meyer.p65


A Tool to Assess Journal Price Discrimination  269

A Tool to Assess Journal Price 
Discrimination1 

Richard W. Meyer 

This econometric study tests pricing practices of publishers and their 
monopoly power. It suggests that traditional publishers will retain their 
market clout as they shift to offering electronic publications. Librarians’ 
common experience with price discrimination was corroborated by a 
powerful model comparing prices charged to institutions while holding 
constant for production costs, source of publication, discipline areas, 
and the availability of titles in electronic format. The model also provides 
a robust selection tool to compare actual prices to model-predicted prices 
among the subscriptions within any given collection and to predict those 
that, statistically, are significantly overpriced. The study results reveal 
that commercial publishers are not the only ones that appear to over­
price titles by a statistically significant amount. Campuses face contin­
ued increases in prices for traditional and electronic resources, but sta­
tistical modeling offers an opportunity for controlling costs. 

ibrarians decide whether to ac- sis of the prices of selected titles can be a 
quire or retain a subscription to powerful way to overcome the negative 
any given serial based on three impact of publisher monopoly power on 
variables: relevance, quality, the expenditure pattern of libraries. 

and price. Comparing its general theme 
to the academic program determines the 
relevance of a journal. A strong correlation 
between the subject of the journal and the 
disciplines covered by the relevant pro­
gram tends to support a favorable deci­
sion. The quality of a title likely will be 
determined subjectively or be dependent 
on survey information and reputation in 
the field. A determination of high quality 
also will tend to support acquisition. These 
two variables are not readily amenable to 
quantitative analysis, but price is. In fact, 
as this article shows, an econometric analy-

Economic theory predicts that when 
barriers to entry diminish, monopoly 
power is eroded by the entry of new com­
petitive products. This means that as mo­
nopoly power diminishes, prices tend to 
be established at rates closer to the value 
placed on them by libraries. By compari­
son, the open systems architecture ap­
proach taken by IBM in the early days of 
the development of the personal com­
puter (PC) market provided opportuni­
ties to many upstart firms that success­
fully emerged with competitively priced 
computers. In contrast, the closed archi-

Richard W. Meyer is Dean and Director of Libraries at the Georgia Institute of Technology; e-mail: 
richard.meyer@library.gatech.edu. Mr. Meyer was Director of the Library at Trinity University in San 
Antonio when this project was conducted. The author gratefully acknowledges the financial support of the 
Andrew W. Mellon Foundation for underwriting this study and for the work of Tanya Pinedo, who as­
sembled the data for the project. Any errors remain those of the author. 

269 

mailto:richard.meyer@library.gatech.edu


270 College & Research Libraries May 2001 

tectural approach applied by Apple Com­
puter imposed a barrier to entry that, over 
time, dampened the growth of the mar­
ket and kept prices high for their alterna­
tive technology. 

Extending this theory to the journal lit­
erature suggests that perhaps the oppor­
tunity provided by electronic technology 
will lower the barriers to entry of new 
journals. In effect, because it might be 
easier for new scholarly journals to get 
started by using desktop publishing tech­
nology, the lowered barriers offered by 
this technology would erode the mo­
nopoly power held by the major print 
publishers. Indeed, desktop publication 
technology, along with major improve­
ments in digital storage capacity, has 
proved effective as a means of introduc­
ing new periodicals. However, new tech-

Because most publishers offer some 
products in print only and others 
within the described electronic set, 
the prices of the electronic version 
might be expected to reflect an 
erosion of monopoly power. 

nology also has been more effective in 
allowing existing print journals to offer 
electronic counterparts. In less than a de­
cade, more than a thousand peer-re­
viewed electronic journals have been in­
troduced to the scholarly environment. 
ARL’s Directory of Electronic Journals, 
Newsletters, and Academic Discussion Lists 
listed 417 peer-reviewed titles in 1996.2 

That figure grew to 1,049 in 1997, with 
hundreds of existing print titles expand­
ing their outreach in electronic versions. 

This rapid expansion of the e-journal 
market suggests that, indeed, there may 
be cost advantages in the electronic envi­
ronment that offer substance to the hope 
that periodical price inflation might come 
under control. Alternatively, expanded 
profit opportunity also might motivate a 
move to offer electronic periodicals 
among traditional publishers. With that 
in mind, the author designed an experi­
ment to determine whether price inflation 

might be dampened by electronic schol­
arship. The rest of this article describes 
the results of an econometric analysis of 
prices for 859 periodical titles for three 
consecutive years. The article concludes 
with a description of an analytical tool 
that may be used to assess journal prices. 

Economic Theory and Model 
To analyze the effects of electronic avail­
ability on journal price, a straightforward 
model was established that applied ordi­
nary least squares (OLS) regression on 
cross-sectional data similar to analyses 
reported by others.3 Earlier models typi­
cally regressed price on a number of vari­
ables to distinguish the statistical rel­
evance of publisher type in determining 
price.4 Not only do these studies confirm 
librarians’ belief that certain publishers 
practice price discrimination, but they 
also show that periodical prices are driven 
by other factors, as well. The costs of pro­
duction based on frequency of issue, 
number of pages, and presence of illus­
trations impact price. The availability of 
alternative revenue from advertising and 
the exchange rate risk for foreign publish­
ers also affect price. Quality measures on 
the content, such as number of times a 
periodical is cited, affect demand, which 
then impacts price. Production economies 
of scale available to some journals with 
large circulation also have been shown to 
affect price.5 

Additional work using an alternative 
model examined the possibility that pub­
lishers exercise monopoly power in set­
ting prices. By substituting a measure of 
monopoly power in place of price, it has 
been shown that publishers have some 
ability to influence price.6 Theory predicts 
that in a competitive market, even when 
it is characterized as monopolistic com­
petition, the price offered to individuals 
will be elastic.7 Faced with a change in 
price of the subscriptions purchased from 
her or his own pocket, a scholar will act 
discriminably. Raise the price to individu­
als, and some will cancel their subscrip­
tions in favor of access to a library. Thus, 
the price of periodicals to individuals is a 



A Tool to Assess Journal Price Discrimination 271 

determinant of demand for library ac­
cess.8 In contrast, the price to libraries, 
which is often much higher than the price 
to individuals, is set at a level intended 
to extract consumer surplus. The differ­
ence in these prices should offer a reason­
able measure of the extent of monopoly 
power, assuming that the individual sub­
scription price is an acceptable proxy for 
the marginal cost of production.9 Even if 
not completely true, some measure of 
monopoly power is represented by the 
difference in the prices. If a dummy vari­
able is then included in the data set for 
whether each journal is available elec­
tronically, this measure should vary sta­
tistically on that dummy. 

By modifying the earlier models, the 
analysis here seeks to determine whether 
monopoly power may be eroded in the 
electronic market. The methodology ap­
plied uses two specifications for an OLS 
regression model. The first regresses in­
stitutional price on the characteristics of 
a set of journal titles held by Trinity 
University’s library. The data set devel­
oped is considerably larger than those 
used in previous studies. Therefore, this 
study attempts to confirm the earlier 
works that concentrated on economics or 
chemistry journals across a larger set of 
disciplines. The specification includes the 
variables established earlier: frequency of 
publication, circulation, pages per year, 
and several dummy variables to control 
for whether the journals contain adver­
tising and for country of publication. 
Dummy variables are included for type 
of publisher, with the residual being com­
mercial. A second specification regresses 
the difference in price for libraries com­
pared to individuals on the same set of 
variables. Both specifications also include 
an additional dummy for electronic avail­
ability, which is intended to show 
whether price or monopoly power of 
given journals is driven in part by that 
publishing opportunity.10 

It is anticipated that at the margin, the 
impact on publishers of Trinity canceling 
some of its print subscriptions would be 
trivial. However, national availability of 

the electronic versions could precipitate 
cancellations among many institutions in 
favor of electronic access. Prices then 
would be adjusted accordingly. Because 
most publishers offer some products in 
print only and others within the described 
electronic set, the prices of the electronic 
version might be expected to reflect an ero­
sion of monopoly power. Thus, the cross-
sectional data would capture the effect of 
electronic availability on monopoly power. 

The larger data set used here, com­
posed of 859 periodical titles represent­
ing nearly all the academic disciplines, 
mitigates several concerns experienced by 
other investigators. The only study found 
in the literature thus far that looks at pub­
lishers from the standpoint of the exer­
cise of monopoly power focused on price 
discrimination.11 This project extends that 
analysis in two ways. First, a much 
broader database is used. Most of the pre­
vious work focused on limited data sets 
of fewer than a hundred titles in a single 
academic discipline. Second, the analysis 
is extended by assuming the existence of 
price discrimination given the difference 
in price to individuals versus libraries for 
most scholarly journals. With controls in 
the model for previous discoveries re­
garding price discrimination, this project 
attempted to test the null hypothesis that 
monopoly power will not increase in the 
electronic domain. 

It is impossible to distinguish the spe­
cific price of each journal from the elec­
tronic titles licensed from vendors such 
as Ebsco, UMI, and other aggregators be­
cause each is priced at a flat fee for the 
entire set of the aggregator. This pricing 
scheme may reflect an attempt by pub­
lishers to capture revenue lost to interli­
brary lending. However, it also may re­
flect publisher expectations that article 
demand will increase when user nondol­
lar costs decrease. Therefore, monopoly 
power will be reflected back on the sub­
scription price of print versions. As a re­
sult, the price of print copies is assumed 
as a proxy for the specific electronic price 
of each title if the copies could be made 
available on a title-by-title basis. 

http:discrimination.11
http:opportunity.10


272 College & Research Libraries May 2001 

However, an alternative result could 
emerge. In monopolistic competition, 
anything that differentiates a product 
may increase its monopoly power. Firms 
that sell laundry detergent spend tremen­
dous amounts of money on advertising. 
They do so to create the impression that 
their product is qualitatively distinguish­
able from others. Similarly, it may be that 
electronic availability of specific titles will 
create an impression of superior quality. 

The general model of the first specifi­
cation is written: y  = a + b LOWPRICE

j 1 j +
b EUROPE  + b GRTBRIT  + b OTHER  +

2 j 3 j 4 j

b RISK b ASSOC  + b FOUND  +
5 j + 6 j 7 j

b GOVERN  + b UNIV  + b FREQ  +
8 j 9 j 10 j

b ARTPGS b PEER  + b CCC  +
11 j + 12 j 13 j

b ARTILLUS  + b ADVERT  +
14 j 15 j

b SUBFEE  + b AGE  + b BOOK  +
16 j 17 j 18 j

b TOTCITES b IMPACT b SCIENCE
19 j + 20 j + 21 j 

+ b SOCSCI  + b ELECTRNIC b CIRC
22 j 23 j + 24 j 

e where, y equals the library price 
+ j ;
(INSTIT) for journal j = 1, 2, 3, … n. The 
general model of the second specification 
is written the same way except that y 
equals an index of monopoly power 
(LERNER). The definitions of indepen­
dent variables are given in table 1, along 
with the expected signs on and calcula­
tions of the parameters b

1
 through b

24
 to 

be estimated by traditional single-regres­
sion techniques. 

It should be understood that most of 
the variables listed in table 1 were sug­
gested based on previous studies that 
have demonstrated their appropriateness. 
Testing with the regression model was 
required to determine the variables ulti­
mately useful to this study. Additional 
variables were introduced as the experi­
ments suggested them. A very brief ra­
tionale for the expected sign and the im­
portance of the variables is in order. 

If the difference in price between what 
publishers charge libraries versus indi­
viduals represents price discrimination, 
a variable for the individual price 
(LOWPRICE) will be a significant predic­
tor of price to institutions (INSTIT). As 
the individual experiences an increase in 
price, substitution of access to the library 
will take place. That is, higher individual 

prices will shift users toward use of the 
library, thus raising demand for library 
subscriptions, which will pull institu­
tional prices higher. The sign on this vari­
able is expected to be positive. 

One group of variables deals with the 
issue of price discrimination based on the 
monopoly power that can be exercised by 
foreign publishers. Publishers in Great 
Britain (GRTBRIT), Western Europe (EU­
ROPE), and other countries outside the 
United States (OTHER) may have enough 
market power to influence price. There­
fore, these variables will carry a positive 
sign if a sizeable market influence is ex­
erted. Some of these publishers also will 
be concerned with currency exchange 
risks (RISK), which they will adjust for 
in prices. However, because they offer 
discounts through vendors to libraries 
that prepay subscriptions, this variable 
will carry a negative sign if the price to 
individuals captures most of the financial 
burden of risk adjustment. 

On the basis of observations over time, 
it is expected that commercial publishers 
price discriminate more than their non­
profit counterparts do. Therefore, in com­
parison to the commercial residual, asso­
ciations and societies (ASSOC), govern­
ment agencies (GOVERN), university 
presses (UNIV), and foundations 
(FOUND) will capture the generally 
lower prices of the nonprofits. The signs 
on all these are expected to be negative. 

All the publishers will experience pro­
duction costs, processing and communi­
cation expenses, that can be exposed 
through variables that control for fre­
quency (FREQ), total pages of articles 
printed per year (ARTPGS), peer review 
(PEER), copyright clearance registration 
expenses (CCC), and the presence of 
graphics, maps, and illustrations 
(ARTILLUS). All of these costs will affect 
price positively to the extent that they are 
passed on to buyers. On the other hand, 
the inclusion of advertising (ADVERT) 
will provide additional revenue to that of 
sales, so this variable is expected to be 
negative because journals that include ads 
will have less incentive to extract revenue 



A Tool to Assess Journal Price Discrimination 273 

TABLE 1

Regression Variables with Expected Signs
 

Dependent Variables: 
INSTIT = The price for library subscriptions
LERNER = Monopoly power as represented by INSTIT minus LOWPRICE 
Independent Variables: Dummies Expected

Sign 
LOWPRICE = Price for individuals +
EUROPE = 1 if the journal published in Europe, 0 otherwise � +
GRTBRIT = 1 if the  ournal published in Great Britain, � +

o otherwise
OTIER = 1 if the journal published outside U.S., Europe, and � +

Great Britain, 0 otherwise
RISK = Standard deviation of the monthly free-market exchange +

rate between the currency of the home country of a foreign
publisher to the U.S. dollar

ASSOC = 1 if the ournal published by an association, � −
o otherwise

FOUND = 1 if the journal published by a foundation, � −
o otherwise

GOVERN = 1 if the journal published by a govt agency, � −
o otherwise

UNIV = 1 if the journal published by a university press, � −
o otherwise

FREQ = Number of issues per year +
ARTPGS = Number of pages printed per year +
PEER = 1 if article submissions are peer reviewed, 0 otherwise � +
CCC = 1 if ournal is registered with the CCC, 0 otherwise � +
ARTILLUS = 1 if the journal contains graphics or illustrations, � +

o otherwise
ADVERT = Number of pages of advertising in journal for the −

year
SUBFEE = 1 if journal requires authors to submit page charges, � −

o otherwise
AGE = Current year minus the date the journal first published − 
BOOK = 1 if the journal publishes book reviews, o otherwise � +
TOTCITES = Sum of the ISI citation measures +
IMPACT = Index of impact from the ISI citation studies +
SCIENCE = 1 if the ournal is in the humanities, 0 otherwise � +
SOCSCI = 1 if the ournal is in the social sciences, 0 otherwise � +
ELECTRNIC = 1 if available in electronic form, 0 otherwise � − 
CIRC = Reported number of subscriptions to the journal + 



274 College & Research Libraries May 2001 

through sales. Similarly, control for jour­
nals receiving revenue from page charges 
or submission fees is captured by another 
dummy variable (SUBFEE), which should 
be significant and negative. New entries 
into the publishing arena are expected to 
experience advertising costs in order to 
increase awareness of their products, 
which will be partially passed on to con­
sumers. Therefore, age (AGE), which is 
the difference between the current date 
and the date the journal started, will be a 
negative predictor of price and monopoly 
power. A dummy variable for journals 
that publish book reviews (BOOK) is in­
cluded to control for publishing cost dif­
ferences in this type of material for those 
journals emphasizing reviews. 

Moreover, a pattern was noted of 
establishing individual prices that 
are almost exactly half the prices 
required of institutional purchasers. 

Previous studies have developed mea­
sures of quality based on rankings of pub­
lications compared to each other within 
a given discipline. Most of these compari­
sons work from information available 
from the Institute for Scientific Informa­
tion (ISI). Data acquired from this source 
showing the impact factor (IMPACT), 
immediacy index, half-life, total cites 
(TOTCITES), and cites per year will be 
tested by using two of these variables to 
capture quality of journals. These vari­
ables are expected to be positive with re­
gard to both price and monopoly power. 

The prices of journals across disciplines 
may be driven by different factors. In gen­
eral, prices are higher in the sciences and 
technical areas and lower in the humani­
ties. This is understandable when one 
considers that essentially no market ex­
ists for scholarly publications in the hu­
manities outside academe. In contrast, 
scientific publications are used heavily in 
corporate research by pharmaceutical 
firms and other industries highly depen­
dent on research. As a result, two addi­
tional dummies are included in the model 
to segment the specification along disci­

pline lines. Two dummy variables (SCI­
ENCE, SOCSCI) will control for differ­
ences in price among the science and so­
cial sciences as compared to the residual 
category of humanities. These variables 
are expected to be positive and strong 
predictors of price. 

Finally, a dummy variable is included 
to determine whether the availability of 
each journal electronically (ELCTRNIC) 
has a positive impact on ability to price 
discriminate. Because it has been hypoth­
esized that monopoly power will erode 
in the electronic arena, this variable 
should be a statistically significant and 
negative predictor of monopoly power. 
However, to the extent that a journal’s 
availability in an electronic format distin­
guishes it from print counterparts, there 
is some expectation that this variable 
could be positive. This would capture 
additional price discrimination by pub­
lishers that are able to capture lost rev­
enue in the electronic environment. 

As indicated in earlier studies, it could 
be expected that circulation (CIRC) would 
capture the effects of economies of scale, 
which those publications distributed in 
larger quantities will experience. Thus, 
this variable is expected to be negative. 
However, it introduces an econometric 
problem because it is likely to be endog­
enous to the determination of price 
(INSTIT) in the first specification and to 
the measure of monopoly power 
(LERNER) in the second. In effect, circu­
lation, which is a measure of demand, 
drives price and, in turn, changes in price 
drive circulation. Therefore, the specifi­
cation here is complicated by the likeli­
hood that a variable’s inclusion for circu­
lation implies simultaneous equations. 
This project attempted to overcome this 
limitation by considering another version 
of the specification with a multistage OLS 
regression. All the variables in the model 
were approximated with data collected 
from original sources. 

Database Development 
At the outset, it was the intention of this 
investigation to build the database for the 



A Tool to Assess Journal Price Discrimination 275 

regression by enhancing the data on sub­
scriptions available from Trinity’s inte­
grated library system. To augment these 
statistics, the number of article pages, the 
number of advertisement pages, and pric­
ing information had to be obtained from 
the journals themselves. Additional infor­
mation such as impact measures, total ci­
tations, and related factors were acquired 
from ISI. Some data were obtained from 
a serials bibliography.12 

Table 2 lists the nondummy variables 
with statistical averages, which are appro­
priate to the model specification as deter­
mined by theory and previous efforts by 
others. The data associated with those 
variables were obtained most readily by 
examining the journals and compiling the 
statistics from the actual items. Because 
literally millions of journal pages had to 
be examined, the investigation focused on 
the subset of the scholarly literature rep­
resented by the Trinity collection. Trinity 
gathers the current issues of every peri­
odical subscription in one location, orga­

nized according to classification number. 
Data were gathered by pulling every 
other current periodical from the display 
shelves. All titles that were obtained free 
of charge, were news oriented, or were 
dependent on advertising revenue were 
dropped from the data collection in favor 
of scholarly, academic titles. 

As might be expected with such a mas­
sive data-gathering project, several prob­
lems developed during the process. Ac­
curate, reliable circulation data proved to 
be difficult to acquire. Although Ulrich’s 
directory tries to provide these figures, 
they sometimes are misleading, missing, 
and/or not updated every year. Alterna­
tively, the circulation figures posted by 
the journals themselves in compliance 
with postal regulations are unavailable 
for foreign-based periodicals. Further­
more, an attempt to retrieve these data 
from the U.S. Post Office revealed that 
that agency does nothing to compile the 
information. Therefore, the figures were 
gathered from the journals themselves 

TABLE 2
Non-dummy Regression Variables

with Minimum, Maximum, and Mean Values for 1997 
Dependent Variables: Minimum Maximum Mean 
INSTIT = The price for library subscriptions 8.00 2,896.00
LERNER = Monopoly power as represented by 0.00 1,856.00
INSTIT minus LOWPRICE 
Independent Variables: Minimum Maximum 

241.00
108.43 

Mean 
LOWPRICE = Price for individuals 5.00 1,968.00
RISK = Standard deviation of the monthly free-market 0.00 184.70
  exchange rate between the currency of the home
  country of a foreign publisher to the U.S. dollar
FREQ = The number of issues per year 1.00 52.00
ARTPGS = Number of pages printed per year 14.00 3,209.00
ADVERT = Number of pages of advertising in journal 0.00 5,104.00
  for the year
AGE = Current year minus the date the journal first 0.00 182.00
  published
TOTCITES = Sum of the ISI citation measures 10.00 296,759.00
IMPACT = Index of impact from the ISI citation studies 0.00 37.29
CIRC = Reported number of subscriptions to
 the journal 249.00 252,573.00 

96.93
0.40

5.90
956.38

28.08
42.95

4,330.54
1.30 

6,033.23 

http:bibliography.12


 

276 College & Research Libraries May 2001 

and compared to the Ulrich’s information. 
When no figure was supplied in the jour­
nal, the Ulrich’s estimate was used. When 
both were available, the investigation re­
lied on the postal reporting of the jour­
nals. No efforts to acquire circulation 
counts from the foreign-based journals 
were made during this phase of research. 

Obtaining price information also 
proved challenging. Prices to libraries are 
usually indicated within each publication. 
Therefore, that source was relied on for 
institutional prices, which were then 
checked against actual Trinity invoices to 
verify accuracy. In many cases, the price 
to individuals was not indicated in the 
journal itself. In fact, this proved to be the 
general case for many large foreign-based 
publishers. The common supposition 
among librarians that individual sub­
scriptions to these titles have declined to 
zero seems to be borne out by answers to 
queries to the publishers requesting the 
price for individuals.13 Answers were in­
consistent and sometimes wildly differ­
ent from year to year. In other cases, the 
publisher responded as if it did not know 
the answer. Moreover, a pattern was 
noted of establishing individual prices 
that are almost exactly half the prices re­
quired of institutional purchasers. 

In some cases, individual prices were 
bound up in membership charges. For the 
purposes of this analysis, the information 
available was interpreted to parse out the 
lowest price that an individual would 
normally pay. Letters to a few societal 
publishers resolved some difficult ques­
tions. The issue of shadow prices associ­
ated with whether some subset of indi­
vidual subscribers would pay association 
dues for services not wanted in order to 
obtain a given periodical was ignored on 
the assumption that the effect on the 
model using aggregated statistics would 
be trivial. Likewise, the opportunity costs 
associated with substituting access in the 
library (transportation to the library, 
searching, photocopying, and so forth) for 
personal subscriptions also were ignored 
on the assumption that these would typi­
cally be borne by subordinates to the re­

searcher and, in the aggregate, would not 
substantially affect the outcome.14 

Data gathering also sometimes ran into 
problems determining whether a pub­
lisher was commercial. In a number of 
cases, periodicals contained indications of 
both a commercial and a societal (or uni­
versity press) involvement. After care­
fully looking at pricing patterns, it became 
apparent that the price tended to be 
driven by commercial issues. In fact, dis­
cussion at a recent conference of univer­
sity presses substantiated that they are 
being pressed by parent institutions to 
stand on their own and produce a profit.15 

Similarly, many societies indicate that 
their publications produce a return to 
equity that offsets dues payments by 
members.16 Therefore, each periodical 
where a combination of commercial and 
societal or university press was involved 
was coded as if it were commercial. 

Unfortunately, also, ISI does not index 
all the titles included in the sample gath­
ered at Trinity. Therefore, quality vari­
ables based on ISI statistics, such as im­
pact factor or total citations to each title, 
could not be included in the analysis for 
many of the observations. This informa­
tion was available for approximately 60 
percent of the database. 

Also early on, it was difficult to deter­
mine reliably when a journal was actu­
ally available electronically. The journal 
itself was relied on to indicate whether it 
had an electronic counterpart. In most 
cases, this information was available and 
could be verified by other sources. How­
ever, in 1995, fewer than fifty titles that 
were part of the database had electronic 
counterparts. By 1997, this information 
could be corroborated and 294 titles for 
which the publishers were offering elec­
tronic versions were in the database. 

Model Results 
Generally, the results of the OLS regres­
sion tests of institutional price conformed 
to both theory and earlier studies. In fact, 
the sign on every variable that held up in 
the regressions conformed to expecta­
tions, with the exception of the variable 

http:members.16
http:profit.15
http:outcome.14
http:individuals.13


A Tool to Assess Journal Price Discrimination 277 

TABLE 3

OLS and Three-stage Analysis


of lnstitutional Price for 1997 (97lNSTlT)
 
Dependent variable: 97INSTIT
Independent Variables: 

OLS Model Three-stage Model 
Term Estimate t Ratio Prob>ltl Estimate t Ratio
Prob>ltl
Intercept -7.7295 -0.30 0.7679 -53.8460 -1.78 0.0750***

97LOWPRICE 0.7345 17.69 <0.0001* 2.9445 14.56 <0.0001*
 
EUROPE 96.5960 3.63 0.0003* 96.2500 2.95 0.0030*

GRTBRIT 81.2282 5.45 <0.0001* 84.7660 4.53 <0.0001*
 
OTHER 23.1433 0.87 0.3837 26.8190 0.82 0.4100

ASSOC -80.7462 -5.39 <0.0001* -91.0110 -4.80 <0.0000*
 
FOUND -62.5348 -2.22 0.0266** -69.7290 -1.98 0.0490**

GOVERN -54.7575 -0.67 0.5022 -56.1010 -0.56 0.5750

UNIV -63.9232 -4.59 <0.0001* -74.9410 -3.96 <0.0000*
 
FREQ 21.9225 14.62 <0.0001*

97ARTPGS 0.0556 11.59 <0.0001*

PEER 53.2032 4.81 <0.0001*

CCC 3.7960 0.32 0.7463

ARTILLUST 17.7048 1.05 0.2937

97ADVERT -0.4852 -7.94 <0.0001*

97SUBFEE -55.2221 -2.99 0.0029*

97AGE -0.8906 -4.65 <0.0001*

BOOK -23.2038 -1.93 0.0546***

SCIENCE 37.0897 1.95 0.0511*** 50.3920 1.78 0.0750***

SOCSCI -17.1302 -1.13 0.2573 -20.3560 -1.11 0.2680

97ELCTRNIC 61.0898 5.51 <0.0001* 57.3430 4.23 <0.0000*
 
* Significant at the 0.01 level
** Significant at the 0.05 level
*** Significant at the 0.10 level 
Summary of Fit
RSquare 0.8105 RSquare .05249
RSquare Adj 0.8053 Durbin-Watson 1.8982
Root Mean Square Error 138.4037 Von Neumann ratio 1.9007
Mean of Response 202.0081
Observations (or Sum Wgts) 744 
Analysis of Variance
Source 
Model
Error
C total 

DF 
20
723
743 

Sum of Squares 
59241126 
13849486
73090612 

Mean Square 
2962056
19156 

FRatio 154.63 Prob>F <.0001 



278 College & Research Libraries May 2001 

TABLE 4

OLS Analysis of Publisher Monopoly Power


for 1997 (97LERNER)
 
Dependent variable: 97LERNER
Independent Variables:

Term Estimate t Ratio Prob>ltl
 
Intercept -27.2726 -1.02 0.3075
EUROPE 95.2394 3.48 0.0005*
GRTBRIT 75.2878 4.93 <0.0001*
OTHER 20.4782 0.75 0.4529
ASSOC -72.6558 -4.73 <0.0001*
FOUND -52.6606 -1.82 0.0685***
GOVERN -47.7689 -0.57 0.5687
UNIV -53.0263 -3.73 0.0002*
FREQ 20.3354 13.39 <0.0001*
97ARTPGS 0.0502 10.34 <0.0001*
PEER 55.6431 4.90 <0.0001*
CCC -0.8208 -0.07 0.9456
ARTILLUST 16.3332 0.94 0.3456
97ADVERT -0.4405 -7.06 <0.0001*
97SUBFEE -56.2801 -2.96 0.0031*
97AGE -0.8804 -4.47 <0.0001*
BOOK -12.8829 -1.05 0.2940
SCIENCE 20.1348 1.04 0.2973
SOCSCI -16.2970 -1.05 0.2941
97ELCTRNIC 64.7188 5.69 <0.0001* 
* Significant at the 0.01 level
** Significant at the 0.05 level
*** Significant at the 0.10 level 
Summary of Fit
RSquare 0.6455
RSquare Adj 0.6362
Root Mean Square Error 142.1684
Mean of Response 110.5228 
Observations (or Sum Wgts) 744 
Analysis of Variance
Source DF Sum of Squares Mean
Square
Model 19 26647512 1402501
Error 724 14633380 20212
C total 743 41280892 
FRatio 69.39 Prob>F <.0001 

for electronic availability 
(ELCTRNIC). For a few vari­
ables determined to be impor­
tant by earlier studies, the 
tests were statistically insig­
nificant. When their removal 
would have diminished the 
power of the model to predict 
by not holding constant for an 
important factor, the variables 
were left in the reported re­
sults. 

The basic models were run 
on data for 1995, 1996, and 
1997. The results were nearly 
the same for all three years, 
with the exception of the vari­
able for electronic availability 
(ELCTRNIC). In both the 
model to predict institutional 
price and the model to predict 
monopoly power, the analy­
ses converged consistently 
with about a hundred obser­
vations lost because of null 
values. The results of the 
analyses are summarized in 
tables 3 and 4. Table 3 reports 
two versions of the results to 
accommodate a statistical 
complication introduced by 
potential endogenity of the 
price charged individuals 
(LOWPRICE). 

To explain these results, 
some caveats apply. First, as­
serting that these statistical 
models prove certain points 
can be misleading. By anal­
ogy, a Missouri road map is a 
model. It would be unreason­
able to try to use such a map 
to prove that St. Louis is lo­
cated at the conjunction of two 
major rivers on the eastern 
boundary of the state. How­
ever, used properly, the map 
makes highly reliable predic­
tions for any traveler. Pro­
vided a traveler in Missouri 
knows where he is to begin 
with, the map provides, with 



A Tool to Assess Journal Price Discrimination 279 

a high degree of certainty, the direction 
to go in and the roads to take to get to St. 
Louis. Once in St. Louis, the traveler could 
corroborate the evidence provided by the 
map that, indeed, the city is located where 
the Missouri and Mississippi rivers join 
at the midpoint of the state’s eastern bor­
der. 

Similarly, it is better to understand that 
statistical models such as OLS regressions 
provide reliable support to make predic­
tions. In fact, these models can predict 
with a degree of confidence in excess of 
90 percent, which is all that any statisti­
cal model can do. Therefore, although the 
results from the tests do not prove per se 
that certain publishers overprice their 
products or hold monopoly power, they 
do provide reliable predictors. In the case 
of the tests described here, the models 
predict that if given periodicals produced 
by certain publishers are examined, their 
price is likely to be too high compared to 
all the other periodicals examined in the 
tests. Furthermore, it can be confidently 
predicted that the outcome is accurate 
nine or more times out of ten. 

Second, the results here apply to a data 
set of periodicals subscribed to by Trinity 
University. The predictions they make 
would apply reasonably well to any 
school with nearly the same subscription 
list and perhaps as well to others with 
similar subscription lists. Although pre­
dicted prices for specific titles would vary 
considerably, the general outcomes of 
these tests could be expected to describe 
conditions for similar kinds of institutions 
with similar core collections. The reliabil­
ity of the predictions would decline if an 
attempt were made to apply them to sub­
stantially smaller or larger collections or 
to collections skewed heavily toward 
fewer disciplines. 

In terms of Trinity’s collection of peri­
odicals, the model predicts the price of 
academic periodicals with an R-squared 
statistic in excess of 0.81, indicating that 
over 80 percent in the variation of the de­
pendent variable library price (INSTIT) 
is explained by the model. Similarly, the 
R-squared statistic on the alternative 

model examining monopoly power 
(LERNER) exceeds 0.64 and thus explains 
over 64 percent of the variation in the 
variable for monopoly power. Both mod­
els have very large F-statistics; thus, both 
are statistically significant at better than 
the 0.01 level. That is, they predict cor­
rectly in excess of 99 percent of the time. 

The outcomes of the models in terms 
of specific independent variables also are 
very reliable. Nearly every independent 
variable conformed to theory, corrobo­
rated previously reported analyses, 
showed the expected sign, and was sta­
tistically significant. A few variables in the 
original function specified failed to be sta­
tistically significant. The variable separat­
ing the broad discipline of social science 
(SOCSCI) and those separating certain 
other factors (OTHER, FOUND, and 
CCC) were left in the model to control for 
important concerns that could contribute 
to price or monopoly power and to com­
plete the relevant dummy sets. The sub­
set of social science periodicals repre­
sented by a dummy variable (SOCSCI) 
was retained to distinguish those titles 
from science and the residual titles, which 
were all humanities. The variable for 
countries outside the United States, Great 
Britain, and Europe (OTHER) was left in 
to distinguish publications published 
outside this country from those published 
within. The costs associated with regis­
tering with the Copyright Clearance Cen­
ter (CCC) that could affect prices was left 
in to provide assurance that the study was 
controlling for this cost of production. The 
extra production costs associated with il­
lustrations (ARTILLUS) were left in to 
control for this issue. 

A few variables that were shown to be 
statistically significant in other studies were 
specified in the original function here but 
were dropped from the results when they 
proved to be very insignificant and when 
they were not associated with other dummy 
variables. Following the work of others 
studying revenue lost to photocopying, this 
study incorporated data from ISI on total 
citations (TOTCITES) and impact factor 
(IMPACT) as proxies for quality variations 



280 College & Research Libraries May 2001 

among titles.17 Neither of these variables 
held up in the final results, in part because 
their values could not be obtained for much 
more than about half the collection. Cita­
tion-based variables may never produce 
significant results because of the cross-dis­
ciplinary nature of this database. Citation 
rates, in general, vary considerably from the 
arts compared to the sciences. 

In an earlier study on economics titles, 
the exchange rate risk faced by foreign 
publishers with the decline of the dollar 
in world markets proved reliable as a pre­
dictor of price. In this study, this variable 
(RISK), as proxied by the standard devia­
tion of the annual exchange rate for the 
currency of each country with the dollar, 
was insignificant. It is likely that this vari­
able did not hold up in the model because 
the exchange rate of dollars for the for­
eign countries represented was reason­
ably steady within the 1995 to 1997 time 
frame of the analysis. Therefore, exchange 
rate risk may have played a minor role in 
setting prices for those years. 

Finally, the variable used to control for 
the circulation rates (subscriptions sold by 
the publishers) was not usable in the 
model. There is a statistical complication 
associated with this variable (CIRC) re­
lated to endogenity and with the variable 
for the price charged to individuals 
(LOWPRICE), which is closely related to 
circulation rates. Also, reliable circulation 
figures were available for too few obser­
vations to produce meaningful results 
using that variable. On the other hand, 
the price charged to individuals turned 
out to be statistically significant and posi­
tive. As this variable (LOWPRICE) is in­
creased, the model predicts and experi­
ence confirms a positive increase in the 
price charged to libraries (INSTIT). This 
is as expected because the loss of revenue 
caused by individual subscription cancel­
lations will be reflected in library prices 
as publishers attempt to make it up. How­
ever, this variable (LOWPRICE) may in­
troduce the same statistical problem that 
the statistic for circulation does. (The 
problem introduced by both variables is 
discussed in the next section.) 

All the other variables expected to con­
tribute to predictions of price and mo­
nopoly power held according to expected 
sign and statistical significance except for 
the dummy variable for electronic avail­
ability. Some variables included in the 
study that did not explicitly contribute to 
costs of production nevertheless contrib­
uted to variations in the dependent vari­
able. Science periodicals (SCIENCE) in the 
collection are more expensive compared 
to periodicals in social science and the 
humanities. Publications originating in 
Western Europe (EUROPE) and Great 
Britain (GRTBRIT) are priced higher, on 
average, than U.S. periodicals. Publica­
tions of associations and societies 
(ASSOC), university presses (UNIV), gov­
ernment publications (GOVERN), and 
foundations (FOUND) are all priced 
lower than commercial publications. 

Other variables that control for factors 
that could contribute to production costs 
were retained in the models because of 
their statistical significance. The costs of 
peer review (PEER), higher frequency of 
publication (FREQ), and higher number 
of pages of article content published 
(ARTPAGES) contribute positively to 
higher prices charged to libraries. Those 
higher prices are thus partially explained 
by higher production costs. Alternative 
sources of revenue from page charges or 
submission fees (SUBFEE) and advertis­
ing (ADVERT) help hold prices down, as 
expected. The models show that what li­
brarians believe to be predictable are in­
deed predictable with a high degree of 
certainty within the data set examined. 

One variable was used to extend this 
study beyond those reported earlier to 
determine the potential impact of elec­
tronic availability (ELECTRNIC). If bar­
riers to entry would be lowered by the 
opportunity to publish offered by elec­
tronic technology, this variable would be 
negative. Alternatively, if the electronic 
domain offered an opportunity for pub­
lishers to retain better control of their 
publications and possibly extend their 
pricing power, it would be positive. In the 
regression run on 1997 data where there 

http:titles.17


A Tool to Assess Journal Price Discrimination 281 

was a large subset of electronically avail­
able periodicals, the results on this vari­
able were statistically significant and 
positive. 

As the primary outcome of the analy­
sis, it is possible to reject the null hypoth­
esis that monopoly power will not in­
crease in the electronic domain. Actually, 
the analysis indicates that the opportu­
nity to publish electronically neither low­
ers barriers to entry nor erodes the mo­
nopoly power of publishers. The dummy 
variable reflecting the availability of elec­
tronic versions of titles (ELECTRNIC) was 
statistically significant and positive in 
both specifications. Therefore, librarians 
can likely expect to see prices continue to 
increase and monopoly power extended 
as publishers introduce electronic ver­
sions of their products. 

Many variations of the model were 
submitted to OLS regression analysis to 
provide some assurance that as few con­
tributing factors as possible would be 
overlooked. In fact, nearly every issue that 
could be assessed quantitatively and in­
cluded was. There are two related factors 
for which a proxy could not be developed: 
economies of scope and economies of 
scale. Presumably, those publishers pub­
lishing greater numbers of journal titles 
could take advantage of sharing editorial 
and other production activities across 
journals by assigning employee slack 
time from one title to another. Economies 
of scope associated with this sharing 
should reduce production costs and, thus, 
price. In fact, some of those publishers, 
particularly Western European commer­
cial houses with large numbers of publi­
cations, actually appear to price higher.18 

Related to this, there should be economies 
of scale associated with titles produced 
in large quantities for each issue. 

When the number of copies printed for 
a given issue is large, the fixed costs of 
production represented by factors such as 
editorial labor or building facilities are 
spread across more sales. Therefore, 
economies of scale come into play and 
prices might realistically be expected to 
be lower. Unfortunately, circulation fig­

ures (CIRC) capture the number of cop­
ies printed but also are linked closely to 
the price of and demand for given publi­
cations. Dealing with this issue in the re­
gression introduced complications. 

Similarly, there is a linkage between the 
price charged to individuals (LOWPRICE) 
and the price charged to libraries (INSTI). 
It expresses itself through demand reac­
tions. As the price to individuals increases, 
subscribers respond by canceling subscrip­
tions, producing a consequent loss of rev­
enue to publishers and an increase in de­
mand for access to library subscriptions. 
Publishers’ attempts to recover lost rev­
enue show up in higher prices charged to 
libraries, which also is a reaction to higher 
demand for library access by those indi­
viduals who still need the content but have 
cancelled personal subscriptions. As a fur­
ther consequence, total circulation de­
creases. The mathematical complications 
introduced into the study model by these 
interactions are discussed further below. 

The Circulation Issue 
Attempts to include a variable for circula­
tion figures, or in other terms the number 
of subscriptions sold, introduce problems 
in the regression analysis. Circulation fig­
ures reported to the U.S. Post Office, by 
law, are recorded within each publication 
at least once a year. Those reports indicate 
the total print run along with the number 
of copies sold, retained in inventory, and 
given away of the average issue for the 
given year. Circulation figures also are re­
ported by Ulrich’s Periodicals Directory. A 
comparison of these sources indicated that 
Ulrich’s numbers usually were close to the 
reported counts of subscriptions sold. 
Therefore, a circulation estimate was com­
piled using the reported numbers, when 
available, and Ulrich’s numbers when the 
journal did not report. The estimated cir­
culation was included as a variable in sev­
eral runs of the model. In most cases, the 
function converged with one-half of the 
observations lost due to null values. The 
variable for circulation (CIRC) carried a 
negative sign but did not hold up as sta­
tistically significant. 

http:higher.18


282 College & Research Libraries May 2001 

The negative sign on the circulation 
variable corroborates the argument that 
there is an inverse relationship between 
circulation and price. That is, price in­
creases produce a response from subscrib­
ers, which results in cancellations. How­
ever, this relationship may not be mod­
eled meaningfully for several reasons. 
Previous work has shown that examina­
tions of this relationship across a broad 
range of titles produce scatter plots rather 
than systematic functions.19 In part, this 
is likely due to the aggregated nature of 
the circulation figures reported. For any 
given journal, neither the internal reports 
nor those given by Ulrich’s distinguish 
quantities sold to individuals from those 
sold to libraries. Because the prices of­
fered to these two groups of subscribers 
differ considerably, the resulting price-
versus-demand relationship is unclear. 

It can be argued that the prices to indi­
viduals (LOWPRICE) and to libraries 
(INSTIT) are determined simultaneously 
and thus there is a danger of biased re­
gression coefficients. To address this con­
cern, the model displayed in the first col­
umn of table 3 was reestimated as a two-
equation model. LOWPRICE was mod­
eled as a function of FREQ, ARTPGS, 
PEER, CCC, ARTILLUS, ADVERT, 
SUBFEE, AGE, and BOOK. Each of these 
variables is hypothesized to affect the net 
cost of producing a journal. The institu­
tional price (INSTIT) is then modeled as 
a function of the predicted values of 
LOWPRICE as well as EUROPE, 
GRTBRT, OTHER, ASSOC, FOUND, 
GOVERN, UNIV, SCIENCE, SOCSCI, and 
ELCTRNIC. A three-stage OLS procedure 
generated the results shown in the sec­
ond column of table 3. 

All of the coefficients retain their signs 
and are within a standard error of their 
OLS counterparts. The p-values also are 
roughly equivalent. The first-stage results 
are not presented here but continue to 
confirm the hypotheses concerning costs 
presented above. LOWPRICE is posi­
tively related to FREQ, ARTPGS, PEER, 
and CCC. ADVERT, SUBFEE, AGE, and 
BOOK all tend to reduce LOWPRICE. As 

was the case in the OLS results, 
ARTILLUS was positive, but statistically 
insignificant. 

Demand for individual and library 
subscriptions is more likely determined 
by the overall size of the market for re­
search in each given discipline. With some 
obvious exceptions, most journals serve 
a restricted audience. It is unlikely that 
any given journal in the humanities 
would be widely read by scholars work­
ing in the sciences. Each journal contains 
unique information not found in any 
other journal. Therefore, titles tend not to 
be in direct competition with each other. 
Also, when a scholarly discipline is stud­
ied by a relatively small contingent of 
scholars, the number of subscriptions is 
likely to be smaller in total. Overall, these 
factors suggest that the demand-versus­
price relationship has to be examined on 
a title-by-title basis or through an alter­
native model of some kind. 

The alternative model also must over­
come an endogenous relationship of cir­
culation in the model specified for this 
study. Placing a variable for circulation 
in the model introduces a classic demand 
and supply in the same equation prob­
lem.20 In effect, when an estimate for cir­
culation is included, the simpler model 
attempts to solve simultaneous equations. 
This is further complicated by the differ­
ence in demand by individuals and insti­
tutions. Therefore, there really are four 
simultaneous equations: demand and 
supply for individual subscriptions, and 
demand and supply for institutional sub­
scriptions. Solving four simultaneous 
equations implies a need for data on both 
subscription prices and both estimates of 
circulation. Because estimates of indi­
vidual-versus-institutional subscriptions 
could not be obtained, it was impossible 
to specify a reliable function to explain 
the relationship statistically. 

The complications introduced by the 
variables requiring a specification to solve 
four simultaneous equations take this 
analysis beyond the scope of this project. 
However, this complication leaves the 
proposed hypothesis test largely unaf­

http:functions.19


A Tool to Assess Journal Price Discrimination 283 

fected. The specified model accommo­
dates every variable previously estab­
lished as exogenous and relevant except 
for a proxy of economies of scope and a 
metric of quality. In the first case, econo­
mies of scope should yield lower prices 
from those publishers producing a very 
large number of titles. Yet, the model dem­
onstrates a correlation between high 
prices and publishers of numerous titles. 
In the second case, a metric of quality can­
not be established for a cross-discipline 
data set. For example, it is meaningless 
to compare the academic quality of a 
music journal to one in physics or in busi­
ness. 

Furthermore, certain patterns showed 
up in the data. These may lead to addi­
tional fruitful analysis, which could ex­
tend the analysis reported here. Some 
titles in the data set are so high priced that 
they effectively have no market except to 
institutions. Where it was impossible to 
obtain the price charged to individuals, 
it was speculated that this was because 
the publisher was not selling to individu­
als. As this was examined, a pattern sug­
gested itself. These titles appeared to be 
very high priced, had low circulation, and 
often were described by users as second 
tier in quality. 

Other Statistical Considerations 
The analyses reported here are based on 
statistical procedures applied using the 
SAS Institute’s JMP™ software, which 
was developed to run on a PC. This par­
ticular version was chosen because, 
among other advantages, it automatically 
applies several standard statistical tests 
to confront the possibility of misleading 
results produced by problems typical of 
OLS regression analyses, such as 
hetereoskedasticy and collinearity. More­
over, the software plots the effects of each 
variable in a way that makes spotting sta­
tistical problems easy. As the various at­
tempts were run, which ultimately pro­
duced the results reported, a few variables 
introduced problems. Only one collinear­
ity issue emerged, as explained above, 
and the few variables that introduced ex­

ceptional leverage were excluded from 
the analysis. Fortunately, the only poten­
tially useful added variable, which was 
based on ISI quality measures, where the 
problems could not be corrected was 
eliminated for other reasons noted above. 

However, the specified model does not 
explain why prices change from year to 
year, especially at an inflation rate exceed­
ing the CPI. This project attempted to deal 
with this question by creating another 
specification to explain the price change 
from 1995 to 1997 based on the change in 
the variables over that same time frame. 
Delta values were calculated by subtract­
ing the 1995 values from the 1997 values 
for all of the variables listed in table 1 
where they were meaningfully possible. 
Most of the dummy variables did not 
change because they were based on loca­
tion or other essentially unchangeable is­
sues. The dummy for electronic availabil­
ity was subject to change, so it was re­
tained along with the delta values. 

Table 5 displays the results of an OLS 
analysis of the change in institution price 
(L INSTIT) on the independent delta val­
ues. When this model was run using only 
the delta values, it converged with a sta­
tistically significant lack of fit. Because the 
lack of fit indicates that statistically sig­
nificant variables were missing from that 
model, the regression was run on the 
same function as described in table 3 but 
substituted delta values for those vari­
ables that changed over time. Two reports 
on this effort are included in table 5. 

As might be expected, the variables 
that predict the price to institutions in the 
basic model also tend to predict changes 
in price over time. In fact, the signs on 
the variables are the same and the statis­
tical significance of all but the one dummy 
variable for foundation publications 
(FOUND) remains. However, this regres­
sion continues to lack some variables that 
could affect price. As noted before, there 
is no reliable metric of quality across the 
data set and trying to provide one is en­
cumbered by inconsistent definitions of 
quality among a broad set of disciplines. 
In addition, it is impossible to control for 



            

            
            

284 College & Research Libraries May 2001 

 

TABLE 5

OLS Analysis of the Change in


Institutional Price from 1995 to 1997 ( lNSTlT)
 
Dependent variable: LINSTIT
Independent Variables:

Term Estimate t Ratio Prob>ltl Estimate t Ratio Prob>ltl
 
Intercept -3.5292 -0.34 0.7310 -2.198156 -0.22 0.8246 
LLOWPRICE 0.0761 3.33 0.0009*      
EUROPE 44.5040 3.87 0.0001* 54.7353 4.99 <0.0001*
GRTBRIT 28.7676 4.84 <0.0001* 32.7037 5.10 <0.0001*
OTHER 13.4242 1.25 0.2131 14.4774 1.17 0.2423
ASSOC  28.4983  4.82 <0.0001*  35.0194  5.36 <0.0001*
FOUND  18.4451  1.63 0.1030  23.5840  1.82 0.0694
GOVERN  15.9448  0.50 0.6157  22.4261  0.60 0.5462
UNIV  17.7830  3.24 0.0013*  22.4015  3.60 0.0003*
FREQ 6.9292 15.38 <0.0001* 7.8379 16.76 <0.0001*
97ARTPGS 0.0361 4.66 <0.0001* 0.0245 2.94 0.0033*
PEER 16.0182 3.65 0.0003* 19.7601 4.06 <0.0001*
CCC 2.2858 0.49 0.6234      
ARTILLUST 4.2592 0.64 0.5212       
LADVERT  0.4191  3.75 0.0002*  0.3635  2.80 0.0053* 
LSUBFEE  11.2972  0.74 0.4616  31.6983  1.96 0.0498**
97AGE  0.2830  3.75 0.0002*  0.3050  3.57 0.0004*
BOOK  11.6550  2.47 0.0139**  13.6738  2.59 0.0097*
SCIENCE 21.0204 2.79 0.0054* 33.6816 4.17 <0.0001*
SOCSCI  0.1130  0.02 0.9849 0.2735 0.04 0.9672 
LELCTRNIC 18.04703 3.9 0.0001* 27.5325 5.33 <0.0001* 
* Significant at the 0.01 level
** Significant at the 0.05 level
*** Significant at the 0.10 level 
Summary of Fit
RSquare
RSquare Adj 
Root Mean Square Error
Mean of Response
Observations (or Sum Wgts) 

0.4851
0.4701

53.8845
33.8169

710 

0.5027
0.4914

63.2643
41.0601

765 
Analysis of Variance
Source DF Sum of

Squares 
Model 20 1884567
Error 689 2000535
C total 709 3885102 

Mean
Square 
94228.4

2903.5 

DF Sum of
Squares 

17 3021962
747 2989770
764 6011731 

Mean
Square 
177762

4002 

FRatio 32.453 Prob>F <.0001 44.4143 Prob>F <0.0001 



A Tool to Assess Journal Price Discrimination 285 

economies of scale in this model, but if a 
variable were available, it would likely 
carry a negative sign. Therefore, in addi­
tion to these and the variables included 
in the model, it could be assumed that at 
least one other significant variable is miss­
ing. At this point, because quality and 
scale would not change dramatically in 
three years, it was further assumed that 
the missing variable would control for 
vagaries in publisher pricing. 

Isolating Specific Publisher Pricing 
The model specified and described above 
provided results that are not surprising 
to librarians. While holding constant for 
as many factors as possible that have been 
claimed to drive price increases by pub­
lishers, the model indicates that some 
publishers overprice their journals com­
pared to other titles. In fact, the statistical 
tool used in the analysis contains the 
means to look at every individual title 
compared to the whole data set to see 
which titles the model predicts will be the 
most overpriced. Table 6 isolates those 
titles priced at amounts statistically sig­
nificantly higher than the model predicts 
for them. This table holds the key to a very 
powerful tool that librarians can use in 
selecting journals to add to or deselect 
from their collections. 

Table 6 isolated the twenty titles for 
which the prices charged by the publish­
ers are statistically significantly higher 
than the model predicts for them within 
the data set. The software used for the 
analysis provides the means to save re­
siduals on every observation. Some of 
those residuals are statistically significant. 
Based on the model reported in tables 3 
and 4, the investigation isolated the most 
overpriced journals using the residuals 
and sorted for those that were statistically 
significant. Therefore, this isolated sub­
set of the data set exposes the titles that 
are the best candidates for cancellation 
based on predicted subscription price for 
the most recent complete year. 

To use the model as a selection tool, 
Trinity would have to expand the data set 
to cover all subscriptions and enter the 

relevant data for every title. Although this 
undertaking may sound somewhat 
daunting, it does not add substantially to 
the record keeping already routine for 
most libraries. With the caveat that the 
information has to be entered into an au­
tomated record-keeping system, the stan­
dard bibliographic and check-in records 
already retained include nearly all the 
quantitative variables important to the 
specified model. Most of the dummy vari­
ables can be recorded once and then used 
indefinitely. The most difficult variable to 
obtain, and one that must wait for the 
completion of the subscription year to 
obtain accurately, is number of article 
pages. 

Although determining the number of 
pages committed to advertising and ar­
ticles was essential to the experiment con­
ducted here, it is not necessary for a 
slightly different model with equal pre­
dictive power. During the analyses, a 
dummy variable was submitted for 
whether each journal takes paid adver­
tisements and a quantitative variable for 
total pages to be used in lieu of number 
of article pages. Without changing any­
thing else, the regressions using these al­
ternatives yielded results closely approxi­
mating those reported in tables 3 and 4, 
based on the original specification. 

In fact, saving residuals on results iso­
lated all twenty of the titles listed in table 
6. Two additional titles identified by the 
simpler model emerged as a result of 
slightly different residuals. For a library 
to use this tool, some simple additions 
need to be made to augment standard li­
brary record keeping for subscriptions. 
Those records need only be submitted to 
the model specified to isolate candidates 
for cancellation based on the extent of the 
difference between the price charged and 
the price predicted by the model. 

Table 6 makes it clear that aggressive 
price escalation may not be limited to com­
mercial publishers. Emerging in this table 
are five societal publishers that priced spe­
cific journals significantly in excess of the 
model predictions. Indeed, pressure from 
membership likely encourages societal 



TABLE 6
Comparison of Actual Institutional Price to Model-predicted Price, Ranked by Percent Difference 

Title Publisher 
Institutional
Price in 1997 

Model-
Predicted 
Price for

1997 
Excess of Actual 

Price over
Predicted Price 

Actual Price
As a Percent 
of Predicted 

Price 
Journal of Econometrics
Review of Scientific Instruments
Journal of Cell Science
Geomorphology
Veterinary Immunology and Immunopathology 
Developmental and Comparative Immunology
Organometallics 
Personality and Individual Differences 
Vision Research 
Computers and Chemical Engineering
Earth Science reviews
Communications in Algebra 
Geophysical Journal International
Cognition
Journal of Molecular Spectroscopy
Inorganic Chemistry 
Journal of Mathematical Analysis and Application 
Journal of Algebra 
International Journal of Energy Research 
Journal of Physical Chemistry A* 

Elsevier Science $1,798
American Institute of Physics $1,030 
Company of Biologists, Ltd $1,195
Elsevier Science $1,185
Elsevier Science $1,463
Elsevier Science $876
American Chemical Society $1,340
Elsevier Science $1,029
Elsevier Science $1,895
Elsevier Science $1,403
Elsevier Science $648
Marcel Dekker Journals $1,975
Blackwell $1,043
Elsevier Science $983
Academic Press $1,603
American Chemical Society $1,395
Academic Press $2,725
Academic Press $2,475
Wiley and Sons $1,795
American Chemical Society $1,955 

$609
$429
$537
$562
$713
$444
$694
$576

$1,066
$809
$379

$1,253
$677
$654

$1,124
$1,020
$2,094
$2,017
$1,496
$1,673 

$1,189
$601
$658
$623
$750
$432
$646
$453
$829
$594
$269
$722
$366
$329
$479
$375
$631
$458
$299
$282 

295�
240�
223�
211� 
205�
198�
193�
179�
178�
173�
171�
158�
154�
150�
143�
137�
130�
123�
120�
117� 

*Indicated titles originated by a society or association that may still be involved with the publication 

286 C
ollege &

 R
esearch

 L
ib

raries 
M

ay
 2001 



 

A Tool to Assess Journal Price Discrimination 287 

leadership to offset the extraction of rev­
enue from members’ dues by making a 
profit on scholarly publications. 

Conclusion 
This experiment yielded some very 
worthwhile results. First, the analysis pro­
vided statistically sound evidence that li­
brarians and scholars should place little 
hope in the expectation that the electronic 
era will readily introduce the kind of 
change needed to diminish publisher mo­
nopoly power. European-based commer­
cial publishers with a broad stable of titles 
are better positioned to introduce elec­
tronic counterparts to their print publi­
cations than scholars are to introduce new 
and competitive online titles. The former 
are aided by a well-funded infrastructure 
and an established editorial process; the 
latter must effectively start from scratch. 
Although not impossible, the commercial 
publishers have an edge.21 

Second, it appears that publishers who 
blame exchange rate risk and production 
costs for the prices of their products may 
be using empty rhetoric. Although the 
study did not prove that a weakening dol­
lar could not be blamed for price in­
creases, it did show, within the short time 
frame covered, that risk is not a reliable 
predictor of price. In short, some price 
increases occurred despite the condition 
of the dollar. 

Third, the experiment offered a pow­
erful statistical tool for librarians to use 
to isolate the most egregious pricing as a 
selection criterion. Nearly all libraries 
base their selection of titles to acquire on 
a combination of three pieces of informa­
tion: price, quality, and potential level of 
use. Experience, intuition, and guesswork 
play major roles in deciding both esti­
mates. The model described here offers 
an opportunity to reduce the guesswork 
implicit in the price analysis. 

Notes 

1. This article was excerpted from the author ’s report, Beating Publisher Price Discrimination 
(San Antonio, Tex., 2000). For a complete report on the project, address queries to the author. 

2. See: Association of Research Libraries. Directory of Electronic Journals, Newsletters, and Aca­
demic Discussion Lists (Washington, D.C.: ARL, 1997). For excellent overviews on the develop­
ment of e-journals, see: Judy Luther, “Full-text Journal Subscriptions: An Evolutionary Process,” 
Against the Grain 9/3 (June 1997): 18, 20, 22, 24; Liza Chan, “Electronic Journals and Academic 
Libraries,” Library Hi Tech 17/1 (Jan. 1999): 10–16. 

3. For a thorough overview of the economic framework, see: Richard W. Meyer, “Monopoly 
Power and Electronic Journals,” Library Quarterly 67/4 (Oct. 1997): 325–49. 

4. See, especially: H. Craig Peterson, “Variations in Journal Prices: A Statistical Analysis,” 
Serials Librarian 17/1&2 (1989): 1–9; ———, “The Economics of Economics Journals: A Statistical 
Analysis of Pricing Practices by Publishers,” College and Research Libraries 53 (Mar. 1992): 176–81; 
George A. Chressanthis and June D. Chressanthis, “The Determinants of Library Subscription 
Prices of the Top-ranked Economics Journals: An Econometric Analysis,” Journal of Economic 
Education 25/4 (fall 1994): 367–82. 

5. Roger Noll and W. Edward Steinmueller, “An Economic Analysis of Scientific Journal 
Prices: Preliminary Results,” Serials Review 18 (spring/summer 1992): 32–37. 

6. George A. Chressanthis and June D. Chressanthis, “Publisher Monopoly Power and Third-
degree Price Discrimination of Scholarly Journals,” Technical Services Quarterly 11/2 (1993): 13– 
36. 

7. Edward Chamberlin, The Theory of Monopolistic Competition (Cambridge, Mass.: Harvard 
Univ. Pr., 1935). 

8. George A. Chressanthis and June D. Chressanthis, “A General Econometric Model of the 
Determinants of Library Subscription Prices of Scholarly Journals: The Role of Exchange Rate 
Risk and Other Factors,” Library Quarterly 64/3 (1994): 270–93. 

9. This theory is based on the classic work: Abba Lerner, “The Concept of Monopoly and the 
Measurement of Monopoly Power,” Review of Economic Studies (June 1934): 157–75. 

10. Two variations in the dependent variable were attempted, including the index of mo­
nopoly power based on the work of Lerner. This second version of the Lerner index provided no 
additional predictive power to the model. 



288 College & Research Libraries May 2001 

11. Chressanthis and Chressanthis, “Publisher Monopoly Power and Third-degree Price Dis­
crimination of Scholarly Journals.” 

12. Ulrich’s Periodicals Directory (New York: R. R. Bowker, 1996–1998). 
13. For a very good summary of trends that relate to this issue as well as general pricing, see: 

Carol Tenopir and Donald W. King, “Trends in Scientific Scholarly Publishing in the United 
States,” Journal of Scholarly Publishing 28/3 (Apr. 1997): 135–70. 

14. Assumptions regarding these two issues were based on an earlier study of scholar de­
mands for journal content in: Charles River Associates, Development of a Model of the Demand for 
Scientific and Technical Information Services (Boston: Charles River Associates, 1979). 

15. Association of American University Presses, annual meeting, Austin, Tex., June 20–12, 
1999. 

16. See, for example: Michael Barr, “ Where Does the Money Go?” Newsletter on Serials Pricing 
Issues 229 (July 13, 1999): 229.1. 

17. For an explanation of price discrimination based on publisher effort to recover revenues 
lost to photocopying, see: S. J. Liebowitz, “Copying and Indirect Appropriability: Photocopying 
of Journals,” Journal of Political Economy 93/5 (1985): 945–57. 

18. Mark J. McCabe, “Academic Journal Pricing and Market Power: A Portfolio Approach.” 
Revised Nov., 2000. Presented at the 2000 AEA meetings in Boston (under review at the AER). 
Available online at http://www.prism.gatech.edu/%7Emm284/JournPub.PDF. 

19. Tenopir and Donald W. King, “Trends in Scientific Scholarly Publishing in the United 
States,” Journal of Scholarly Publishing 28/3 (Apr. 1997): 135–70. 

20. Bruce Kingma, personal correspondence with the author. 
21. Programs such as the SPARC initiative and discipline servers such as that at Los Alamos 

probably offer more viable opportunities for new approaches to compete with the commercial 
establishment. 

http://www.prism.gatech.edu/%7Emm284/JournPub.PDF