A model of recommended retail prices

• Published date: 01 May 2017
• DOI: http://doi.org/10.1111/1756-2171.12179
• Author: Dmitry Lubensky
• Date: 01 May 2017

RAND Journal of Economics

Vol.48, No. 2, Summer 2017

pp. 358–386

A model of recommended retail prices

Dmitry Lubensky∗

Manufacturers frequently post nonbinding public price recommendations, but neither the ratio-

nale for this practice nor its impact on prices is well understood. I develop a model in which

recommendations signal a manufacturer’s productioncost to searching consumers, who then form

beliefs about retail prices. Increasingsearch makes consumers reject offers for the manufacturer’s

and competitors’ products more often, and I show that both consumers and the manufacturer

prefer moresearch when the production cost is low and less searchwhen it is high. With incentives

thus aligned, manufacturer recommendations informconsumers via cheap talk, and their removal

harms both parties.

1. Introduction

Manufacturers use nonbinding recommended retail prices in markets ranging from grocery

products to big ticket items such as electronics, appliances, and cars. These recommendations,

which come in a varietyof for ms such as list prices, manufacturer suggested retail prices (MSRPs),

sticker prices, etc., are visibly printed on product packaging and often promoted by the manu-

facturer through costly advertising. The existence of a link between price recommendations and

market outcomes has both been shown empirically (e.g., Faber and Janssen, 2008; De Los Santos,

Kim, and Lubensky, 2016) and also implicitlyassumed in the myriad studies that use recommen-

dations as a proxy for transaction prices (e.g., Berry, Levinsohn, and Pakes, 1995). There is also

anecdotal evidence that recommendations can directly affect the decisions of market participants,

for example, consumers often expect a discount off the MSRP when buying a new car, and

strategic dealers take this into account as they set prices. However, despite the evidence that price

recommendations affect behavior, our understanding of how they do so is quite limited. Due to

the fact that recommendations are nonbinding, the mechanism by which they have an impact and

the motives of the manufacturer in making them are still not well understood.

A common explanation is that recommendations act as price ceilings. This story is com-

pelling because most products sell at or below MSRP and because the manufacturer’s rationale

for imposing a price ceiling in order to reduce double marginalization is well established. Yetthis

explanation of recommendations is incomplete. First, price recommendations are not binding, at

∗Indiana University; dmitry.lubensky@gmail.com.

Thanks to Josh Cherry, Kai-Uwe K¨

uhn, Francine Lafontaine, Stephan Lauermann, Doug Smith, and Mike Stevens for

insightful feedback on the early version of this article. Thanks also to Mike Baye, Rick Harbaugh, John Maxwell, Jeff

Prince, Michael Rauh, Eric Rasmusen, Collin Raymond,Babur de Los Santos, Matthijs Wildenbeest, and the participants

of the Consumer Search and Switching Cost Workshopsin 2013 and 2014 for helpful comments on this version.

358 C2017, The RAND Corporation.

LUBENSKY / 359

least in name, and thus in jurisdictions where resale price maintenance is legal, it is not clear

why a manufacturer would make a recommendation instead of imposing a price ceiling directly.1

In addition, recommendations often do not bind in practice, for instance, most cars sell strictly

below MSRP but very few sell at MSRP. Last, manufacturers publicize their recommendations

and an explanation of recommendations as explicit price ceilings ignores the potential role played

by consumers.

This article presents an alternative explanation in which price recommendations affect

consumer search. I develop a model in which a manufacturer faces consumers with unit demand

who search among sellers of his product and sellers of competing products, observing a price and

a utility shock at each visit. The manufacturer’s cost is uncertain, and thus consumers do not know

the distribution of downstream prices. In particular, a consumer visiting a seller does not know

whether it is optimal to accept the current offer or continue searching. A price recommendation

informs consumers of the manufacturer’s cost, and thus of the continuation value of rejecting.

In this way, recommendations directly affect consumers’ search decisions, and by extension, the

prices set by retailers.

Although it benefits consumers to incorporate informative recommendations into their search

decisions, the incentive for a manufacturer to make recommendations is not immediately clear.

I demonstrate that in revealing his cost and thereby affecting search, the manufacturer faces a

trade-off. Specifically, consider consumers A and B, each currently marginal at a manufacturer’s

retailer and at a competitor. By making both consumers more optimistic about the distribution

of downstream prices and thus continue searching, the manufacturer reduces the probability of

selling to A from one to the continuation probability and increases the probability of selling to B

from zero to the continuation probability. More search, benefits the manufacturer if and only if

the continuation probability is sufficiently high.

Given these incentives for affecting search, the question is whether the manufacturer can

do so by credibly revealing his costs through price recommendations. A price recommendation

is pure cheap talk—it is not a falsifiable statement of fact2and it is no costlier to recommend a

higher price than a lower one. Therefore, if the manufacturer had incentiveto mislead consumers,

they in turn would rationally ignore recommendations and no information could be transmitted.

In order for nonbinding nonfalsifiable recommendations to have an effect, the manufacturer must

prefer to report truthfully.

The article’s main result is that the interests of consumers and the manufacturer are aligned

with respect to search, and thus credible signalling is possible. In the model, the manufacturer’s

cost has either a low or a high realization. When the cost is low, the manufacturer sets a low

wholesale price which leads to low retail prices, in turn making his product more attractive on

average than the products of competitors. The low-cost manufacturer thus faces a high continu-

ation probability that a searching consumer eventually buys from him and consequently prefers

more search. Therefore, he truthfully reveals his low cost and leads consumers to expect low

prices. Similarly, when his cost is high, the manufacturer sets a high wholesale price, making his

product on average less attractive than competing products and thus inducing a low continuation

probability. In this case, the manufacturer benefits from less search and revealshis cost tr uthfully

to induce consumers to expect higher prices. Because the manufacturer has incentive to reveal

truthfully in both states, he can inform consumers using cheap talk.

This ability to credibly communicate the continuation value of searching is unique to the

manufacturer. By contrast, a downstream seller always benefits by making visiting consumers

maximally pessimistic about their outside options, regardless of the true state. The model thus

predicts that whereas manufacturer price recommendations influence consumer search, cheap

1For instance, MSRPs are commonlyused in the United States where the Supreme Court r uled in 1997 in State Oil

Co.v.Kahnthat price ceilings are not inherently unlawful.

2It is difficult to hold a manufacturer liable whenhe recommends a price and a retailer ignores the recommendation.

By contrast, other statements on product packaging, such as “New York Times Best Seller” on a book jacket, are factual

and punishable by law if false.

C

The RAND Corporation 2017.