Allowable
Market Shifts in the Sharing Economy: The Impact of Airbnb on Housing Rentals
Hui Li, Yijin Kim & Kannan Srinivasan
Management Science, forthcoming
Abstract:
This paper examines the impact of Airbnb on the local rental housing market. Airbnb provides landlords an alternative opportunity to rent to short-term tourists, potentially leading some landlords to switch from long-term rentals and thereby, affecting rental housing supply and affordability. Despite recent government regulations to address this concern, it remains unclear how many and what types of properties are switching. Combining Airbnb and American Housing Survey data, we estimate a structural model of property owners' decisions and conduct counterfactual analyses to evaluate various regulations. We find that Airbnb mildly cannibalizes the long-term rental supply. Cities where Airbnb is more popular experience a larger rental supply reduction, but they do not necessarily have a larger percentage of switchers. Affordable units are the major sources of both the negative and positive impacts of Airbnb. They cause a larger rental supply reduction, which harms local renters; they also create a larger market expansion effect, which benefits local hosts who own affordable units and may be less economically advantaged. Policy makers need to strike a balance between local renters' affordable housing concerns and local hosts' income source needs. We also find that imposing a linear tax is more desirable than limiting the number of days a property can be listed. We propose a new convex tax that imposes a higher tax on expensive units and show that it can outperform existing policies in terms of reducing cannibalization and alleviating social inequality. Finally, Airbnb and rent control can exacerbate each other's negative impacts.
Regulatory Spillovers and Data Governance: Evidence from the GDPR
Christian Peukert et al.
Marketing Science, forthcoming
Abstract:
We document short-run changes in websites and the web technology industry with the introduction of the European General Data Protection Regulation (GDPR). We follow more than 110,000 websites and their third-party HTTP requests for 12 months before and 6 months after the GDPR became effective and show that websites substantially reduced their interactions with web technology providers. Importantly, this also holds for websites not legally bound by the GDPR. These changes are especially pronounced among less popular websites and regarding the collection of personal data. We document an increase in market concentration in web technology services after the introduction of the GDPR: Although all firms suffer losses, the largest vendor -- Google -- loses relatively less and significantly increases market share in important markets such as advertising and analytics. Our findings contribute to the discussion on how regulating privacy, artificial intelligence and other areas of data governance relate to data minimization, regulatory competition, and market structure.
Economics of Ransomware: Risk Interdependence and Large-Scale Attacks
Terrence August, Duy Dao & Marius Florin Niculescu
Management Science, forthcoming
Abstract:
Recently, the development of ransomware strains and changes in the marketplace for malware have greatly reduced the entry barrier for attackers to conduct large-scale ransomware attacks. In this paper, we examine how this mode of cyberattack impacts software vendors and consumer behavior. When victims face an added option to mitigate losses via a ransom payment, both the equilibrium market size and the vendor's profit under optimal pricing can actually increase in the ransom demand. Profit can also increase in the scale of residual losses following a ransom payment (which reflect the trustworthiness of the ransomware operator). We show that for intermediate levels of risk, the vendor restricts software adoption by substantially hiking up price. This lies in stark contrast to outcomes in a benchmark case involving traditional malware (non-ransomware) where the vendor decreases price as security risk increases. Social welfare is higher under ransomware compared with the benchmark in both sufficiently low- and high-risk settings. However, for intermediate risk, it is better from a social standpoint if consumers do not have an option to pay ransom. We also show that the expected ransom paid is nonmonotone in risk, increasing when risk is moderate despite a decreasing ransom-paying population. For ransomware attacks on other vectors (beyond patchable vulnerabilities), there can still be an incentive to hike price. However, market size and profits instead weakly decrease in the ransom amount. When studying a generalized model that includes both traditional and ransomware attacks, our results remain robust to a wide range of scenarios, including threat landscapes where ransomware has only a small presence.
Personal Increasing Returns: Analytics and Applications
Casey Mulligan
NBER Working Paper, March 2022
Abstract:
The human capital investment model with endogenous labor supply is generalized to consumer and health behaviors while retaining the tractability of comparative-static analysis of a single first-order condition. Accounting for the endogenous specialization responses is essential to properly distinguish supply and demand factors and to understand how the magnitude of their effects vary across time and circumstances. Even signing effects of policy interventions can hinge on the existence and extent of personal increasing returns. Applications include the gender gap in earnings, the dynamics of substance abuse, effects of taxes on human capital, the tradeoff between product quality and quantity, and unintended consequences of energy regulation. Metrics are provided for assessing the extent of personal increasing returns.
Regulating Native Advertising
Yue Wu, Esther Gal-Or & Tansev Geylani
Management Science, forthcoming
Abstract:
Native advertising is not fully transparent to consumers because it bears similarity to editorial content. Increasing the opaqueness of native ads can raise publishers' click-through rate, but can also negatively affect consumers' quality perception of the publishers' editorial content and lead to lower profitability. In this paper, we develop a game-theoretical model of native ads to investigate the economic implications of regulation. Our model considers two types of publishers, who differ in the quality of their editorial content. We show that publishers have incentives to self-regulate native ads through lower opaqueness in order to signal their high quality to the market. We find that stricter regulation can make native ads more opaque, on average, because it can eliminate the incentives of high-quality publishers to distinguish themselves from low-quality publishers. Consequently, strengthening regulation can yield lower consumer surplus and social welfare.
The Battle for Homes: How Does Home Sharing Disrupt Local Residential Markets?
Wei Chen, Zaiyan Wei & Karen Xie
Management Science, forthcoming
Abstract:
As cities debate how to regulate Airbnb and other home-sharing services, we study the impacts of home sharing on local residential real estate markets. By accommodating transient travelers with short-term rental properties, home-sharing platforms have evolved as a major alternative channel that attracts the growing supply of residential properties. However, on the demand side of local residential markets, home-sharing platforms are not a viable option for residents. To demonstrate this dynamic between home sharing and local residential markets, we leverage a unique quasi-experiment on Airbnb-a platform policy that caps the number of properties a host can manage in a city-and find that the policy reduced rents (in the long-term rental markets) and home values (in the for-sale housing markets) by about 3% and did not affect the price-to-rent ratio. Consistent with the conjecture, we find that the policy impacts can be attributed to increased supply in local residential markets because of the policy. Quantitatively, our estimates suggest that, if the density of affected Airbnb properties is 1% higher in a market, the policy may further decrease rents and home values by about 0.03%-0.06%, which is similar across each policy-affected city. Our empirical findings add to the debate about the impacts of home sharing on local residential markets with a novel data set and a unique identification strategy. Practically speaking, our research is a timely response to the debate on regulating home sharing and has implications for various stakeholders of the residential real estate markets.
Competition in Congested Service Networks with Application to Air Traffic Control Provision in Europe
Nicole Adler, Eran Hanany & Stef Proost
Management Science, forthcoming
Abstract:
We analyze congested network-based markets and their impact on competition, equilibrium charges and efficiency. Several strategies are explored including price caps, mergers and investments in new technologies. We find that congested networks served by collaborating (serial) and competing (parallel) firms may lead to excessive prices. Additionally, oligopolists may only serve captive demand, leading to inefficiently low flows. Perhaps surprisingly, permitting a firm with market power to horizontally integrate with a competitor may improve efficiency. We also show that price caps in congested networks are ineffective due to their failure to signal the existence of scarce resources. Instead, partial vertical integration may prove beneficial by creating incentives to expand capacity through technology adoption, provided the price cap regime is dropped. The model is subsequently illustrated with a case study of air traffic control provision in Western Europe, in which it is shown that substantial changes in the regulation are required in order to create a more cost efficient sector with increased capacity.
The Road Not Taken: Technological Uncertainty and the Evaluation of Innovations
David Tan
Organization Science, forthcoming
Abstract:
When venturing into unfamiliar areas of technology, inventors face ex ante technological uncertainty, that is many possible alternative technological paths going forward and limited guidance from existing technological knowledge for predicting the likelihood that a given path will successfully result in an invention. I theorize, however, that this ex ante technological uncertainty becomes less apparent when evaluating inventions in hindsight. When one knows that a given technological path turned out to be successful ex post, it may be difficult to appreciate the ex ante plausibility of reasons to prefer alternative paths. As a result, inventions may seem more obvious to those evaluating inventions with the benefit of hindsight. My theory yields a counterintuitive implication; when inventors venture into less familiar areas of technology, there is a greater risk of evaluators overestimating obviousness due to hindsight bias. Empirical evidence comes from novel data on accepted and rejected patent applications, including hand-collected data from the text of applicant objections to obviousness rejections and examiners' subsequent reversals of rejections in response to applicant objections.
The influence of patent assertion entities on inventor behavior
Mukund Chari et al.
Strategic Management Journal, forthcoming
Abstract:
Patent assertion entities (PAEs) are intermediaries that acquire patents from inventors and license them to firms that use the intellectual property to develop products. We consider how PAE intermediation influences inventor behavior by reducing the costs to monetize their inventions. Using a proprietary dataset that tracks PAE lawsuits, we find that, as PAE intermediation for a given class of technologies increases, larger numbers of focused inventors (i.e., small firms, universities, and labs) that typically lack commercializing capabilities begin to produce inventions in this class. Further, we find that, compared to their larger counterparts, focused inventors are particularly responsive to increasing PAE intermediation by producing greater numbers of inventions, albeit inventions that likely advance the state of the art only incrementally.
Patent Publication and Innovation
Deepak Hegde, Kyle Herkenhoff & Chenqi Zhu
NBER Working Paper, February 2022
Abstract:
How does the publication of patents affect innovation? We answer this question by exploiting a large-scale natural experiment-the passage of the American Inventor's Protection Act of 1999 (AIPA)-that accelerated the public disclosure of most U.S. patents by two years. We obtain causal estimates by comparing U.S. patents subject to the law change with "twin" European patents which were not. After AIPA's enactment, U.S. patents receive more and faster follow-on citations, indicating an increase in technology diffusion. Technological overlap increases between distant but related patents and decreases between highly similar patents, and patent applications are less likely to be abandoned post-AIPA, suggesting a reduction in duplicative R&D. Firms exposed to one standard deviation longer patent grant delays increased their R&D investment by 4% after AIPA. These findings are consistent with our theoretical framework in which AIPA provisions news shocks about related technologies to follow-on inventors and thus alters their innovation decisions.