Does Price Transparency Improve Market Efficiency? Implications of Empirical Evidence in Other Markets for the Health Sector
Does Price Transparency Improve Market
Efficiency? Implications of Empirical Evidence in
Other Markets for the Health Sector
Updated April 29, 2008
D. Andrew Austin
Economist/Analyst in Economics
Government and Finance Division
Jane G. Gravelle
Senior Specialist in Economic Policy
Government and Finance Division
Does Price Transparency Improve Market Efficiency?
Implications of Empirical Evidence in Other Markets for
the Health Sector
Consumer advocates, proponents of wider use of market incentives in the health
care sector, and some policy makers have called for greater price transparency. These
measures might include posting prices in an accessible form or regulations
constraining price discrimination (different prices charged to different customers).
Price transparency implies that consumers can obtain price information easily, so
they can usefully compare costs of different choices. Price transparency may also
mean consumers understand how prices are set and are aware of price discrimination.
In health care markets consumers often have difficulty finding useful price data. In
particular, few consumers have a clear idea of what hospital stays or hospital-based
procedures will cost, or understand how hospital charges are determined.
Many empirical studies have investigated how changes in price transparency
have affected various markets. Most of this evidence, largely relating to advertising
restrictions and lower search costs on the Internet, suggests that price transparency
leads to lower and more uniform prices, a view consistent with predictions of
standard economic theory. If this evidence could be applied to the health market, it
would suggest that reforms that increase transparency would reduce prices. In cases
involving NASDAQ and Amazon.com, public reaction created pressure to change
pricing strategies. A few studies, involving intermediate goods in one case and less
clearly identified advertising effects in others, found that transparency raised prices.
However, the special characteristics of the health market make it difficult to
directly apply empirical evidence gathered from other markets. These characteristics
include limits on competition among hospitals, complicated products that vary in
quality, intermediate agents (physicians) who make choices, and third-party payment
of costs through insurance. The dispersion of prices for similar health care
procedures is high, which suggests that these markets are not working well with
respect to price outcomes, as would be expected in ordinary competitive markets. In
addition, prices paid by different types of payers vary dramatically. On average,
patients without insurance or who pay their own bills pay much more relative to what
private insurers, Medicare, and Medicaid pay.
Despite these complications, greater price transparency, such as accessibly
posted prices, might lead to more efficient outcomes and lower prices. Some markets
where lifting advertising restrictions led to lower prices also involved complicated
products such as eye care, suggesting that the complex nature of health care may not
be a barrier to benefits from price transparency. Internet comparison shopping sites
also appear to have lowered prices for many products. Better price information might
allow patients, either directly or through their physicians, to obtain better value for
health care services. Several states and health insurers now provide online data on
hospital costs. These price transparency initiatives, at least so far, have had little
visible effect on pricing. Public pressure, which in some cases has caused hospitals
to curtail aggressive bill collection tactics, might change hospitals’ and health care
providers’ pricing behavior. This report will be updated as events warrant.
In troduction ......................................................1
Empirical Evidence on the Effects of Price Transparency...................2
What Are the Implications for Health Care Markets?......................4
Why Do Different Prices Persist? Differentiated Products
and Price Discrimination....................................5
Cost Structures and Pricing......................................6
Special Characteristics of the Health Care Markets....................8
Health Care Is Complicated..................................8
Physicians as Agents.......................................8
Patients Pick Physicians and Hospitals Pick Physicians............9
Other People’s Money Pays for Most Hospital Care...............9
Patients Have Poor Information About Hospital Quality and Costs..10
Summary: Special Characteristics of Health Care Markets.............11
Nuts and Bolts...............................................13
Price Variation Among Hospitals................................14
How Does Hospital Price Dispersion Compare To Other Markets?......19
Implications of Hospital Price Dispersion..........................21
Price Transparency Initiatives of Governments, Insurers, and Interest Groups..23
Does Price Transparency Reduce Price Variability?
Some Preliminary Results..................................26
How Would Greater Price Transparency Affect the Health Care Sector?......30
Internet Price Comparison Sites..................................32
Will the Health Sector Change Like Other Industries?................33
Appendix: Review of Empirical Studies on Price Transparency.............35
Pricing Reforms in Financial Markets.............................35
“Dynamic Pricing” at Amazon.com...............................38
Ready-Mixed Concrete: Intermediate Markets May Run Differently.....39
Restrictions on Advertising.....................................40
Vision Exams and Eyeglasses...............................40
Availability of Consumer Price Information....................43
Product Quality Information................................44
Search Costs and the Internet....................................44
Prices and the Internet.....................................45
Empirical Research on Price Transparency: Conclusions.............47
List of Figures
Figure 1. Hospital Charges for Selected Diagnostic Tests.................15
Figure 2. Hospital Charges for Two Common Analgesics.................16
Figure 3. Distribution of Average Charges Per Stay for
Normal Vaginal Birth..........................................20
Figure 4. Distribution of Average Charges Per Stay for Heart Failure........21
Figure 5. Price Distribution for a Samsung HP-R6372 HDTV.............22
Figure 6. Distribution of Average Charges Per Stay For Normal Birth,
Figure 7. Scatter Plot for Changes in Avg. Daily Charges and Discharges
for Normal Birth (DRG 373)....................................29
List of Tables
Table 1. Average Costs and Charges for Selected Hospitals,
By Type of Payer.............................................17
Table 2. Hospital Payment-To-Cost Ratios By Type of Payer, 1991-2000....18
Table 3. Variability of Average Hospital Charges and
Samsung HDTV Prices........................................23
Does Price Transparency Improve
Market Efficiency? Implications of Empirical
Evidence in Other Markets for the Health
Price transparency helps consumers obtain price information easily, which
allows them to make useful comparisons of costs of alternative choices. Price
transparency may also mean that consumers understand how prices are set and are
aware of any price discrimination (different prices charged to different customers).
In health care markets consumers often have difficulty finding useful price
information. In particular, few consumers have a clear idea of what hospital stays or
hospital-based procedures will cost, or understand how hospital charges are
determined. Prices charged by hospitals vary significantly across hospitals and vary
within hospitals across categories of patients.
Transparent prices play a key role in the efficient allocation of goods and
services. Under certain conditions, the decentralized and self-interested decisions of
firms and households in a price system yield resource allocations that avoid waste
and that match what suppliers make and what consumers want, which is how
economists define efficiency. Financial economics researchers typically define
markets as efficient when prices reflect all available information and when prices
adjust swiftly as new information arrives. If buyers and sellers do not know what
prices are, then some mutually agreeable trades will fail to occur, thus creating
inefficiencies. If buyers can see and compare prices for the same good offered by
different sellers, the buyers then save money by choosing the cheapest vendor. If
goods are similar but not identical, buyers then can compare prices and qualities
offered by different sellers and pick whichever offer suits them best. The buyers’
ability to choose an offer that suits them best puts tremendous pressure on all sellers
to lower prices, improve quality, or both. Without such competitive pressure firms
that are less efficient or that are earning excess profits can remain in the market, and
prices will be higher than they would otherwise be.
Lack of transparent prices may also contribute to price discrimination, which
can cause different customers to pay higher prices, an outcome that may be
acceptable in some markets but may lead to undesirable consequences in others. For
example, if the customers with the least bargaining power also tend to be those with
the least ability to pay, such discrimination may be deemed particularly undesirable.
Barriers to price transparency include both explicit restrictions on information
(such as government restrictions on price advertising or concealment by firms of
prices or price-setting approaches, including negotiated prices) and costs of search
by consumers. The simplest theories suggest that more information about prices
should decrease prices and also bring prices closer together, but certain theories
predict that more price information could raise average prices, and advertising might
raise prices by increasing demand or brand identification.
The first section of this paper briefly reviews the empirical studies of the effect
of changes in price transparency on prices and quality of goods in a variety of
industries. Most of this evidence relates to markets where buyers are the final end
users of the good, and the bulk of evidence suggests that more transparent prices lead
to lower prices and transactions costs. This section includes examples of direct
effects of price transparency acting through normal market mechanisms (as in the
case of lifting advertising restrictions or reducing search costs) as well as instances
in which publicity about pricing strategies altered firms’ behavior. (An appendix
contains a more detailed discussion.)
The second section addresses the extent to which this evidence might be
applicable to the health care market. It addresses certain special characteristics of the
health care market which may reduce the importance of prices as signals, for
example, the complicated nature of health care, the intermediation of physicians in
making health care choices including choosing hospitals, and the presence of third
party payment (e.g., insurance companies).
The third section then turns to a closer examination of how prices are actually
set by hospitals and the evidence that exists on price dispersion both across hospitals
and across patient categories.
The fourth section discusses some initiatives undertaken by governments,
insurers, and interest groups to improve information about prices and to regulate
The final section draws the pieces together, suggesting that while it is difficult
to determine the consequences of greater consumer price transparency, it is
reasonable to believe that greater transparency would improve outcomes.
Empirical Evidence on the Effects
of Price Transparency
Isolating the effects of price transparency from other determinants of price is
empirically difficult, and the literature contains a variety of approaches used to
identify these effects. A more detailed discussion of this extensive literature is
presented in the appendix.
Some examples of the effects of price transparency relate to the effect of
publicity about pricing practices that may be viewed as inappropriate and that may
lead to fears of regulatory involvement or consumer backlash. One such example
relates to NASDAQ. In 1994, William Christie and Paul Schultz, two Vanderbilt
University financial economists, noticed that NASDAQ dealers almost never quoted
prices using odd eighths (i.e., 1/8, 3/8, 5/8, and 7/8) for many high-volume stocks of
companies such as Microsoft, Intel, and Apple. This practice effectively created a
quarter dollar minimum spread between sellers’ asks and buyers’ bids, which
increased the trading profits of dealers. The day after these economists issued a press
release about their findings the practice was abandoned, and spreads for several
major stocks fell by about half.1
Some other examples of transparency in financial markets suggested
transparency lowered prices. When Island, an electronic communications network,
ceased displaying limit order data in 2002, trading costs rose; when Island resumed
a year later, trading costs fell. Another study found prices more volatile after hours
than during regular market hours when trades are immediately reported.
A second example of the effect of publicity involves the case of Amazon.com,
the internet seller. Amazon, according to reports, used characteristics gathered about
individual customers from the Internet itself (such as whether a customer was new
to the site, what browser the customer was using and what the customer purchased
in the past, etc.) to charge different prices to different individuals. Once this strategy
was publicized, the protests led Amazon to cease the pricing variations and
apologiz e. 2
Another case study focused on the intermediate market. In 1993, the Danish
Competition Authority required that all ready-mixed concrete contracts be made
public, which it hoped would stimulate greater competition. Instead, average prices
rose by 15%-20% and other factors such as changing demand conditions played no
discernable effect.3 There are two possible explanations for this unexpected increase
in prices with publicity. First, public prices may make collusion among sellers easier.
Rivals can observe sellers who undercut their competitors, and may be able to mete
out punishments in various ways. Second, price transparency may alter the strategic
incentives of sellers, inducing them to become tougher bargainers.
A larger body of studies estimates the effects of restrictions on advertising and
posting of prices. Most of these studies involved comparing jurisdictions that banned
certain types of advertising, primarily for vision exams and eyeglasses. Some studies
focused on the effects of restrictions on the advertising of prescription drugs and
alcoholic beverages and restrictions on posting gasoline prices. (It is important with
advertising, which can increase demand for branded products, to examine cases
where some outside authority, in this case the government, restricts advertising.) Two
studies examined the effects of local advertising of food prices, one examining the
effects of the 1978 newspaper strike in New York City and another where researchers
provided advertising via direct mail. Although studies of quality are more difficult
1 William H. Christie and Paul H. Schultz, “Did NASDAQ Market Makers Implicitly
Collude?,” Journal of Economic Perspectives, vol. 9, summer 1995, pp. 199-208.
2 Robert M. Weiss and Ajay K. Mehrotra, “Online Dynamic Pricing: Efficiency, Equity and
the Future of E-commerce,” Virginia Journal of Law & Technology, vol. 6, no. 11 (2001),
available at [http://www.vjolt.net].
3 Svend Albaek, Peter Møllgaard, and Per. B. Overgaard, “Government Assisted Oligopoly
Coordination? A Concrete Case,” Journal of Law and Economics, vol. 45, December 1997,
to undertake, two studies examined these effects: one study examined the effect of
mandatory fat content labeling and another the effect of requiring restaurants to post
hygiene quality grade cards. Almost all of these studies found that more information
on prices and quality lowered prices, improved quality, or both.
The final part of the appendix discusses the relatively new and growing body of
studies on the effect of better price information and lower search costs through
computers and the Internet. Studies have examined a wide range of items:
automobiles, books and CDs, airline tickets, and life insurance. The evidence was
mixed for cars and for books and CDs, but showed reductions in prices for airline
tickets and insurance. These studies suggested that consumers using comparison
sites did pay lower prices and later studies, as the Internet became more common,
more frequently pointed to lower prices. Part of the difficulty of studying the effect
of the Internet is that Internet sellers may offer benefits to customers compared to
conventional sellers, so that the evidence on price comparison sites, which appeared
to reduce prices and price variation, may be more relevant than comparing prices of
Internet and conventional sellers.
Considering all of the evidence of price transparency, the majority of the
empirical studies tend to find that greater price transparency, including advertising
and reduction in costs of finding information through the Internet, leads to lower and
more uniform prices.
What Are the Implications for Health Care Markets?
Can the evidence from other markets be used to analyze the effects of greater
price transparency in health care markets, or provide guidance about what measures
might best be considered? While the special features of the health care market that
distinguish it from other markets are well known among health economists,
researchers and policy makers have sought ways to capture the potential gains from
increasing efficiency in the health care sector by the introduction of market-like
reforms. Whereas published prices in other markets provide important signals of the
true economic value of goods and services in other parts of the economy, the
impenetrability of many health care billing practices creates a barrier to rational
decision making and analysis.
Prices in the health care markets reflect physician charges, hospital pricing,
prescription drugs, costs for medical devices and diagnostics, as well as other types
of health care goods and services. Certain market characteristics of industries that
provide many of these products are important in analyzing the effects of price
transparency: they are subject to quality differences (and are thus not entirely
homogeneous products); the product may be one whose nature and benefits are not
easily understood by the customer; sellers charge different prices to different
customers and customers pay different (and often small) shares of the costs because
of insurance; and within specific geographic areas there may be few providers, at
least in the case of hospitals. These aspects of the health care market not only mean
that prices will vary but they also (in many cases) complicate the consumers’
understanding of expected prices or their response to price differences; they also may
mean that it is difficult for prices to bring about economic efficiency (for example,
because of lack of competitive markets). All of these aspects of the health care
market therefore may mute the effects of transparency on prices.
Prices clearly vary in the health industry, and why they vary is relevant to the
implications of price transparency. The discussion below reviews basic aspects of
pricing that lead to different prices in a market and are relevant to discussing barriers
to the effect of transparency on prices in the health market. The first section
discusses two reasons that different prices persist for the same product: product
differentiation and price discrimination. As we shall see, both characteristics exist
in the health care market. Secondly, the cost structure of an industry may lead to
market power that allows different prices to be charged. Following that discussion,
some specifics of the health care market and how they relate to pricing characteristics
are discussed. Many of these characteristics are directly related to the role of price
in consumers’ decisions. Finally, the empirical evidence on price transparency
presented in the first part of this report is examined in light of these issues.
Why Do Different Prices Persist? Differentiated Products
and Price Discrimination
The “Law of One-Price,” which states the same good will sell for the same
price, is a simple consequence of buyers’ ability to pick the most advantageous offer.
In many situations, however, prices will vary. This may happen because two goods
are not identical. For example, a store in a more convenient location can charge more
than a store in an out-of-the-way location. Spending time in a resort during peak
season is different than spending time in the same resort during low season.
Conversely, as the real estate maxim states, if the price of an apartment with a view
is the same as an otherwise similar apartment without a view, then there really isn’t
a view. Moreover, products that otherwise seem quite similar may be differentiated,
if no more than in consumers’ minds, by brand, and certainly a great deal of
advertising appears directed at differentiating similar products, which permits
suppliers to increase prices and profits. Because health care depends on location,
quality, and patient characteristics it is not a homogeneous product, and so some
price differential is expected.
Some sellers may gain larger profits by charging different prices to different
groups of consumers. For this to happen, firms must have some market power,
meaning that they can raise their average selling price by cutting back on the amount
they sell. If the seller can identify different groups that differ in their sensitivity to
price changes, and if buyers cannot resell or use arbitrage, then firms will earn higher
profits by charging groups with lower price sensitivity a higher price.4 For instance,
airlines know that business travelers are usually less sensitive to prices than leisure
travelers. By imposing “Saturday night stayover” requirements for cheaper fares,
4 In economic theory charging different groups different prices is called “third-degree” price
discrimination. First degree price discrimination occurs when sellers have information on
the price sensitivity of individuals, and second degree price discrimination occurs when
sellers use quantity discounts.
airlines are able to charge higher prices to business travelers who want to sleep in
their own beds on weekends.
Firms can price discriminate in a number of ways.5 Consumer electronics
manufacturers offer mail-in rebates in order to charge higher prices to customers who
either value their time highly or who are poorly organized, and who therefore fail to
obtain those rebates. Car dealers charge different prices for identical cars, an
outcome of the bargaining process.
Price discrimination often benefits some classes of consumers: those who would
probably pay higher prices under uniform pricing. If airlines could not charge
business passengers higher fares, leisure travelers would certainly have to pay higher
fares. Some price discrimination schemes, such as college financial aid, are often
justified on the grounds of fairness, although they can also be explained by the desire
to maximize profits. Hospitals before the Medicare Act often sought to justify
charging different rates to different customers on the grounds of fairness, although
some economists who examined the issue at the time were skeptical.6 Hospitals in
the current health finance environment — dominated by large insurers and managed
care firms on the private side and Medicare and Medicaid on the public side —
typically attempt to charge more to uninsured patients who have less ability to
negotiate, even though uninsured patients are more likely to have lower incomes than
Cost Structures and Pricing
The structure of costs within an industry has important effects on the nature of
pricing. Firms with market power, which often arises from cost structures, will have
some ability to set prices differently from cost, and may be more resistant to
competitive pressures that result from price transparency.
Firms will have limited market shares and will face strong competitive pressures
to keep profit margins low when firms have
!fixed costs that are small relative to operating costs that can be
added or cut in the short run (variable costs), and
!unit costs that increase as output increases.
On the other hand, if fixed costs are large relative to variable costs or if firms
use an increasing returns technology, then uniform pricing may be difficult to
5 For one list of marketing techniques designed to charge different prices to different
customers, see F. M. Scherer and David Ross, Industrial Market Structure and Economic
Performance (Boston: Houghton-Mifflin, 1990), pp. 491-494.
6 R. A. Kessel, “Price Discrimination in Medicine,” Journal of Law and Economics, vol. 1,
1958, pp. 20-53. Kessel examines physicians’ fees and argues the setting of higher fees for
those with more means to be a standard case of price discrimination to maximize profits.
7 This point is analyzed in more detail in the section entitled “Price Variation by Payer.”
maintain, especially if the firm cannot store its output.8 Economic theory suggests
that industries that have high fixed costs and which sell perishable goods or services
face strong pressures to charge different customers different prices and compete in
markets subject to unstable prices.9 Increasing returns can often be found in
industries with network characteristics. For example, a phone connection is more
valuable within a large network than within a small one because more connections
are possible. Learning-by-doing effects are another example of increasing returns.
In addition, many hospitals provide indigent care for which they are not wholly
compensated. Such hospitals must find other ways to finance this care, which often
involve cross-subsidies. In these conditions, a simple flat-rate price system may not
be a viable strategy for hospitals. Therefore, imposing greater transparency of health
care prices may require closer attention to cross-subsidies and uncompensated
training and care.
The hospital industry has some natural monopoly or natural oligopoly
characteristics. A natural monopoly exists where incremental costs fall as output
rises through the relevant range of output for a market. A natural monopoly would
suffer losses if it set prices equal to incremental cost, which is a standard condition
for socially efficient pricing. Therefore, a natural monopoly must be supported by
some subsidy or must charge prices above incremental cost, which from an economic
perspective causes inefficiencies and market distortions. Industries with natural
monopoly characteristics are often regulated, and prices are often set administratively
through rate-of-return type regulations. The outputs of industries regulated under
rate-of-return procedures, however, are much simpler than the set of outputs which
hospitals provide. For example, electric power distribution, which generally has been
subject to rate-of-return regulation, deals with a single commodity which is uniform
in its physical characteristics.10
Entry of new firms in an industry with natural monopoly characteristics is
inefficient because at least some firms will be forced to operate at inefficiently low
levels. For example, entry of a new hospital might cause the average number of
empty beds in a market area to increase, which increases average prices. Because of
the hospital industry’s natural monopoly characteristics, state and federal regulators
have often imposed restrictions, such as Certificates of Need, on entry of new
hospitals. Theoretical models have been developed to better understand the tradeoffs
8 Technically, fixed costs and increasing returns create non-convexities in a firm’s
production function. This will cause gaps in the firm’s supply curve, so that supply and
demand curves might not intersect. In this case, there is no market equilibrium.
Experimental evidence suggests that pricing can be extremely erratic in such cases.
9 Lester G. Telser, “Competition and the Core,” Journal of Political Economy, vol. 104, no.
10 Even if electricity is physically homogeneous, costs of generation and demand for power
vary by time of day. Nonetheless, electric power, even if differentiated by time of day, is
much more homogeneous than outputs provided by the health sector.
between the gains in competitive pressure and the loss of scale economies.11 In U.S.
v. Carilion Health System a federal district court accepted the argument of two
hospitals that wished to merge that higher market concentration would lead to lower
prices, and rejected the Department of Justice’s claim that the merger would raise
prices, providing an illustration of a case where the scale economy argument
Special Characteristics of the Health Care Markets
Health care markets differ from markets for standardized commodities described
in economics textbooks in several important ways. The special features of health
care have had a strong effect on the evolution of health care markets. Five key
features of health care markets are discussed below; in general, they point to price
being a less important signal than it typically is in other markets. Prices could,
however, become more important with a shift to insurance types such as Health
Saving Accounts where consumers confront higher prices at the margin.
Health Care Is Complicated. By its nature, health care cannot be easily
standardized, making price dispersion difficult to monitor. Different diseases affect
different people in different ways, and treatments that work for one patient may fail
to help another. Patients may not know what disease or condition is affecting them,
and may have difficulty in articulating what is wrong with them and what they would
like treatment to accomplish. Hospitals are sometimes described as “job shops” to
emphasize their dissimilarity to assembly lines. Thousands of different types of
procedures may be performed in an average general hospital, and even specialized
hospitals must be equipped to face a wide range of conditions and complications.
Because hospitals produce many different outputs with many of the same inputs,
allocating costs to particular outputs or to specific patients can be somewhat
arbitrary. There is no unambiguous way to allocate the costs of employing nurses,
pathologists, accountants, and billing clerks to specific procedures or patients.
Hospital management strategies that seek to assign such costs to specific “profit
centers” appear to rely more on rules of thumb than on precise economic calculations.
Physicians as Agents. Because patients cannot always know what they
want, physicians must serve as their agents. In most cases, physicians will make a
preliminary diagnosis, recommend which specialists will be seen, and determine
whether a patient is admitted to a hospital or not. It is true that ethical and
professional guidelines stress that physicians must act in the best interests of the
patient. Still, physicians may be swayed directly or indirectly by insurers,
pharmaceutical companies, hospitals, and peers in ways that might not benefit
11 Rabah Amir, “Market Structure, Scale Economies, and Industry Performance,” working
paper University of Southern Denmark at Odense, August 2000, available at
[ h t t p : / / www.econ.ku.dk/ wpa/ p i n k/ 2000/ 0008.pdf ]
12 U.S. v. Carilion Health System, 707 F. Supp. 840 (Western District of Virginia, 1989).
For an economic and legal analysis of this case see David Eisenstadt, “Hospital Competition
and Costs: The Carilion Case (1989),” in John E. Kwoka and Lawrence J. White, eds., The
Antitrust Revolution: The Role of Economics (New York: Harper Collins, 1994).
patients. While the vast majority of physicians feel a strong professional
compunction to provide the best care possible, they also face pressure to reduce costs
to patients or insurance companies. The problem of agents considering their own
interests, along with those on whose behalf they act, exists in this market as well as
many other markets.13
Patients Pick Physicians and Hospitals Pick Physicians. Because
patients rely upon physicians as their agents, patients often do not choose which
hospital they enter. Rather, patients choose a physician, and the physician’s
admitting privileges determine where the patient goes. Hospital credentials
committees decide which physicians get admissions privileges based on a physician’s
training, residency program, malpractice record, and other relevant information.
Although some physicians have admitting privileges at more that one hospital, the
available evidence suggests that most physicians admit the bulk of their patients to14
one hospital. A patient needing an operation may have some choice of hospital if
her physician provides referral to more than one surgeon. While this provides the
patient with some choice, the patient rarely has detailed information about cost and
quality, and is rarely in a position to make an informed choice.
If a patient wishes to go to a certain hospital, then the patient must select a
physician with privileges there. Insurance companies offer physician directories
which list hospital affiliations, and hospitals often sponsor “physician-finder”
services that feature “their” M.D.s. Therefore, patients may have sufficient
information to figure out which physicians they would need to choose in order to go
to a particular hospital in the event of some medical condition. (Emergency
admissions are generally sent to the nearest hospital with an emergency room or to
a hospital which specializes in trauma cases.) In some cases they may have
information on quality through studies that rank hospitals. The fact remains,
however, that patients are usually in a poor position to choose a hospital which best
suits their needs because they lack the right information and because they are
shielded from information about cost differences among hospitals.
Other People’s Money Pays for Most Hospital Care. Hospitals get
slightly less than a third of their revenue from Medicare, another third from private
insurers and slightly more than a sixth of their revenue from Medicaid.15 While
public or private insurance protects patients from the financial consequences of a
hospital stay, insurance also makes patients insensitive to prices. By the time a
patient reaches a hospital deductible, out-of-pocket payment limits for most insurance
policies may have been reached for many patients. In particular, for the most
complicated episodes (which account for a disproportionate share of hospital costs),
13 The principal-agent problem, as it is referred to in economics, occurs in many contexts,
including corporate managers acting on the behalf of stockholders and tenants making
decisions that affect owners of property.
14 Douglas R. Wholey and Lawton R. Burns, “Convenience and Independence: Do
Physicians Strike a Balance in Admitting Decisions?,” Journal of Health and Social
Behavior, vol. 32, no. 3 (September 1991), pp. 254-272.
15 Uwe E. Reinhardt, “The Pricing of U.S. Hospital Services: Chaos Behind A Veil of
Secrecy,” Health Affairs, vol. 25, January/February 2006, pp. 57-69.
most patients may be fully covered or fully bankrupt. In either case, price plays little
or no role in either choice of treatment or location of treatment.
Patients may indirectly choose their hospital and nature of their care through
their choice of insurance plan, and as noted above, through their choice of physician.
Many plans using Preferred Provider Organization (PPO) approaches restrict policy
holders’ choice of hospital, or impose financial penalties for using hospitals outside
the PPO network. One plan may be cheaper than another because it is able to drive
a harder bargain with hospitals or because it can restrict the cost or amount of care
which policy holders receive. While consumers can obtain information about
features of different insurance plans, that information arguably is often incomplete
Patients Have Poor Information About Hospital Quality and Costs.
Patients may also be in a poor position to choose their own hospital because they
have little access to information about hospital prices and quality or are not familiar
with the information that is available (such as hospital ratings). As with any other
good or service, a good decision about hospital selection must be supported with
adequate information on costs and quality. Hospitals in most states are not required
to make public individual prices for items, and other resources for comparative
pricing information are limited. Aetna, for example, has provided price information
for physician services in selected areas, but this information is available only to its16
The impenetrability of hospital bills is legendary. Hospital bills for privately
insured patients routinely run for pages and contain hundreds of individual items.
Hospital billing and coding have become arcane arts, practiced by highly specialized
clerks and consultants. Insurers and government analysts have access to files that can
be used to generate meaningful average costs, but this information is not available
Compounding the problems patients face, they generally have access to little
useful information about health care quality. In part this is due to the inherent
complexity of medical care and the difficulty of defining and measuring quality.
Consumers can quickly judge the quality of most goods they buy on a daily or weekly
basis, and make changes in shopping routines accordingly. In some cases, such as
obstetrics, word-of-mouth and reputation may lead patients to reasonably well-
informed choices among hospitals. In general, however, hospital stays are for most
an infrequent event and not many patients have enough experience or connections to
compare experiences in a range of different hospitals.
Large corporations, insurance companies, and government agencies have
developed extensive databases containing information reflecting the quality of health
16 Testimony of Robin Downey, Vice President and Head of Product Development, Aetna,
in U.S. Congress, House Committee on Ways and Means, Subcommittee on Health, Hearingthnd
on Price Transparency, 109 Cong., 2 sess., July 18, 2006. The expansion to the
Washington area was reported in January W. Payne, “The Secret’s Out: Aetna Members
Gain Access to Care Price, Quality Data,” Washington Post, August 22, 2006, pp. F1, F4.
care. The development of large electronic databases has opened the possibility of
creating quality indices based on sophisticated statistical methods. Presently,
however, these data are largely unavailable to consumers. Traditional approaches to
quality monitoring in health care focus on “zero/one” indicators. Physicians are
licensed, and others are barred from providing medical care. Hospitals are accredited
and providers are certified for Medicare reimbursement. Such measures, however,
serve only to set lower bounds.
Providing consumers with more useful data on outcomes may improve health
care quality.17 Of course, outcome data must include risk adjustments, so that
statistics reflect the fact that healthier patients will on average have better outcomes.
For example, the United Network for Organ Sharing, established by Congress in
1984, collects data on all transplant operations in the United States. Risk-adjusted
outcome data for each transplant center are available at [http://www.unos.org].
Public availability of risk-adjusted outcome data puts pressure on surgeons and
transplant centers to improve performance. New York State has published risk-
adjusted average mortality rates for cardiac surgery since 1991. Once New York
State started publishing average mortality rates, patients at a top-performing hospital
or surgeon reportedly had about half the chance of dying as did those who picked a
hospital or surgeon from the bottom-performing 25%.18 Massachusetts maintains a
website with death rates for coronary artery bypass graft (CABG) operations for
specific hospitals and surgeons. This site lists the number of procedures performed
by specific surgeons for several other types of operations.19 Pennsylvania published
a report on cardiac surgery that listed hospital-specific data on average charges,
average payment by commercial insurers and Medicare, and risk-adjusted mortality
and readmission rates. This report also listed surgeon-specific data on risk-adjusted
mortality and readmission rates for CABG procedures.20 Data presented in the report
showed little connection between average charges and adjusted mortality rates.21
Summary: Special Characteristics of Health Care Markets
If the market satisfies conditions of the model of perfect competition, which
imply that consumers are fully informed and can choose the lowest price, prices will
converge to the cost of producing the last unit of output and goods will be distributed
17 For a more extensive analysis of the potential of giving consumers with useful outcome
data see Michael E. Porter and Elizabeth O. Teisberg, Redefining Health Care: Creating
Value-Based Competition on Results (Allston, Mass: Harvard Business School, May 2006).
18 Ashish K. Jha and Arnold M. Epstein, “The Predictive Accuracy of The New York State
Coronary Artery Bypass Surgery Report-Card System,” Health Affairs, vol. 25, no. 3, 2006,
19 These data reports are available at [http://www.mass.gov/healthcareqc].
20 Pennsylvania Health Care Cost Containment Council, “Cardiac Surgery in Pennsylvania
21 Reed Abelson, “In Health Care, Cost Isn’t Proof of High Quality,” New York Times, June
efficiently.22 More generally, the “Law-of-One-Price” asserts that consumers’ ability
to choose the most advantageous offer will ensure that the same good will sell for the
same price. To the extent that transparent pricing helps markets rapidly converge by
bringing prices in line with incremental costs, it promotes economic efficiency.
Many markets do not satisfy conditions of the model of perfect competition. If
consumers are poorly informed, or hindered from taking their most advantageous
option, prices might not converge to efficient levels, if they converge at all. While
such problems can arise in markets for simple goods, the problems are exacerbated
for more complex goods and services, such as health care. Several aspects of health
markets, including natural differentials in the product due to differences in quality
and patient characteristics and the widespread practice of price discrimination, limit
the effects of price transparency. In addition, other important characteristics interfere
with price signals and competitive pricing outcomes: the product is complicated,
physicians rather than consumers tend to determine the product purchased, patients
generally do not directly pick hospitals, many costs are covered by third parties, and
patients have poor information about costs.
In sum, health care patients often have only a limited and indirect ability to
choose which hospital they will be treated in the event of some medical episode.
Choosing a different hospital may require a change of physician or of insurance plan.
Even if patients could switch among hospitals more easily, their incentives to search
for cheaper hospital care are dulled by third-party payment, and patients typically
lack price and quality data that would be necessary for them to make a fully informed
choice. Much of the difficulty in instituting market-like reforms in the health care
sector stems from the nature of health care itself, and from the ways health care
institutions have evolved to deal with special features of health care. Improvements,
while possible, would probably be neither quick nor easy.
These characteristics, however, all point to some important conclusions. Prices
as signals are diluted and muted in the health care market as compared to many other
markets. That muting of price signals tends to suggest that improvements in price
transparency may be less effective in the health care market than in other markets and
that this problem is particularly serious with hospital pricing. At the same time, the
lack of understandable price information in the health care market may suggest
significant room for improvement. To understand this last issue, it is important to
be clear about just how complex and dispersed hospital pricing is, an issue
considered in the following section.
As the previous section suggests, the barriers to direct consumer choice are high
for hospitals, and it is for hospitals that many initiatives, discussed below, have been
made to improve information and transparency. Hospital costs are also a major
22 Efficiency here means no waste in production and that all gains from trade are exhausted.
portion of health care costs, accounting for 31% of the $2 trillion of costs in 2005.23
To interpret and apply the evidence on price transparency requires a more specific
understanding of how hospitals set prices. This section provides an overview of how
hospitals set and administer prices. This section also investigates the variability of
Nuts and Bolts
Every hospital maintains a “chargemaster,” a document which lists prices for
each item and procedure offered by the hospital.24 A chargemaster may contain about
10,000 to 20,000 separate items. By comparison, the U.S. tariff schedule has about
10,000 separate rate lines, and a regular supermarket sells about 15,000 items.25 A
Lewin Group study of hospital pricing practices found that few hospitals in its sample
conducted systematic reviews of their chargemasters.26 Many hospitals stated that
their charges had little relation to costs, although hospitals that were larger, urban,
or which conducted substantial amounts of research were more likely to report some
link between costs and chargemaster prices. Supplies and pharmaceutical charges
appeared to be reviewed more regularly and were more likely to be related to costs.
Most hospitals in the Lewin sample charged higher markups on less-expensive items.
Prices listed on the chargemaster bear little resemblance to what is actually paid.
On average, insurers and patients paid hospitals about 38% of their “charges” in
2004.27 Medicaid pays about 17% of total hospital revenues.28 Medicaid payment
arrangements differ by state. All states use a prospective payment system for
Medicaid hospital reimbursement, with most either paying a flat fee according to
diagnosis related groups (DRGs) or paying a flat per diem rate. All states also make
23 Centers for Medicare and Medicaid Service, Office of the Actuary, National Health
24 Uwe E. Reinhardt, “The Pricing of U.S. Hospital Services: Chaos Behind A Veil of
Secrecy,” op. cit.
25 U.S. International Trade Commission, Simplification of the Harmonized Tariff Schedule
of the United States, Investigation No. 332-388, Publication 3318, June 2000; Food
Marketing Institute Facts and Figures website, available at [http://www.fmi.org/facts_figs/
26 Allen Dobson, Joan DaVanzo, Julia Doherty, and Myra Tanamor, “A Study of Hospital
Charge Setting Practices,” Lewin Group report no. 05-4, December 2005, available at
[http://www.me dpac.go v/ publi cations/contractor_reports/Dec05_Charge_setting.pdf].
27 Uwe E. Reinhardt, “The Pricing of U.S. Hospital Services: Chaos Behind A Veil of
Secrecy,” op. cit., p. 57.
28 Ibid., p. 61.
special payments to hospitals for unusually high-cost cases, and most make payments
to hospitals that serve low-income or medically needy populations.29
Medicare pays a flat fee for inpatient care based on the average relative cost of
a case within one of about 600 DRGs. A DRG weight, reflecting the relative cost
and complexity of a given diagnosis code, is multiplied by a monetary conversion
factor. Medicare payments are adjusted to reflect differences in regional labor costs
and some other local factors. Other adjustments are made for outliers
(extraordinarily complex cases with exceptionally high costs) and “disproportionate
share” adjustments made for hospitals that serve a larger than usual portion of
indigent patients. DRG weights are recalculated to account for changes in
technology, practice patterns, and other trends. Congress typically adjusts the
monetary conversion factor each year. From time to time, the Medicare Payment
Advisory Commission (MEDPAC) proposes technical changes in the definition of
DRGs and in payment and adjustment details.
Private insurers are responsible for about a third of the hospitals’ revenues
(hospital revenues were $612 billion in 2005).30 Private insurers’ payment
arrangements vary: some pay a fixed portion of charges, some pay negotiated per
diems or pay flat fees according to DRGs. Private insurers typically use Medicare’s
list of DRGs, but may assign their own weights. Medicare’s calculations of DRG
weights use claim experiences of Medicare beneficiaries, who are older than the
average private health plan policy holder, and so may not reflect relative costs for
younger patient populations. Private insurers vary in their ability to extract discounts
from hospitals, and arrangements between insurers and hospitals are tightly guarded
According to many analysts familiar with health care finance, Medicare and
Medicaid payments on average fall short of the fully allocated costs associated with
patients in those programs.31 Thus hospitals must shift costs to private insurers,
increase efficiency, or reduce services to balance their books. As a result, payments
for a particular patient’s case will reflect not just the complexity of the case and the
resources used, but also depend on the negotiating prowess of the patient’s insurer.
Price Variation Among Hospitals
Prices for specific items may vary wildly from one hospital to the next, as
Figure 1 and Figure 2 show. For instance, a comprehensive metabolic panel, which
costs $97 at San Francisco General, costs $1733 at Doctors Hospital in Modesto,
29 Some specialized hospitals, such as psychiatric hospitals, are often reimbursed differently
than general hospitals. For a detailed description of Medicaid hospital reimbursement
policy, see CRS Report RL32644, Medicaid Reimbursement Policy, by Mark Merlis.
30 Ibid., for the share. Total hospital costs are from the Centers for Medicare and Medicaid
Services, Office of the Actuary, National Health Statistics Unit.
31 Allen Dobson, Joan DaVanzo, and Namrata Sen, “The Cost-Shift Payment ‘Hydraulic’:
Foundation, History, And Implications,” Health Affairs, vol. 25, no. 1 (2006), pp. 22-33.
about 18 times more expensive. To some extent disparate prices reflect different
markup formulae, which act to allocate hospital overhead costs among items.
Figure 1. Hospital Charges for Selected Diagnostic Tests
Sacr amen t o
West Hills Hospital, West
Cedars-Sinai, Los Angeles
UC Davis, SacramentoComplete blood count
Comprehensive metabolic panel
Scripps Memorial, La
Jolla, San DiegoChest X-Ray (Two views, basic)
San Francisco General,
$0 $200 $400 $600 $800 $1,000 $1,200 $1,400 $1,600 $1,800
Source: Reproduced from Lucette Lagnado, “California Hospitals Open Books, Showing Huge Price
Differences,” Wall Street Journal, Dec. 27, 2004, p. A1. Data obtained from individual hospitals.
Figure 2. Hospital Charges for Two Common Analgesics
$26. 79Sac ramen t o
$3.28West Hills Hospital, West
$0.12Cedars-Sinai, Los Angeles
$1.00UC Davis, Sacramento
$7.06Scripps Memorial, LaTylenol (or acetaminophen) onetablet, 325 mg
$11.44Jolla, San Diego
$5.50San Francisco General,Percocet (one tablet, 5-325 mg)
$0 $ 5 $10 $1 5 $ 20 $25 $30 $3 5 $ 40
Source: See source for Figure 1.
Table 1 presents data on average costs and charges by type of payer for three
hospitals, all located in urban areas. In each case, the average charges for managed
care patients were about 20%-30% above average operating costs as reported to the
Centers for Medicare and Medicaid Services (CMS). By contrast, average charges
for uninsured patients were substantially higher.
Table 1. Average Costs and Charges for Selected Hospitals,
By Type of Payer
O’ConnorSt. LouisePalm Beach GardensCommunity Hospital
San Jose,(Catholic)Palm Beach Gardens,
CAWest Gilroy, CA CA
Avg. Operating Cost$1,631$1,376$1,501
per Patient per Day
Collected from$1,940 $1,773$1,774
Billed the$5,951 $5,508$7,414
Collection Rate97% 96%32%
from the Uninsured
Source: Heartland Institute analysis of Centers for Medicare and Medicaid’s Medicare Cost
Reports data for 2002. Reproduced from Randy Suttles and Merrill Matthews, Jr., “Hospital
Pricing: Separate and Unequal,” Health Care News, September 1, 2003.
Table 2 presents payment-to-cost ratios by type of payer for community
hospitals from 1991 to 2000. The mix of services that each type of payer funds
differs, which precludes direct comparisons of payment rates across payers.
Nonetheless, these data underline the point that the relationship between costs and
payments differs among payers. Average Medicare payments since the mid 1990s
nearly match hospital costs, while Medicaid payments, on average, fall short of
covering costs. The ratio of payments to costs is highest for private payers (i.e.,
private insurers and managed care firms), although that ratio fell significantly during
the 1990s. The ratio of payments to costs is lowest for uncompensated care, although
many hospitals receive subsidies from state and local governments, not reflected in
Table 2, that serve to defray expenses associated with uncompensated care.
Data in Table 2 lump all uninsured payers together, although these payers
include indigent patients, from whom much smaller payments may be received, and
non-indigent patients. We were unable to locate aggregate data that would separate
these two groups. However, an illustration based on aggregate California data,
provided in testimony by Glenn Melnick, shows the importance of this distinction.
The average chargemaster price for an appendectomy in 2002 was $18,229; the
indigent uninsured paid $1,783, the Medicare payment was $4,805, the managed care
payment $6,174, and payments by the non-indigent uninsured was $8,143.32 The
payment from the non-indigent, indeed, did fall below the list price, and may reflect
both ad hoc discounts and failure to collect the payment. Even so, the uninsured non-
indigent paid a third more than the managed care patients and 70% more than
Medicare patients for this procedure. Melnick also points out that the list price
remains important not only because some uninsured patients are charged the list
price, but also because of stop-loss provisions in contracts (where list is paid above
a threshold), lack of contracts with all third party providers, and out-of-network use.
He also points out that increasing revenues is an incentive to charge a high list price.
Table 2. Hospital Payment-To-Cost Ratios By Type of Payer,
Y e ar Medicare Medicaid UncompensatedCar e P rivateP ayers
1992 88.8 90.9 18.9 131.3
1993 89.4 93.1 19.5 129.3
1994 96.9 93.7 19.3 124.4
1995 99.3 93.8 18.0 123.9
1996 102.4 94.8 17.3 121.5
1997 103.6 95.9 14.1 117.6
1998 102.6 97.9 13.2 113.6
1999 101.1 96.7 13.2 112.3
2000 100.2 96.1 12.1 112.5
Source: MEDPAC analysis of American Hospital Association data. Reproduced from Table B-11
in Medicare Payment Advisory Commission, Report to the Congress: Medicare Payment Policy,
March 2002. Data for years 2001 and after are unavailable.
Some hospitals have been strongly criticized for charging uninsured patients,
who typically have less ability to pay for care than insured patients, far higher prices.
In some apparently isolated circumstances, news stories detailing some hospitals’
attempts to use aggressive collection methods against uninsured patients purportedly
caused those hospitals to cancel those debts.33
32 Testimony of Glenn Melnick, in U.S. Congress, House Committee on Ways and Means,
Subcommittee on Health, March 9, 2004.
33 Randy Suttles and Merrill Matthews, Jr., “Hospital Pricing: Separate and Unequal,”
Health Care News, September 1, 2003, available at
Although some hospitals and hospital associations have argued that some
federal regulations prohibit hospitals from offering discounts and fee waivers on a
case-by-case basis,34 the Centers for Medicare and Medicaid Services (CMS)
contends that no federal law prevents hospitals from reducing or waiving charges for
an indigent uninsured patient so long as such reductions or waivers conform to the
hospital’s indigency policy. Moreover, the CMS Inspector General has stated that
it is “highly unlikely” that hospitals that waived charges to indigent uninsured
patients would run afoul of the federal anti-kickback statute.35
More detailed analysis of hospital charge and cost data shows that uninsured and
self-pay patients are charged, when confronted with the full list price, on average,
about 2½ times more than what insurers pay hospitals, and about three times
Medicare-allowable costs.36 The gap between what uninsured and self-pay patients
pay and what insurers pay hospitals appears to have widened since the mid 1980s.
How Does Hospital Price Dispersion Compare
To Other Markets?
Chargemaster prices charged by different hospitals for the same procedure can
vary wildly, as noted in Figure 1 and Figure 2. Actual charges for specific
procedures, which are generally lower than chargemaster prices, also vary widely,
although information on them is unavailable. Chargemaster prices are nevertheless
important, because they are prices billed to uninsured patients who do not have
discounts, and are the starting point for discounted prices.
Figure 3 shows the distribution of average charges per stay for normal vaginal
birth for California hospitals in 2004, which aside from newborn care is the most
common DRG.37 (The discrete data are converted into a smoothed curve using a
technique called kernel density estimation.) Average charges at the mode of the
smoothed distribution lie between $5,000 and $10,000. The distribution has a fat
right-hand tail, indicating more variation on the high side of charges than on the low
Figure 4 shows average charges per stay by hospital for heart failure and shock
in 2004. Unlike the conditions which occur at birth, heart attack victims have
34 Metropolitan Chicago Healthcare Council, Report of the Task Force on Charity Care and
Collection Practices of the Illinois Hospitals Association and the Metropolitan Chicago
Healthcare Council, September 11, 2003, available at
35 Centers for Medicare and Medicaid Services, “Questions On Charges For The
Uninsured,” available at [http://www.cms.hhs.gov/AcuteInpatientPPS/downloads/
36 Gerard F. Anderson, “From ‘Soak The Rich’ To ‘Soak The Poor’: Recent Trends In
Hospital Pricing,” Health Affairs, vol. 26, no. 3 (May/June 2007), pp. 780-789.
37 Details of the California price transparency initiative are discussed below. Because of the
way Kaiser-Permanente health plans are structured, Kaiser hospitals did not report charges
and are therefore excluded from the analysis.
substantially less time to plan their hospital stay. Indeed, the typical heart attack
victim has no time to select a hospital or to consult with his physician about
treatment options. Further, because of variation in the time spent in hospitals, the
variation of total charges per episode is much greater in the case of heart attacks, with
a handful of hospitals having average charges above $500,000.
Figure 3. Distribution of Average Charges Per Stay for
Normal Vaginal Birth
400060008000100001200016000200002400028000Average Charges Per Stay (Current Dollars)
Source: State of California, Office of Statewide Health Planning and Development, Healthcare
Information Division. Data are smoothed using two related methods, one yielding the jagged line and
the other the smooth line. Both lines represent kernel density estimates. For the jagged line the kernal
halfwidth is set at $300. For the smooth line the kernal halfwidth is set to minimize mean square error
for Gaussian distributions. Unit of observation is the hospital.
Figure 4. Distribution of Average Charges Per Stay for
15000250003500045000550006500075000100000125000140000Average Charges Per Stay (Current Dollars)
Source: See source for Figure 3. Dotted line represents kernal density estimator with halfwidth of
Implications of Hospital Price Dispersion
Does evidence on the effects of price transparency in other markets, which by
and large supports the view that better information on pricing reduces prices, imply
that greater price transparency would affect health markets in the same way, despite
the specific structures and characteristics of the health care market? Of course, how
the examples are applied depends on how pricing information is provided. For
example, allowing the public to examine charge books and data on actual average
charges at a hospital’s finance office provides more limited access than posting that
information on the Internet. Additional information could be conveyed by providing
information on the pricing of complete, but typical, procedures as well. (Selective
reporting could provide opportunities for hospitals to game the system by lowering
costs on the reported procedures and raising costs on others.) Even more information
could be conveyed by also reporting prices for the different categories of patients
(Medicare, Medicaid, uninsured, or insured by specific health plans).
One caution is that prices of goods commonly sold on the Internet also show
substantial price variation, although the degree of price dispersion may be less than
for average daily hospital charges. For example, Figure 5 shows prices for a
Samsung HP-R6372 high definition television found using two common Internet
price search engines, Froogle.com and Pricescan.com. The mode of the smoothed
distribution is slightly less than $6,000, which is slightly less than the mode for daily
average charges for normal vaginal birth. However, the right-hand tail of the
distribution of TV prices is not nearly as fat as the distribution of average daily
charges for normal vaginal birth. (Note: horizontal scales differ for each figure.)
Only one seller listed a price for the Samsung TV above $8,000, and 37 of 47 sellers
posted prices between $5,500 and $7,500. By contrast, 10 of 251 California hospitals
charged more than $9,000 per day and 33 charged less than $3,000 per day.
Figure 5. Price Distribution for a Samsung HP-R6372 HDTV
4000 6000 8000 10000 12000
Source: Searches conducted at [http://www.froogle.com] and [http://www.pricescan.com] on August
9, 2006. Price distributions smoothed using same methods as described in Figure 3.
A formal way of comparing variability of distributions with different averages
is to compute coefficients of variation. Table 3 presents statistical estimates of price
variability for two of the most common types of hospital episode as well as for a
similarly expensive consumer good, namely, a particular HDTV. The coefficient of
variation is a dimension-free measure, and thus is an appropriate tool for comparing38
different distributions. As expected, the coefficients of variation for average
hospital charges for normal birth and for heart attacks are substantially greater than
for the Samsung television.
The comparison of HDTV prices advertised by retailers and average charges per
day for a given DRG is not an “apples-to-apples” comparison. Prices advertised by
retailers do not necessarily represent actual sales prices. Posted prices on the Internet
may vary considerably, even if prices at those websites that make most of the sales
38 The coefficient of variation is the standard deviation divided by the mean (average).
Among hospitals that reported charges for both procedures the coefficient of variation for
charges per stay for Heart Failure and Shock (DRG 127) was 0.678 and 0.420 for Vaginal
Delivery w/o Complicating Diagnoses (DRG 373).
vary less.39 To the extent that most units are sold by sellers with prices near the
minimum posted price, sales-weighted measures of price variability will be less than
Table 3. Variability of Average Hospital Charges and Samsung
Vaginal Delivery w/oper day$5,280$1,9330.366242
Complicating Diagnosesper stay$10,350$4,2860.414
Heart Failure and Shock393
Samsung HP-R6372 HDTV $6,254$1,2530.20047
Source: See preceding figures. Data are for 2005.
We checked whether combined average daily charges for mother and baby
varied less than average charges for normal vaginal birth alone, which could occur
if different hospitals allocated charges to mother and baby differently. The
coefficient of variation for the sum of average daily charges for normal newborn and
normal vaginal birth, however, was about the same (.356) as for normal birth alone
(.366). The coefficient of variation for average stay charges for the sum of normal
birth and normal newborn care (.416) was nearly the same as for normal birth alone
These illustrations are just examples of pricing variability and do not constitute
a statistically valid universe. Nevertheless, they do indicate considerably more price
variability for medical procedures than for an expensive consumer durable that might
be expected to show much more variation than more frequently purchased
commodities. They also show much more variation for an unanticipated procedure
(heart failure) than for an anticipated one (birth). They are suggestive, therefore, of
a considerable amount of price variability in hospital costs.
Price Transparency Initiatives of Governments,
Insurers, and Interest Groups
Several states have enacted regulations intended to enhance price transparency
in the health sector in general, and hospital pricing in particular. Several private
insurers also allow policyholders access to online tools that allow some price
39 Erik Brynjolfsson and Michael D. Smith, “Frictionless Commerce? A Comparison of
Internet and Conventional Retailers,” Management Science, vol. 46, April 2000, pp. 563-
comparisons for medical procedures.40 California has required hospitals to provide
a variety of pricing data to the public, discussed in more detail below. Average
hospital charges per day and per stay for selected DRGs are available on state
government websites sponsored by Arizona, California, Florida, Maryland, and
Massachusetts.41 Other states, such as Iowa, New Hampshire, and Wisconsin, in
cooperation with state hospital associations, provide some pricing information.
Aetna has published price information for physicians and hospitals in the
Cincinnati area, and recently extended this program to other parts of the country.
Other insurers, including Cigna, Humana, United HealthCare, and Wellpoint have
created websites that provide price comparison data for certain procedures.42
Hospitals also submit data to the Centers for Medicare and Medicaid Services
(CMS), which compiles annual Medicare Cost Reports (MCR). The MCRs contain
extensive information about hospitals’ cost structures and finances. These reports,
which are quite large and complex, are available for download on the CMS website.
The website HospitalVictims.com provides cost data for individual hospitals derived
from Medicare Cost Reports, suggesting that hospitals with high charge-to-cost ratios
be avoided, or that the patient negotiate for a discount.43 It suggests that a high
charge-to-cost ratio is evidence of a significant amount of price discrimination and
a likelihood that the uninsured patient will be charged a high price.
Initiatives to impose price transparency requirements on hospitals, such as
allowing the public to inspect chargemaster data or have access to average daily
charges data, were motivated in part by a desire to allow consumers to make
informed choices about selecting hospitals. Better information on prices, according
to this view, would increase competitive pressure on hospitals, slowing the growth
of hospital prices and reducing price variability. These initiatives are relatively new
and do not yet appear to have had significant effects on the level and dispersion of
In August 2006, Executive Order 13410 called for greater transparency of
quality and price information and for more widespread use of information technology
in federal health care programs using compatible data standards.44 The executive
order also directed federal agencies to develop health care quality measurement
40 National Conference of State Legislatures, “State Legislation Relating to Disclosure of
Hospital and Health Charges,” April 2007, available at [http://www.ncsl.org/programs/
health/T ransparency.htm#T able1].
41 The National Conference of State Legislatures has links to the state websites, along with
many private insurers’ websites: [http://www.ncsl.org/programs/health/Transparency.htm].
43 See [http://www.hospitalvictims.com/].
44 Executive Order 13410, “Promoting Quality and Efficient Health Care in Federal
Government Administered or Sponsored Health Care Programs, August 22, 2006.
Additional information is available at the Department of Health and Human Services’s
“Value-Driven Health Care” website: [http://www.hhs.gov/transparency/fourcornerstones/
programs. The National Coordinator for Health Information Technology within the
U.S. Department of Health and Human Services oversees these initiatives, although
other offices also have major responsibilities.
The executive order directed federal agencies to “make available ... to the
beneficiaries or enrollees of a Federal health care program (and at the option of the
agency, to the public) the prices that it, its health insurance issuers, or its health
insurance plans pay for procedures to providers.” It was reported that the Bush
administration earlier in 2006 declined to release Medicare claims data to the
Business Roundtable, which had requested them.45 The Business Roundtable is an
association of chief executives of very large corporations. Whether the order
signifies a change in policy or there was another reason for not releasing these data
The effects of the executive order on pricing information are unknown,
including how widely available the information is, since the implementation of the
order is in its early stages. But it is an example of another government initiative to
provide more information about pricing.
In some areas, the initiatives outlined by the Executive Order parallel ongoing
efforts. Several federal agencies have already taken some measures to provide
federal health care users with better price and quality information. For example, the
Federal Employees Health Benefit Program (FEHBP) provides a website that
compares premiums, plan details, and customer satisfaction measures for all plans.46
Changes made in response to the order appear minor.47 CMS (Centers for Medicare
and Medicaid Services) now publishes summarized inpatient price data for the 30
most common elective DRGs for individual hospitals. These data are taken from
Medicare Provider Analysis and Review (MEDPAR) data, which has been collected
since 1991. However, locating this information on the CMS website may be difficult
for consumers since the website covers a range of material.48
Medicare’s “Hospital Compare” website, accessed via the Medicare.gov site,
allows beneficiaries to see data that compares how closely different health care
providers follow accepted treatment protocols.49 Whether such initiatives give
consumers enough relevant information in an easily accessible way, whether patients
and their families would be able to locate such information, and whether such
information would motivate patients to make major changes in their treatment plans
is unclear. One consulting firm concluded that while a previous version of the
Hospital Compare website “does an average job of presenting the quality
information, it lacks the robust data found in commercially available products and
45 Robert Pear, “Employers Push White House to Disclose Medicare Data,” New York
Times, April 11, 2006.
47 The Office of Personnel Management’s efforts to implement these initiatives are described
on its website, available at [http://www.opm.gov/insure/health/executiveorder.asp].
leaves consumers fumbling with insufficient help.”50 In June 2007 a redesigned
HospitalCompare website was launched that allows limited comparisons of hospital
mortality rates for heart failure and heart attacks with national mortality rates.51
However, nearly all hospitals were judged to have mortality rates “no different than
the U.S. national rate.” Out of almost 4,500 hospitals, only 17 were recognized as
“above average” in treating heart attacks and only seven were rated “below
On the other hand, more information about health care provider quality and
pricing is becoming available on the Internet, and these sources will continue to
evolve. A major review of information available on websites that provide hospital
price and quality information expressed concern that some consumers might be
confused rather than enlightened by the reported data, but also noted that momentum
continues to build for making health care data more easily available to consumers.53
The following section of this report presents an analysis of the California price
transparency initiative’s effect on the dispersion of hospital prices.
Does Price Transparency Reduce Price Variability?
Some Preliminary Results
The California hospital price transparency initiative, according to analysis of
available data, has had negligible or no observable effect on hospital prices.
In September 2003, California legislators passed Assembly Bill 1627,54 which
required hospitals (except for certain small and rural hospitals) to make chargemaster
data public by July 1, 2004, either in electronic form or by allowing onsite55
inspection. Sponsors of this bill contended that these reporting requirements would
50 Katy Henrickson, Hospital Comparison Tools Scorecard Summary: Centers For Medicare
And Medicaid Services: Key Findings From “The Forrester Wave: Hospital Comparison
Tools, Q4 2005,” October 13, 2005, available at [http://www.forrester.com/Research/
Docume nt/Excerpt/0,7211,37929,00.html ].
51 Hospital Quality Alliance, “HQA Adds Enhanced Hospital Quality Information to
‘Hospital Compare’ Web Site,” June 22, 2007, available at [http://www.fah.org/issues/
52 Michael S. Gerber, “Hospitals Are Beyond Compare: Data on Cardiac Care Show Almost
No Differences Nationwide,” Washington Post, July 3, 2007.
53 Delmarva Foundation, The State-of-the-Art of Online Hospital Public Reporting: A
Review of Fifty-One Websites, Report Prepared for the CMS Hospital Three State Pilot
Project, July 2005. Available at [http://www.delmarvafoundation.org/newsAndPublications/
54 Helen Sanderson, “Cost of Care: New Law Lets Patients Examine Hospital Price Lists,”
North Coast Weekly, August 11, 2005, available at [http://www.northcoastjournal.com/
55 The Wall Street Journal article, referenced in Figure 1 above, was based on these
prevent hospitals from “gouging” customers and would make patients into better-
informed consumers.56 In July 2005, hospitals had to begin submitting chargemaster
data to the Office of Statewide Health Planning and Development Healthcare Quality
& Analysis Division (OSHPD). In 2004 and 2005, hospitals also had to list charges
for 25 common services or procedures. In 2006, hospitals were required to submit
data on average charges for 25 common diagnosis-related groups (DRGs). The state
of California makes these data available online.
If patients became better-informed customers, most economists would expect
that hospitals that raised their prices more would lose patients, unless there were
offsetting increases in the quality of medical care or level of amenity.57 That is, if
customers are sensitive to and aware of prices, increases in hospital prices would be
negatively related to changes in hospital admissions, other things equal.
If consumers were becoming more sensitive to price as a result of greater price
transparency, then one might expect to see stronger effects for procedures for which
patients can plan ahead. Expectant mothers planning for a normal vaginal birth can
compare what various hospitals have to offer and their prices, unlike victims of
sudden medical emergencies. Figure 6 shows the distribution of average daily
charges (adjusted for general inflation) for normal vaginal birth at California
hospitals in 2003, 2004, 2005, and 2006. Over this time period, the modal (i.e., most
frequent) nominal price drifts upwards because average daily charges have been
rising faster than the general price level. The distribution of prices shows no signs of
chargemaster data. For further details on these requirements, see the State of California’s
Office of Statewide Health Planning and Development Healthcare Information Division’s
website at [http://www.oshpd.ca.gov/HID/Products/Hospitals/Chrgmstr/FAQ.html#Q2].
56 California State Assembly, “Bill Analysis for Assembly Bill 1627,” available at
[http://info.sen.ca.gov/ pub/ 03-04/ bi ll/asm/ab_1601-1650/ab_1627_cfa_20030527_17362
57 This also presumes that demand factors, such as demographics and income, were held
constant. Changes in these factors over the period analyzed here are likely small relative
to changes in hospital prices.
58 The same analysis was performed for average charges per stay, rather than average daily
charges. The results were nearly identical.
Figure 6. Distribution of Average Charges Per Stay For Normal Birth,
300060009000120001500018000210002400027000Average Charges Per Stay (2006 Dollars)
Source: State of California’s Office of Statewide Health Planning and Development, Healthcare Information DivisionNote: Kaiser hospitals submitted no average charge data, and so are excluded.
GDP Price Index used to convert charges into 2006 dollars. Also see notes for Figure 3.
Figure 7. Scatter Plot for Changes in Avg. Daily Charges and Discharges
for Normal Birth (DRG 373)
1-99 Discharges in 2003
Percentage Change in Discharges 2003-2006
-35% -20% 0% 20% 40% 60% 80% 100% 140%
Percentage Change in Avg. Daily Charges 2003 to 2006
Source: State of California’s Office of Statewide Health Planning and Development, Healthcare Information DivisionNotes: GDP Price Index used to convert charges into 2006 dollars.
Kaiser hospitals, which submitted no average charge data, are excluded.
State of California’s Office of Statewide Health Planning and Development, Healthcare Information Division.
Hospitals that had increased average daily charges for normal vaginal birth, on
average, did not lose patients. Figure 7 (above) presents a scatter plot with
percentage change in hospital discharges on the vertical axis and percentage change
in average daily charges on the horizontal axis. Different plotting symbols divide
hospitals into four categories defined by the number of (normal) births in 2003. If
expectant mothers avoided hospitals that raised their prices, then a downward-sloping
relationship would be evident between the two variables. Regression analysis shows
a statistically significant, albeit small, positive relationship between changes in
average charges and changes in hospital volume for normal births over the 2003-
Several explanations are possible for the lack of a discernable relationship
between changes in average charges and changes in hospital volume. Differences in
perceived quality or care or amenity levels may matter more than price for many
patients, especially if insurance coverage insulates them from prices. Patients’
relationships with their physicians and those physicians’ relationships with hospitals
might reduce patients’ sensitivity to hospital prices. Alternatively, patients may care
about prices, but might be unable, unwilling, or disinclined to examine online price
data. Finally, changes in prices might correlate to offsetting changes in quality or
amenity levels. Distinguishing among these explanations would require more
sophisticated data. However, the available evidence, while preliminary, suggests that
the California price transparency initiative so far has had little observable effect
where it might have been expected to have the greatest effect.
How Would Greater Price Transparency Affect the
Health Care Sector?
The experience of the Danish Competition Authority, noted above (in the
section titled Empirical Evidence on the Effects of Price Transparency), suggests that
imposing price transparency in negotiations between sellers and buyers of
intermediate goods does not necessarily lead to sharpened competition or lower
prices. At the same time, some evidence suggests that information about the process
of setting prices, including practices of price discrimination, may produce a change
in pricing, as in the NASDAQ and Amazon cases. Much of the remaining evidence
also suggests that transparency lowers prices and makes them more uniform.
The evidence cited on price transparency involves two types of effects: a
response through publicity effects and a response through normal market
mechanisms. The price discrimination that occurs in hospitals — brought about
partly by government policies with respect to Medicare and Medicaid, partly due to
bargaining power of insurance companies (and the desire to set high list prices to
59 One outlier was excluded. An indicator variable for Tenet Healthcare hospitals, which
Bill 1627’s sponsors claimed had aggressively sought to increase hospital prices, was
statistically insignificant. Regression results available upon request.
leave room for discounting),60 and partly through providing free care for the indigent
— leads to potentially high prices for a small segment of uninsured individuals. As
more of these pricing differences are revealed and spotlighted, public opinion might
force a reduction in cross subsidies (charging some patients higher prices to cover the
costs not fully applied to other patients).61 Indeed, such a response has already
occurred. An example is the case of the state of Minnesota, which entered into a
voluntary agreement with most of its hospitals to limit the charges for uninsured
patients. Under the agreement, uninsured patients with $125,000 or less in annual
income would pay no more than the amount paid for the procedure by the private
insurance company that provided the greatest amount of the hospital’s revenue.62
The Minnesota example suggests that publicity can affect pricing. What about
the effects through normal market mechanisms? The survey of evidence included
cases where price transparency did not affect prices, or in some instances, led to
higher prices. In addition, many of the studies analyzed goods that lack the special
characteristics of health care. These shortcomings do not, however, necessarily mean
that price transparency in the health sector would not be beneficial.
First, the ready-mix concrete example, in which price information resulted in
higher prices also involved for-profit businesses, which presumably were attempting
to maximize profits. This example may not apply to many hospitals that are non-
profit and may have different behavioral responses.63
Second, the evidence from the advertising studies includes not only simple
uniform goods such as alcoholic beverages and gasoline, but complex differentiated
products such as vision exams, where quality matters. And while insurance pays
60 See the discussion in Lucette Lagnado, “California Hospitals Open Books, Showing Huge
Price Differences,” Wall Street Journal, December 27, 2004, p. A1.
61 Cross subsidies are intra-firm transfers that support some activities or lines of business
using net revenues earned in other activities or lines of business.
62 Minnesota Hospital Association and Office of Minnesota Attorney General Mike Hatch,
“Hospitals Step Forward to Sign Voluntary Agreement with Attorney General’s Office on
Billing and Collection Practices,” June 2, 2005.
63 Objectives of not-for-profit hospitals are an important area of research in health
economics, and although there has been a presumption that any surplus might be used for
charitable care, evidence on that issue is mixed. While providing a complete review is
beyond the scope of this report, see for example, Richard G. Frank and David S. Salkever,
“The Supply of Charitable Services by Nonprofit Hospitals: Motives and Market Structure,”
RAND Journal of Economics, vol. 22, autumn 1991, pp. 430-440; and Edward C. Norton and
Douglas O. Staiger, “How Hospital Ownership Affects Access to Care for the Uninsured,”
RAND Journal of Economics, vol. 25, spring 1994, pp. 171-185. Mark Pauly once described
hospitals as “doctors’ workshops,” whose decisions were made with an eye to maximizing
the welfare of physicians. Since that time hospital administrators reportedly have become
more professional and more powerful. See Mark Pauly, Doctors and Their Workshops:
Economic Models of Physician Behavior, (Chicago: Univ. of Chicago Press, 1980). In any
case, non-profits’ objectives may differ from those of for-profit firms. Some evidence
suggests that non-profits maximize output or revenues; e.g., Richard Steinberg, “The
Revealed Objective Functions of Non Profit Firms,” RAND Journal of Economics, vol. 17,
winter 1986, pp. 508-526.
much of the cost of medical care, the studies summarized above also included
examples of price reductions for prescription drugs after direct advertising to
consumers, whose prices are also subject to third party payment.64 In these cases as
well, the evidence suggests that prices fell after advertising was permitted, without
deterioration in quality.
Third, evidence from the Internet suggested that price comparison sites may
help reduce commodity prices, including differentiated commodities that are subject
to bargaining (automobiles). Over time, price comparison websites have become
more sophisticated and are playing an increasingly important role in consumer
behavior in many markets.
Internet Price Comparison Sites
The Internet has begun to affect the availability of price information in the
health care sector, although this does not appear to have influenced a large proportion
of consumers. According to the New York Times, 32 states require hospitals to
publish price information.65 Some new websites provide consumers with data on
health care costs. For example, Vimo [http://www.vimo.com] provides information
on average list prices and average negotiated prices charged by hospitals for specific
procedures. One company, My Medical Control, provides a negotiation service for
consumers through its website [http://www.mymedicalcontrol.com]. A consumer
forwards a bill, via the website, to a claims adjuster who negotiates a reduced rate
with the provider. This company then deducts a 35% fee and returns the remainder
to the consumer. At present, such websites have little observable effect on health
care markets. In the future, however, such sites could have large effects.
The Carol.com website allows consumers to compare prices and offerings of
health providers in the Twin Cities region of Minnesota, and in addition it allows
them to book services. The intention of the website’s creators is to follow the
example of web-based booking services such as Expedia.com, which have
transformed the travel industry in the past decade. Many state governments have
opened their own sites that allow consumers to compare prices or provider
charact eri s t i cs.66
The effect of information on quality is much more difficult to obtain, and it is
hard to make a judgment based on the available evidence. As noted above, the
United Network for Organ Sharing publishes risk-adjusted outcome data on its
website [http://www.unos.org]. Some other organizations, also noted above, also
publish some data reflecting quality of health care.
64 John F. Cady, “An Estimate of the Price Effects of Restrictions on Drug Advertising,”
Economic Inquiry, vol. 44, December 1976, pp. 493-510; Steven W. Kopp, “Direct-To-
Consumer Advertising and Consumer Prescription Prices,” Drug Information Journal, vol.
65 Michael Mason, “Bargaining Down That CT Scan Is Suddenly Possible,” New York
Times, February 27, 2007.
66 Many of the state government health comparison and information sites are listed at
Will the Health Sector Change Like Other Industries?
One of the most important differences between hospital care and other
commodities is that typically patients pick physicians and physicians pick hospitals.
Although this characteristic means that direct consumer pressure to hold down prices
(or at least have a sensible pricing system) is more difficult, it does not mean that
physicians would not become more sensitive to differences in costs among various
hospitals on behalf of their patients, particularly if their patients raise questions about
these costs. Not everyone in a market is required to be attentive to price for pressure
to be exerted at the margin. Moreover, publicity about price differentials may result
in voluntary compliance by hospitals. Nevertheless, this aspect of the delivery of
hospital services makes it more difficult to apply evidence from other markets to the
expected outcome of introducing more price transparency in health care markets.
Changes in the airline industry might provide some insight into how increased
price transparency and competition could affect the hospital industry. While the air
travel and hospital industries have important structural differences, airlines, like
hospitals, have high fixed costs and offer a non-storable product. Before the Airline
Deregulation Act of 1978 (P.L. 95-504), airlines competed largely on the basis of
amenity levels rather than on price. The Airline Deregulation Act restricted the Civil
Aviation Board’s price administration powers, and led to the abolition of the board
in 1984. After deregulation, several new airlines entered the market, while several
major airlines went bankrupt and exited the market. Increasing competitive pressure
led airline companies to cut back amenities to passengers and led to contentious
negotiations with labor unions that resulted in sharply reduced wages in many cases.67
Employees with highly specialized skills, such as pilots and mechanics, appeared to
fare better in resisting wage and salary reductions compared to other employees. Air
service to some small cities, supported by implicit cross subsidies, ceased, while
service to some other small cities expanded, in part because some airlines found ways
to serve such markets at lower cost. Lower fares (in real terms) led to an enormous
expansion in air travel and increases in air travel employment. Some relatively new
airlines, such as Southwest Airlines, prospered and expanded, while other airlines
struggled, including several major carriers that declared bankruptcy.
Were price transparency to improve, and if consumer choice in health care were
to become more sensitive to price differentials, then economic analysis would
suggest that these effects would increase pressure on hospitals to become more
productively efficient, that is, to use fewer inputs to produce the same or greater
output. Cost-cutting measures would put pressure on health sector salaries and
wages, which some occupational groups would resist more successfully than others.
Services, such as indigent care, now in part supported by implicit cross subsidies,
could face cutbacks unless direct subsidies to support such services were increased.
Innovative providers, however, may find ways to expand access to health care by the
indigent using more efficient and cheaper methods. Some prices might fall, along
with amenity levels. Lower prices, in turn, could expand access to health care, and
67 U.S. Government Accountability Office, Airline Deregulation: Reregulating the Airline
Industry Would Likely Reverse Consumer Benefits and Not Save Airline Pensions, GAO-06-
to the extent that demand for medical procedures is sensitive to price, could expand
the volume of medical services provided. Some existing health care providers,
especially those unable to change their cost structures and operating procedures
quickly, would be at a comparative disadvantage to more nimble providers. Such
changes would produce both winners and losers, just as airline deregulation produced
winners and losers. Increased price transparency, however, to the extent that it
allowed health care markets to function more efficiently, would be expected to
generate more gains than losses.
Appendix: Review of Empirical Studies on Price
Pricing Reforms in Financial Markets
The effects of price transparency on how financial markets function depend on
how those markets are set up. Financial exchanges are structured as auction markets68
or dealer markets. In an auction market, such as the New York Stock Exchange
(NYSE), investors send orders to a specialist, who coordinates trading for a particular
stock. Investors can send market orders, which are to be executed immediately for
the best possible price, or limit orders, which instruct a broker to buy a stock at a set
price or to sell a stock at a set price. The specialist executes market orders by
matching them with orders from the other side of the market, or by buying or selling
on his own account. Limit orders that are not executed are entered into the
specialist’s order book. In a dealer market, such as NASDAQ, orders for a particular
stock flow to market makers who then post bids (i.e., prices at which buyers are
willing to trade) with asks (i.e., prices at which sellers are willing to trade) via an
electronic market. In NASDAQ each stock must have at least two market makers,
and for major stocks there may be 30 or more market makers.
Price transparency can mean several things in financial markets. The most basic
form of price transparency is the timely reporting of executed trades. A second form
of transparency is information about outstanding limit orders listed in a specialist’s
order book. Order book information can signal impending price movements, and a
trader with special knowledge about outstanding orders can make profits. For
example, an order book with many buy orders just above the market price and very
few sell orders may signal that the market price is about to rise, and a specialist who
buys before that rise occurs will reap profits. A third form of transparency concerns
information about how dealers or specialists handle orders. A dealer often has some
discretion in how and when orders are executed and may sometimes exploit that
discretion to earn profits at the expense of the investor who placed the order.
Past NASDAQ pricing practices illustrate the importance of the third form of
price transparency. In 1994, William Christie and Paul Schultz, two Vanderbilt
University financial economists, noticed that NASDAQ dealers almost never quoted
prices using odd eighths (i.e., 1/8, 3/8, 5/8, and 7/8) for many high-volume stocks of
companies such as Microsoft, Intel, and Apple. This practice effectively created a
quarter dollar minimum spread between sellers’ asks and buyers’ bids, which
increased the trading profits of dealers. The day after these economists issued a press
release about their findings the practice was abandoned, and spreads for several
major stocks fell by about half.69
68 For a more detailed description of the structure of modern financial markets, see Hans R.
Stoll, “Electronic Trading in Stock Markets,” Journal of Economic Perspectives, vol. 20,
no. 1 (winter 2006), pp. 153-174.
69 William H. Christie and Paul H. Schultz, “Did NASDAQ Market Makers Implicitly
Collude?,” Journal of Economic Perspectives, vol. 9, summer 1995, pp. 199-208. The U.S.
Economists often argued that collusion is difficult or impossible with large
numbers of traders. A more careful argument is that collusion depends on the ability
to make explicit or implicit agreements, and maintaining agreements may be more
difficult for larger groups. Should a large group of sellers collude, each seller has
strong incentive to increase his or her market share by making small reductions in
price. If a seller can reduce its price and increase sales without other sellers noticing,
then it will reap extra profits. For example, many members of the Organization of
Petroleum Exporting Countries (OPEC) have been suspected of making hidden side
deals which allow them to sell more oil than their OPEC quotas specify, which may
have led to softened oil prices.
In the case of NASDAQ, it appears that a very simple rule — no trading on odd
eighths — created artificially high trading spreads, which allowed dealers to reap
higher profits. Young traders reportedly were cautioned not to narrow inside spreads
by using odd-eighths, and traders who violated the no-odd-eighths convention may
have been subject to intimidation or isolation. In addition, securities dealers rely on
trades with other dealers to rebalance their inventories of stocks in order to minimize
financial risks associated with sudden price movements. If other dealers refused to
trade with a dealer who violated the pricing convention, then that dealer would be
exposed to higher levels of financial risk. Furthermore, the practice of
“preferencing” among NASDAQ dealers, which involves guaranteeing flows of
orders to preferred dealers or dealer subsidiaries, meant that order flows were less
sensitive to spreads. A dealer who violated the pricing convention in order to attract
order flow would therefore gain little additional market share because of existing
“preferencing” arrangements, which in turn reduced incentives for dealers to compete
by narrowing spreads.
While no evidence was found that this pricing convention was the result of an
explicit collusive agreement, that convention enhanced traders’ profits for many
years.70 While investors and regulators were not aware this pricing convention
existed, transparency of dealers’ prices, which were visible on trading monitors,
made enforcement of the pricing convention possible. All other dealers could
immediately observe if any dealer violated the no-odd-eighths convention.
While prices of stocks and other equities are publicly published, bond prices are
less transparent, which has put small investors at a distinct disadvantage relative to
large trading institutions. Trading of stocks is highly centralized, but except for U.S.
Department of Justice (DOJ) concluded that the even-eighths convention was “vigorously
enforced through industry-wide peer pressure, and intimidating telephone calls to, and
refusals to deal with, market makers who did not quote bid and ask prices in conformance
with the convention.” See the DOJ “Competitive Impact Statement,” U.S. v. Alex Brown
& Sons Inc., et al., U.S. District Court for the Southern District of New York, pp. 16-17.
Also see U.S. General Accounting Office, Security Market Operations: The Effects of SOES
on the Nasdaq Market, GAO/GGD-98-194, August 1998.
Treasury securities, most bond trading occurs “over the counter.”71 In the past decade
transparency of bond prices has improved. In particular, the Trade Reporting and
Compliance Engine (TRACE), which was launched by the National Association of
Security Dealers (NASD) in July 2002, reports bond trades within 15 minutes, and
covers a large portion of the fixed income and bond market.72 Before the
introduction of TRACE, some argued that improved transparency of prices would
come at the cost of reduced market liquidity, meaning that some large bondholders
or dealers would trade less frequently in order to protect proprietary pricing
information. However, the expansion of trading volume has improved or maintained
Because large traders may gain some proprietary advantage from keeping the
traded prices of bonds hidden, the advance of bond price transparency has been slow.
The European Union’s “Markets in Financial Instruments Directive,” which comes
into force November 1, 2007, requires traders to provide real-time trading data for
a wide range of financial instruments and markets.
Finance researchers contributing to the new “market microstructure” literature
have taken several approaches to analyzing the effects of price transparency. The
market microstructure approach looks at how individual traders act in financial
markets.74 In addition to the well-known Christie and Schultz work on NASDAQ,
other research has found other ways to examine the effects of price transparency. An
electronic communications network named Island discontinued displaying limit order
data in three exchange-traded funds (ETFs) in which it played a dominant role from
September 2002 to the end of October 2003 rather than comply with a regulatory
mandate. During this time period ETF prices adjusted less quickly and trading costs
rose. When Island resumed displaying limit order data, trading costs fell.75 Another
study compared trades before, during, and after the regular trading day to examine
the effects of price transparency. Trades made during the regular trading day are
immediately reported and available to all investors. Much less information is
available about trades that occur before or after regular hours, and because trade
71 Testimony of Vanguard Group Principal Christopher M. Ryon, in U.S. Congress, Senate
Committee on Banking, Housing, and Urban Affairs, “An Overview of the Regulation of thethnd
Bond Markets,” hearings, 108 Cong., 2 sess., June 17, 2004.
72 Annette L. Nazareth, SEC Commissioner, “Remarks Before the TBMA Legal and
Compliance Conference,” U.S. Securities and Exchange Commission, New York, New
York, February 7, 2006.
73 M. Goldstein, E. Hotchkiss, and E. Sirri, “Transparency and Liquidity: A Controlled
Experiment on Corporate Bonds,” Babson College working paper, 2005, available at
74 For surveys of the market microstructure literature, see Bruno Biais, Larry Glosten, and
Chester Spatt, “The Microstructure of Stock Markets,” Institut d’Économie Industrielle
(IDEI) working paper #253, Toulouse, France, May 28, 2004; and Ananth Madhavan,
“Market Microstructure: A Survey,” Journal of Financial Markets, vol. 3, no. 3, August
75 Terrence Hendershott and Charles M. Jones, “Island Goes Dark: Transparency,
Fragmentation, and Regulation,” Review of Financial Studies, vol. 18, no. 3, 2005, pp. 743-
volumes are much smaller, there are fewer prices to report. Barclay and Hendershott
found that prices are more volatile after hours, suggesting that pre-open and after-
close markets are less efficient than markets during regular trading hours.76
In some cases existing firms have beat back efforts to improve transparency in
order to keep a strategic advantage over would-be entrants. For instance, following
Mexico’s 1994 financial crisis the World Bank sought to create a credit registry,
which would list all assets pledged as collateral by borrowers.77 A credit registry
allows any lender to see what a loan applicant has already pledged in collateral, thus
giving potential lenders a better opportunity to price risk. Incumbent banks strongly
opposed creation of the registry because they could already obtain information about
lenders, while less established lenders could not. Although a credit registry would
have expanded and strengthened Mexico’s financial system, it was thwarted by banks
who feared a more competitive environment.
“Dynamic Pricing” at Amazon.com
The Internet seller Amazon.com’s “dynamic pricing” experiment illustrates how
marketing strategies can affect prices and create a consumer backlash. Dynamic
pricing is a term that has come to be used to refer to a particular type of price
discrimination. Price discrimination usually takes the form of sorting customers into
groups with different price sensitivity based on their purchasing behavior.78 For
instance, for airline fares a Saturday night stay-over requirement separates price-
insensitive business travelers from price-sensitive tourists. Price discrimination
typically raises prices for some groups and lowers them for others. In 2000, two
episodes of differential pricing by Amazon were publicized; the second episode
involved the sale of DVDs. Amazon, according to reports, used characteristics
gathered about individual customers from the Internet itself (such as whether a
customer was new to the site, what browser the customer was using and past
purchases, etc.) to charge different prices to different individuals.
Amazon stated that it was simply conducting tests, but nevertheless apologized
and promised not to do it again.79 The same availability of information that permits
individualized pricing also makes it much easier to expose such price differentials,
as occurred with the Amazon case. Once this strategy was publicized, the protests
76 Michael J. Barclay and Terrence Hendershott, “Price Discovery and Trading After
Hours,” Review of Financial Studies, vol. 16, winter 2003, pp. 1041-1073.
77 Raghuram G. Rajan and Luigi Zingales, “The Road to Prosperity: Saving Capitalism from
Capitalists,” World Bank Transition Newsletter vol. 14, July/August/September 2003, pp.
78 The Robinson-Patman Act (15 U.S.C. §13) prohibits some forms of price discrimination
for the purpose of destroying competition. Many lawyers, however, consider it difficult to
win cases based on this act. The U.S. Supreme Court (FTC v. Ruberoid Co., 343 U.S. 470,
72 S. Ct. 800, 96 L. Ed. 1081 ) contended that the language of the act was
“complicated and vague in itself and even more so in its context.”
79 This event has been discussed in many articles; see, for example, David Streitfeld, “On
the Web, Price Tags Blur,” Washington Post, September 27, 2000, p. A01.
led Amazon to cease the pricing variations and apologize. This example illustrates
that a consumer backlash against differential pricing affected pricing behavior and
provides evidence that people generally disapprove of price discrimination based on
Ready-Mixed Concrete: Intermediate Markets May Run Differently
Antitrust authorities and consumer groups have often advocated price
transparency on the grounds that consumers could more easily make comparisons
among sellers, which would sharpen competition among sellers. Competition
generally leads to greater efficiency and lower prices. Price transparency, however,
can change the workings of markets in unexpected ways, which can lead to higher
prices. For example, in 1993, the Danish Competition Authority required that all
ready-mixed concrete contracts be made public, which it hoped would stimulate
greater competition. Instead, average prices rose by 15%-20% and other factors such
as changing demand conditions played no discernable effect.81
There are two possible explanations for this unexpected increase in prices.
First, public prices make collusion among sellers easier. Rivals can observe sellers
who undercut their competitors, who may be able to mete out punishments in various
ways. Second, price transparency may alter the strategic incentives of sellers,
inducing them to become tougher bargainers. Hviid and Møllgaard, motivated by
the Danish concrete case, developed a model in which different buyers negotiate with
a seller of an intermediate good.82 Some buyers are better informed than others,
which makes them tougher bargainers. If less-informed buyers can observe prices
negotiated by more-informed buyers, then the seller will become less willing to offer
lower prices to the informed buyers. This happens because the seller understands
that by offering an informed buyer a better price creates an obligation to offer less-
informed buyers a better price. Thus, in this model greater price transparency, in the
sense that less-informed buyers are allowed to see prices negotiated by informed
buyers, can actually increase average prices. The underlying logic resembles that of
price discrimination, where different prices are charged to different groups of
consumers, with lower prices for those who are more sensitive to price. In this model
buyers differ in their bargaining power, whereas in standard price discrimination
models consumers differ in price sensitivity. Bargaining power and high price
sensitivity are related because both depend on the availability of good alternatives.
More generally, some competition experts argue that some exchanges of
information about production costs or prices among sellers often have anti-
competitive effects. In particular, flows of information among firms can make
80 This may depend on how price differences are described. For instance, although senior-
citizen discounts are common and uncontroversial, a surcharge for children and working age
adults, which would have the same effect, might be a controversial pricing policy.
81 Svend Albaek, Peter Møllgaard, and Per. B. Overgaard, “Government Assisted Oligopoly
Coordination? A Concrete Case,” Journal of Law and Economics, vol. 45, December 1997,
82 Morten Hviid and H. Peter Møllgaard, “Countervailing Power and Price Transparency,”
CIE discussion papers 2000-01, University of Copenhagen, Department of Economics, 2000.
coordination or collusion easier, as the cases of the Danish ready-mix concrete and
the NASDAQ odd-eighths pricing convention suggest. On the other hand, flows of
information to buyers make price comparisons among sellers easier and thus make
consumers more sensitive to prices. Therefore, in general giving firms better price
or cost information about other firms may harm competition, but giving consumers
better price or cost information may enhance competition.83
The Hviid and Møllgaard model in some ways resembles the negotiations
between hospitals and insurers. Hospitals engage in negotiations with private
insurers, which make about one-third of hospital payments. Some insurers are in a
stronger bargaining position than others due to better data analysis, larger size, or
managerial talent. The Hviid and Møllgaard model and the Danish experience with
price transparency in the concrete market suggest that it is not inevitable that greater
price transparency in hospital markets would lead to lower average prices. Most of
the evidence discussed below, however, suggests that for a variety of markets more
information on prices leads to lower overall prices.
Restrictions on Advertising
In determining the effects of greater price transparency, restrictions on
advertising which vary across jurisdictions or across time can provide evidence on
the effects, as advertising can make price comparisons easier. Advertising has
sometimes been banned for some goods and services. For example, many states
prohibited lawyers and other professionals from advertising prices. In general, most
studies that examined prices across jurisdictions that restricted or permitted
advertising found lower prices in those jurisdictions that permitted advertising.
Some studies also examined changes over time, involving a control group, which
allows a simple method of controlling for other variables. The findings of this body
of evidence may provide important insights about how improving price information
for consumers in the health sector, where price-oriented advertising is uncommon
and basic information about prices is often unavailable or difficult to obtain, might
affect the level and dispersion of prices.
An important consideration is distinguishing between voluntary advertising and
restrictions by a third party. Also, for some types of commodities, it is possible that
low prices signal inferior quality. The clearest test of the effect of advertising occurs
when a third party (usually the government) prevents advertising. Note that many of
the studies discussed below are older because most advertising bans no longer exist,
although their findings remain relevant.
Vision Exams and Eyeglasses. Several of the studies that compared
effects across jurisdictions focused on optometry and the pricing of vision exams and
83 Per Baltzer Overgaard, “Market Transparency, Information Exchange and Competition,”
presented at the workshop on Competition Strategies and Competition Law hosted by the
Center for International Economic Law and Department of Economics, Swedish School of
Economics and Business Administration, Helsinki, October 14, 2003, available at
[ h t t p: / / www.econ.au.dk/ vi p_ht m/ pover gaar d/ pbohome/ webpape r s / t r a n s p c o mp h e l s i n ki .pdf]
eyeglasses, as past rules restricting advertising varied across states. Benham84
examined the effects of advertising on eyeglasses by comparing prices paid in states
with and without advertising restrictions in 1963. He first pointed out that the effect
of advertising is theoretically ambiguous, as it may increase demand as well as
competition. Subsequently, he separated the sample into states that permitted no
advertising, that permitted advertising but not price advertising, or that permitted any
type of advertising. He found the lowest prices in states with no restrictions, but also
some benefit from advertising without price advertising. Overall, complete
advertising restrictions caused prices to be higher by 25% or more. In two
subsequent studies Feldman and Begun compared prices for vision examinations,
controlling for quality (using length of exam and office equipment).85 In the first
study they found that state bans on price advertising by either opticians or
optometrists had an insignificant effect on prices, but prices were higher by 16%
when advertising was banned for both. In the second study they found that prices
were higher by 11% when state governments and state optometry boards imposed
bans. This study also indicated that the variance of prices increased with advertising
restrictions. Maurizi and Moore found that eyeglasses and contact lenses are less
expensive “if the optician or optometrist provides price information by telephone and
advertises outside the telephone book.”86
Bond, Kwoka, Phelan, and Whitten87 report the results of an experiment where
survey interviewers were sent to report on both the prices and characteristics of
vision exams and eyeglasses and outcomes measured by an examination of the
quality of the eyeglasses and evaluation of prescriptions. The study found that prices
were lower in cities where advertising was restricted and chain firms did not operate;
quality was about the same. Kwoka88 studied exams by optometrists, dividing the
observations into cities where advertising was not allowed, and cities where it was,
which included non-advertisers who practice in professional-looking offices, those
who do not advertise but have prominent signs in storefronts, small firms who are
affiliated with firms that do advertise, and those who advertise heavily. This study
found that advertisers offered lower prices than non-advertisers and also that non-
84 Lee Benham, “The Effect of Advertising on the Price of Eyeglasses,” The Journal of Law
and Economics, vol. 25, October 1972, pp. 337-352.
85 Roger D. Feldman and James W. Begun, “The Effects of Advertising Restrictions:
Lessons from Optometry,” Journal of Human Resources, vol. 13, 1978, pp. 247-262; “Does
Advertising of Prices Reduce the Mean and Variance of Prices?” Economic Inquiry, vol. 18,
July 1980, pp. 487-492.
86 Alex R. Maurizi and Ruth L. Moore, “The Impact of Price Advertising: The California
Eyewear Market After One Year,” Journal of Consumer Affairs, vol. 15, no. 2, 1981, pp.
87 Ronald S. Bond, John E. Kwoka, Jr., John J. Phelan, and Ira Taylor Whitten, Effects of
Restrictions on Advertising and Commercial Practice in the Professions: The Case of
Optometry, Federal Trade Commission Staff Report, Washington, DC, U.S. Government
Printing Office, September 1980.
88 John E. Kwoka, “Advertising and the Price and Quality of Optometric Services,”
American Economic Review, vol. 74, March 1984, pp. 211-216.
advertisers in non-restricted markets offered lower prices than firms in restricted
markets, but the differences were not nearly as large.
Time spent in the exam provides a proxy measure for quality. Optometrists that
advertised spent less time in exams, but non-advertisers in markets in which
advertising was allowed spent more time in exams than those in markets with
advertising restrictions. These findings suggest that high quality service is not
endangered by advertising. Overall, the analysis found quality was higher and price
lower when advertising was permitted. Haas-Wilson89 explored other restrictions on
optometrists, but found media advertising reduced average prices and no effect on
quality. Haas-Wilson and Savoca,90 who analyzed survey data collected by the
Federal Trade Commission, found that advertising restrictions on optometrists had
no effect on the quality of contact lens outcomes.
Prescription Drugs. Restrictions on advertising prescription drugs,
according to some research, also lead to higher prices. In 1976, Cady91 found that
prescription drug prices were 4.3% higher on average in states restricting advertising
of prices than in states allowing such advertising. The restrictions examined included
limitations on outdoor signs with information identifying the products and prices
offered by the pharmacy, prohibitions on implying the pharmacy has discount drugs,
prohibitions on price advertising, and prohibitions of promotional schemes such as
senior citizens’ discount. He also found that the quantity of prescription drugs
bought was unaffected. Cady found no evidence that advertising or lower prices
would increase the consumption of drugs, as supporters of advertising restrictions
had contended. (This result would not necessarily apply to drug manufacturers’
current advertising to consumers that promotes potential benefits of drugs, but does
not advertise prices.) Kopp analyzed how the initiation of direct-to-consumer
advertising affected retail drug prices from 1986 through 1992. He found that
average retail margins of 13 drugs that were advertised fell on average by 40% after
the introduction of direct-to-consumer advertising, while the change in average price92
for 120 drugs that were not advertised did not fall.
Gasoline. The final set of cross section studies related to restrictions on
posting gasoline prices. In 1972, Maurizi93 compared prices in cities with ordinances
against posting large signs advertising price at gasoline stations and found that
ordinances against the signs increased the variation in prices, but reduced the average
89 Deborah Haas-Wilson, “The Effect of Commercial Practice Restrictions: The Case of
Optometry,” Journal of Law and Economics, vol. 29, April 1986, pp. 165-186.
90 Deborah Haas-Wilson and Elizabeth Savoca, “Quality and Provider Choice: A
Multinomial Logit-Least-Squares Model with Selectivity,” Health Services Research, vol.
91 John F. Cady, “An Estimate of the Price Effects of Restrictions on Drug Advertising,”
Economic Inquiry, vol. 44, December 1976, pp. 493-510.
92 Steven W. Kopp, “Direct-To-Consumer Advertising and Consumer Prescription Prices,”
Drug Information Journal, vol. 30, 1996, pp. 59-65.
93 Alex R. Maurizi, “The Effect of Laws Against Price Advertising: The Price of Retail
Gasoline,” Western Economic Journal, vol. 10, October 1972, pp. 321-329.
price. He considered the price differences unimportant because he was unable to
completely control for discounts in wholesale prices in areas subject to price wars,
but did consider the variation evidence that restrictions on signs reduce competition.
A subsequent critique by Marvel94 argued that Maurizi’s results were not valid
because of a statistical issue, except for premium gasoline. A subsequent study by
Maurizi and Kelly,95 with access to a more extensive database, indicated that posting
prices reduced prices.
Alcoholic Beverages. Two studies analyzed changes in restrictions on
advertising and alcoholic beverages. Luksetich and Lofgreen96 examined the effect
of an accidental repeal of liquor advertising restrictions in Minnesota, which led to
an ability to post prices and distribute price lists. The result was a decline in price
and slightly more variability in price. This latter effect was not predicted by the
simple theory; however, the authors suspect it arose from abandoning wide usage of97
the manufacturer’s suggested retail price. Milyo and Waldfogel found that when
restrictions on advertising in Rhode Island were eliminated, advertising stores cut
prices on products they advertised and on products advertised by rivals. Non-
advertising stores did not change prices, and advertising stores did not change prices
of items not advertised. Also stores with the initial lower prices were more likely to
advertise, and advertising stores drew more consumers.
Availability of Consumer Price Information. Some studies were also
done on changes in information. Two studies related to food prices. Glazer98 used
the 1978 newspaper strike in New York City to examine the pattern of price
movements compared to neighboring jurisdictions on several commodities whose
prices could easily be altered, such as produce and meat. He found that prices went
up in stores that normally advertised in the newspapers, relative to stores in other
jurisdictions and to stores that did not advertise. He found the effects relatively small
and that they declined over time, speculating that individuals may have found other
sources of information on prices, such as radio. Grant and Devine99 used an
experiment in two Canadian cities where, in one city, price lists for a market basket
of supermarket goods were provided via newspaper advertising and by direct mail to
a sample of consumers, while this information was not provided in the other city.
94 Howard P. Marvel, “Gasoline Price Signs and Price Behavior: Comment,” Economic
Inquiry, vol. 7, January 1979, pp. 146-149.
95 Alex R. Maurizi and Thom Kelley, Prices and Consumer Information, American
Enterprise Institute, Washington, DC, 1978.
96 William Luksetich and Harold Lofgreen, “Price Advertising and Liquor Prices,” Industrial
Organization Review, vol. 4, 1976, pp. 13-25.
97 Jeffrey Milyo and Joel Waldfogel, “The Effect of Price Advertising on Prices: Evidence
in the Wake of 44 Liquormart,” American Economic Review, vol. 89, December 1999, pp.
98 Amihai Glazer, “Advertising, Information and Prices — a Case Study,” Economic Inquiry,
vol. 19, October 1981, pp. 661-671.
99 D. Grant Devine and Bruce W. Marion, “The Influence of Consumer Price Information
on Retail Pricing and Consumer Behavior,” American Journal of Agricultural Economics,
vol. 62, May 1979, pp. 228-237.
The study found that supermarket prices fell in the city with the advertising and mail
data compared to the city without it. Food prices eventually declined by 7%, and the
variation also declined. Prices began to rise when the public information program
Product Quality Information. Examining the effect of information on100
product quality is difficult. We summarize two related studies. Mathios examined
the effect of mandatory nutrition labeling on salad dressings. Low fat products
advertised fat content on a voluntary basis, but high fat products (which varied in fat
content) did not. Following the mandatory labeling, sales in the highest fat products
declined significantly, suggesting that consumers used the information to make more
desirable choices. Jin and Leslie101 studied hygiene report cards for restaurants. In
1997, a Los Angeles television program showed unsanitary conditions in some
restaurants. Los Angeles County officials responded by requiring restaurants to post
hygiene quality grade cards. Incorporated cities in the county, however, retained the
power to pass their own regulations. In cities that delayed requiring restaurants to
post report cards, restaurants could display voluntarily hygiene report cards once an
inspection occurred. The authors, by analyzing variations in the timing of
implementation of the report card requirement, found evidence that the displaying
cards increased hygiene scores, but were concerned that this may have reflected
“grade inflation.” However, they also found an increase in revenues and a decrease
in food-borne illnesses in the areas posting hygiene scores, compared to other areas.
Search Costs and the Internet
In some markets consumers obtain price information with difficulty or at high
cost. For example, car buyers traditionally have had to negotiate with car dealers in
person. Obtaining a price quote from a dealer can therefore require several hours of
effort, from identifying local dealers, traveling to the dealer’s lot, and negotiating
with salesmen and finance specialists. When obtaining price information is costly,
a consumer may settle for a given firm’s price, even though further search might have
identified a firm with lower prices. The economic theory of search describes a
consumer’s optimal strategy when obtaining price quotes is costly. A consumer gets
a price quote, then either decides to search further or to settle for one of the price
quotes he has in hand. An optimal search rule balances the cost of obtaining an102
additional price quote against the expected gains of further search. If a consumer
has previous experience in the market, and knows something about the distribution
of prices, then computing an optimal stopping rule for a search is straightforward.
If the distribution of prices is unknown, then no known optimal stopping rule exists.
100 Alan D. Mathios, “The Impact of Mandatory Disclosure Laws on Product Choices: An
Analysis of the Salad Dressing Market,” Journal of Law and Economics, vol. 48, October
101 Ginger Zhe Jin and Philip Leslie, “The Effect of Information on Product Quality:
Evidence From Restaurant Hygiene Cards,” Quarterly Journal of Economics, vol. 118, no.
102 Search theory was initiated by George Stigler’s article, “The Economics of Information,”
Journal of Political Economy, vol. 69, June 1961, pp. 213-25.
In search theory models, firms cannot price discriminate, but consumers still pay
different prices. On average, consumers who search more pay lower prices. Because
consumers have different costs of search, different firms will offer different prices.
Firms with higher prices earn higher markups on a smaller number of sales, while
firms with lower prices have smaller markups but a higher number of sales. If search
costs for consumers fall, then both average prices and price dispersion fall.
Prices and the Internet. Many economists expected that the Internet, which
enabled the emergence of cheap and efficient price searching mechanisms, would
lead to lower prices. Some studies, conducted when the Internet use had just started
to spread to the general public, found higher prices online, although later studies
tended to show some price reductions. Pricing and marketing techniques have
changed as the Internet has evolved, often in different ways for different markets. In
addition, studies of Internet pricing have become more sophisticated over time. In
general, later studies, and studies of comparison sites, tend to find lower prices as a
result of the Internet.
Cars. Lee103 studied an electronic automobile auction network in Japan and
found that prices can be higher than in more traditional markets, even after
controlling for quality. This effect might be attributable to the reduction in
transaction costs and the better matching of desired car type. In two papers,
Settlemeyer, Morton, and Silva-Risso104 examined the effect of the Internet on car
prices and found that prices were lower for direct Internet buying. Buyers referred
to offline dealerships also paid lower prices, apparently because additional
information increases bargaining power and because of the referral service.
Books and CDs. Bailey,105 in one early Internet pricing study, found that
prices for books, CDs, and software in 1996 and 1997 were higher online than in
conventional outlets. Brynjolfsson and Smith,106 however, studying a later period and
using a more sophisticated methodology, found prices for books and CDs on the
Internet were 9% — 16% lower than prices in conventional outlets. Although posted
Internet prices showed considerable dispersion, so that an unweighted measure of
price variation for Internet sellers exceeded that for conventional sellers, prices
weighted by market share varied less than conventional sellers’ prices. This effect
occurred because sales at a few Internet booksellers, whose prices were relatively
103 H.G. Lee, “Do Electronic Marketplaces Lower the Price of Goods?” Communications of
the ACM, vol. 41, January 1998, pp. 73-80. (Based on a review on the ACM website by S.
Srinivasan at [http://portal.acm.org/citation.cfm?id=268122&coll=portal&dl=ACM].)
104 Florence Settlemeyer, Fiona Scott Morton, and Jorge Silva-Risso, “Cowboys or Cowards:
Why are Internet Car Prices Lower?” mimeo, November 2005 (also appeared as National
Bureau of Economic Research Working Paper 8667, December 2001); and “How the
Internet Lowers Prices: Evidence from Matched Survey and Auto Transaction Data,”
National Bureau of Economic Research Working Paper 11515, August 2005.
105 Joseph Bailey, Electronic Commerce: Prices and Consumer Issues for Three Products:
Books, Compact Discs, and Software (Paris: OECD, 1998).
106 Erik Brynjolfsson and Michael D. Smith, “Frictionless Commerce? A Comparison of
Internet and Conventional Retailers,” Management Science, vol. 46, April 2000, pp. 563-
close to one another, comprised a large proportion of book sales. Clay, Krishman,
Wolff, and Fernandes,107 in 2001, found that book prices were no lower on the Web
than at physical booksellers. They also found evidence of product differentiation,
given the higher prices charged by Amazon, compared to both Barnes & Noble
online and Borders online. Goolsbee and Chevalier108 found significant price
variability for books on the Internet. Waldfogel and Chen109 found that those who
used price comparison sites reduce their shopping at branded retailers, such as
Amazon, by a tenth if performing price comparison, and by a fifth if comparing both
price and quality. Price comparison site users reduced purchases from Amazon and
from offline chains.
Airline Travel. Verlinda and Lane110 found an increase in unrestricted airline
fares relative to restricted fares as Internet price searches increased, but this
difference was statistically insignificant. Over the time period of this study the share
of restricted tickets decreased substantially. This trend, on which the authors did not
focus, could be interpreted as an increase in quality, as it allows more travelers
flexibility in their travel plans. In addition, airline fares had long been subject to
comparison through travel agents, which means the increase in information may not
have been as great for this product as for other products. Clemons, Hann, and Hitt
found similar tickets on different sites in 1997 varied on average by 18%.111 By
2002, Chen found these differences had narrowed to 0.3%-2.2% for fares available
at multiple travel websites.112 This convergence appears to stem from several major
changes in the air travel market. First, the launch of several online ticket agencies
and airlines’ efforts to promote their own direct ticketing websites have substantially
changed the online travel market. Between 1997 and 2002, use of online travel
agencies increased elevenfold. Second, more consumers buy air tickets on the113
Internet. According to one recent estimate, 60% of travelers buy tickets on-line.
107 Karen Clay, Ramayya Krishman, Eric Wolff, and Danny Fernandes, “Retail Strategies
on the Web: Price and Non Price Competition in the Online Book Industry,” Journal of
Industrial Economics, vol. 49, December 2001, pp. 521-540.
108 Austan Goolsbee and Judith Chevalier, “Measuring Prices and Price Competition Online:
Amazon and Barnes & Noble,” National Bureau of Economic Research working paper 9085,
109 Joel Waldfogel and Lu Chen, “Does Information Undermine Brand? Information
Intermediary Use and Preference for Branded Web Retailers,” National Bureau of Economic
Research working paper 9942, September 2003.
110 Jeremy A. Verlinda and Leonard Lane, “The Effect of the Internet on Pricing in the
Airline Industry,” working paper, November 2004, available at [http://www.ags.uci.edu/
111 E.K. Clemons, I. Hann, and L.M. Hitt, “Price Dispersion and Differentiation in Online
Travel: An Empirical Investigation,” Management Science, vol. 48, no. 4, 2001, pp. 521-39.
112 Jihui Chen, “Difference in Average Prices on the Internet: Evidence from the Online
Market for Air Travel,” Economic Inquiry, vol. 44, no. 4, October 2006, pp. 656-670.
113 Ibid., p.656.
Life Insurance.Brown and Goolsbee114 found that the appearance of Internet
sites which allowed for comparisons among term life insurance policies led to
significant decreases in prices. This study found that an increase in the share of
individuals using the Internet comparisons of 10% led to a 5% decrease in price.
Summary of Internet Studies. The evidence from Internet studies is mixed,
and it is, of course, possible that Internet purchasers are willing to pay higher prices
to purchase on the Internet because of the reduction in transactions cost or other
The characteristics of the Internet as it evolves have complex effects on
marketing and pricing strategies. The Internet is well suited to increasingly
sophisticated price comparison tools, which tend to reduce prices and price
dispersion for those who use them. The evidence on the use of comparison sites (as
opposed to direct sales on the Internet), which may be most relevant to the question
at hand, seems to suggest that having access to direct price comparisons reduces
prices when consumers use price comparison sites. Baye and Morgan contend that
prices reached via price comparison sites are lower than prices obtained directly from115
a vendor’s website.
On the other hand, some Internet characteristics make entry of new firms
difficult. Internet traffic patterns show strong winner-take-all features: a small
number of websites account for a large proportion of total traffic. Designing,
building, and maintaining a major retail website are expensive tasks. Some Internet
sellers have been able to establish strong brand identification that permits higher
prices. Because of these characteristics, in some product markets a few dominant
firms may be able to maintain substantial market power in the Internet Age. Highly
visible firms, however, can be vulnerable to public pressure, as the case of Amazon’s
dynamic pricing experiment illustrates.
Empirical Research on Price Transparency: Conclusions
Most research suggests that when better price information is available prices for
goods sold to consumers fall. The largest and most straightforward body of evidence
relates to the effect of advertising, where nearly all research indicates advertising
prices is associated with lower prices. This reduction in prices suggests that
advertising’s increased information on prices and increases in competition outweigh
any tendency to increase prices through increasing demand and brand identification.
Evidence on price comparison sites on the Internet also seems to support this view.
(Again, this conclusion may not apply to current manufacturers’ drug advertising that
does not include price information.)
114 Jeffrey R. Brown and Austan Goolsbee, “Does the Internet Make Markets More
Competitive? Evidence from the Life Insurance Industry,” Journal of Political Economy,
vol. 110, June 2002, pp. 481-507.
115 Michael R. Baye and John Morgan, “Information Gatekeepers and Price Discrimination
on the Internet,” Economic Letters, vol. 76, no. 1 (June), pp. 47-51.
Evidence for markets in intermediate goods is more complicated. When
middlemen are involved the effects of price transparency depend on the particulars
of market structure. Price transparency gives buyers and sellers important
information about the true economic value of goods, services, or assets, but may also
enable traders to observe deviations from collusive practices. Allowing weaker
bargainers to see prices negotiated by stronger bargainers will change incentives
facing buyers and sellers, and can lead to price increases. In financial markets dealers
need to trade with other dealers on a frequent basis to rebalance portfolios and take
actions to maintain liquidity, which leads to a complex relationship among price
transparency, trading costs, and market efficiency. Studies in experimental financial
economics suggest that price transparency can either increase or decrease prices.116
In short, how price transparency affects intermediate goods markets is an active area
of research, and settled conclusions have not yet been reached.
In traditional economic theory consumers react to price differences because
lower prices mean that consumers can buy more goods and services. The
unwillingness of consumers to pay higher prices imposes market discipline upon
firms. Other mechanisms, however, may act to discipline firms as well. Firms that
charge unusually high prices may face political or legal pressure. For example,
sellers of gasoline may face complaints of price gouging with sharp price increases,
as happened in some states following Katrina.117 Also consumers are willing to
punish firms by not doing business with them, even if this action reduces the welfare
of consumers. For example, many consumers reported that they had resolved not to
buy from Amazon.com after experiencing “dynamic pricing,” even if this meant that
they would pass up advantageous offers in the future.118 NASDAQ spreads narrowed
not because of consumer pressure, but because NASDAQ administrators feared
adverse media coverage and lawsuits filed by investors and regulators. Thus, price
transparency may impose discipline upon firms, even if this occurs through non-
116 For instance, Glosten notes that one experimental study found that “transparency involves
lower spreads and more ‘efficient’ prices,” while another study found that “transparency
involves lower spreads and less ‘efficient’ prices (emphasis added).” See Lawrence R.
Gloten, “Introductory Comments: Bloomfield and O’Hara, and Flood, Juisman, Koedijk, and
Mahieu,” Review of Financial Studies, vol. 12, no. 1, 1999, pp. 1-3.
117 James McPherson, “Retail Gas Prices Jump, Deliveries Falter as Katrina’s Energy Effects
Spread,” September 1, 2005, available at [http://www.signonsandiego.com/news/nation/
118 David Streitfeld, “On the Web, Price Tags Blur,” Washington Post, September 27, 2000,