Default contribution rates for 401(k) pension plans powerfully influence workers' choices. Potential causes include opt-out costs, procrastination, inattention, and psychological anchoring. We examine the welfare implications of defaults under each of these theories. We show how the optimal default, the magnitude of the welfare effects, and the degree of normative ambiguity depend on the behavioral model, the scope of the choice domain deemed welfare-relevant, the use of penalties for passive choice, and other 401(k) plan features. Depending on which theory and welfare perspective one adopts, virtually any default contribution rate may be optimal. Still, our analysis provides reasonably robust justifications for setting the default either at the highest contribution rate matched by the employer or -contrary to common wisdom -at zero. We also identify the types of empirical evidence needed to determine which case is applicable.A data appendix is available at: http://www.nber.org/data-appendix/w17587 6 In principle, these two effects are separable (e.g., upon electing a contribution rate of 3%, the default for the next period could change to 4%), but in practice they always go hand-in-hand (in the same example, the new default would be 3%).7 It is also natural to assume that τ (0) = 0 and τ (x) < 1.
In the short-run, peer producers decide whether to host on a particular day. Because of the flexible nature of their supply, we hypothesize that these producers will be highly responsive to market conditions, hosting travelers when prices are high, and using accommodation for private use when prices are low. In contrast, because hotels have a fixed number of rooms dedicated to travelers' accommodation, they will typically choose to transact even when demand is relatively low, while they won't be able to expand capacity during peaks in demand. These di↵erences imply that peer supply elasticity should be higher than hotels' supply elasticity on average. We validate this prediction by estimating a peer supply elasticity that is twice as high as hotels' elasticity. The heterogeneous entry of peer hosts across cities and over time has surplus implications. We estimate our short-run equilibrium model to quantify the e↵ect of Airbnb on total welfare and its distribution across travelers, peer hosts, and hotels. Travelers benefit from Airbnb for two reasons. First, flexible sellers o↵er a di↵erentiated product relative to hotels. Second, they also compete with hotels by expanding the number of rooms available. This second e↵ect is particularly important in periods of high demand when hotels are capacity constrained and can thus charge higher prices. Consequently, we find that the increase in consumer surplus from Airbnb is concentrated in city-days of peak demand, which the accommodation industry defines as compression nights. In those cities and periods, flexible sellers allow more travelers to stay in a city without greatly a↵ecting the number of travelers staying at hotels. Our data mainly come from two sources: proprietary data from Airbnb, and data from STR, which tracks supply and demand data for the hotel industry. We obtain data on average prices and rooms sold at a city, day, and accommodation type level between 2011 and 2014 for the 50 largest US cities. 1 We first document heterogeneity in the number of Airbnb listings across cities and over time. Cities like New York and Los Angeles have grown more quickly, reaching supply shares exceeding 15% and 5% respectively in 2014, while cities like Oklahoma City and Memphis have grown more slowly, with less than 1% supply shares at the of 2014. Within each city over time, the number of available rooms is higher during peak travel times such as Christmas and the summer. The geographic and time heterogeneity suggests that hosts flexibly choose when to list their rooms for rent on Airbnb, and are more likely to do so in cities and times when the returns to hosting are highest. In Section 2, we incorporate this intuition into a model of the market for accommodations. In this model, rooms for accommodations can be provided by dedicated or flexible sellers, and products are di↵erentiated. We include two time-horizons. The long-run horizon is characterized by the entry decision of flexible sellers given the new Airbnb platform. We model the decision of flexible sellers to jo...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.