Twenty‐five years of Review of Financial Economics: A bibliometric overview

• Author: Debidutta Pattnaik,H. Kent Baker,Satish Kumar
• Published date: 01 January 2020
• DOI: http://doi.org/10.1002/rfe.1095
• Date: 01 January 2020

Rev Financ Econ. 2020;38:3–23. wileyonlinelibrary.com/journal/rfe

|

3

© 2019 University of New Orleans

1

|

INTRODUCTION

The scope of the Review of Financial Economics (RFE) is broad. It publishes empirical research covering all areas of financial

economics. The journal began publishing in the 1970s as the Mississippi Valley Journal and subsequently became the Review

of Business and Economic Research (RBER) in the early 1980s. RFE adopted its current name in 1994. It is the official journal

of the University of New Orleans published by Wiley since 2018. Before 2002, RFE was a semi-annual publication. In 2002,

the journal started publishing four issues a year. Also beginning in 2002, RFE introduced a special issue, usually on a popular

current financial topic. Tarun K. Mukherjee and Gerald A. Whitney are RFE’s current editors.

In 2018, Scimago ranked RFE among the top 500 most influential sources classified under the category of economics,

econometrics, and finance. Its source normalized impact per paper (SNIP) is 0.408. SNIP measures contextual citation impact

by weighting citations based on the total number of citations in a subject field. A journal with a SNIP of 1.0 has the median

number of citations for journals in that field.

RFE exhibits steady growth in its impact factors furnished by Research Papers in Economics (RePEc). In June 2010, RFE’s

simple impact factor (SIF) in RePEc was 0.92. SIF, as per Zimmermann (2013). is measured as the sum of all citations to a jour-

nal divided by the number of articles published in the journal. Its recursive impact factor (RIF) was 0.04, which is the weight

of each citation of the journal. Among the other RePEc indicators, RFE’s discounted impact factor (DIF) in 2010 was 0.29.

Unlike SIF, DIF discounts each citation by its age. For example, a citation to RFE in 2015 is discounted by 0.25 in 2018. Thus,

DIF gives an edge to the most current citations. RFE’s recursive discounted impact factor (RDIF) in 2010 was 0.06. RDIF is a

Received: 16 September 2019

|

Revised: 6 December 2019

|

Accepted: 6 December 2019

DOI: 10.1002/rfe.1095

ORIGINAL ARTICLE

Twenty-five years of Review of Financial Economics:

A bibliometric overview

H. KentBaker1

|

SatishKumar2

|

DebiduttaPattnaik2

1Department of Finance and Real Estate,

Kogod School of Business, American

University, Washington, DC, USA

2Department of Management Studies,

Malaviya National Institute of Technology,

Jaipur, Rajasthan, India

Correspondence

H. Kent Baker, Department of Finance and

Real Estate, Kogod School of Business,

American University, 4400 Massachusetts

Avenue, NW, Washington, DC 20016, USA.

Email: kbaker@american.edu

Abstract

The Review of Financial Economics (RFE) has published empirical research cover-

ing all areas of financial economics since 1994. It celebrated its silver jubilee year of

publishing in 2018. Using bibliometric techniques, we analyze the journal's impact,

its prominent topics and most prolific authors including their affiliated institutions

and countries. We also identify the bibliographic couplings of authors and their af-

filiated institutions and countries, co-citations of journals, and co-occurrences of the

authors’ specified keywords. Our results show that about 83% of the published works

receiving at least one citation between 1994 and 2018 and about 68% are co-authored.

Among the important themes discussed in RFE, the words “stock”, “market,” and

“risk” occupy central positions in RFE publications. Bibliographic coupling analysis

identifies six clusters: (a) macroeconomic indicators, (b) investments, (c) financial

institutions, (d) stock market, (e) corporate governance, and (f) corporate financial

decisions.

KEYWORDS

bibliometrics, Gephi, Review of Financial Economics, Scopus, text analytics with R, VOSviewer

4

|

BAKER Et Al.

recursive measure of DIF by excluding citations from the same journal (Zimmermann, 2013). In 2010, RFE’s h-index, which

shows the h number of papers with at least h citations, was 7.

In September 2018, these figures had substantially improved for RFE. The first number is the 2018 impact score and the

number in parentheses is the 10-year history. Hence, these measures are as follows: simple impact factor 4.96 (2.46), recursive

impact factor 0.45 (0.27), discounted impact factor 1.03 (0.78), recursive discounted impact factor 0.09 (0.06), and h-index 24

(12). Additionally, RFE’s Euclidean citation score, which is the Euclidean length of its list of citations, is 234.44 (81.11). This

evidence indicates RFE’s growing influence and impact over time.

RFE is indexed in almost all major search engines including Scopus and Web of Science (WOS). Currently, it

is also in the Emerging Science Citation Index's (ESCI) journal list. RFE is ranked “B” in the ABDC (Australian

Business Dean Council) 2016 journal ranking. It is rated “1” in ABS (Association of Business Schools) Academic

Journal Guide (AJG) 2018, which means that RFE meets normal scholarly standards, including a general expectation

of peer review.

In recognition of RFE celebrating 25years of publication, this study provides a retrospective. It offers an in-depth anal-

ysis of the publication trend and citation structure of RFE articles, its most prolific authors, and their affiliated institutions

and countries. We also highlight the major themes discussed in RFE, classify RFE articles into six bibliographic clusters,

and present an overview of its content. Our mapping analysis validates the descriptive findings and visualizes the co-ci-

tation of the journals cited in RFE unveiling their intellectual associations. Through bibliographic coupling analyses, we

also explore the semantic association of RFE authors and their affiliated institutions and countries. The mapping analysis

visualizes the thematic links of the major discussions in RFE authors by examining the co-occurrences of their specified

keywords. Applying text analytics with R, the study highlights the most frequent discussions included in RFE between 1994

and 2018.

The remainder of the paper proceeds as follows. Section 2 discusses the study methodology and section 3 presents the de-

scriptive and network results. Section 4 graphically portrays the bibliographic data. Section 5 highlights the study's conclusions

and discusses potential limitations.

2

|

METHODS

The Scopus database was the source of the bibliographic data used in this study. It is the largest multidisciplinary

database of peer-reviewed literature in social science research (Bartol, Budimir, Dekleva-Smrekar, Pusnik, & Juznic,

2014; Norris & Oppenheim, 2007). Researchers widely recognize and frequently access Scopus for quantitative analyses

(Durán-Sánchez, Del Río-Rama, Álvarez-García, & García-Vélez, 2019; Guerrero-Baena, Gómez-Limón, & Cardozo,

2014).

With the application of quantitative techniques, bibliometric studies analyze the bibliographic material, classify the data and

construct representative summaries (Broadus, 1987; Pritchard, 1969). For example, researchers use bibliometrics to analyze

topics (Blanco-Mesa, Merigó, & Gil-Lafuente, 2017; Chung & Cox, 1990), journals (Andrikopoulos & Trichas, 2018), univer-

sities (Merigó, Muller, Modak, & Laengle, 2019), and countries (Mas-Tur et al., 2019).

In this study, we present a bibliometric overview of RFE in the form of both descriptive and network analyses. Our descrip-

tive analyses include the total number of publications, citations, citations per publication, and the citations per cited publication.

We present productivity and impact in the form of an h-index (Hirsch, 2005). Our network analyses involve bibliographic cou-

plings, co-citations, and co-occurrences.

We use VOSviewer and Gephi software to carry out major portions of the mapping analyses (Bastian, Heymann, &

Jacomy, 2009; van Eck & Waltman, 2017). VOSviewer uses two standardized weights—the number and total strength of the

links—for graphically visualizing the nodal network. The size of the nodes and the interlinking lines connecting the nodes

denote link relevance and strength. In general, a link represents a relation or connection between two items, which could be

a source, an author, an author's affiliation such as an institution or a country, or a keyword. Although the strength of a link

essentially represents significance or intensity of a relation in a network, its implication varies according to the type of biblio-

metric analysis. For example, the strength of a link for a bibliographic coupling indicates the number of cited references two

publications have in common; in case of co-authorships, the link visualizes the number of co-authored publications between

two researchers. Similarly, in case of co-occurring keywords, the strength of a link portrays the number of publications in

which both the terms occur together. We use VOSviewer and Gephi to visualize the bibliographic networks and a text mining

package (“tm” package) in R to visualize the important words discussed in the extant literature presented in the form of a

word cloud.