VAT and income tax add up, with the fine on top. From that point on, enforcement is self-financing.

This requires two small legal steps: retrospective tax assessment on the basis of platform data must be made possible, and the fine must rise to a deterrent level.

Its cost. None. It generates revenue.

3. Platform-side filtering: no advertising without a valid number

What we propose. Airbnb and Booking should not allow a listing to go live without a valid, verified registration number, and should remove listings that are not validated.

Why. Today neither platform verifies the number given. That is how 2,764 non-existent and 1,472 missing identifiers can occur.

The legal basis already exists. EU Regulation 2024/1028 has been applicable since 20 May 2026.⁵⁹ It requires platforms to verify the accuracy of the data uploaded and to report data monthly per property (registration number, exact address, listing URL), while the member state must operate a single digital entry point from which the removal of non-compliant listings can also be initiated and from which a fine can be imposed on the platform as well.

The open question: where does Hungary stand on setting up the digital entry point? Without it the regulation cannot take effect, and Hungary forfeits, through its own omission, the one instrument that would solve the problem at system level.

Its cost. Setting up the entry point. The regulation makes it mandatory.

4. A uniform Budapest tourist tax base

What we propose. A uniform definition of the tax base and filing regime across all 23 districts, plus a central, machine-readable tariff register. The rate may continue to differ by district.

Why. Today there are districts where the tax is 4 per cent of the accommodation charge, and others where it is a fixed amount per guest night. Because of this the platform cannot technically collect it: 23 different rules cannot be built into one booking flow.

If it were uniform, Airbnb and Booking could collect and remit the tax directly. This has two consequences:

• Evading the tourist tax becomes technically impossible, because the money comes off at the moment of booking and does not depend on the host's return.
• The honest host's administration is reduced, with one monthly return less to file.

The French, Italian, German, Swiss and Bratislava experience is in section 5.5.

Its cost. Legislation. In exchange, collection efficiency jumps — see the French figures.

5. Uniform Budapest-wide regulation of licensing and inspection

What we propose. A Budapest framework rule, with room for districts to manoeuvre, covering licensing, inspection and registration.

Why. Today 23 districts work with 23 different sets of conditions. On one side of the street a permit is easy to obtain, on the other difficult or impossible. The content and interfaces of the registers differ too. This creates legal uncertainty and makes cross-checking impossible.

Its cost. Legislation.

6. Handing over BPDB free of charge

What we propose. We hand over the system, free of charge, with access for the authorities.

Why. It is built and running. It shows on a map what is wrong with each listing, broken down by district and by operator, and produces an exportable list. Nothing needs to be developed, nothing procured, and it costs nothing.

Background. We offered it to two districts. One turned it down because it has a live contract with an outside company. A freedom-of-information request revealed that it pays HUF 381,000 gross every six months for this⁶⁰, while 812 unlicensed listings are running in the district. The other district turned it down because it does not negotiate with market players.

---

8. Implementation timeline

What can be done immediately, without amending legislation:

What can be done in the short term, with legislative amendment:

What can be done in the medium term:

The last row is the point. We are not saying that quantitative restriction is never needed. We are saying that first we must know how big the real problem is.

---

9. Risks and counter-arguments

"GuestGuru is speaking out of self-interest." Yes, and we say so openly. As a service provider we live off lawful operation, and the non-compliant competitor harms us too. That does not make the numbers any less checkable, and the correspondence with the authorities is available verbatim. If our proposals are adopted, we too will operate in a stricter environment.

"This is vigilante policing." It is not. We do not release names, we do not call anyone, and we do not denounce individual operators in public. We are offering a measurement tool to the body whose job this is by law.

"BPDB is not flawless." It is not. We estimate coverage and classification accuracy at about 95 per cent. Some are flagged wrongly, for example because they mistyped the identifier. That is also why it is not evidence: it is a starting point for a regulatory investigation. The presumption of innocence applies to everyone concerned, and that is why we also do not count the 1,402 listings without classification among the unlicensed.

"If we clean up the market, the housing crisis will remain." Probably yes. We do not promise otherwise. According to international research, the effect of restricting short-term letting on rents is between zero and a few per cent. That is precisely why we propose not to expect the housing solution from this. In Budapest 160,723 homes are unoccupied, of which 95,320 stand genuinely empty; short-term letting is 1.1 per cent of the housing stock (3.6). The orders of magnitude do not meet.

"The ban does at least reduce nuisance in residential buildings." In Terézváros 864 listings are running today. If the source of the nuisance is disproportionately the non-compliant operators, then the ban backfired: the responsible operator left and the irresponsible one stayed. We have not measured this and do not state it as fact. But it is the risk that comes with the current policy.

What our proposal does not solve either. Some of the non-compliant operators will switch to long-term letting after enforcement, or simply stop. The resulting increase in tax revenue is one-off and limited. The system-level benefit lies not in the one-off collection but in the fact that afterwards the market will be measurable and manageable.

---

10. Further, smaller points for improvement

These are not part of the main package of proposals, but each would reduce the burden on compliant operators and each would improve data quality.

NTAK could compile the tourist tax and tourism contribution returns. Hosts send daily summaries to NTAK. The same data then has to be submitted separately, in a return, to the council and to NAV. Unnecessary duplication and a source of error.

The NTAK identifier is not in itself a unique identifier. One dwelling may contain three separate units, with separate entrances and separate listings, lawfully under the same identifier. This also complicates measurement. It would be more logical for separately marketed units to receive separate identifiers or markings.

The listing URL is missing from the registers. If the council or NTAK register contained the link to the listing, it would be possible to say immediately, from any identifier or URL, whether a property is legal. Today this matching is the most costly part of detection.

The line between short-term and long-term letting is not clear. The legislation taxes the two differently, but there is no precise definition of what makes a letting short-term. We asked the councils: they said they can only decide it case by case. This is legal uncertainty.

The base of the tourist tax is interpreted differently by district. In some districts the cleaning fee is included, in others not. Proposal 4 would settle this too.

The council inspection every six years is unnecessary, because the classification has to be carried out every three years anyway.

The itemised flat-rate tax is tied to the number of rooms, which does not reflect a home's revenue-generating capacity. It would be fairer to tie it to capacity or floor area.

---

11. Methodology, sources, limitations

Data sources

Limitations that must be stated

1. A listing is not a dwelling. One home may be advertised on both platforms, and one home may contain several units. We estimate that the 15,825 listings correspond to 10,000–12,000 unique units. Every use of the word "listing" should be read this way.
2. BPDB is about 95 per cent complete. It does not contain every listing, and the classification is not flawless either.
3. AirDNA estimates, it does not measure. The error of the estimate is unknown.
4. The tax shortfall is a lower-bound estimate. See the list in section 3.4 of what is not included.
5. The Infojegyzet does not link the decline to the ban. The figure belongs to Parliament; the interpretation is ours.
6. The New York rent data does not come from a peer-reviewed study but from a press analysis based on market data. The hotel price data, however, comes from a peer-reviewed study.
7. We have not measured what share of complaints in residential buildings can be linked to non-compliant properties. This is our professional conviction, not a measurement result.

Who is writing this

GuestGuru Kft. manages 180 homes in Budapest and six in Malta. We have Airbnb and Booking account contacts, we are members of Hungarian professional bodies, and we maintain a free knowledge base for hosts. In this matter our partner is the Hungarian Apartment Letting Association.

We are not an authority and we do not want to play volunteer police. We are defending our own market. Our interest goes only this far: that operating lawfully should not be a competitive disadvantage, and that regulation should not punish compliant accommodation instead of the non-compliant.

GuestGuru Kft. · Révay utca 6. fszt. 7, 1065 Budapest · hello@guest.guru

Sources

Links were checked on 13 August 2026. The academic publishers' sites (ScienceDirect, Wiley, Emerald) may require a subscription for the full text; the citation and the DOI identify the study without them.

1. BPDB (Budapest Database), GuestGuru Kft.'s own market database. A merge of the district councils' accommodation registers, the NTAK register and listings on Airbnb and Booking.com. Queried on 12 August 2026.↩
2. The public accommodation registers of the Budapest district councils, loaded into BPDB. 12,445 permits, assigned to 8,081 named providers. Queried on 13 August 2026.An aggregation based on provider names. It groups by identical names, so it cannot see ownership links: actual concentration may be higher than this, not lower.↩
3. Anastasi, S. C.; Marsella, A.; Melo, V.; Stephenson, E. F.; Wagner, G. A. (2025): Short-term rental bans and the hotel industry: Evidence from New York city. European Journal of Political Economy, vol. 89. Article ID: PII S0176-2680(25)00085-0. https://www.sciencedirect.com/science/article/abs/pii/S0176268025000850↩
4. nerhotel.hu, "Kinél cseng a kassza?" [Whose till is ringing?]. A civic database of accommodation and hospitality venues attributed to owners linked to the governing circle, with ownership links citing K-Monitor's public database. The database holds 455 entries, of which 149 are in Budapest and, within those, 32 are hotels. Queried on 13 August 2026. https://www.nerhotel.hu/A database built by a civic organisation, not official statistics. The ownership links are journalistic and public-data identifications, not official findings. It should be cited accordingly.↩
5. Alberto Hidalgo – Francisco J. Velázquez: The economic impacts of short-term rentals and regulations: A literature review. FEDEA, Documento de Trabajo 2026/02, February 2026. https://documentos.fedea.net/pubs/dt/2026/dt2026-02.pdfA working paper, not peer-reviewed. A literature review, not an independent measurement.↩
6. AirDNA estimated last-twelve-months revenue (revenue_ltm) for the active Airbnb listings flagged as unlicensed in BPDB. Queried on 12 August 2026.AirDNA estimates rather than measures; the error of the estimate is unknown.↩
7. National Bank of Hungary official exchange rate, 12 August 2026: HUF 364.64/EUR. https://www.mnb.hu/arfolyamok↩
8. Act CXVII of 1995 on Personal Income Tax. From 1 January 2025 the itemised flat-rate tax for private individuals providing paying-guest accommodation is HUF 150,000 per habitable room per year in municipalities where the number of guest nights exceeded 2 million in the second year preceding the tax year. Budapest is such a municipality. https://njt.hu/jogszabaly/1995-117-00-00 https://nav.gov.hu/ado/szja/A_fizetovendeglatokat_erinto_valtozasokSection 57/A(4c) of the Act obliges the tax authority (NAV) to publish the list of affected municipalities by 31 January each year. In 2025 Budapest is the only entry on that list. A private individual may elect the itemised flat-rate tax for at most three properties; companies are taxed differently. The definition of a "habitable room" differs between NAV, NTAK and some district councils.↩
9. BPDB, measurement deduplicated to unique NTAK identifiers, August 2026. The 14,602 dwelling-type Airbnb and Booking listings map to 9,415 unique properties (on average 1.55 listings per dwelling); at dwelling level there are 10,703 units let short-term, of which 6,703 are compliant and about 4,000 unlicensed (39%).The difference between the listing-level numbers (15,825 active listings, 5,374 unlicensed, 34%) and the dwelling-level ones is deduplication: the same dwelling may advertise on several platforms. The two levels must not be mixed.↩
10. HCSO 2022 census database, table WBL018, HU11 (Budapest): 961,061 dwellings, of which 800,338 occupied and 160,723 unoccupied (16.7%). Queryable without authentication. https://nepszamlalas2022.ksh.hu/adatbazis/The figure of 170,000 circulating in the press is the HCSO's 2023 preliminary release; the final database gives 160,723. Nationally the same correction went from 599,000 to 571,997.↩
11. HCSO 2016 microcensus, volume 7 (Housing conditions), table 3.3.2. Unoccupied dwellings in Budapest by use: 78,973 standing empty, 15,418 seasonally or secondarily occupied, 13,025 used for other purposes (as an office, surgery or shop). https://www.ksh.hu/mikrocenzus2016/docs/tablak/07/07_3_3.xlsThis is the only official survey of the use of unoccupied dwellings; the 2022 census no longer publishes this breakdown, so we carry the measured level forward.↩
12. Átlátszó: freedom-of-information request to all 23 Budapest district councils, 2020: 3,698 empty council-owned homes out of 38,114 (9.7%). https://atlatszo.hu/kozpenz/2021/01/21/az-onkormanyzati-lakasok-kozel-tiz-szazaleka-uresen-all-a-fovarosban-a-legtobb-a-8-keruletben/↩
13. GuestGuru: Budapest's empty homes. The full derivation of the housing-stock breakdown, its methodology and downloadable charts. /feketezok/ures-lakasok↩
14. Budapest Research Forum, Q4 2025: 4,461,680 m² of modern Budapest office stock, 12.5% vacancy (557,710 m² of vacant office space). https://www.portfolio.hu/ingatlan/20260121/meglepo-adat-erkezett-a-budapesti-irodapiacrol-csokkent-az-uresedes-812538↩
15. HCSO: Housing market prices, house price index, Q4 2025. Annual increase: Budapest 21, county seats 24, smaller towns 23, villages 37 per cent. https://www.ksh.hu/s/kiadvanyok/lakaspiaci-arak-lakasarindex-2025-iv-negyedev/index.html↩
16. Csorba György: Rövid távú szálláskiadás 2 [Short-term rental 2]. Infojegyzet 2026/6, Office of the National Assembly, Information Service for Members of Parliament, 1 June 2026. Data source for Figure 2: HCSO Dissemination database, GB2012. https://www.parlament.hu/infoszolgThe Infojegyzet publishes the figure but does not link it to the Terézváros ban, and does not draw this conclusion from it. The data belongs to Parliament; the interpretation is ours.↩
17. Tourist tax and accommodation revenue series of Budapest District VI (Terézváros), updated on 29 July 2026.↩
18. HCSO STADAT 27.2.1.2: Number of foreign trips to Hungary and the related expenditure by length of stay, quarterly. Q1 2026, multi-day trips: 1,492 thousand trips, 4,496 thousand days spent, HUF 146,787 million of expenditure, i.e. HUF 32,600 per day. Updated on 5 June 2026. https://www.ksh.hu/stadat_files/tur/hu/tur0043.htmlA national average across all foreign multi-day visitors, and it includes accommodation charges. Q1 is the weakest season. A visitor day and a guest night in commercial accommodation are not the same concept, so the value derived from this is an order-of-magnitude estimate.↩
19. Alberto Hidalgo – Massimo Riccaboni – Francisco J. Velázquez: The effect of short-term rentals on local consumption amenities: Evidence from Madrid. Journal of Regional Science, 64(3): 621-648, 2024. DOI: 10.1111/jors.12685. https://doi.org/10.1111/jors.12685↩
20. Mohammed Alyakoob – Mohammad S. Rahman: Shared Prosperity (or Lack Thereof) in the Sharing Economy. Information Systems Research, 33(2): 638-658, 2022. DOI: 10.1287/isre.2021.1076. https://doi.org/10.1287/isre.2021.1076↩
21. HCSO STADAT 27.8.1.9: Gross revenue of commercial accommodation establishments by type. Hotels, 2019: accommodation charges 291,852, food and drink 117,583, other 86,029, total 495,464 million HUF. Food and drink is 23.7 per cent. https://www.ksh.hu/stadat_files/tur/hu/tur0023.htmlAn archived table covering 2001–2021, no longer updated. We use 2019 because the 2020–2021 data are distorted by the pandemic; the ratio, however, is stable, at 23.5 per cent in 2021 as well.↩
22. Karimov, A. – Kamann, D-J. F. – Gyurácz-Németh, P.: Local spending patterns of tourists in Greater Budapest and the Lake Balaton tourism regions. An exploratory study on the non-accommodation budget across Airbnb and hotel guests. Turizmus Bulletin, vol. XXV, no. 4 (2025), pp. 4–13. DOI: 10.14267/TURBULL.2025v25n4.1. Student's t-test: t = −6.775, df = 101, p < 0.001. https://doi.org/10.14267/TURBULL.2025v25n4.1The study measures a PROPORTION, not an amount: what share of non-accommodation spending goes on local goods and services. The authors themselves note that a smaller share of a larger budget may still be more in absolute terms. The sample is 103 people; it is exploratory research.↩
23. Guaita Martínez, J. M. – Martín Martín, J. M. – Salinas Fernández, J. A. – Ribeiro Soriano, D.: Tourist accommodation, consumption and platforms. International Journal of Consumer Studies, 47(3): 1011-1022, 2023. DOI: 10.1111/ijcs.12881. Granada, 1,343 questionnaires. https://doi.org/10.1111/ijcs.12881A single city, 2018 data. The authors themselves flag the risk of endogeneity: someone who would stay longer and spend more variously is more likely to choose platform accommodation in the first place.↩
24. Eltűntek a turisták, bajban vannak a terézvárosi éttermek [The tourists are gone, Terézváros restaurants are in trouble]. Turizmus.com, 24 June 2026, based on a statement by the Hungarian Hospitality Employers' Association. https://turizmus.com/cikk/vendeglatas/terezvaros-ettermek-fprgalomcsokkenes-airbnb-tiltas-mvi-eltuntek-a-turistak↩
25. Chiara Farronato – Andrey Fradkin: The Welfare Effects of Peer Entry: The Case of Airbnb and the Accommodation Industry. American Economic Review, 112(6): 1782-1817, 2022. DOI: 10.1257/aer.20180260. https://doi.org/10.1257/aer.20180260 https://andreyfradkin.com/assets/airbnb_welfare_paper.pdf↩
26. Georgios Zervas – Davide Proserpio – John W. Byers: The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry. Journal of Marketing Research, 54(5): 687-705, 2017. DOI: 10.1509/jmr.15.0204. https://doi.org/10.1509/jmr.15.0204The earlier 2015 working-paper version reported a 13% effect in Austin; the published study reports 8–10%. We always cite the published value.↩
27. Jin, G. Z.; Wagman, L.; Zhong, M. (2024): The Effects of Short-Term Rental Regulation: Insights from Chicago. NBER Working Paper 32537. https://www.nber.org/papers/w32537↩
28. Local Law 18 of 2022, New York City (Short-Term Rental Registration Law). Enforcement began on 5 September 2023. The law is applied by the city's Office of Special Enforcement. https://www.nyc.gov/site/specialenforcement/index.page https://en.wikipedia.org/wiki/Local_Law_18_of_2022The second link is a summary article, not a primary source. The official text of the law is available in the New York City Council's legislative records.↩
29. New York City short-term rental market after Local Law 18. Hospitality Net, 2025. https://www.hospitalitynet.org/news/4124666.html↩
30. NYC's Airbnb ban failed to lower rents. AOL / The Wall Street Journal analysis based on CoStar and Miller Samuel data, September 2025. https://www.aol.com/news/nyc-airbnb-ban-failed-lower-212121367.htmlA press analysis based on market data, not a peer-reviewed study. We found no peer-reviewed causal study of the effect on rents.↩
31. Kaihang Zhao – Tal Shoshani – Davide Proserpio: How Short-Term Rental Regulations Reshape Urban Spending: Evidence from New York City's Restaurant Sector. SSRN, 6 January 2026. Method: propensity score matching and difference-in-differences, SafeGraph transaction data, 3,220 restaurants, July 2022 – July 2024. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6065366 https://www.realab.blog/p/when-airbnb-leaves-town-how-new-yorksA working paper, not peer-reviewed. The second link is a summary produced with the authors' involvement; the detailed methodological figures come from there.↩
32. Int. 1107-2024, New York City Council. The proposal stalled at committee stage; its status is "Filed (End of Session)", 31 December 2025. https://legistar.council.nyc.gov/LegislationDetail.aspx?ID=7019728↩
33. What does banning short-term rentals really accomplish? Boston University, Insights. Short-term letting accounted for 1.4 per cent of New York's housing stock. https://insights.bu.edu/what-does-banning-short-term-rentals-really-accomplish/↩
34. Änderung des Zweckentfremdungsverbot-Gesetzes (ZwVbG). GÖRG, 11 April 2018. The amendment entered into force on 20 April 2018; displaying the registration number has been mandatory since 1 August 2018. https://www.goerg.de/de/aktuelles/veroeffentlichungen/11-04-2018/aenderung-des-zweckentfremdungsverbot-gesetzes-zwvbg↩
35. Raad van State, judgment in cases 202102768/1/A3 and 202102675/1/A3, 31 May 2023. The housing act did not authorise the blanket ban imposed on three inner-city neighbourhoods. https://www.raadvanstate.nl/@137502/202102768-1-a3-202102675-1-a3-en/↩
36. Changes to the Lisbon Municipal Regulation on Local Lodging. PLMJ, December 2025. The amendment entered into force on 6 December 2025. https://www.plmj.com/en/knowledge/informative-notes/Changes-to-the-Lisbon-Municipal-Regulation-on-Local-Lodging/34253/↩
37. Councillors agree changes to Edinburgh's short-term lets licensing policy. City of Edinburgh Council, January 2025. https://www.edinburgh.gov.uk/news/article/14148/councillors-agree-changes-to-edinburgh-s-short-term-lets-licensing-policy↩
38. Rosenblatt v. City of Santa Monica, U.S. Court of Appeals for the Ninth Circuit, 2019; and the December 2019 settlement between the city and Airbnb. https://www.santamonica.gov/press/2019/12/10/settlement-with-airbnb-guarantees-compliance-with-home-sharing-ordinance↩
39. Barcelona mayor welcomes Constitutional Court ruling on tourist apartment restrictions. Catalan News, March 2025. The aim is to phase out all of the roughly 10,000 licences by 2028. https://www.catalannews.com/society-science/item/barcelona-mayor-welcomes-constitutional-court-ruling-on-tourist-apartment-restrictions↩
40. Chaves-Fonseca, C. (2024): Short-term rentals and residential rents: evidence from a regulation in Santa Monica. International Journal of Housing Markets and Analysis. Using synthetic control and synthetic difference-in-differences. DOI: 10.1108/IJHMA-01-2024-0001. https://www.emerald.com/insight/content/doi/10.1108/IJHMA-01-2024-0001/full/html↩
41. Bibler, A.; Teltser, K. et al. (2025): the effect of the San Francisco registration requirement. Real Estate Economics. DOI: 10.1111/1540-6229.12537. https://onlinelibrary.wiley.com/doi/10.1111/1540-6229.12537↩
42. Kyle Barron – Edward Kung – Davide Proserpio: The Effect of Home-Sharing on House Prices and Rents: Evidence from Airbnb. Marketing Science, 40(1): 23-47, 2021. DOI: 10.1287/mksc.2020.1227. In the median US zip code a 1 per cent increase in the number of listings raises rents by 0.018 per cent and house prices by 0.026 per cent. https://doi.org/10.1287/mksc.2020.1227↩
43. Sophie Calder-Wang: The Distributional Impact of the Sharing Economy on the Housing Market. Airbnb took 0.68 per cent of New York's rental stock; if every such home returned to the long-term market, rents would change by 0.71 per cent. The median tenant's loss is USD 125 a year. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3908062A working paper under review at the American Economic Review; not a peer-reviewed publication, and it should be cited as such.↩
44. Le 1er juillet, Airbnb va généraliser la collecte de la taxe de séjour dans les 23 000 communes. Banque des Territoires, June 2018. https://www.banquedesterritoires.fr/le-1er-juillet-airbnb-va-generaliser-la-collecte-de-la-taxe-de-sejour-dans-les-23000-communes↩
45. Code général des collectivités territoriales, Article L. 2333-34, as amended by Article 162 of the 2019 Finance Act; the proportional rate for unclassified accommodation was introduced by Article 44 of the amended 2017 Finance Act. See also the French Senate's written answer of 2019. https://www.senat.fr/questions/base/2019/qSEQ190510413.html↩
46. Taxe de séjour: the central register of municipal tariffs, published as open data (DELTA), Direction générale des Finances publiques. https://taxesejour.impots.gouv.fr/FR/↩
47. Airbnb remits €58 million in tourist tax to French municipalities for 2019. Airbnb Newsroom, December 2019. https://news.airbnb.com/airbnb-remits-e58-million-in-tourist-tax-to-french-municipalities-for-2019/A figure published by Airbnb. The 2018–2019 jump is a clean signal because the set of municipalities did not change in the meantime.↩
48. Airbnb: ces villes qui ont le plus profité de la taxe de séjour reversée par la plateforme. Boursorama, 2026. https://www.boursorama.com/immobilier/actualites/airbnb-ces-villes-qui-ont-le-plus-profite-de-la-taxe-de-sejour-reversee-par-la-plateforme-4951a999cb623356222fba10c9978175Data from Airbnb sources in a secondary press report.↩
49. Automated tax collection tool launches in Italy. Airbnb Newsroom. The tool "consolidates more than 1,000 different tourist tax rules into a single digital solution". https://news.airbnb.com/automated-tax-collection-tool-launches-in-italy↩
50. Airbnb, imposta di soggiorno supera i 110 milioni in Italia. ItaliaOggi, 2026. https://www.italiaoggi.it/diritto-e-fisco/airbnb-imposta-di-soggiorno-supera-i-110-milioni-in-italia-dq6dys1u↩
51. In what areas is occupancy tax collection and remittance by Airbnb available? Germany. Airbnb help centre, queried on 12 August 2026. The cities listed: Dresden, Dortmund, Frankfurt am Main, Wiesbaden. https://www.airbnb.com/help/article/2285↩
52. Tourist tax in Germany. Trippz, 2026. Germany has no national tourist tax act; every municipality works with its own decree, its own rate and its own deadline. https://trippz.com/tourist-tax/germany↩
53. Airbnb signs new tax collaboration in Switzerland. Airbnb Newsroom. Switzerland has no national tourist tax; collection depends on agreements concluded canton by canton. https://news.airbnb.com/airbnb-signs-new-tax-collaboration-in-switzerland/↩
54. More states require short-term rental marketplaces like Airbnb and Vrbo to collect lodging taxes. Avalara MyLodgeTax, November 2025. Where a uniform state rule applies, collection is automatic; "home rule" municipalities that set their own rules drop out. https://www.avalara.com/mylodgetax/en/blog/2025/11/more-states-require-short-term-rental-marketplaces-like-airbnb-and-vrbo-to-collect-lodging-taxes.html↩
55. City of Bratislava signs agreement on automated collection of taxes. Airbnb Newsroom. In force from 1 July 2021; this was the first such agreement in the Visegrád Four. https://news.airbnb.com/city-of-bratislava-signs-agreement-on-automated-collection-of-taxes↩
56. Tourist tax. Bratislava.sk, queried on 12 August 2026. A single city decree with two bands: €3.50 in the Old Town and €3.00 in the other boroughs, per person per night. https://bratislava.sk/en/city-of-bratislava/taxes-and-levies/tourist-tax↩
57. Correspondence between GuestGuru Kft. and the authorities, between 13 May and 30 July 2026. The complete verbatim material is available on request.↩
58. Act CLXIV of 2005 on Trade, and Government Decree 239/2009 (X. 20.) on the detailed conditions for pursuing accommodation service activities. https://njt.hu↩
59. Regulation (EU) 2024/1028 of the European Parliament and of the Council of 11 April 2024 on data collection and data sharing relating to short-term accommodation rental services. Applicable from 20 May 2026. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1028↩
60. Freedom-of-information request to the Józsefváros council, summer 2026.↩