author affiliation index, finance journal ranking, and the pattern...

Author Affiliation Index, Finance Journal Ranking, and the Pattern of Authorship

Carl R. Chen* University of Dayton

Ying Huang

Manhattan College

Abstract ________________________________________________________________________ In this paper we use a new method to rank finance journals and study the pattern of authorship/co-authorship across journals. Author Affiliation Index is a cost-effective and intuitively easy-to-understand approach to journal rankings. We define Author Affiliation Index as the ratio of articles authored by faculties at the world’s top 80 finance programs divided by the total number of articles by all authors. Forty-one finance journals are ranked according to this index. If properly constructed, Author Affiliation Index provides an easy and credible way to supplement the existing journal ranking methods. Our ranking system reveals journal-researcher clienteles, and we find that collaboration (co-authoring) between faculty within elite programs exists only in top-tier and near-top-tier journals. Publications in low-tier journals by researchers of elite programs are driven by their co-authors. Collaboration between faculty in elite and non-elite programs, however, is more prevalent than that within elite programs across all tiers of journals. Co-authorship among top 80 programs, nevertheless, is more common in top-tier journals; while co-authorship between top 80 and other programs is more dominant in lower-ranked journals. JEL classification: G00 Keywords: Finance journal ranking, author affiliation index, authorship pattern _________________________ * Corresponding author: Carl R. Chen, William J. Hoben Professor of Finance, Department of Economics and Finance, University of Dayton, 300 College Park, Dayton, Ohio 45469-2251. Tel: (937) 229-2418, Fax: (937) 229-2477, E-mail:[email protected]. Helpful comments from an anonymous reviewer and Jeff Netter, the editor, are gratefully acknowledged.

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Abstract ________________________________________________________________________ In this paper we use a new method to rank finance journals and study the pattern of

authorship/co-authorship across journals. Author Affiliation Index is a cost-effective and

intuitively easy-to-understand approach to journal rankings. We define Author Affiliation

Index as the ratio of articles authored by faculties at the world’s top 80 finance programs

divided by the total number of articles by all authors. Forty-one finance journals are

ranked according to this index. If properly constructed, Author Affiliation Index provides

an easy and credible way to supplement the existing journal ranking methods. Our

ranking system reveals journal-researcher clienteles, and we find that collaboration (co-

authoring) between faculty within elite programs exists only in top-tier and near-top-tier

journals. Publications in low-tier journals by researchers of elite programs are driven by

their co-authors. Collaboration between faculty in elite and non-elite programs, however,

is more prevalent than that within elite programs across all tiers of journals. Co-

authorship among top 80 programs, nevertheless, is more common in top-tier journals;

while co-authorship between top 80 and other programs is more dominant in lower-

ranked journals.

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I. Introduction In this study we devise and employ a new method to rank finance journals, and to

examine the authorship/co-authorship pattern of some finance journals. Rating journal

quality is crucial for faculty seeking promotion, tenure, and new job hunting; and for

administrators in determining merit pay increases. Institutions use journal rankings to

publicize the superiority of their faculty and where their departments stand relative to

peer institutions. For example, the Department of Finance in Arizona State University

sponsors a web page that ranks top 20 institutions based upon publications in the top 4

finance journals.1 Borokhovich et al. (1995) find association between business schools’

prestige and their publication productivity. Tamkang University in Taiwan offers

considerable amount of bonuses to faculty who publish in a certain set of academic

journals. As shown in Chan, Chen, and Steiner (2002), faculty seeking relocation to a

better institution are required to have more and better publications than the incumbent

faculty in the target school. These examples demonstrate the importance of journal

quality rating. Nevertheless, journal rankings are very controversial with the exception of

a small number of journals that can be unambiguously regarded as top-notch.

Two methods have been commonly employed for journal rankings so far. The

most frequently adopted method is the impact factor based upon journal citations.

Institute of Scientific Information (ISI) compiles a Journal Citation Report (JCR) which

reports impact factors of selected journals. In the literature some authors supplemented

the JCR with additional journals (e.g., Zivney and Reichenstein, 1994, Alexander and 1 See http://wpcarey.asu.edu/finance/rankings/results.cfm.

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Mabry, 1994, Chan, Fok, and Pan, 2000). However, it is noted that there are drawbacks

when journals are ranked by impact factors. Alexander and Mabry (1994) contend that

citation-based journal ranking method suffers from self-citation bias. Amin and Mabe

(2000) also argue that the value of the impact factor is affected by sociological and

statistical factors. Sociological factors include the subject area of the journal and the

average size of co-authorship. For example, the mean impact factor for fundamental life

science is more than 3.0, while the same statistic for mathematics and computer science is

less than 0.5. Statistical factors refer to the journal size and the citation measurement

window which typically is two years (a one-year citing window and a two-year cited

window).2 The year-to-year variation of the journal’s impact factor is the largest for

smaller-sized journals (< 35 articles per year), and the smallest for large-sized journals (>

150 articles per year).

In a recent article in the Chronicle of Higher Education, it is reported that some

journal editors and journal publishers manipulate the type of articles in order to raise the

impact factor. For example, review articles tend to get cited more often than the original

research articles ― 7 out of the top 15 science journals are review publications.

Therefore, the editorial board of Journal of Environmental Quality has decided to

emphasize review articles in order to shore up the journal’s impact factor. Other ways to

distort the impact factor include running editorials that cite numerous articles from

previous issues, and publishing fewer articles so that the denominator of the impact factor

equation becomes smaller.3

2 Impact factor of journal A can be calculated as the ratio of (citations in year t to articles published in A in year t-1 and year t-2) / (articles published in A in year t-1 and year t-2). 3 In Richard Monastersky, “The Number That’s Devouring Science,” Chronicle of Higher Education, October 14, 2005, p A12 - 17.

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A different method for journal rankings is based upon survey of faculty,

department administrators, and/or journal article authors. Borde, Cheney, and Madura

(1999) rank 55 finance, insurance, and real estate journals by surveying 218 finance

department chairs among whom 125 responded. A recent article by Oltheten,

Theoharakis, and Travlos (2005) ranks top 40 journals, consisting of finance, economics

and accounting journals, with a global survey of 862 finance academics. While survey

studies provide an alternative way of assessing journal quality, they are also subject to

biases. They have been criticized on the grounds of self-serving and predisposition bias

(Jobber and Simpson 1988, and Todorov and Glanzel 1988). Oltheten et al. (2005) find

that senior faculty rank journals differently from junior faculty and European/Asian

academics rank journals differently from their US counterparts. In addition to the

changes in research goals as suggested by Oltheten et al., many senior faculties may also

have passed their prime research time and thus are less familiar with the newer and

upcoming journals. Kim, Morse, and Zingales (2006) echo this view suggesting that the

productivity of economics and finance faculty is at the highest during their rookie years,

but declines monotonically with age and rank. This “slow-fading memory” creates a bias

in favor of older journals with which senior faculties are more familiar. For example, in

Borde et al. (1999), Journal of Financial and Quantitative Analysis is ranked the second,

while Review of Financial Studies, a comparatively new journal, is ranked a distant fifth;

a result inconsistent with the impact factor analysis and the views of many top

researchers. Other newer journals such as Journal of Corporate Finance and Journal of

Financial Markets are not included in the survey. Similarly, home bias helps explain why

European/Asian academics rank European/Asian-based journals higher.4 4 Many academic institutions also consider other ways to justify the quality of a journal, such as the

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The objective of this research is threefold. First, we propose in this paper an

Author Affiliation Index as another alternative measurement of finance journal quality.

Author Affiliation Index can be constructed in view of the proportion of articles that are

written by authors affiliated with top-notch research institutions in the journal. The basic

premise of the Author Affiliation Index is as follows: to protect their reputation capital,

top-ranked institutions employ productive faculty who accomplish high-quality and

influential researches. Therefore, when this group of researchers aspires to and publishes

more articles in certain journals, these journals become more influential and are of better

quality. Of course, the reverse could also be true. That is, a reputable journal will only

select high quality research to publish.

Here three notions are relevant to our analysis. (1)Although all articles written by

these authors are not of high quality, top-ranked institutions generally have a higher

standard on faculty research. To preserve their reputation capital, these institutions often

require their faculty to publish in a certain set of journals with relatively clear-cut pecking

order. Indeed, Fishe (1998) finds that full professors affiliated with a top 20 finance

department place an average of 1 out of 3 articles in the top 3 finance journals, while

professors in other non-top 20 Ph.D. granting programs have a much lower ratio. Top-

ranked journals, therefore, have higher authorship concentration from top finance

departments. Hence it is interesting to verify this pattern in a dataset that consists of more

editorial board composition, the institutional affiliation of the journal, and/or acceptance rate. These, however, are very noisy measures of journal quality. For example, acceptance rate is widely adopted as an important factor to rank journals, but it is subject to many drawbacks and is perhaps the most misleading benchmark on journal quality ranking. First, the acceptance rates as in Cabell’s (2005) are self-reported. Second, even if accurate, acceptance rate of a journal is subject to authors’ self-selection bias. It is, therefore, meaningless to compare an acceptance rate of 10% for the Journal of Financial Economics with an equal acceptance rate of a lower-ranked journal. This authors’ self-selection bias is especially acute for many finance journals which often charge a significant amount of submission fee.

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journals differing in quality and finance programs that go beyond major research

universities.

(2) The validity of the Author Affiliation Index does not require the knowledge of

the direction of causality between the quality of the journal and the reputation of author

affiliations. The direction of causality is not our main concern. Instead, we are interested

in the association between journal quality and who publish in these journals. A significant

correlation is all that is needed for the efficacy of the index. (3) Author Affiliation Index

is admittedly not a perfect instrument to measure journal quality, so are citation-based

impact factors and survey-based faculty perceptions. What we are proposing is an

alternative measure that is intuitively clear, easy to compute, and capable of providing

credible and objective assessment of finance journal quality.

The second objective of this work is to rank popular finance journals using

Author Affiliation Index, to compare our rankings with prior studies, and to validate this

ranking system using a series of sensitivity analysis.

The third objective of our research is to investigate the pattern of authorship/co-

authorship across a spectrum of journals differing in quality. This exercise serves two

purposes. (1) Fishe (1998) finds that researchers at elite universities place a significant

portion of their research in top-tier journals, but journals ranked 5-15 are good substitutes

for top-tier journals at non-elite Ph.D. programs. Using our journal rankings, we will be

able to examine if similar “substitution effect” exists in various levels of finance

programs. (2) Kim et al. (2006) document that collaboration between researchers of elite

and non-elite programs has become very common in a set of top-ranked economics and

finance journals. Our inquiries in this study are able to answer such questions as whether

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this pattern of co-authorship extends beyond top-ranked journals and whether the

observed pattern is consistent with our journal ranking system. Our results also provide

useful information for prospective authors who are searching for the right co-authors to

work with, and the appropriate journals to publish their work.

Based upon various definitions of the Author Affiliation Index, our findings

indicate that Journal of Finance, Review of Financial Studies, Journal of Financial

Economics, Journal of Financial and Quantitative Analysis, and Journal of Business

unambiguously claim the top five spots in finance journal rankings. Some newer journals,

such as Journal of Corporate Finance and Journal of Financial Markets, while ranked

lower or not ranked at all in the other studies, score impressively in our analysis.

Compared with prior studies, our rankings are highly correlated with most of those

journal rankings. Using our ranking system, we find that journal ranks increase in

conformity of authorship from elite (top 80) universities. For non-elite research

universities, journals in the near-top-tier caliber appear to be their primary target journals

and thus good substitutes for top-tier publications. Furthermore, collaboration (co-

authoring) between faculty in elite and non-elite programs is more prevalent than that

within elite programs across all tiers of journals, consistent with Kim et al. (2006) that the

externality of affiliation with elite colleges has disappeared. Co-authorship between top

80 programs, however, is still more common in top-tier journals; while co-authorship

between top 80 and other programs is more dominant in lower-ranked journals.

The remainder of the paper is structured as follows: Section II discusses the

construction of the Author Affiliation Index and the pros and cons of various definitions.

Forty one finance journals are ranked according to the Authors Affiliation Index in

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Section III. In Section IV we test the sensitivity of the journal ranking to different

definitions of the Index. Patterns of authorship and co-authorship are reported in Section

V. Finally, Section VI concludes.

II. Methodology

A. The formula

The original Author Affiliation Index was devised by Harless and Reilly (1998) to

rank journal quality for their institution’s internal consumption. It is subsequently

employed in evaluating operations management journals (Gorman and Kanet, 2005). The

original formula (Harless and Reilly, 1998, and Gorman and Kanet, 2005) for the Index

takes the form of:

∑

∑

∈

∈

+=

mi iii

mi ii

j nyx

nxAAI

/)(

/ (1)

where AAIj measures the Author Affiliation Index for journal j; xi is the number of

authors from a set of top US institutions (x) in article i; yi is the number of US academic

authors in article i not from the top institution set (y); n is the total number of authors in

article i, and i is drawn from a set of m articles.

The efficacy of the original formulation of the Author Affiliation Index, therefore,

depends on a number of factors. First, it is very important to determine what constitutes

the sample of top-notch research institutions (dataset x). That is, which universities and

how many universities should be included in this dataset? The original formula employed

in Harless and Reilly (1998) defines this dataset as comprising of top 60 US business

schools. However, there are problems associated with this pool of top 60 business

schools. First, should this pool of institutions be business schools in general, or discipline

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specific? For example, Brown University is included in this pool of business schools, but

in fact Brown does not have a business school although it houses strong non-financial

economists. Therefore, isn’t it more sensible to compile a set of top-notch programs for

each discipline?

Second, it may be problematic to assume that the top program set is equal in size

for all disciplines as the size of each discipline in the business schools differs

substantially. For instance, MIS is a much smaller discipline than finance, hence

inappropriate to use same sized dataset x. One size obviously could not fit all.

Third, the original formula considers only US academic institutions in the

numerator and the denominator in Equation (1), excluding non-academics as well as non-

US academic institutions. This approach is likely to create a bias in favor of journals that

have disproportionately more non-US authorships and journals that publish articles

authored by non-academics.

To see how Equation (1) works, we use hypothetical data in Table 1 for the

purpose of demonstration. According to Harless and Reilly (1998), which was later

adopted in Gorman and Kanet (2005), both the numerator and the denominator in

Equation (1) take account of only US academics. That is, datasets x and y contain only

US academics. For example, for article 1 where both authors are from the top US

university set, namely Harvard and Duke, the contribution to the numerator of Equation

(1) is 1.00 and the contribution to the denominator is also 1.00, given that both

institutions are US academics. The contribution to the numerator of article 2 is reduced

by half because Alabama is not in the top US university set. In articles 4 and 5, Harvard

counts in the numerator and the denominator, but JP Morgan as well as the University of

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Kuwait contribute to neither because they are not US academics. As for the case of

article 8, the contributions to the numerator and the denominator are both zero because

neither institution is US academics. On the other hand, in article 9 Alabama and CUNY-

Hunter do not contribute to the numerator, but weigh in fully to the denominator because

both are non-top US academics. On the basis of this hypothetical example, total

contribution to the numerator is 3.16 while that to the denominator sums up to 6.17.

Taken together, an AAI of 0.51 is created for this journal.

B. Potential biases

Obviously there are biases that may result from this method of reasoning. The

first type of bias arises because the formula is in favor of international journals that

publish inordinate number of papers written by non-US academics. The second type of

bias seems to benefit a journal that has myriads of non-academic participants. These

biases may not be serious decades ago when finance literature production in regions other

than North America was close to negligible, but can be significant today when European

and Asian authors contribute substantially to the research in finance.

These two types of biases are demonstrated in Table 2. Panel A illustrates the

calculation of AAI using a hypothetical journal that has disproportionately larger

authorships from non-academics and non-US academics. Panel B illustrates a

hypothetical journal with heavy concentration of US academics. The resulting differences

in AAIs are striking. AAI scores 1.00 (the upper bound) for Journal A, and a much lower

0.40 for Journal B. It is noted that all top-ranked universities are identical in both

journals, and the only difference emanates from the non-US academics and non-

academics in Journal A substituted by US academics in Journal B, hence a big

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discrepancy in the denominators. The implicit assumption of this ranking result is the

“superiority” of non-US academics and non-academics over US academics, which can

hardly be plausible.

One important question remains to be addressed in calculating AAIs is thus the

definition of datasets x and y in Equation (1). The biases that we have discussed above

stem from the definition of y. To avoid the non-US academics and non-academics bias

inherent in the original formula and the subsequent applications, we define the set (x+ y)

as including all authors, irrespective of academics or non-academics, and US or non-US

academics. To accommodate this new definition, x is also re-defined as containing all

top-tier universities, US or non-US. This definition excludes non-academics from dataset

x. Any possible bias as an outcome from this exclusion is presumably non-consequential,

since the major non-academic contributor in finance journals is perhaps the Fed.

Authorships from the Fed, however, are spread out into different branches. Technically

speaking, they do not belong to the same institution, just like UCLA and UC-Berkeley

are not the same university. Individual Fed branches, therefore, are not likely to be in the

top-notch institution set although they are quite productive in aggregate. To properly

handle this potential caveat, we also rank the journals based upon various definitions of x

and y, and further compare the upshot of the ranking differentials.

C. Definition of dataset x

As discussed in Section I, Harless and Reilly (1998) incorporate top 60 US

business schools in dataset x. Gorman and Kanet (2005) conduct sensitivity analysis to

see if changes of the size and composition of dataset x would lead to significant journal

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ranking alterations in the discipline of operations management. Both studies, however,

focus only on US academics. Our approach, being different from prior studies, is more

comprehensive and seeks to rectify potential pitfalls. x used in this paper is expanded to

incorporate not only US academics, but also non-US academics that qualify as top-tier

universities. We thus employ top 80 finance programs, US or non-US, in x. Sensitivity

analyses based upon different x and (x+ y) are conducted in Section IV.

To define top 80 finance programs, two issues are relevant. First, why top 80

finance programs are adopted, instead of, say, top 20? Although the top 20 finance

programs probably are truly “top-notch”, there are a few reasons why a broader set of

programs is more appropriate to use. (1) Journal rankings are valued not just by a handful

of elite colleges; they are equally important for institutions that reward faculty

scholarship. In fact, all AACSB accredited business schools require their faculty to

maintain faculty scholarship. Yet, tenure and promotion requirements could be quite

different between elite and non-elite, and between Ph.D. granting and non-Ph.D. granting

institutions. In general, an elite college values publications in a limited set of journals,

while non-elite colleges have more flexible standards. Essentially, Fishe (1998) shows

that the majority of Ph.D. granting institutions allow substitutes in research credentials

for full professors. Specifically, he finds that newly promoted full professors affiliated

with lower-ranked (non-top 20) Ph.D. granting finance departments publish an average of

19.6% and 32.4% of their articles in the top 4 and 5-15 ranked journals, respectively.

Hence faculty at lower-ranked schools have fewer publications in the top four finance

journals if they have a significant number of publications in the next tier of finance

journals. Limiting the dataset to a narrow list of elite universities, therefore, will leave out

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a large portion of second-tier journals that count as legitimate research outlets in non-elite

universities.

(2) The distinction between elite and non-elite universities is getting fuzzier. Kim

et al. (2006) demonstrate that there was a positive externality of being affiliated with an

elite university in the 1970s; this effect weakened in the 1980s and disappeared in the

1990s. They argue that the de-localization of production externalities renders faculty

more mobile, making it easier for non-elite universities to attract away the most talented

researchers with higher salary. Moreover, the decreasing communication costs have

increased co-authorship between elite and non-elite universities. In fact, they suggest

most of the increases in co-authorship occurred between elite and non-elite colleges.

Given these findings, it further justifies our choice of an enlarged set of top-notch

universities for the current study.

A concurrent question is: will the top 80 finance programs be excessive? To

alleviate any concern for this rather subjective number, sensitivity analyses based upon

different x and (x+ y) are carried out in Section IV. A few statistics, however, help to

explain the appropriateness of this dataset. There are more than 3,000 business schools

worldwide, among which 514 representing 21 countries are AACSB accredited. All

AACSB accredited business schools are required to maintain faculty scholarship. Our

choice of top 80 programs represents only slightly over 15% of all AACSB accredited

schools. In the sensitivity analysis, we also check a narrower (wider) dataset x including

only the top 60 (100) programs worldwide, which constitute less than 12% (20%) of all

AACSB accredited schools.

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The second issue involves the composition of the top 80 finance programs. Since

research quality is our focal point, it makes sense to define the top 80 finance programs

strictly in terms of research output. Popular magazine rankings such as Business Week

and US News and World Report take into consideration some other factors consisting of

teaching, student SAT scores, and university financial resources, which tend to penalize

public universities. These rankings are also not discipline specific. Chan, Chen, and Lung

(2005) compile a list of top finance programs on the basis of publications in various sets

of finance journals during the 15-year period from 1991 to 2004. Their dataset includes

20 major finance journals, but they also rank finance programs based upon top 5 journals.

Oltheten et al. (2005) record little disagreement among academics on what constitute the

top-tier journals, but the disagreement becomes more significant when one goes down the

pecking order of journal quality. According to Oltheten et al., Journal of Finance,

Journal of Financial Economics, Review of Financial Studies, Journal of Financial and

Quantitative Analysis, and Journal of Business are generally perceived as the top 5

finance journals.5 Finance programs ranked by these five journals seem to stir the least

controversy.6 Therefore, we adopt Chan et al.’s top finance programs list in our analysis.

Note that their ranking is a global ranking, thus suits our definition of the dataset x well.

The list of top 80 (and top 100 for sensitivity analysis) finance programs worldwide is

shown in the Appendix. 7

5 Only European academics consider Journal of Banking and Finance one place above Journal of Business. 6 The variation in the number of weighted articles published in these top 5 journals is more significant for the higher-ranked institutions. The variation becomes meaninglessly small when one moves down to the bottom half of the list. Since we are interested in top research finance programs only for the numerator in Equation (1), the small variation among lower-ranked institutions is not a concern. 7 A small number of major universities either have a “combined” department of economics and finance (e.g., Columbia, Rutgers, and Baruch College), or have no finance department (e.g., Princeton). Our definition of finance programs, therefore, applies to institutions that have sufficient contribution to the top-

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D. A numerical example

In Table 3 we demonstrate the calculation of AAI using our definition of x and

(x+y). Since all institutions, US and non-US, academics and non-academics, contribute to

the denominator of Equation (1), the denominator for each article must sum up to one.

Using this approach, the Author Affiliation Index computed from Table 3, where the

author affiliation data entries are identical to those of Table 1, is a smaller 0.316 as

opposed to 0.51 shown in Table 1.

III. Ranking Finance Journals Using Author Affiliation Index

A. AAI rankings

We rank 41 finance journals by applying our calculation of the AAI values. In

Equation (1), dataset x contains the top 80 finance programs worldwide ranked on the

basis of publications in the top 5 finance journals, while dataset (x+ y) includes all

authors: US or non-US academics, academics or non-academics. m, the number of

articles drawn from each journal, is set to equal 60. To obtain these sample articles, we

begin with the latest issue of each journal as of July 2005, and work backward until 60

articles are selected. Gorman and Kanet (2005) demonstrate that the AAI becomes

stabilized when the size of m increases to 50 or larger.

tier finance literature. Although Princeton does not have a finance department, its economics department does have a finance group that harbors a few very productive financial economists, hence is included in the top “finance programs” list. Since these schools are already included in our top 80 finance programs, their organizational structure per se does not impact our “finance journal rankings”. Faculty at these schools, especially Columbia and Princeton also publish in top-tier economics journals, and there is no doubt that publications in these economics journals are valued equally, if not more than top 3 finance journals. However, as shown in Fishe (1998), publications in top-tier economics journals are confined to researchers at elite (e.g., top 20) programs. Since these elite programs also publish heavily in top-tier finance journals, the exclusion of top economics journals when identifying top finance programs produces little biases, if any.

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We reconfirm this notion for the finance journals by examining six journals

three top-tier journals and three well-established and highly regarded older journals. A

few interesting results emerge from Figure 1. First, for most journals, AAI converges

and becomes considerably stable after the size of m reaches 40 or more. Second, Review

of Financial Studies (RFS) consistently scores higher in terms of AAI than do Journal of

Finance (JF) and Journal of Financial Economics (JFE) irrespective of size m. Financial

Management (FM) also coherently beats Journal of Financial Research (JFR) and

Financial Review (FR) once the size of m exceeds 10. JFR, on the other hand, persists in

having higher AAIs than FR when m exceeds 35. Therefore, a consistent behavior of the

AAIs is observed for various finance journals when m is greater than 40, suggesting that

our choice of 60 sample articles to evaluate AAIs is well justifiable.

The selected 41 journals are the most popular finance journals indexed by the

Finance Literature Index8 and are very similar to the journals included in prior studies

such as Borde, Cheney, and Madura (1999) and Oltheten et al. (2005), with only few

exceptions. We exclude such prestigious economic journals as American Economic

Review, Journal of Political Economy, and Econometrica, although they are highly

regarded by financial economists and are cited often. This is done for the following two

reasons. First, although these journals are frequently cited by finance research, they

publish mostly non-financial economics articles. For example, finance research cites

Econometrica frequently because of the methodology used (e.g., GARCH process).

Although these journals are widely envisioned to be the best economic journals, cross-

8 J.L. Heck, Finance Literature Index, 1999.

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disciplinary bias exists, as such they are ranked below top 5 finance journals according to

the survey of finance faculty in Oltheten et al. (2005).

Second, the top 80 finance programs used in this paper may not be the best x to

calculate the AAIs for these non-finance journals. This is because articles in these

economics journals are published mostly by finance faculty from elite universities only

(Fishe, 1998). For the same reason, those well-cited accounting journals, such as Journal

of Accounting Research, are also excluded from our study. Obviously, it is not fair to

rank accounting journals using top finance programs. Furthermore, we do not include

educational journals, journals that target primarily for practitioners as well as those

mainly consisting of invited articles.

Table 4 presents the results of such ranking. Not to our surprise, Journal of

Finance, Review of Financial Studies, Journal of Financial Economics, Journal of

Financial and Quantitative Analysis, and Journal of Business take the top five spots,

which is in accordance with those findings by prior journal ranking research such as

Oltheten et al. (2005). It is clearly indicated that Journal of Finance and Review of

Financial Studies practically tie for the leading position, while Journal of Financial

Economics is placed third. These top 5 journals are followed by some newcomers, such

as Journal of Corporate Finance and Journal of Financial Markets, which are situated

only slightly below the top 5. Journal of Financial Intermediation along with two older

journals, Financial Analysts Journal and Financial Management complete the top 10 list.

Financial Analysts Journal, however, has a higher ratio of invited papers, thus potentially

biases the AAI upward.

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B. Comparison of rankings with prior studies

In Table 5 we compare our AAI-based rankings with the results obtained in

related studies. Among these studies, Borde et al. (1999) and Oltheten et al. (2005) report

survey-based rankings by surveying department chairs and faculty. Our analysis is

broader in scope encompassing more finance journals. Compared with Oltheten et al.’s

top 10 list, this study differs from theirs on two journals, i.e., Journal of Financial

Markets and Journal of Banking and Finance. The former journal is ranked number 7 in

our study but a distant 16 in theirs, whereas the latter is number 6 in Oltheten et al., but a

lagging 23 in ours. It is known that Journal of Financial Market is a newer journal

specializing in financial market microstructure subjects, while Journal of Banking and

Finance is a well-established journal based in Europe. Evidently, familiarity and “slow-

fading memory” play some role in the discrepancies.

On the other hand, Chan et al. (2000), Borokhovich et al. (1995), and Zivney and

Reichenstein (1994) offer citation-based rankings. Since Borokhovich et al. and Zivney

and Reichenstein examine an earlier period, the number of finance journals considered in

their studies is very limited. The citation-based ranking in effect is cumbersome to

construct and uses only a two-year citation window, thus year-by-year variations pose a

problem. Cross-disciplinary comparison is also problematic under this method. For

example, Journal of Risk and Insurance is ranked quite low (22nd place) in Chan et al.’s

study, but is a 12th-ranked journal using AAI.9

In Table 6, we report the Spearman rank correlations between the AAI-based

ranking and rankings from five comparable studies. Asymptotic standard errors are

9 Some of the journal ranks in comparison studies are altered after non-finance journals are excluded from the ranking. Therefore, the ranks reported in Table 5 may not be identical to the ranks reported in the original article.

20

shown inside the parentheses. The Spearman rank correlation coefficients between AAI-

based ranking and survey-based rankings are 0.7616 and 0.7445 respectively for Oltheten

et al. (2005) and Borde et al. (1999). Both statistics are statistically significant at the 1%

level. Comparing AAI-based with citation-based rankings, the correlation coefficients are

0.7218, 0.7227, and 0.9131 respectively for Chan et al. (2000), Borokhovich et al. (1995),

and Zivney and Reichenstein (1994). Again, they are all significant at the 1% level. It can

be seen that the rank correlation is the highest between our study and Zivney and

Reichenstein’s as manifested by 91 percent. This is partially due to the small sample of

well-established journals employed in their study, hence less likely to have significant

variations in journal ranks.10

IV. Is AAI Sensitive to Different Definitions of x and (x + y)?

A. Rankings when only US academics are considered in datasets x and (x+ y)

As has already been pointed out in Section II, the method of Harless and Reilly

(1998) and Gorman and Kanet (2005), which are in favor of journals that publish more

articles written by non-US academics, may have induced bias in examining journal

rankings. To investigate the extent of this bias, in this subsection we proceed to re-rank

all 41 journals with narrower sets of x and (x+ y), with the former including top 80 US

academics and the latter excluding non-academics as well as non-US academics. In other

words, only US academics contribute to the numerator and the denominator in Equation

(1). Results under this new arrangement are reported in Table 7. The new AAIs and the

corresponding new ranking positions are presented in Columns 2 and 3. For comparison

10 Gorman and Kanet (2005) find lower correlations between AAI-based ranking and other rankings in a set of operations management journals. We attribute their lower efficacy to the bias that results from the exclusion of non-US academics and non-academics in their study.

21

purpose, we also report the original rankings from Table 4 in Column 4. It is clearly

indicated that the narrower definitions of x and (x+ y) produce results deceptively

favoring journals with disproportionately large number of non-US academics. For

example, European Journal of Finance ranks unexpectedly number one within this “US

only” dataset, but is only placed 37 with our method. Similar patterns can be perceived in

European Financial Review, European Financial Management, and International

Finance. By computing the Spearman rank correlation between this new AAI and our

original AAI, we find that the correlation coefficient is 0.625. More importantly, the rank

correlation between Oltheten et al.’s (2005) survey-based ranking and this new AAI is a

much smaller 0.4044. Therefore, the model proposed by Harless and Reilly (1998), and

later embraced by Gorman and Kanet (2005), is likely to conceal a significant degree of

distortion tilting toward journals with large number of non-US authorships.11

B. Rankings when the top finance programs pool is enlarged

In this subsection, we enlarge the dataset to top 100 instead of the previous top 80

(worldwide) in x. One hundred finance programs represent roughly 20% of all AACSB

accredited schools. As can be seen in the Appendix, the top 80 set includes only 9 non-

US academic institutions, but 8 more non-US academics show up when an additional 20

universities are added. The expansion of dataset x by 20%, therefore, enhances the

presence of non-US academics by almost 90%. Examining Table 8, however, we find

that the pecking order of these 41 finance journals does not appear to change much after

the top programs pool is broadened to 100. Three journals, however, benefit from this

11 Theoretically, this bias may be lessened by increasing the number of articles used to compute the AAI. However, the bias still exists even for a very large set of articles. Furthermore, some journals do not have enough issues and articles to form a very large database.

22

larger pool, namely, Journal of Empirical Finance, Journal of Behavior Finance, and

Pacific-Basin Finance Journal, with the first journal moving up 5 ranks, the second 10

ranks, and the third 8 ranks. Non-US based journals, such as Journal of Empirical

Finance and Pacific-Basin Finance Journal, may capitalize on the added non-US

academics in the top 100 list. The Spearman rank correlation between this new AAI and

the original AAI (based upon top 80 programs) is 0.9655 with an asymptotic standard

error of 0.0197.

C. Rankings when the top finance programs pool is reduced

In this subsection, we reduce the dataset to top 60 instead of the previous top 80

(worldwide) in x. Sixty finance programs are tantamount to approximately 12% of all

AACSB accredited schools. As can be seen in the Appendix, the top 60 set includes only

5 non-US academic institutions. Once again, Table 9 shows that the pecking order of

these 41 finance journals remains almost intact after the top programs pool is narrowed to

60. This is particularly true for the top 10 journals, with minor alterations in the pecking

order for the same set of journals. For example, Journal of Finance claims the crown,

while Financial Management is now ahead of Financial Analysts Journal by one place.

The top 10 journals list, therefore, is robust to the size of x. In addition, two journals

evidence more significant changes in terms of rank. Journal of International Money and

Finance moves up 7 places from 32 to 25, while Review of Financial Economics drops 7

places from 24 to 31. The Spearman rank correlation between this new AAI and the

original AAI (based upon top 80 programs) is 0.9645 with an asymptotic standard error

of 0.015.

23

D. Rankings when all non-academics are excluded

Since our dataset x comprises only academic institutions while (x+y) contains all

types of author affiliations, this measure may penalize journals that have larger

percentage of non-academic authors. This bias, if any, is theoretically small because few

non-academic institutions can qualify as top contributors to finance research although

collectively they might be significant. In this subsection, we re-calculate AAIs by altering

dataset (x+y) to include only academic institutions, and the results are presented in Table

10. The top 10 journal set exhibits little variation as a result of this change. Other

journals, like International Finance, Journal of Portfolio Management, and Journal of

Fixed Income, benefit more from this alternative computation. As expected, these

journals have more non-academic authorships. The Spearman rank correlation between

our original ranking and this new ranking is 0.9297 with an asymptotic standard error of

0.0419.

V. Pattern of Authorship and Co-authorship

In this section we choose six journals to examine the pattern of authorship and co-

authorship across journals differing in quality. Interesting issues addressed here include,

but are not limited to: (1) In what way are the pecking order of journals and author

affiliations related? To address this question, we further break down the finance programs

into elite, top 80, and other institutions. This may provide more insight as to why certain

journals are ranked higher than the others. (2) Kim et al. (2006) find that in top-ranked

journals co-authorship between authors of elite and non-elite departments has increased

dramatically in the past three decades. Is the collaboration limited to top-ranked journals

24

only, or does similar pattern also occur across a spectrum of journals? (3) Why would

researchers at the top schools publish in journals other than top-ranked ones? Is it because

of co-authorship? (4) Is the co-authorship pattern similar or different across journals?

That is, is there a journal-specific co-authorship clientele? The answer to this last

question has implication for Fishe’s (1998) study. Fishe identifies the journal

“substitution effect” for a group of Ph.D. granting institutions only. Our broader coverage

of journals and finance programs may provide some evidence on whether this journal

substitution effect extends to lesser universities.

Fishe (1998) studies the research standards for full professors at 90 Ph.D. granting

institutions and finds that authors affiliated with top 20 finance programs place 1 out of 3

of their articles in top 3 finance journals, while the same statistic declines substantially

for lower-ranked programs. Lower-ranked finance programs have different minimum

research expectations and full professors (as well as associate professors) of these

programs are able to find substitutes for the top 3 finance journals. His classification of

top 15 finance journals, however, is based upon Borokhovich et al. (1995), which in turn,

relies on older studies, hence newer finance journals such as Journal of Financial

Markets, Journal of Financial Intermediation, and Journal of Corporate Finance are not

included. We revisit this issue from an opposite angle and ask the question whether our

rankings of journals reflect the same publication pattern found in Fishe (1998).

The six journals chosen for this further analysis are Journal of Finance (JF),

Journal of Financial Economics (JFE), Journal of Corporate Finance (JCF), Journal of

Financial Markets (JFM), Journal of Financial Research (JFR), and Financial Review

25

(FR). JF and JFE are top 3 finance journals;12 JCF and JFM are newer journals ranked in

the top 10, hence can be considered as near-top journals; and JFR and FR are popular

good quality older finance journals but outside of our top 10 list. JFR is ranked 14, while

FR is ranked 20 in our ranking system.13 Therefore, these six journals represent sample

journals from three “tiers”; hence suitable for our study of the authorship/co-authorship

patterns.

Table 11 reports some statistics that are relevant to our inquiries. Row 1 shows

the percentage of articles that have at least one author from the top 20 finance programs.

Top-tier journals, JF and JFE exhibit substantially larger percentage of their publications

authored by researchers affiliated with top 20 programs. This percentage becomes lower

for the near-top-tier journals (i.e., JCF and JFM), and declines further to merely 3% in

FR. As such, JF and JFE serve as the primary research outlets for researchers at elite

programs, while JCF and JFM are their secondary outlets. Similar pattern could also be

observed when we enlarge author affiliations to the top 80 programs. The higher

statistics reported in row 2, however, imply that JCF and JFM now join the group of

primary target journals for researchers in this enlarged pool of top programs. This result

is thus consistent with the finding of Fishe (1998) that higher-ranked programs require

their faculty to publish in better journals, and lower-ranked programs allow for

substitutions of lesser journals. Take JCF as an example. 62% of all articles have at least

one author/co-author from top 80 finance programs, suggesting that JCF probably is

considered as a target journal as well as a close substitute for top-tier journals by the non-

12 JFE is chosen instead of Review of Financial Studies (RFS) because RFS and JF are very close in our ranking system. 13 JFR and FR are ranked higher in some prior studies. For example, in Fishe (1998) JFR is ranked 11 and FR 12.

26

elite major finance programs. The same cannot be true for FR where only 28% (3%) of

the articles have at least one author/co-author from top 80 (top 20) programs. FR,

therefore, is not viewed as a fair substitute for top-tier journals by the top 80 programs

although it may be regarded as one of the major research outlets for non-top 80 schools.

Kim et al. (2006) study the location-specific component in research productivity

and find that the externality of being affiliated with an elite college disappeared in the

most recent decade and that collaboration between faculty of elite and non-elite

universities becomes easier and has increased dramatically. Since they only examine top

journals, the extensive co-authorship they discover could be limited to certain group of

institutions. Therefore, we reexamine the implication of their study to see if similar

pattern of co-authorship occurred across a spectrum of journals differing in quality. Our

exploration yields several interesting observations.

First, rows 3 and 7 of Table 11 reveal that the wide-spread practice of co-

authorship is not limited to top-tier journals. The percentages of solo (co-authored)

articles are 30% (70%), 31.7% (68.3%), and 25% (75%) for JF, JFM, and JFR,

respectively. Regardless of journal quality, therefore, the number of co-authored articles

far exceeds that of solo authored articles by a ratio of more than two to one.

Second, confirming Kim et al. (2006), collaboration between faculty at elite and

non-elite programs is more prevalent than that within elite programs. Use JF as an

example, collaboration between faculty from the same or other elite programs is 26.2%

(0.143+0.119) of all co-authored articles, while the same statistic for collaboration

between faculty of elite and non-elite programs is 35.8% (0.191+0.167). Although the

numbers vary across journals, similar pattern is observed for all. A better view of the

27

results can be achieved in Figure 2, which helps to answer a few more questions. For

instance, why do researchers at elite universities also publish in non-top-tier journals? Is

it because of co-authorship? Taking JCF as an example, we find that 15% of the solo

authored articles are done by faculty from top 20 programs, and 5% (0.025+0.025) of the

co-authored articles are written by authors from within the elites. Clearly, some top-notch

scholars choosing to publish their research in journals of this level is not entirely because

their co-authors from lower-ranked programs want to do so. As a consequence, near-top-

tier journals, though not the primary outlets for researchers at elite programs, are

acceptable secondary outlets for these researchers. For lower-tier journals (JFR and

FR),14 co-authorship between faculty of elite programs is non-existent in our sample.

Publication of researchers at elite programs in this category of journals, therefore, is more

likely to be driven by the co-authors at non-elite programs. The fact that papers co-

authored within the elite programs do not seek JFR and FR as publication outlets thus

reconfirms our earlier rankings, where JCF and JFM are better ranked journals.

Third, the pattern of collaboration between faculty at top 80 and non-top 80

programs varies depending on journal quality. Figure 3 plots this pattern. Use JFE as an

example, collaboration between faculty from the same or other top 80 programs is 48.8%

(0.139+0.3499) of all co-authored articles, while the same statistic for collaboration

between faculty of top 80 programs and “others” (non-top 80 and non-academic

institutions) is a smaller 30%. It is possible that the ability of these non-top 80 program

authors to publish in top-tier journals is due to their co-authors. Both JF and JFE have the

same pattern. For the remaining four journals, however, co-authorship between top 80

14 “Lower-tier” is a relative term. JFR and FR are “lower-tier” journals compared with the other four journals studied in this section.

28

programs and “others” is more prominent (see Figure 3). For example, 24.4%

(0.049+0.195) of the co-authored articles in JFM are written by faculty from within the

top 80 programs, and 36.6% between top 80 programs and “others”. Since only 22% of

all multiple authored articles are co-authored among “others”, researchers from “others”

enhance their chance of publication in the near-top-tier journals by co-authoring with

faculty at top 80 programs. At the low end of the spectrum, only 4.1% (0.021+0.02) of

the FR co-authored articles are between top 80 program faculty, while 17.4% is between

top 80 programs and “others”. Since 58.7% of multiple authored articles are co-authored

by faculty within “others”, FR is not likely the primary target journal for the top 80

programs and authors from these top 80 programs publish their research in FR mainly

because of their co-authors.

Finally, the last row of Table 11 presents the percentages of multiple authored

articles that are accomplished between authors outside the top 80 programs. The number

ranges from 2.4% for JF to 58.7% for FR. Collaboration between faculty outside the top

80 programs, therefore, has a very slim chance of hitting JF. However, the odds increase

substantially with JFR and FR. This finding is consistent with our reasoning above that

FR is a primary target journal for programs beyond the top 80; researchers from top 80

programs publish in this journal because of their co-authors.

VI. Conclusions

Traditional journal rankings are either based on survey or impact factors

constructed from citations. Survey-based rankings suffer from self-serving bias, home

bias, surveyors’ “slow-fading memory” about older journals, and the lack of familiarity

29

with newer journals if the researchers are no longer research-active. Citation-based

ranking system has limitations of its own. Not only it is very time-consuming to

construct, but the choice of the number of cited journals to compose the impact factor is

debatable. The impact factor is also not immune from manipulation. Moreover, besides

the short citation window, many finance journals are not included in the Social Science

Citation Index.

This paper ranks 41 popular finance journals based upon a new method Author

Affiliation Index. We define AAI as the ratio of articles authored by faculty at the

world’s top 80 finance programs divided by the total number of articles by all authors.

This journal ranking method, therefore, provides the academics with an alternative

measurement of journal quality in addition to the traditional survey-based and citation-

based journal ratings. The efficacy of AAI-based journal rankings, however, depends on

a number of factor inputs including the definition of top-institution dataset, and the

decision to include/exclude non-US academics and non-academic authors. For example,

the AAI model used in Harless and Reilly (1998) and Gorman and Kanet (2005)

considers only US academics, which inevitably introduces bias against journals with the

majority contributors from US academics. We demonstrate that such bias is not trivial.

Similarly, including/excluding non-academics also has influence over journals that have

heavy non-academic representations. We argue in this paper that our definition of the

AAI mitigates these biases.15

15 One may suspect that lower-ranked journals can manipulate AAI by rejecting articles written by authors affiliated with lesser institutions. Although we cannot preclude such possibilities, it is not very likely for two reasons. First, as long as the journal is blind refereed, the editor will find it hard to persistently reject a well-received article written by a lower-ranked institution’s author. After all, AAI is not the only criteria to journal ranking, and a good quality article tends to have greater impact factor. Second, the limited supply of articles written by authors affiliated with top-ranked institutions will render the lower-ranked journals

30

According to our analysis of AAI, Journal of Finance, Review of Financial

Studies, Journal of Financial Economics, Journal of Financial and Quantitative Analysis,

and Journal of Business are the top five finance journals, being consistent with the

ranking results in a recent survey-based study by Oltheten et al. (2005) as well as some

citation-based studies.

The results from AAI also point out that Journal of Corporate Finance, Journal

of Financial Markets, Financial Analysts Journal, Financial Management, and Journal

of Financial Intermediation join force to complete the top 10 list. Three of these five

journals are newer journals and are not ranked in many of the earlier studies. Even when

they are ranked by some studies, the lack of familiarity with these journals tends to lead

to lower ranking positions for newer journals in a survey-based ranking system although

they may be better ranked in citation-based studies. These five near-top finance journals

are also “specialized” in the sense that they focus on a narrower defined subject area. For

example, Journal of Financial Markets specializes in microstructure, Journal of

Corporate Finance in corporate finance, while Journal of Financial Intermediation in

financial institutions. Specialized journals excelling in the finance research arena

conforms to the rapid development in the financial markets which frequently requires

more sophisticated intellectual exchanges in more finely defined subject areas. In the

decision to cease the publication of Journal of Business, the editor attributes it to the

advancement of very high quality specialized finance journals that overshadow the

original mission of Journal of Business.

unable to print if they insist on publishing only articles that enhance AAI. The publishers often show their concerns when the manuscript flows are interrupted.

31

Overall, our AAI-based journal ranking is highly correlated with the findings in

prior studies. For example, the Spearman rank correlation between our ranking and

Oltheten et al.’s (2005) is 76% which is statistically significant at the conservative level

of 1% or higher. The correlations with rankings drawn from other studies are also

reasonably strong and significant. Therefore, when properly constructed, AAI offers an

easy and credible way to supplement the existing journal ranking methods. We thus offer

the finance academics a sensible and feasible alternative to rank finance journals.

In the end, we examine the pattern of authorship/co-authorship for six journals

representing 3 tiers of finance journals. This exercise reveals the existence of the journal-

researcher clientele which is consistent with our ranking system. A few interesting results

emerge. First, on average more than two-thirds of all articles are co-authored, and this

pattern exists across journals of different quality. Second, in general higher-ranked

journals publish a larger proportion of articles authored/co-authored by researchers at

prestigious universities. Articles by top program researchers, however, also pop up in

lower-ranked journals time and again, but this proportion declines rapidly with journal

ranks. Third, across all six journals, researchers of elite programs co-author more articles

with people pertaining to non-elite programs than from within elites. Fourth, for JF and

JFE, researchers collaborating within the top 80 programs are more prevalent than

between top 80 and non-top 80 programs, although the opposite is true for the other four

journals. Fifth, researchers of elite programs place most of their researches in top-tier

finance journals, but near-top-tier journals such as JFM and JCF are also their research

outlets, suggesting that these journals are fair, though not perfect substitutes for top-tier

journals. This substitution effect almost completely disappears for the next tier journals

32

such as JFR and FR. A few elite program researchers publish in the lower-tier journals

because of their co-author(s) from non-elite programs. Sixth, the fact that near-top-tier

journals (e.g., JFM and JCF) have high concentration of top 80 program authors implies

that these journals are the primary target journals and are good substitutes for top-tier

journals at these programs. Seventh, collaboration within non-top 80 programs has slim

chance of hitting top-tier journals such as JF, but lower-tier journals such as FR are the

primary publication outlets for them. Overall, the pattern of authorship/co-authorship

over a spectrum of journals is thus consistent with the journal rankings based upon our

ranking system.

33

References

Alexander, J.C., and R.H. Mabry, 1994. Relative Significance of Journals, Authors, and Articles Cited in Financial Research,” Journal of Finance 49, 697-713. Amin, M., and M. Mabe, 2000. Impact Factors: Use and Abuse, Perspectives in Publishing, 1, Elsevier Science. Borde, S.F., J.M. Cheney, 1999. A Note on Perceptions of Finance Journal Quality. Review of Quantitative Finance and Accounting, 89-96. Borokhovioch, K.A., R.J. Bricker, K.R. Brunarski, and B.J. Simkins, 1995. Finance Research Productivity and Influence. Journal of Finance, 49, 1691-1717. Cabell, D.W.E., 2005. Cabell’s Directory of Publishing Opportunities in Economics and Finance. Cabell’s Publishing Inc. Beaumont, Texas. Chan, K.C., R.C.W. Fok, and M.S. Pan, 2000. Citation-Based Finance Journal Ranking: An Update. Financial Practice and Education, 132-141. Chan, K.C., C.R. Chen, and T.L. Steiner, 2002. Production in Finance Literature, Institutional Reputation, and Labor Mobility in the Academia: A Global Perspective. Financial Management, 31, 131-156. Chan, K.C., C.R. Chen, and P.P. Lung, 2005. A Global Ranking of Finance Programs by Finance Literature Productions: 1991-2004. Conference paper, Financial Management Association 2005 Annual Meeting. Fishe, R.P.H., 1998. What Are the Research Standards for Full Professor of Finance? Journal of Finance 52, 1053-1079. Gorman, M.F., and J.J. Kanet, 2005. Evaluating Operations Management-Related Journals via the Author Affiliation Index. Manufacturing and Service Operations Management 7, 3-19. Harles, D., and R. Reilly, 1998. Revision of the Journal List for Doctoral Designation. Unpublished report, Virginia Commonwealth University, Richmond, VA, http://www.bus.vcu.edu/economics/harless/harlessp.htm. Heck, J.L., 1999. Finance Literature Index, 6th edition, Irwin/McGraw Hill. Jobber, D., and P. Simpson, 1988. A Citation Analysis of Selected Marketing Journals. International Journal of Research in Marketing 5, 137-142.

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Kim, E.H., A. Morse, and L. Zingales, 2006. Are Elite Universities Losing Their Competitive Edge? University of Michigan and University of Chicago working paper. Monastersky, R., 2005. The Number That’s Devouring Science, Chronicle of Higher Education, A12 - 17. Oltheten, E., V. Theoharakis, and N.G. Travlos, 2005. Faculty Perceptions and Readership Patterns of Finance Journals: A Global View. Journal of Financial and Quantitative Analysis, 40, 223-239. Todorov, R., and W. Glanzel, 1988. Journal Citation Measures: A Concise Review. Journal of Information Science 14, 47-56. Zivney, T.L., and W. Reichenstein, 1994. The Pecking Order in Finance Journals. Financial Practice and Education, 77-87.

35

Table 1

AAI Calculations Based upon Harless and Reilly Contribution to both numerator and denominator are calculated based upon Equation (1) where only US academic institutions are considered. Article Author Affiliations Contribution to Contribution to Numerator Denominator 1 Harvard, Duke 1.00 1.00 2. Harvard, Alabama 0.50 1.00 3. Harvard, Alabama, CUNY-Hunter 0.33 1.00 4. Harvard, JP Morgan 0.50 0.50 5. Harvard, U Kuwait 0.50 0.50 6. Harvard, Alabama, 0.33 0.67 JP Morgan 7. U Kuwait, Alabama 0.00 0.50 8. U Kuwait, U Nairobi 0.00 0.00 9. Alabama, CUNY-Hunter 0.00 1.00 10. JP Morgan, Fed 0.00 0.00 Total: 3.16 6.17 AAI = 3.16/6.17 = 0.51 ________________________________________________________________________ Note: Institutions with bold face font are assumed from a set of top-notch universities.

36

Table 2 AAI Calculation Based upon Harless and Reilly Is Biased in Favor of Non-US and Non-academic Authorship Contribution to both numerator and denominator are calculated based upon Equation (1) where only US academic institutions are considered. Panel A: Journal with more non-US and non-academic authorship

Article Author Affiliations Contribution to Contribution to Numerator Denominator 1 Harvard, Duke 1.00 1.00 2. Harvard, JP Morgan 0.50 0.50 3. Harvard, U Kuwait 0.50 0.50 4. U Kuwait, U Nairobi 0.00 0.00 5. JP Morgan, Fed 0.00 0.00 Total: 2.00 2.00 AAI = 2.00/2.00 = 1.00 Panel B: Journal with US academic authorship only

Article Author Affiliations Contribution to Contribution to Numerator Denominator 1 Harvard, Duke 1.00 1.00 2. Harvard, Alabama 0.50 1.00 3. Harvard, CUNY-Hunter 0.50 1.00 4. Alabama, CUNY-Hunter 0.00 1.00 5. Auburn, Villanova 0.00 1.00 Total: 2.00 5.00 AAI = 2.00/5.00 = 0.40 ________________________________________________________________________ Note: Institutions with bold face font are assumed from a set of top-notch universities.

37

Table 3 AAI Calculations Based upon Our Definition of Dataset x and (x + y). Based upon Equation (1), data set x includes top-80 finance programs worldwide; while data set (x + y) includes authors from all affiliations. ________________________________________________________________________ Article Author Affiliations Contribution to Contribution to Numerator Denominator 1 Harvard, Duke 1.00 1.00 2. Harvard, Alabama 0.50 1.00 3. Harvard, Alabama, CUNY-Hunter 0.33 1.00 4. Harvard, JP Morgan 0.50 1.00 5. Harvard, U Kuwait 0.50 1.00 6. Harvard, Alabama, 0.33 1.00 JP Morgan 7. U Kuwait, Alabama 0.00 1.00 8. U Kuwait, U Nairobi 0.00 1.00 9. Alabama, CUNY-Hunter 0.00 1.00 10. JP Morgan, Fed 0.00 1.00 Total: 3.16 10.0 AAI = 3.16/10.0 = 0.316 ________________________________________________________________________ Note: Institutions with bold face font are assumed from a set of top-notch universities.

38

Table 4 Ranking Finance Journals Based upon AAIs

∑

∑

∈

∈

+=

mi iii

mi ii

j nyx

nxAAI

/)(

/

where xi is drawn from the top 80 university set x; (xi + yi) includes authors from all types of affiliations, and m=60.

Journal Rank Journal Title AAI 1 Journal of Finance 0.803 1 Review of Financial Studies 0.803 3 Journal of Financial Economics 0.709 4 Journal of Fin and Quantitative Analysis 0.599 5 Journal of Business 0.558 6 Journal of Corporate Finance 0.511 7 Journal of Financial Markets 0.484 8 Financial Analysts Journal 0.372 9 Financial Management 0.370 10 Journal of Financial Intermediation 0.353 11 Mathematical Finance 0.294 12 Journal of Risk and Insurance 0.292 13 European Finance Review 0.286 14 Journal of Financial Research 0.272 15 Journal of Derivatives 0.250 16 Journal of Financial Services Research 0.247 17 Fin Markets, Institutions and Instruments 0.242 18 Journal of Computational Finance 0.239 18 Journal of Empirical Finance 0.239 20 Financial Review 0.206 21 Review of Quantitative Fin and Acct 0.203 22 European Financial Management 0.199 23 Journal of Banking and Finance 0.197 24 Review of Financial Economics 0.194 25 Quarterly Review of Econ and Fin 0.189 26 Journal of Fixed Income 0.181 27 International Finance 0.172 28 Journal of Portfolio Management 0.158 29 Journal of Futures Markets 0.150 30 International Review of Econ and Finance 0.147 30 Journal of Behavioral Finance* 0.147 32 Journal of International Money and Finance 0.142 33 Multinational Finance Journal 0.133 34 J of Multinational Financial Management 0.128 35 Journal of Int. Fin Markets, Inst. & Money 0.119 36 Pacific-Basin Finance Journal 0.114 37 European Journal of Finance 0.097 38 Journal of Business Fin and Acct 0.094 39 International Review of Financial Analysis 0.071 40 Global Finance Journal 0.042 41 Applied Financial Economics 0.028

* 51 articles since first issue in 2003.

39

Table 5 Comparison of Different Ranking Studies This table compares AAI rankings of finance journals with prior studies. Ranks reported for comparable studies may not correspond to the original ranks after the exclusion of non-finance journals. Journal Title AAI Oltheten Borde Chan Zivney Borokhovich Journal of Finance 1 1 1 1 2 3 Review of Financial Studies 1 3 5 3 4 2 Journal of Financial Economics 3 2 3 2 1 1 Journal of Fin and Quantitative Analysis 4 4 2 5 5 5 Journal of Business 5 5 4 4 3 4 Journal of Corporate Finance 6 9 NR 18 NR NR Journal of Financial Markets 7 16 NR NR NR NR Financial Analysts Journal 8 8 9 10 6 8 Financial Management 9 7 8 11 7 7 Journal of Financial Intermediation 10 10 13 7 NR NR Mathematical Finance 11 17 NR 8 NR NR Journal of Risk and Insurance 12 23 6 22 NR NR European Finance Review 13 20 NR NR NR NR Journal of Financial Research 14 12 10 16 10 12 Journal of Derivatives 15 21 NR 12 NR NR Journal of Financial Services Research 16 NR 20 15 8 13 Fin Markets, Institutions and Instruments 17 NR 26 NR NR NR Journal of Computational Finance 18 NR NR NR NR NR Journal of Empirical Finance 18 11 NR 6 NR NR Financial Review 20 14 19 21 13 10 Review of Quantitative Fin and Acct 21 NR 18 26 NR NR European Financial Management 22 24 NR NR NR NR Journal of Banking and Finance 23 6 7 9 11 11 Review of Financial Economics 24 NR 24 NR NR NR Quarterly Review of Econ and Fin 25 NR NR 25 NR NR Journal of Fixed Income 26 NR 21 20 NR NR International Finance 27 NR NR NR NR NR Journal of Portfolio Management 28 13 11 14 9 9 Journal of Futures Markets 29 24 16 17 12 8 Journal of Behavioral Finance* 30 NR NR NR NR NR International Review of Econ & Finance 30 NR 22 NR NR NR Journal of International Money and Finance 32 18 12 13 NR 6 Multinational Finance Journal 33 NR NR NR NR NR J of Multinational Financial Management 34 NR 27 27 NR NR Journal of Int. Fin Markets, Inst. & Money 35 NR 28 NR NR NR Pacific-Basin Finance Journal 36 25 NR 19 NR NR European Journal of Finance 37 NR NR NR NR NR Journal of Business Fin and Acct 38 22 15 24 14 14 International Review of Financial Analysis 39 NR NR NR NR NR Global Finance Journal 40 NR 25 NR NR NR Applied Financial Economics 41 NR NR NR NR NR * 51 articles since first issue in 2003; NR denotes no ranking.

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Table 6 Spearman Rank Correlations of AAI-based and Comparison Group Rankings This table analyzes the Spearman rank correlations between the AAI-based journal ranking and prior studies which are either survey-based or citation-based. ________________________________________________________________________ Oltheten Borde Chan Borokhovich Ziveney & et al. et al. et al. et al. Reichenstein ________________________________________________________________________ Rank Correlation 0.7616 0.7445 0.7218 0.7227 0.9131 Asymptotic Standard Error (0.116) (0.111) (0.1087) (0.048) (0.1747) N 24 26 26 14 15 ________________________________________________________________________

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Table 7 Rankings when Only US Academics are Considered in Equation (1) This table reports journal rankings when only US academics are considered in the numerator and the denominator of Equation (1). Journal Title . New AAI New Rank Original Rank European Journal of Finance 1.000 1 37 Review of Financial Studies 0.961 2 1 Mathematical Finance 0.958 3 11 European Finance Review 0.939 4 13 Journal of Finance 0.896 5 1 Journal of Financial Economics 0.883 6 2 European Financial Management 0.864 7 22 Journal of Fin and Quantitative Analysis 0.812 8 4 Journal of Financial Intermediation 0.802 9 10 Journal of Computational Finance 0.792 10 18 Journal of Business 0.715 11 5 Journal of Corporate Finance 0.713 12 6 Journal of Financial Markets 0.703 13 7 International Finance 0.702 14 27 Journal of Fixed Income 0.640 15 26 Journal of Derivatives 0.635 16 15 Journal of Empirical Finance 0.611 17 18 Journal of Portfolio Management 0.592 18 28 Journal of Banking and Finance 0.569 19 23 Journal of Risk and Insurance 0.553 20 12 Financial Analysts Journal 0.548 21 8 Journal of Financial Services Research 0.518 22 16 Pacific-Basin Finance Journal 0.507 23 36 Financial Management 0.500 24 9 Fin Mkts, Institutions and Instruments 0.497 25 17 Journal of Intl Money and Finance 0.485 26 32 Journal of Int. Fin Mkts, Inst. & Money 0.444 27 35 Multinational Finance Journal 0.436 28 33 International Review of Econ & Finance 0.388 29 30 Review of Quantitative Fin and Acct 0.361 30 21 Journal of Financial Research 0.339 31 14 Review of Financial Economics 0.328 32 24 Journal of Futures Markets 0.323 33 29 Quarterly Review of Econ and Fin 0.320 34 25 Journal of Behavioral Finance* 0.317 35 30 J of Multinational Fin Mgt 0.298 36 34 Financial Review 0.273 37 20 Journal of Business Fin and Acct 0.229 38 38 International Review of Financial Analysis 0.218 39 39 Applied Financial Economics 0.163 40 41 Global Finance Journal 0.129 41 40 * 51 articles since first issue in 2003.

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Table 8 Rankings when the Top Finance Programs Pool Is Increased to 100 This table reports journal rankings when the numerator of Equation (1) includes top 100 finance programs worldwide. Journal Title New AAI New Rank Original Rank Review of Financial Studies 0.842 1 1 Journal of Finance 0.820 2 1 Journal of Financial Economics 0.731 3 3 Journal of Business 0.653 4 5 Journal of Fin and Quantitative Analysis 0.637 5 4 Journal of Financial Markets 0.564 6 7 Journal of Corporate Finance 0.550 7 6 Financial Analysts Journal 0.472 8 8 Financial Management 0.447 9 9 Journal of Financial Intermediation 0.389 10 10 Journal of Risk and Insurance 0.369 11 12 Mathematical Finance 0.361 12 11 Journal of Empirical Finance 0.341 13 18 European Finance Review 0.336 14 13 Journal of Financial Research 0.330 15 14 Journal of Derivatives 0.312 16 15 Journal of Financial Services Research 0.283 17 16 Journal of Computational Finance 0.281 18 18 Fin Mkts, Institutions and Instruments 0.272 19 17 Journal of Behavioral Finance* 0.258 20 30 Journal of Banking and Finance 0.255 21 23 Quarterly Review of Econ and Fin 0.248 22 25 Review of Quant Fin and Acct 0.244 23 21 Financial Review 0.244 24 20 European Financial Management 0.243 25 22 Review of Financial Economics 0.219 26 24 International Review of Econ & Finance 0.217 27 30 Pacific-Basin Finance Journal 0.206 28 36 Journal of Intl Money and Finance 0.203 29 32 Journal of Fixed Income 0.200 30 26 Journal of Portfolio Management 0.183 31 28 Multinational Finance Journal 0.183 32 33 Journal of Futures Markets 0.175 33 29 J of Multinational Fin Mgt 0.172 34 34 International Finance 0.172 35 27 Journal of Int. Fin Mkt, Inst. & Money 0.167 36 35 Journal of Business Fin and Acct 0.117 37 38 European Journal of Finance 0.114 38 37 Intl Review of Financial Analysis 0.096 39 39 Global Finance Journal 0.086 40 40 Applied Financial Economics 0.064 41 41 * 51 articles since first issue in 2003.

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Table 9 Rankings when the Top Finance Programs Pool Is Decreased to 60 This table reports journal rankings when the numerator of Equation (1) includes top 60 finance programs worldwide.

Journal Title New AAI New Rank Original Rank Journal of Finance 0.673 1 1 Review of Financial Studies 0.667 2 1 Journal of Financial Economics 0.666 3 3 Journal of Fin and Quantitative Analysis 0.501 4 4 Journal of Business 0.472 5 5 Journal of Financial Markets 0.447 6 7 Journal of Corporate Finance 0.439 7 6 Financial Management 0.317 8 9 Financial Analysts Journal 0.300 9 8 Journal of Financial Intermediation 0.275 10 10 European Finance Review 0.247 11 13 Mathematical Finance 0.239 12 11 Journal of Computational Finance 0.239 12 18 Journal of Financial Services Research 0.233 14 16 Journal of Risk and Insurance 0.219 15 12 Journal of Derivatives 0.200 16 15 Journal of Empirical Finance 0.200 16 18 European Financial Management 0.195 18 22 Fin Markets, Institutions and Instruments 0.178 19 17 Journal of Financial Research 0.175 20 14 International Finance 0.164 21 27 Quarterly Review of Econ and Fin 0.164 21 25 Journal of Portfolio Management 0.153 23 28 Financial Review 0.147 24 20 Journal of Intl Money and Finance 0.142 25 32 Review of Quantitative Fin and Acct 0.133 26 21 Journal of Banking and Finance 0.133 26 23 Journal of Fixed Income 0.131 28 26 Journal of Futures Markets 0.108 29 29 International Review of Econ & Finance 0.106 30 30 Review of Financial Economics 0.103 31 24 Pacific Basin Finance Journal 0.092 32 36 European Journal of Finance 0.089 33 37 Journal of Behavioral Finance* 0.082 34 30 Multinational Finance Journal 0.081 35 33 Journal of Int. Fin Markets, Inst. & Money 0.072 36 35 Journal of Business Fin and Acct 0.069 37 38 J of Multinational Financial Management 0.058 38 34 Intl Review of Financial Analysis 0.032 39 39 Global Finance Journal 0.025 40 40 Applied Financial Economics 0.019 41 41 * 51 articles since first issue in 2003.

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Table 10 Rankings when Only Academics are Included This table reports journal rankings when only academic institutions are considered in both the numerator and the denominator of Equation (1).

Journal Title New AAI New Rank Original Rank Journal of Finance 0.875 1 1 Review of Financial Studies 0.847 2 1 Journal of Financial Economics 0.774 3 3 Journal of Fin and Quantitative Analysis 0.651 4 4 Journal of Business 0.574 5 5 Journal of Corporate Finance 0.541 6 6 Journal of Financial Markets 0.520 7 7 Financial Analysts Journal 0.490 8 8 Journal of Financial Intermediation 0.466 9 10 Financial Management 0.391 10 9 Journal of Financial Services Research 0.388 11 16 International Finance 0.385 12 27 Journal of Computational Finance 0.384 13 18 Journal of Portfolio Management 0.358 14 28 Fin Mkts, Institutions and Instruments 0.358 15 17 European Finance Review 0.353 16 13 Journal of Risk and Insurance 0.328 17 12 Mathematical Finance 0.319 18 11 Journal of Fixed Income 0.312 19 26 Journal of Derivatives 0.293 20 15 Journal of Financial Research 0.279 21 14 Journal of Empirical Finance 0.260 22 18 Journal of Banking and Finance 0.251 23 23 European Financial Management 0.233 24 22 Review of Financial Economics 0.232 25 24 Financial Review 0.226 26 20 Quarterly Review of Econ and Fin 0.221 27 25 Review of Quantitative Fin and Acct 0.207 28 21 Journal of Intl Money and Finance 0.182 29 32 Journal of Futures Markets 0.175 30 29 Intl Review of Economics & Finance 0.169 31 30 Journal of Behavioral Finance* 0.169 32 30 Multinational Finance Journal 0.144 33 33 J of Multinational Fin Mgt 0.134 34 34 Journal of Int. Fin Mkts, Inst. & Money 0.128 35 35 Pacific Basin Finance Journal 0.123 36 36 European Journal of Finance 0.111 37 37 Journal of Business Fin and Acct 0.097 38 38 International Review of Fin Analysis 0.078 39 39 Global Finance Journal 0.044 40 40 Applied Financial Economics 0.031 41 41 * 51 articles since first issue in 2003.

Table 11 Pattern in Authorship This table reports pattern of authorship in six finance journals: Journal of Finance (JF), Journal of Financial Economics (JFE), Journal of Corporate Finance (JCF), Journal of Financial Markets (JFM), Journal of Financial Research (JFR), and Financial Review (FR). Authorship Pattern JF JFE JCF JFM JFR FR

% articles with at least one author from top 20 0.55 0.48 0.15 0.22 0.05 0.03 % articles with at least one author from top 80 0.87 0.75 0.62 0.58 0.38 0.28 % solo authored articles 0.3 0.283 0.333 0.317 0.25 0.233 From top 20 0.39 0.35 0.15 0.105 0 0.07 From top 21-80 0.28 0.35 0.6 0.37 0.33 0.36 From “others” 0.33 0.29 0.25 0.53 0.67 0.57 % co-authored articles 0.7 0.717 0.667 0.683 0.75 0.767 At least one from top 20 0.62 0.53 0.15 0.22 0.05 0.03 At least one from top 80 0.95 0.77 0.55 0.63 0.4 0.24 All from top 20 and same school 0.143 0.116 0.025 0.024 0 0 All from top 80 and same school 0.238 0.139 0.125 0.049 0.067 0.021 All from top 20 but not same school 0.119 0.163 0.025 0 0 0 All from top 80 but not same school 0.381 0.349 0.075 0.195 0.11 0.02 At least one from top 20, one from 21-80 0.191 0.209 0.025 0.146 0.067 0 At least one from top 20, one from “others” 0.167 0.116 0.075 0.097 0 0.022 At least one from top 80, one from “others” 0.333 0.30 0.375 0.366 0.222 0.174 All from “others” 0.024 0.116 0.375 0.22 0.51 0.587

Figure 1 Convergence of AAI as the number of articles increases This figure illustrates the AAI scores for six finance journals. It is revealed that AAI converges when the number of articles employed increases.

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Figure 2 Co-authorship Pattern between Elite and Non-Elite Programs This figure depicts the percentages of all multiple authored articles that are: (1) co-authored by authors within elite programs; and (2) co-authored between faculty at elite and non-elite programs for Journal of Finance, Journal of Financial Economics, Journal of Corporate Finance, Journal of Financial Markets, Journal of Financial Research, and Financial Review.

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Figure 3 Co-authorship Pattern between Top 80 and Non-Top 80 Programs This figure exhibits the percentages of all multiple authored articles that are: (1) co-authored by authors within top 80 programs; and (2) co-authored between faculty at top 80 and non-top 80 programs for Journal of Finance, Journal of Financial Economics, Journal of Corporate Finance, Journal of Financial Markets, Journal of Financial Research, and Financial Review.

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Appendix. The 100 institutions with most weighted articles appearing in top 5 finance journals We report rankings based upon the top 5 finance journals. The weight is by institution and by co-authorship. The top 5 finance journals are Journal of Finance, Journal of Financial Economics, Journal of Financial and Quantitative Analysis, Review of Financial Studies, and Journal of Business.

Institution Country Rank Wt number of articles

NYU US 1 130.44 U Penn US 2 108.46 U Chicago US 3 102.33 Harvard U US 4 94.17 U Michigan US 5 86.58 UCLA US 6 85.83 Columbia U US 7 65.00 Duke U US 8 59.17 MIT US 9 57.83 Northwestern U US 10 56.83 Ohio State U US 11 56.75 Stanford U US 12 53.83 Cornell U US 13 51.04 U Rochester US 14 48.20 U Southern California US 15 45.67 U Illinois US 16 45.33 U British Columbia Canada 17 40.25 London Business School UK 18 35.67 Yale U US 19 34.78 UT-Austin US 20 34.58 Purdue U US 21 34.50 U Washington US 22 34.17 Arizona State U US 23 33.58 U North Carolina US 24 33.29 UC-Berkeley US 25 32.67 Carnegie Mellon U US 26 32.58 Indiana U US 27 31.92 U Florida US 28 31.67 U Maryland US 29 31.50 Boston College US 30 29.33 Virginia Tech US 31 27.50 UW-Madison US 32 25.58 Washington U US 33 25.17 U Notre Dame US 34 24.90 Vanderbilt U US 35 24.78 Penn State U US 36 23.75 Southern Methodist U US 37 23.25

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U Georgia US 38 22.50 U Minnesota US 39 22.50 Emory U US 40 22.25 U Utah US 41 21.92 Michigan State U US 42 21.42 Rutgers U US 43 21.33 U Iowa US 44 20.67 HK U Science and Technology Hong Kong 45 19.96 Dartmouth College US 46 19.25 Princeton U US 47 19.00 Tulane U US 48 18.17 Georgetown U US 49 17.83 U Arizona US 50 17.50 INSEAD France 51 16.58 LSU US 52 15.75 Baruch College US 53 15.67 UC-Irvine US 54 15.50 U Toronto Canada 55 14.33 U Virginia US 56 14.21 Rice U US 57 13.96 U Oregon US 58 13.67 U Pittsburgh US 59 13.25 UC-Davis US 60 12.83 Georgia State U US 61 12.75 U Missouri US 62 12.50 U Oklahoma US 63 12.33 U South Carolina US 64 12.25 Tel-Aviv U Israel 65 12.21 U Houston US 66 11.71 McGill U Canada 67 11.17 UC-Riverside US 68 11.00 BYU US 69 10.58 Clemson U US 70 10.00 U Colorado US 71 9.92 Santa Clara U US 72 9.83 U Alberta Canada 73 9.58 U Miami US 74 9.50 Case W Reserve U US 75 9.50 Boston U US 76 9.08 Iowa State U US 77 8.83 London School of Economics UK 78 8.67 Texas A&M U US 79 8.58 SUNY-Buffalo US 80 8.50 U Cincinnati US 81 7.58

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College William and Mary US 82 7.50 HEC France 83 7.33 Georgia Tech US 84 7.17 UW-Milwaukee US 85 7.17 Hebrew U Israel 86 7.03 Syracuse U US 97 6.67 Fordham U US 88 6.42 Oxford U UK 89 6.29 UC-San Diego US 90 6.25 Chinese U Hong Kong Hong Kong 91 6.13 North Carolina State US 92 6.08 UT-Dallas US 93 6.00 U W Ontario Canada 94 5.92 Southern Illinois U US 95 5.83 National U Singapore Singapore 96 5.58 Queen's U Canada 97 5.58 Washington State U US 98 5.33 Erasmus U Netherlands 99 5.29 George Mason U US 100 5.17

Source: Chan, Chen, and Lung (2005).

author affiliation index, finance journal ranking, and the pattern...

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