Owning, Using and Renting: Some Simple Economics of the "Sharing Economy"

TL;DR: In this article, a survey of consumers broadly supports the modeling assumptions employed, for example, ownership is determined by individuals' forward-looking assessments of planned usage, and the analysis examines bringing-to-market costs such as labor costs and transaction costs, and considers the operating platform's pricing problem.

Abstract: New Internet-based markets enable consumer/owners to rent out their durable goods when not using them. Such markets are modeled to determine ownership, rental rates, quantities, and surplus generated. Both the short run, before consumers can revise their ownership decisions, and the long run, in which they can, are examined to assess how these markets change ownership and consumption. The analysis examines bringing-to-market costs, such as labor costs and transaction costs, and considers the operating platform's pricing problem. A survey of consumers broadly supports the modeling assumptions employed. For example, ownership is determined by individuals' forward-looking assessments of planned usage.

Summary

1 Introduction

• In traditional rental markets, owners hold assets to rent them out.
• After the P2P rental market emerges, owners and non-owners use the good as if they were renting the good at the market-clearing rental rate.
• Another aspect that is relevant to BTM costs is how amenable a good is to “temporal division” and, hence, renting.
• The authors main finding is that income is only important in determining ownership for a small number of goods (e.g., vacation homes); for most goods, planned usage was the primary driver, supporting their basic modeling framework.

2 Related work on modeling and quantifying the sharing economy

• Other work on the “sharing economy” has discussed its features and implications qualitatively.
• Edelman and Geradin (2015) represents another example in this vein.
• They also find that total ownership could increase following sharing, for more or less the same economic reasons the authors identify—the papers differ in at least two important ways.
• Another closely related paper (in part) is Einav et al. (2015), which covers some of the same ground in explaining why peer-to-peer markets are flourishing now.
• They also model consumers choosing among ownership, rental and non-participation.

3 Factors explaining the rise of peer-to-peer rental markets

• The somewhat obvious economic rationale for P2P rental markets is that the owners of most durable goods use them far less than 100% of the time.
• For P2P rental markets to draw in individual owners, the platform must find ways to fill in these gaps and give owners firm-like resources.
• Consider that Uber is only possible because both sides of the market now carry with them taximeters (when running the appropriate software) at all times: a smartphone with GPS technology allows for the precise measures of distance traveled.
• Hagiu and Wright (2014) analyzes whether it is better to be a marketplace or a re-seller (with the Amazon versus eBay question being a clear motivation).
• 8Both Horton (2014a) and Fradkin (2013) consider the role played by platforms in overcoming search frictions related to buyers trying to match with unavailable sellers—Fradkin in the case of Airbnb and Horton in the case of oDesk/Upwork.

4 Model

• Before anyone can “share,” someone has to own and others have to not own (but still want to consume at least some of the good).
• The authors model is built on the notion that goods can usefully be thought of as having an intensive margin of usage, which in turn drives the extensive margin decision (i.e., ownership).
• First, the authors assume that there are no BTM costs (such as labor and transaction costs).
• Next, the authors introduce BTM costs (such as depreciation, labor, and transaction costs) and see how this changes the short-run equilibrium and whether a P2P rental market can emerge.
• The authors then turn their attention to the long-run case, where owners and non-owners can revise their ownership decisions.

4.1 Consumer decision about ownership based on expected usage

• Every consumer has a unit of time to allocate to various activities, some of which involve using a good.
• Using the good brings decreasing marginal utility.
• The c(x) term is the opportunity cost of time, which grows as more time is spent with the good in question rather than with the best alternative use of one’s time.
• This unused capacity is what they will be able to rent out, plus whatever amount becomes available because the owner reduces their usage to reap rental income.

4.2 Three consumption possibilities with two consumer types but no rentals

• There are three important potential market configurations with respect to ownership: (1) everyone owns, (2) no one owns, and (3) some own and others do not.
• For their purposes, (3) is the interesting case.
• The faint dotted lines illustrate the construction of the regions.
• The authors are particularly interested in the rectangle where high-types own but low-types do not, because in this region the purchasing high-types have excess capacity, αH < 1, but the low-types still value usage of the good, αL > 0, despite their non-purchase.
• The immediate possibility of mutually beneficial rental exists between the two types (in the other market configurations a revision in the ownership decision is needed to support a P2P rental market).

4.3 Short-run P2P rental market equilibrium

• The authors now suppose that through some technological advance it becomes possible for the high-types to rent their entire excess capacity to the low-types, with no BTM costs.
• No one can revise their original ownership decision in light of this advance.
• If they had purchased the good, the low-types would consume αL .
• (5) Note that the short-run equilibrium rental rate is proportional to the difference between what low-types would consume if they owned, (1−θ)αL , and high-types would leave unused in the absence of the P2P rental market, θ(1−αH ).
• When the valuation of the high-types goes down from αH to α′H , with α ′ H < αH , the supply curve shifts out (the dashed curve labeled S1(r )), such that even at r = 0, the available supply, which would be θ(1−α′H ), exceeds the demand from low-types, (1−θ)αL , thereby creating a glut.

4.5 Bringing-to-market costs: labor, capital depreciation, and transaction costs

• The authors model thus far has assumed that owners can provide their unused quantities of the good to the market at no cost.
• Now, the authors assume that the owner of the good must pay a BTM cost.
• Let that cost on a per-unit basis be γ.10 Under this scenario, the market clears with zero rental rate and both owners and non-owners get their preferred levels of usage.

4.6 Bringing-to-market costs and existence of the peer-to-peer rental market

• If BTM costs are sufficiently high, then no P2P rental market will exist.
• This condition comes from the requirement that r < 2αL ; otherwise, the cost of consuming any of the good for a non-owner exceeds the marginal utility.
• There is no P2P rental market when the reduced transaction volume from the BTM costs equals the amount that would be supplied in equilibrium in the absence of those costs.

4.7 Revised ownership without bringing-to-market costs

• The authors now consider what happens in the long run, when owners and non-owners can revise their ownership decisions.
• For expositional ease, the authors will posit once again that BTM costs are zero.
• In the long-run P2P rental equilibrium, the rental rate equals the product market purchase price, and ownership does not depend on either usage patterns or valuation.
• For the long-run market to clear, the authors have to determine what fraction of consumers would choose to own.
• As ownership does not depend on valuation given that BTM costs are zero, the authors assume that both consumer types are equally likely to own.

4.8 Product market demand in the long-run P2P rental market equilibrium

• Many commentators on the “sharing economy” have assumed that the emergence of P2P rentals would reduce ownership.
• This is likely to occur in situations where both consumer types have high valuations (making demand high and supply limited).
• Recall that in the pre-P2P rental market with two consumer types, if p >α2H , then no consumer buys the good (2).
• Many teams now facilitate a resale market for their season ticket holders, charging a modest fee to enable resales over the Internet.
• These parameter values suggest the possibility of a transitory short-run phase in which low-types get access that disappears once former-owners become renters and bid up the rental rate.

4.10 Long-run P2P rental market equilibrium with bringing-to-market costs

• Now the authors consider the same long-run outcome, but assume positive BTM costs.
• In the presence of BTM costs, a firm that bought the good solely to rent would not merely earn no profits (as in the case with no BTM costs) but would instead suffer a loss.
• Now consider Equilibrium (2), in which some of the low-types own.
• On the question of elasticity, Cullen and Farronato (2014) use data from TaskRabbit to show that workers on this platform are highly elastic, with demand shocks met by large increases in hours worked.

4.11 More complex BTM cost structures

• Other possibilities are quite plausible.the authors.
• The authors have assumed costs are homogeneous for all sellers in the P2P rental market.
• To illustrate the rising cost context, Uber drivers may find it cheap to supply one hour of labor after their 9-5 jobs, but find two hours nearly impossible if they have to pick up their kids from daycare at 6pm.
• Both the heterogeneity of costs and the possibility of fixed costs suggest that in practice, the extensive margin of supply is important: when rental rates go up, more owners of the good are pulled into the market.
• Many of these owner/suppliers will be reaping inframarginal benefits because they have a range where their BTM costs are below those priced into the market.

4.12 The platform’s incentives for reducing costs

• One of the BTM costs faced by participants in P2P rental markets is the fee imposed by the platform.
• While more complicated price structures are possible, the most common price structure seems to be an ad valorem charge (sometimes with a minimum payment amount and some fixed fees): this is the pricing structure of both Airbnb and Uber.
• For any level of the BTM cost, the platform can obtain higher revenue by reducing γ0 and raising τ by an offsetting amount.
• This suggests that the platform has stronger incentives to lower BTM costs when demand is elastic, as the shifting out of the supply curve will greatly enlarge the quantity transacted without significantly reducing price.
• The platform charges the highest rates when the market is imbalanced with respect to owners and sellers, which is also where quantity transacted changes little with the imposition of the charge (i.e., the 1 2 τ(1−θ)θ term is small).

4.13 Competition with conventional rental firms

• The model predicts that in the long run, owning a good purely to rent it out offers no profits when BTM costs are zero and a loss when BTM costs are greater than zero.
• The entrance of Airbnb lowered revenues by as much as 10% in some market segments; it also seems to be lowering prices.
• On the ride-sharing side, there are several signs that Uber is securing market share at the expense of existing taxi firms, such as falling medallion prices and notable bankruptcies.
• Edelman and Geradin (2015) give the example of how a conventional hotel can, with a front-desk, handle the exchange of keys for hundreds of guests—a common source of friction for Airbnb rentals.

5 The attributes of goods and the feasibility of renting

• In the model, the purchase price, the valuation of owners and non-owners, the size of the pool of owners and non-owners, and the BTM costs of a good all affected whether a P2P rental market was possible.
• The authors provide data on the attributes of some of these goods as a test of their modeling 13“Yellow cab to file for bankruptcy”, San Francisco Examiner, January 6th, 2016.
• Goods that traditionally have been rented are expensive, durable goods that are used infrequently but whose usage can be planned in advance.
• This notion of shareability as being related to the patterns of how goods are characteristically used also interests us (though the authors differ from Benkler in that in their approach, the ownership decision and the amount of slack capacity are not “givens” but rather economic decisions themselves).
• Predicting which goods are profitable candidates for P2P rental is a task best left to entrepreneurs whose judgments will ultimately be evaluated by the market.

5.1 Main empirical results

• The authors find strong evidence that respondents who predicted that they would use a good more are more likely to own that good.
• Among non-owners, planned usage was cited more often than a lack of income as the reason for non-ownership, with the exception of certain extremely expensive goods like vacation homes.
• The predictability of usage and the size of usage sessions for a good tend to be positively correlated.
• In other words, goods that are used unpredictably tend to be used for relatively short periods.
• These are also the goods where P2P rental markets seem to have had the most success.

5.2 Design and administration of the survey

• The survey focused on consumer decision making and usage patterns for a variety of goods.
• There is little reason to think its members would have highly idiosyncratic consumption patterns.
• Furthermore, for their purposes, the MTurk population is willing—and has the incentive—to answer a tedious set of questions carefully.

5.3 Ownership by an individual’s planned usage

• In the model, consumers considered how much they would use some good and then compared the resultant usage utility against the purchase price.
• Furthermore, while higher household income predicts ownership, the strong association between expected usage and ownership persists even after taking income into account.
• To elicit expected usage, the authors asked respondents to select how often they would use a good in time units, using familiar measures of time to label the responses, e.g., one hour a week, one hour a day and so on.
• In Column (2), a control for the log of family income is included; in Column (3), a respondent fixed effect is added.
• The coefficient on the estimated usage regressor in Column (1) implies that a doubling of expected usage for some good—say using a BBQ grill two hours a week instead of one hour—is associated with about a 2.5 percentage point increase in the probability of ownership.

5.4 Self-reported reasons for non-ownership

• The regression results in Table 1 suggest that both income and predicted usage are important for explaining the ownership decision.
• These two factors are presumably more or less important for different kinds of goods.
• 18Household incomes imputed by taking the midpoint of the range associated with each bin (i.e., a respondent’s selecting $10,000-$19,999 is imputed to have a $15K family income).
• In Figure 5, the authors plot the per-good percentage of non-owners citing income as the reason for non-ownership (out of non-owners that cited either income or usage—very few cited space).
• There are some goods for which income was not cited at all (e.g., sewing machine, tuxedo, canoe), and several others where usage was overwhelmingly more likely to be cited.

5.5 Aggregate usage chunkiness and predictability

• Two major practical determinants of the feasibility of a P2P rental market are the predictability and size of usage sessions.
• Goods for which it is easy to predict when they will be needed (perhaps because it is easy for the owner to choose when to use the good with little loss in utility) would be easier to rent (or lend out).
• For each good, respondents were asked to rate the unpredictability of usage on a 1-5 scale (1 was highly predictable and 5 was highly unpredictable) as well as chunkiness (1 was one big chunk— and 5 was low chunkiness—lots of little chunks).
• A toothbrush is used in small chunks (2 minutes according to the ADA) and its usage is highly predictable (after every meal, if ADA prescriptions are followed).
• These common-sense answers are not particularly illuminating, but they do show subjects were paying attention and offering reasonable answers.

5.6 Predictability, chunkiness, and ownership

• The authors now test whether the predictability and chunkiness measures are related to individual ownership.
• In Column (2), the authors instead use the chunkiness measure as the predictor and also find a positive and highly significant effect of about the same magnitude.
• The effect for each measure is reduced (though a formal hypothesis test would fail to reject a difference relative to the estimate when each measure appeared alone).
• One concern with their approach might be that respondents prone to reporting high or low chunkiness and predictability scores might be idiosyncratically more or less likely to own the good.
• In Column (4), the authors use the same specification as Column (3) but include a good-specific effect.

5.7 Aggregate ownership and renting patterns at the level of the good

• This paper was motivated in part by the recent flourishing of P2P rental markets.
• Both axes are on a square root scale to better show the data.
• There are a number of goods that show medium ownership levels (e.g., around 50%) and yet zero recorded instances of renting, which could indicate potential P2P rental market candidates.
• Goods that are used during special occasions like weddings, celebrations, and vacations show the highest rates of rental and lowest rates of ownership, e.g., tuxedos, vacation homes, jet ski, tuxedos, canoes, and bouncy castles.
• To confirm the visual pattern of renting declining in ownership, Column (1) of Table 3 reports an estimate of FRACRENTg =β0 +β1FRACOWNg +ǫ, (30) where FRACRENTg is the fraction claiming to have rented good g and FRACOWNg is the fraction of respondents reporting to own good g .

6 Conclusion

• The sharing economy has dramatically impacted several important markets in just a few years, notably those for ride services and for very short-term apartment rentals.
• Consider that in some formulations of the consumer problem, consumers consume some positive amount of every good offered.
• If a low-BTM rental market existed for both blender types, consumers could act upon their taste for diversity and use both types without owning both blenders.
• One long-term reaction to the rise of P2P rental markets is that firms might change the goods that they offer.
• 20 Similarly, technologies that make it easier to monitor usage (GPS, embedded sensors, streaming video of how they are being used and so on) should make contracting easier and reduce some of the informational asymmetries that contribute to transaction costs.

Figures

Figure 8: Fraction of respondents owning various goods

Figure 9: Fraction of respondents reporting having rented various goods

Figure 4: Google automatically generated query suggestions for “Airbnb for ” partial query

Figure 3: Market clearing in the short-run peer-to-peer rental market

Figure 6: Usage predictability versus chunkiness

Table 3: Fraction of respondents owning a good versus fraction having rented a good

Figure 7: Fraction of respondents reporting having rented a good versus fraction reporting owning that good

Figure 5: Fraction of non-owners citing income as the reason (rather than usage) for not owning a good

Figure 2: Three consumer market possibilities in the absence of peer-to-peer rental, with two consumer types

Figure 1: Consumer’s optimal usage of a good and resultant decision about whether to purchase that good

Figure 11: Mean chunkiness index by good

Figure 10: Mean unpredictability index by good

Table 1: Respondent estimates of the fraction of time spent using a good andwhether they own that good

Table 2: Unpredictability and chunkiness of good usage and their association with good ownership.

Full text

NBER WORKING PAPER SERIES
OWNING, USING AND RENTING:
SOME SIMPLE ECONOMICS OF THE "SHARING ECONOMY"
John J. Horton
Richard J. Zeckhauser
Working Paper 22029
http://www.nber.org/papers/w22029
NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
February 2016
Thanks to Andrey Fradkin, Ramesh Johari, Arun Sundararajan, Samuel Fraiberger, Hal Varian and
Joe Golden for helpful discussions and comments. The views expressed herein are those of the authors
and do not necessarily reflect the views of the National Bureau of Economic Research. Author contact
information, datasets and code are currently or will be available at http://www.john-joseph-horton.com/
At least one co-author has disclosed a financial relationship of potential relevance for this research.
Further information is available online at http://www.nber.org/papers/w22029.ack
NBER working papers are circulated for discussion and comment purposes. They have not been peer-
reviewed or been subject to the review by the NBER Board of Directors that accompanies official
NBER publications.
© 2016 by John J. Horton and Richard J. Zeckhauser. All rights reserved. Short sections of text, not
to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including
© notice, is given to the source.

Owning, Using and Renting: Some Simple Economics of the "Sharing Economy"
John J. Horton and Richard J. Zeckhauser
NBER Working Paper No. 22029
February 2016
JEL No. D23,D47,L1
ABSTRACT
New Internet-based markets enable consumer/owners to rent out their durable goods when not using
them. Such markets are modeled to determine ownership, rental rates, quantities, and surplus generated.
Both the short run, before consumers can revise their ownership decisions, and the long run, in which
they can, are examined to assess how these markets change ownership and consumption. The analysis
examines bringing-to-market costs, such as labor costs and transaction costs, and considers the operating
platform’s pricing problem. A survey of consumers broadly supports the modeling assumptions employed.
For example, ownership is determined by individuals’ forward-looking assessments of planned usage.
John J. Horton
Leonard N. Stern School of Business
Kaufman Management Center
44 West Fourth Street, 8-81
New York, NY 10012
john.horton@stern.nyu.edu
Richard J. Zeckhauser
John F. Kennedy School of Government
Harvard University
79 John F. Kennedy Street
Cambridge, MA 02138
and NBER
richard_zeckhauser@harvard.edu

Owning, Using and Renting:
Some Simple Economics of the “Sharing Economy”
John J. Horton
Leonard N. Stern School of Business
New York University
*
Richard J. Zeckhauser
Har vard Kennedy School
Har vard University
February 12, 2016
Abstract
New Internet-based markets enable consumer/owners to rent out their durable goods when not us-
ing them. Such markets are modeled to determine ownership, rental rates, quantities, and surplus
generated. Both the short run, before consumers can revise their ownership decisions, and the long
run, i n which they can, are examined to assess how these markets change ownership and consump-
tion. The analysis examines bri nging-to-market costs, such as labor costs and transaction costs, and
considers the operating platform’s pricing problem. A survey of consumers broadly supports the
modeling assumptions employed. For example, ownership is determined by individuals’ forward-
looking assessments of planned usage.
JEL L1, D23, D47
Keywords: Sharing economy; peer-to-peer markets; rentals; Airbnb; Uber; bringing-to-market costs;
transaction costs
1 Introduction
In traditional rental markets, owners hold assets to rent them out. In recent years, technology startup
firms have created a new kind of rental market, in which owners sometimes use their assets for personal
consumption and sometimes rent them out. Such markets are referred to as peer-to-peer or “shari ng
economy” markets. To be sure, some renting by consumer-owners has long existed, but it was largely
confined to expensive, infrequently used goods, such as vacation homes and pleasure boats, usually
with longer duration rental periods. More often, consumer-owner goods were shared among family and
friends, commonly without explicit payment. In contrast, these peer-to-peer (P2P) rental markets are
open markets, and the good is “shared” in exchange for payment.
A prominent example of a P2P rental market i s Airbnb, which enables individuals to rent out spare
bedrooms, apartments, or even entire homes. Airbnb and platforms like it have been heralded by many,
*
Author contact information, datasets and code are currently or will be available at http://www.john-joseph-horton.com/
Thanks to Andrey Fradkin, Ramesh Johari, Arun Sundararajan, Samuel Fraiberger, Hal Varian and Joe Golden for helpful dis-
cussions and comments.
1

as they promise to expand access to goods, diversify individual consumption, bolster efficiency by in-
creasing asset utilization, and provide income to owners (
Sundararajan, 2013; Edelman and G eradin,
2015; Botsman and Rogers, 2010). The business interest in these platforms has been intense; Airbnb
alone has attracted nearly $2.4 billion in venture capital investment and was valued at $25.5 billi on dur-
ing their most recent funding round.
1
Companies organizing sharing markets have also attracted policy
interest, much of it negative (
Slee, 2015; Malhotra and Van Alstyne, 2014; Avital et al., 2015).
Critics charge that the primary competitive advantage of these platforms is their ability to duck costly
regulations—regulations that protect third-parties.
2
However, the counter-argument is often made that
existing regu lations were designed to solve market problems that these sharing economy platforms solve
in an innovative fashion, primarily with better information provision and reputation systems (Koopman
et al.
, 2014), thereby making top-down regulation unnecessary. A better understanding of these markets,
and progress in resolving this policy debate, requires elucidating what economic problem these markets
address, why they are emerging now, and what their properties are likely to be in both the short- and
long-runs. This paper seeks to provide that elucidation.
Our first major question is why P2P rental markets only became a force in the 21st century. The eco-
nomic problem P2P rental markets are able to solve—under-utilization of durable goods—is hardly new.
We argue that technological advances, such as the mass adoption of smartphones and the falling cost
and rising capabilities of the Internet, while clearly important, only provide part of the story. P2P rental
markets rely heavily on the hard-won industry and academic exper ience in the design and management
of online marketplaces. In particular, recommender systems and reputation systems, which emerged
during the early days of electronic commerce, are central to the function of P2P rental markets. The
knowledge so conveyed allows P2P rental platforms to overcome—or at least substantially ameliorate—
market problems such as moral hazard and adverse selection. We develop this argument in more depth
and point out relevant works from the literature.
Our second major question i s what are the economic properties of P2P rental markets. For exam-
ple, what determines the rental rate and the quantity exchanged in a P2P rental market? How much
total surplus is “unlocked” by the P2P rental market, and how is it distributed? How does the short-run
situation—where existing owners rent to non-owners—differ from the long run in which owners and
non-owners alike can revise their ownership decisions in light of the presence of a P2P rental market?
Does overall ownership increase or decrease, and who owns what goods in the new equilibrium? When
1
http://www.crunchbase.com/organization/airbnb; Uber, which also has a substantial P2P rental market (albeit with a sub-
stantial labor component) was valued at $62.5 billion in their last funding round. http://www.wired.com/2015/12/airbnb-
confirms-1-5-billion-funding-round-now-valued-at-25-5-billion/.
2
For example, Dean Baker, in an opinion piece for the Guardian characterizes Airbnb and Uber as being primar il y based on
“evading regulations and breaking the law.” “Don’t buy the sharing economy hype: Airbnb and Uber are facilitating rip-offs.”,
The Guardian, May 27th, 2014. Access online on January 19th, 201 6. http://www.theguardian.com/commentisfree/2014/
may/27/airbnb-uber-taxes-regulation. See
Horton (2014b) for a discussion of the externalities imposed by Airbnb-style
subletting in rented apartments. Edelman and Geradin (2015) discuss both the promised efficiencies of “sharing economy”
platforms as well as the regulatory issues they raise. Cannon and Summers (2014) offer a playbook for sharing economy com-
panies to win over regulators.
2

there are substantial bringing-to-market costs (such as labor, excess depreciation, and transaction costs),
who bears them, and how does it affect the short- and long-run equilibria?
To address these questions, we develop a simple model in which consumers initially decide w hether
to purchase a good based on their expected usage. We consider a case where there are owners and non-
owners, with the owners using the good less than 100% of the time and non-owners, while not purchasing
the good, would use it some of the time if they did own it.
3
Some technological/entrepreneurial inno-
vation then creates a P2P rental market that allows owners to rent their unused capacity to non-owners.
For clarity, we first assume that owners face no bringing-to-market (BTM) costs (i.e., no depreciation,
labor or transaction costs from rentals).
After the P2P rental market emerges, owners and non-owners use the good as if they were renting the
good at the market-clearing rental rate. Renters do face the rental rate, while for owners, the possibility
of rental creates a new opportunity cost for their own usage. The rental rate is increasing in the valuation
of the owners, which reduces supply, and the valuation of the renters, which increases demand. The
short-run rental market does not necessarily clear: if pre-P2P rental unused capacity exceeds demand,
a glut results. In practice, the inherent costs of bringing excess capacity to the market assures an above
zero price floor.
In addition to the short run, we consider a long run where owners and renters alike can revise their
ownership decisions. We find that if the short-run cost to rent the good 100% of the time is below the
purchase price, then ownership is less attractive. This will reduce purchase demand for the product. In
the long-run P2P rental market equilibrium, the purchase price equals the rental rate (when normalizing
the life of the good to 1). Owners and renters receive the same utility at the margin, thereby decoupling
individual preferences from ownership. The model offers an intuitive test for whether total ownership
will decrease in the long ru n: ownership decreases if the short-run rental rate is below the purchase price.
Surplus increases in both the short- and long-run P2P rental market equilibria relative to the pre-
sharing status quo. Although owners have less consumption, they are more than compensated with
rental i ncome that exceeds their utility loss. The greatest gains in surplus are obtained when original
non-owners value the good nearly as highly as owners, suggesting that goods where income (rather than
taste or planned usage) explains ownership could offer the greatest increase in surplus. The existence of
a P2P rental market allows for a higher maximum price in the product market, as it can generate positive
demand for a good at prices for which even high-types would not buy without the possibility of rental.
When we assume that owners do face BTM costs, the model predictions change in several important
ways. If BTM costs are sufficiently high, no P2P rental market can exist in the short run. If the market
can exist, the BTM costs raise the rental rate and lower the quantity of the good transacted in the market,
in the both the long run and short run. However, BTM costs—being the equivalent of a per-unit sales
3
While we assume a purchase price that splits consumers into owners and non-owners, other equilibria are possible, such as
one where everyone owns the good. For a given set of consumer valuations, there is a range of product market prices that can
support a short-run P2P rental market. To support a P2P rental market, the purchase price of the good must be low enough that
there is a pool of owners, but not so low that everyone with any usage demand for the good already owns the good. Of course,
in the long-run ownership decisions can be revised.
3

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Nber working paper series owning, using and renting: some simple economics of the "SHARING ECONOMY"" ?

Both the short run, before consumers can revise their ownership decisions, and the long run, in which they can, are examined to assess how these markets change ownership and consumption. The analysis examines bringing-to-market costs, such as labor costs and transaction costs, and considers the operating platform ’ s pricing problem. 

Q2. What is the main reason why the P2P rental market is so important?

Given the energy and vision of entrepreneurs, new developments in both technology and the effective communication of information, P2P rental markets have the potential to transform additional markets. 

Q3. What are the major technological shocks that made some of these P2P rental markets feasible?

The maturation and increasing penetration of the Internet and the proliferation of smartphones (with high-resolution digital cameras) were the technological shocks that made some of these P2P rental markets feasible. 

Q4. What are the signs that Uber is securing market share at the expense of existing taxi firms?

On the ride-sharing side, there are several signs that Uber is securing market share at the expense of existing taxi firms, such as falling medallion prices and notable bankruptcies. 

Q5. What is the effect of the short-run cost to rent the good?

The authors find that if the short-run cost to rent the good 100% of the time is below the purchase price, then ownership is less attractive. 

Q6. What are the types of goods that show the highest rates of ownership?

Goods that are used during special occasions like weddings, celebrations, and vacations show the highest rates of rental and lowest rates of ownership, e.g., tuxedos, vacation homes, jet ski, tuxedos, canoes, and bouncy castles. 

Q7. What are the obvious candidates for examining the emergence of P2P rental markets?

Some obvious candidates include examining whether the emergence of P2P rental markets increases access by non-owners, change ownership decisions, and affects rental rates. 

Q8. What is the way to predict when a good will be needed?

Goods for which it is easy to predict when they will be needed (perhaps because it is easy for the owner to choose when to use the good with little loss in utility) would be easier to rent (or lend out). 

Q9. How can a platform increase its revenue by lowering BTM costs?

the platform can always increase revenue by lowering BTM costs, as it can simply increase its own fee accordingly, keeping the rental rate and transaction volume unchanged (but making more revenue on each unit transacted). 

Q10. What were the only goods where a larger fraction of respondents cited income rather than usage?

The only goods where a larger fraction of respondents cited income rather than usage were high-end headphones and vacation homes. 

Q11. How much is the probability of ownership associated with a doubling of expected usage?

The coefficient on the estimated usage regressor in Column (1) implies that a doubling of expected usage for some good—say using a BBQ grill two hours a week instead of one hour—is associated with about a 2.5 percentage point increase in the probability of ownership. 

Q12. What is the condition that ownership will increase in the long run?

The condition is that ownership will increase in the long run when the short-run rental rate was above the purchase price, or that rSR > p. 

Q13. What is the effect of a higher rental rate on the consumption of the high-type owners?

The loss in utility for the high-type owners due to reduced consumption is∆vH = [ 2αH (αH − r /2)− (αH − r /2) 2 ]︸ ︷︷ ︸New−[ α2H ] ︸ ︷︷ ︸Old= −r 24 . (7)As the authors would expect, the greater the rental rate, the greater the loss in this consumption utility, as a higher rental rate encourages owners to consume less. 

Q14. What are the kinks in the product demand curve?

Product demand in the long run is just the fraction of consumers owning the good, orD1(p) = fOW N= θαH + (1−θ)αL −p/2. (21)Before the P2P rental market emerged, there were “kinks” in the product market demand curve at α2H and α2L .