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Regulating the sharing economy: The effects of day caps on short- and long-term rental markets and stakeholder outcomes
Open accessAbstract
Home sharing platforms have experienced a rapid growth over the last decade. Following negative publicity, many cities have started regulating the short-term rental market. Regulations often involve a cap on the number of days a property can be rented out on a short-term basis. We draw on rich data for short-term rentals on Airbnb and for the long-term rental market to examine the impact of short-term rental regulations with a day cap on various stakeholders: hosts, guests, the platform provider, and residents. Based on a difference-in-differences design, we document a sizable drop in Airbnb activity. Interestingly, not only targeted hosts (i.e., hosts with reservation days larger than the day cap), but also non-targeted hosts reduce their Airbnb activity. The reservation days of non-targeted hosts decrease between 26.27% and 51.89% depending on the treatment. Targeted hosts experience a similar decline. There is, nevertheless, significant non-compliance: more than one third of hosts do not comply with enacted short-term rental regulations. Additional analyses show that few properties are redirected from short-term rental to long-term rental use and that there is no significant drop in long-term rents. Drawing on a theoretical model, we tie the estimated effects to changes in stakeholders’ welfare: Regulations significantly reduce the welfare of hosts, and the loss ranges between 46.30% and 9.02%. The welfare loss of the platform provider is proportional to the loss of the hosts. Welfare of guests decreases moderately ranging between 4.5% to 4.1%. The welfare of residents increases minimal. These results question the effectiveness and desirability of the studied short-term rental regulations.
Overview
CoChat Summary
TL;DR
This paper studies day-cap short-term rental regulations in Berlin, Hamburg, and Munich using Airbnb and long-term rental data. It finds sizable declines in Airbnb activity for both targeted and non-targeted hosts, substantial non-compliance, little redirection to long-term rentals, and welfare losses for hosts, guests, and the platform with minimal resident benefit.
Key findings
- Short-term rental regulations reduced Airbnb reservation days by 18.48%–49.77% for targeted hosts and by 26.27%–51.89% for non-targeted hosts; active properties declined by 25.19%–44.82% for targeted hosts and 45.19%–63.43% for non-targeted hosts.
- Non-compliance was substantial: more than one third of hosts did not comply, and in Munich the share of properties rented out for more than 56 days increased to 46.6% in 2019.
- Only relatively few properties were redirected from short- to long-term rental use, ranging from 185 in Munich to 1,067 in Hamburg, and long-term rents showed no significant drop.
- Welfare losses were estimated at 46.30%–9.02% for hosts and 4.5%–4.1% for guests; platform provider welfare loss was proportional to host losses, while resident welfare increased minimally.
Methods
- The authors develop a theoretical model of monopolistic competition in short- and long-term rental markets to derive propositions and express stakeholder welfare changes as functions of observed market outcomes.
- Data cover all German Airbnb transactions from 2015–2019 from AirDNA for entire properties, plus long-term rental price data from RWI/Immoscout24; treated cities are Berlin, Hamburg, and Munich, with untreated German cities over 100,000 inhabitants as controls.
- The empirical design is a difference-in-differences model at the 1 km × 1 km grid-month level, estimated separately for reservation days, active properties, and prices, distinguishing targeted from non-targeted hosts and using wild bootstrap inference and robustness checks.
Limitations
- The paper states that more fine-grained data are needed to isolate individual regulation design elements and to better understand mechanisms, especially motivations of non-targeted hosts; it also notes that resident effects are studied only through the housing market, leaving other externality channels for future research.
- The text makes evident that the data lack detailed host background information and do not identify primary versus secondary residences, so Berlin and Hamburg non-compliance findings are interpreted cautiously; diversion to other platforms cannot be fully ruled out.
- Welfare estimates are described as upper bounds because outside options and unobserved profits are not observed, and the data frame ends in December 2019, excluding the Covid period.
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0 Valid · 0 Not valid · 9 Not checked · 132 Own results and interpretations
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In the paper
“In robustness checks (cf.Online Appendix A.5.4), we show that our estimates remain robust when we restrict the set of control grids to those in the largest untreated German cities (i.e., Dusseldorf, Essen, Frankfurt, and Leipzig).”
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > Methodology
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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- Rests on an assumption not shown here.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Proposition P1, moreover, predicts that the number of active properties offered by targeted hosts declines.We also find support for this proposition (p = 0.000).”
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > Baseline findings
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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In the paper
“Comparing the treatments in the city of Hamburg and Munich, which both established a 56-day cap, shows-in relative terms-stronger effects for Hamburg, which additionally requires hosts to register with the city (Δ ATT_rel = + 10 p.p.).”
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > Baseline findings
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption not shown here.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition, we find at least some support for Proposition P5a that predicts that regulations with a registration requirement decrease the number of active properties offered by targeted hosts more than regulations without a registration requirement.”
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > Baseline findings
hedgedstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption not shown here.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The point estimates are positive across all studied short-term rental regulations and point to a slight increase in short-term rental prices in response to the regulations (Table 5).”
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > Baseline findings
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption not shown here.
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Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > Impact of regulations on long-term rental market
“The analysis draws on our estimates of the regulation-induced changes in the number of active Airbnb properties per gridwhich, in support of Proposition P2, suggest that the number of targeted properties declines in the wake of short-term rental regulations.”
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > P2 Short-term rental regulations that impose day caps result
“P2 Short-term rental regulations that impose day caps result in an increase in short-term rental prices.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > Baseline findings
“Finally, we test Proposition P3, which proposes that the average short-term rental price increases in the wake of a short-term rental regulation.”
§ Regulating the sharing economy: The effects of day caps on shortand long-term rental markets and stakeholder outcomes > P2 Short-term rental regulations that impose day caps result
“P3 Short-term rental regulations that impose day caps result in an increase in the number of properties offered for long-term renting.”
Citations
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Discrete Choice Theory of Product Differentiation
Anderson, S. P., de Palma, A., & Thisse, J.-F. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/2450.001.0001 · Cited by 2,324
Causal Inference Using Potential Outcomes: Design, Modeling, Decisions
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- Basuroy S., Kim, Y., & Proserpio, D. (2022). Estimating the impact of Airbnb on the local economy: Evidence from the restaurant industry. Available at SSRN: https://ssrn.com/abstract=3516983.
- Lee, D. (2016). How Airbnb short-term rentals exacerbate Los Angeles’s affordable housing crisis: Analysis and policy recommendations. Harvard Law Policy Review, 10(1), 229–254.
- RWI (2020). RWI real estate data - Apartments for rent - suf. RWI-GEO- RED. Version: 1. RWI - Leibniz Institute for Economic Research. Dataset. https://doi.org/10.7807/immo:redwk:suf:v3.wk:suf:v3. · DOI
Cited by
The spatial effect of short-term rental regulations: The comparison between Barcelona and Paris
Bei, G. (2024) · Cities · doi:10.1016/j.cities.2024.105603 · Cited by 37
Data sharing and tax enforcement: Evidence from short-term rentals in Denmark
Garz, M., & Schneider, A. K. (2023) · Regional Science and Urban Economics · doi:10.1016/j.regsciurbeco.2023.103912 · Cited by 19
Self-citationTaxation of short-term rentals: Evidence from the introduction of the “Airbnb tax” in Norway
Garz, M., & Schneider, A. K. (2023) · Economics Letters · doi:10.1016/j.econlet.2023.111120 · Cited by 16
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The Impact of iBuyers on Housing Market Dynamics
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Metadata
- Authors
- Gauß, P., Gensler, S., Kortenhaus, M., Riedel, N., & Schneider, A.
- Affiliations
- University of Münster (DE)
- Jönköping University (SE)
- Corresponding author
- Gensler, Sonja
- Venue
- Journal of the Academy of Marketing Science
- Published
- 2024-06-15
- Volume
- 52
- Issue
- 6
- Pages
- 1627-1650
- ISSN
- 0092-0703 (ISSN-L)
- 1552-7824
- OpenAlex
- W4399704749
- Cited by
- 25
- References
- 46
- Citations by year
- 2026: 10 · 2025: 7 · 2024: 4
- FWCI
- 5.05
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- creativecommons.org/licenses/by/4.0 (tdm)
- creativecommons.org/licenses/by/4.0 (vor)
- Locations
- Journal of the Academy of Marketing Science (publishedVersion, cc-by)
- SSRN Electronic Journal (submittedVersion)
- Econstor (Econstor) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Universität Münster
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Sharing Economy and Platforms
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Housing Market and Economics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Keywords
- short-term rental regulation, home-sharing platforms, Airbnb, regulatory compliance, stakeholder well-being, housing market effects, sharing economy
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