Ranking of economic journals: A statistical survey and analysis.

Ramrattan, Lall B. ; Szenberg, Michael

I. Introduction

The literature has focused on two prominent features of economics journals. One group has documented several underlying qualitative criteria in order to rank the journals. The other has attempted to make inferences from the compensation characteristics of the editors and editorial staff of the journals. In addition to these efforts, modem literature has assessed the expansion of economics journals to the domain of the Internet, and examined the shifting of their subject matter from the abstract to the less technical. Unfortunately, there are additional questions relating to the early concerns that remain unanswered. Successful rankings in the past have only considered the demand side viewpoint, ignoring the production characteristics of the journals. The lack of adequate data limits one's ability to estimate significant results of an econometric model. The purpose of this paper is to present the results of a larger survey in order to challenge some of the hypotheses in current literature, and to shed new ligh t on modern concerns about the technical competence of practitioners in economics and the effects of editorial compensation on the journals.

Several well-known surveys and studies have adequately documented the initial concerns. An early study by Liebowitz and Palmer (1984) used the number of citations a journal was credited with in the literature in order to rank them. A survey by Laband and Piette (1994) expanded this methodology to include the number of pages published and allowed for entry and exit of journals over time. A more recent article has shown how to use such a page-counting methodology to rank not only journals, but also the economics departments from which the articles originated (Dusansky and Vernon, 1998). These studies examined objective characteristics of the journal. A citation was viewed as the ". . . scientific community's version of dollar voting by consumers for goods and services" (Laband and Piette, 641). However, the supply side, production, or input characteristics, such as the magnitude and arrangement of the production staff, can also be used to establish the value of the journals. This paper collected such data to en able a supply side ranking.

A previous study (Lee and Szenberg, 1988) addressed the concern of literature on the effect of compensation of journal editors and editorial staff on the cost of journals to libraries and other subscribing institutions. Using the results from a survey of 50 economics journals, it explored the relationship between compensation of editors and editorial staff and circulation, controlled by qualitative characteristics such as institutional affiliations- government, university, and other. Among its results, it found that the elasticity between circulation and compensation was about 0.35, implying that a one unit percent increase in circulation would have a 35 percent increase in the editor's compensation. However, that study did not have significant t-values, implying that a larger sample or an improved specification was required. The present study utilized a larger sample, and concentrated on an improved specification guided by careful data exploration techniques. Factor analysis was used to sort out and create i ndices of colinear variables, in order to enhance modeling of the hypotheses.

Over the last two decades, the literature has documented a movement away from the technical and formalist writing style to a more practical and business oriented style within the discipline of economics. One such study by the Commission on Graduate Education in Economics (COGEE, 1991) was concerned with "what they see as 'empty formalism in the profession today." COGEE prescribed that the technical nature of the subject matter must be explained and justified, and not just exorcised from the discipline. In response, instructors of economics and their colleagues "... are relying on The Journal of Economic Perspectives (JEP) and The Journal of Economic Literature (JEL) to stay current in areas in which they may not specialize" (Becker, 1998, 128).

The advent of the Internet has caused a paradigm shift in the way journals distribute their literature and cut costs. The services of JSTOR, for instance, which include providing current and back issues of economics journals on the web, has been a strategic cost saving move for libraries and sponsor institutions. As Varian documented, the cost to digitize journal articles is about 50 cents per page. If capital costs are added for storing printed journals, he concluded, "... there may be considerable savings to digitization" (Varian, 1997, 97). Within the new Internet environment, Goffe and Parks (1997, 79) have, in a sense, resuscitated the pricing question raised by Lee and Szenberg (1988) that "editorial text editing costs do not change much in the electronic world." They proceed to argue that cost reduction of journals is a function of editorial work completed, implying that an explanation can be found within a model that accounts for staff inputs, including variables such as editorial assistants, secretar ies, and other salaried help. This study accommodates such gaps in the literature.

This paper proposes to answer questions noted above via the results of a survey of various economics journal editors. The next section describes the sample design, followed by data exploration techniques. The ranking section provides an alternative way of ranking the journals from the production characteristics end. The last section explains how an econometric model can be built to answer questions regarding both the cost and quality aspects of journals.

II. Sample Design

The sample design was a simple random survey of economics journals. We pulled a random sample of 250 out of the 600 journals (excluding the 50 or so governmental publications) for which the Journal of Economic Literature publishes articles in its "Contents of Current Periodicals" (Volume XXXVII (1), March 1999, 344-401). Sampling was conducted using a mailed questionnaire, email, telephone, and written follow-ups. The sample size of responses necessary to be considered significant varies depending on the proportion of expected responses for this type of survey. If we assume a 50:50 chance of receiving a response, then with a universe of 550, we would expect 226 responses received to be within a 95% confidence interval. The survey had 90 responses, which puts it at a 90% confidence level. (1) The "Report of the American Economic Association (ABA) Committee on the Journals" actually received 635 out of 1,100 or a response rate of 57.6% (AEA Papers and Proceedings, Volume 90 (2), May 2000, 528). The AEA also doe s a "Universal Academic Questionnaire" (UAQ) survey. In May 1999, it received 331 responses and in May 2000, 305 responses (ibid. 534). The universe of that survey is not given, but knowing that its membership (Regular, Junior, Life, and Honorary) exceeds 20,000, the response rate cannot be substantial. Using the AEA response percentage for the "AEA Committee on the Journals" study would require slightly less than 222 responses to reach a 95 percent confidence level, but compared with the UAQ study, our response rate is very attractive according to Snedecor and Cochran (1959).

The questionnaire had six parts corresponding to general, editorial, secretarial, professional, compensatory, and refereeing characteristics. The general section asked five questions regarding publications, circulation, invited articles, subscribers, and sponsors. The next two sections asked three questions regarding the number of editors, type of editors, (associate, assistant, and managing) and secretaries (part-time, full-time and others). The professional section had four questions seeking information regarding graduate assistants, copy editors, proofreaders and others. The section on compensation asked for four types of compensation data. The compensation for referees was designated as a dummy variable to equal "yes" if referees were paid.

The descriptive statistics in Table 1 show that average circulation is about 4,855 per year, with approximately 2,761 accounted for by paid subscription. About 80 percent of the journals have an institutional sponsor, and they publish an average of 4 or more issues per year. The study did not aim at a stratification of sponsors by institutional affiliations, such as government and universities. The expected number of invited articles is only about 20 percent. On average, the journals have about 7 associate editors. There are ten times as many associate and three times as many assistant as managing editors.

Data on compensation to editors was sparse. We had to supplement compensation figures with estimates for the reduction in teaching time for editors. The methodology we use is consistent with Lee and Szenberg (1988). We used the May 2000 figure of $90,068 from the ABA UAQ survey for tenured or tenure-track academic economists as equivalent to that of a representative editor. That figure was decreased by the percentage of teaching reduction indicated by the respondents.

We used factor analysis for data exploration. Factor analysis has the advantage of reducing the data to a few central variables and revealing something about how the data cluster. It helps identify relationships between observed values that cannot be discerned in an obvious way. Table 2 shows our extraction of five factors from the sample survey. The numbers indicate factor loading and explain how closely the 17 variables are correlated with the five factors. (2) The last row shows that the five factors combined explain about 53 percent of the variance in the data. The last column, the communality or [h.sup.2], demonstrates what percentage of variation in a variable is explained by the five factors taken together. We see that 81 and 86 percent of the variation in subscription and circulation, respectively, is accounted for by the five factors taken together.

The first factor is loaded in variable 2 (circulation). We have a priori knowledge that circulation has some relationship to subscription, which is brought out by the second highest loading on paid subscription (variable 3) with circulation. However, factor analysis also brings out the less obvious relationships like the association of other types of assistants (variable 12) and percent of invited articles (variable 4) to heavily circulated or heavily subscribed journals. A similar analysis shows that factor 2 is loaded in copy editors (variable 14) and in proofreaders (variable 15), and is bi-polar with the number of issues (variable 1). Factor 3 is loaded in the technical nature of the journals (variable 11), which is associated with managing editors (variable 8), and is not in concert with the percentage of invited articles (variable 3). Factor 4 is loaded in payments to referees (variable 17) and in the number of full-time secretaries (variable 10), and factor 5 is loaded in graduate assistants (variable 13).

It is worth observing if any variable loads highly in more than one of the factors. Almost all the variables fit this criterion. Their influence is spread broadly across several factors. The number of issues a journal publishes annually (variable 1) is bi-polar between factors 3 and 4, vs. factor 2. Sponsors (variable 5) is positively loaded in factors 4 and 5. While associate editors (variable 6) is loaded in factor 3, assistant editors (variable 7) is loaded in factors 2 and 4.

III. Ranking of Journals

In this section we propose a ranking of journals based on their production characteristics (Table 3). Unlike the demand side ranking mentioned above, this ranking is based on the journals' supply side characteristics. The method extracted the principal components of the set of variables identified in Table 1 and ranked the journals on a weighted average of their scores. Because the literature does not identify weights, we decided to give each variable equal weight in the ranking. There are two sets of rankings because the inclusion of the compensation variable severely limits the number of journals on which scores are available. However, if the compensation variable is excluded, we can rank 72 out of the 92 journals, 20 being excluded for having no data in some of their cells. When compensation is included, we can only rank 41 journals. The first column in Table 3 presents the ranking excluding compensation and the second column displays the ranking including compensation.

When compensation is included, the Journal of Economic Perspectives (JEP) is ranked first. Laband and Piette (1994, Tables 1 and A1) ranked the JEP fourteenth, based on citations in articles, and eleventh based on citations per character. Having started in the 1980s, it may appear that the JEP has worked its way up the ladder over time. However, time does not appear to be the influential factor. As Becker (1998) has pointed out, the JEP may have moved up in rank by providing the practitioners in the field with a non-technical source to stay abreast of the literature. Additionally, the table below shows that when compensation is left out of the editorial picture, the JEP ranking falls to number sixty-one, implying that having a strong and deep pocketed sponsor like the American Economic Association (AEA) is essential for the high quality of the journal.

IV. Model and Estimation

In this section, we specify and estimate a model to explain some current and ongoing questions in the literature. In particular, we will address two central issues: cost and the technical nature of journals.

A. A priori Specifications

The factor analysis above helps identify an econometric model to further explain the data. The cluster of Factor 1 among circulation, subscription, and percentage of invited articles indicates that those variables are, in a sense, redundant, as they are found to have significant causal links. We can choose one or the other, or have an index of them based on their degree of colinearity. To use all of them in an econometric model would add surplus meaning to the data. Therefore, we make the following specifications of the model to be estimated:

Lcomp = c(1) + c(2) * Lcir + c(3) * secpt + c(4) * gass + c(5) * prass + c(6) * cass (1)

Tech = c(7) + c(8) * Linvpct + c(9) * Lasso + c(10) * secft (2)

Issues = c(11) + c(12) * refbin + c(13) * Lass + c(14) * prass (3)

The variables are defined in Tables 1 and 4. L represents their logarithmetic value, and c(*) is the coefficient to be estimated. The list of instrumental variables we use represents the following modification of the data set. All independent variables, such as circulation, percentage of invited articles, and the index of assistants, were excluded.

Our a priori knowledge of Equation 1 draws from the work of Lee and Szenberg (1988), who used circulation as a prominent predictor variable for compensation, controlling for a variety of sponsorship variables such as university, government, and association in the background. We now attempt to improve that specification by keeping the sponsor in the background as an instrumental variable, and by explicitly adding a set of other effort variables.

The specification of Equation 2 is aimed at ascertaining whether the journals are maintaining their technical formalism, considering the recent call to be more pragmatic and business oriented. A validation of this specification would tell us that the goals, as expounded in the Journal of Economic Literature survey (COGEE, 1991), of keeping the essential technical aspects of economics, while making it somewhat user-friendly, would be asserted. We think that the technical journals would most likely be the ones to search for the best article and not necessarily invite an article. This has a two-pronged implication. First, reaching out to persons specialized in their field can produce a technical product. However, reaching out can also guarantee publication, regardless of whether or not the product is scientific. Technical journals would reach out to the more mature thinkers and, therefore, be more affiliated with associate rather than assistant or managing editors, and have a negative association with the percen tage of invited articles.

Equation 3 is specified to account for the wide range of the number of issues published by a journal, which, as Table 1 noted, may range from 2 to 12 per year. As the average number of issues exceeds four per year, the amount of work required to publish them is more challenging. The potential increase in the number of issues would necessarily engage the whole range of editors (associate, assistant, and managing), which we combined into an index called "Lass," which should have an overall positive effect. On one hand, the higher rate of production, measured by more frequent issues, could justify the journals' efforts to make payments to referees as well, and should also have an overall positive effect. On the other hand, greater emphasis on proof-reading would diminish the number of issues published, and have an overall negative effect.

B. Results and Implications

The estimated coefficients and their statistical properties are listed in Table 4, below. We obtained the best results using simultaneous equations with the GMM estimating technique (Greene, 2000). All the variables show significant t-values, which are mostly significant at the 99 percent confidence level.

The result of Equation 1 is most striking. It demonstrates that the elasticity between circulation and compensation to editors is 0.64, almost double that of the earlier estimate of 0.35 in the Lee and Szenberg (1988) study. On the one hand, part-time secretaries and graduate assistants tend to reduce compensation. On the other hand, proof-readers and copy editors enhance compensation, which would be apparent if all those functions were consolidated in the same person.

We note here the manner in which this result can shed some light on the issues considered in the Lee and Szenberg (1988) study, namely, that rising journal costs, in turn, escalate the costs of library items. As mentioned previously, if we interpret the predictor variables as a dollar value vote for the journal, then we can make some implications for pricing. Elasticity could be used to ascertain mark-ups above cost under conditions of profit maximization. Defining Markup = (Price - Cost)/Cost, and using the notion that marginal revenue, marginal cost, and price are the same for profit maximization under perfect competition, we obtain the optimal markup for the journals by the formula: 1/(1-inverse elasticity) - 1. Because we are dealing with an inelastic case, i.e., the elasticity for circulation is 0.65, the formula will not allow a markup. To that extent it underscores the earlier finding that journals do not escalate production costs of library items. We note that while our conclusion did not change from the previous study, the forces that enable it are different. Our results have incorporated the state of the economy wherein the advent of the Internet has put a downward pressure on costs, as we cited above.

The results of Equation 2 validate the hypothesis that technical journals would be the most likely to have associate editors, and not likely to invite articles. This provides a significant explanation for the existence of technical journals in the face of rapid changes towards the practical side of business. We can speculate that the conditions for the existence of this state of affairs can be ascribed to the journals being more user-friendly and keeping technical aspects contained in their pages to the essentials. The rise of the Journal of Economic Perspectives to the number one position illustrates this trend.

The signs of the results of Equation 3 are in accordance with what we expected. On the one hand, the more the referees (Retbin) are compensated and the higher the index of assistants (Lass), the more likely the journals are to have multiple issues. On the other hand, an emphasis on proofreading, or an equivalent increase in proofreaders, slows down the frequency of journal publications, as hypothesized.

V. Conclusions

This paper sets out to revisit methods to rank and assess cost and quality of economics journals via a statistical survey. The data allowed a ranking from the production or supply side of the journals as opposed to only the demand side ranking that was previously used in the literature. We were also able to get significant estimates to validate some hypotheses regarding editor compensation and the technical nature of the subject. In particular, we found that the elasticity of compensation with respect to circulation, i.e., 0.65, confirms the finding in the literature.

Regarding quality, this article validates some propositions discussed by the Commission on Graduate Education in Economics. The results indicate that while there have been complaints that the subject matter of economics has become increasingly technical, the journals have not abandoned essential formalism in their content. The Journal of Economic Perspectives' rise in rank to the number one position supported this finding as well. The JEP has risen to fill the major function of providing the specialist with a non-technical source to keep abreast of the literature. Finally, the significance of the production side viewpoint is underscored by the results of Equation 3, which show a significant relationship between administrative efforts and a journals' quality.

TABLE 1

Descriptive Statistics

Variables N Mean Min. Max.

 1. Issues per Year (Issues) 92 4.848 2 12
 2. Circulation (Cir) 85 4,855 200 80,000
 3. Paid Subscriptions (Sub) 91 2,761 0 40,000
 4. Pct.. of Invited Articles 84 19.92 0 100
 (Invpct
 5. Sponsor Binary (1 = Yes) (Spon) 89 0.7978 0 1
 6. Associate Editors (ASSO) 92 7.15 0 40
 7. Assistant Editors (ASSI) 92 2.359 0 41
 8. Managing Editors (Mng) 92 0.7554 0 6
 9. Part-time Secretary (SECPT) 92 0.5027 0 4
10. Full-time Secretary (SECFT) 92 0.1984 0 1
11. Technical Binary (1 = Yes) 89 0.5393 0 1
 (Tech)
12. Other Assistants (OASS) 92 0.2609 0 2
13. Graduate Assistants (GASS) 92 0.375 0 10
14. Copy Editors (CASS) 92 0.4565 0 1
15. Proof Readers (Prass) 92 0.3098 0 5
16. Teaching Reduction (Teachcut) 90 0.553 0 25

TABLE 2

Rotated Factor Loadings and Communalities Varimax Rotation

Variable Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

 1. Issues -0.082 -0.648 0.242 0.276 -0.104
 2. Cir 0.928 -0.000 -0.016 -0.029 -0.021
 3. Sub 0.891 0.048 -0.024 -0.036 -0.119
 4. Invpct 0.208 0.167 -0.625 -0.148 -0.188
 5. Spon -0.226 0.043 0.003 0.321 0.287
 6. ASSO -0.192 -0.419 0.353 -0.023 -0.49
 7. ASSI 0.037 0.261 -0.298 0.194 -0.088
 8. Mng 0.138 0.045 0.534 0.061 -0.111
 9. SECPT -0.178 0.154 0.123 -0.423 -0.445
10. SECFT 0.016 0.188 -0.101 0.652 -0.102
11. Tech -0.027 0.121 0.733 -0.271 -0.036
12. OASS 0.694 -0.106 -0.022 0.103 0.238
13. GASS -0.040 0.003 0.133 -0.137 0.765
14. CASS -0.128 0.689 0.028 0.323 0.038
15. Prass -0.096 0.749 0.199 0.099 -0.081
16. T. cut -0.110 -0.350 0.3 12 0.138 -0.321
17. Refbin 0.028 *** -0.022 *** 0.069 0.735 -0.029
Variance 2.3683 1.9414 1.6732 1.6253 1.3666
% Var 0.139 0.114 0.098 0.096 0.08

Variable Communality/[h.sup.2]

 1. Issues 0.572
 2. Cir 0.863
 3. Sub 0.812
 4. Invpct 0.52
 5. Spon 0.239
 6. ASSO 0.578
 7. ASSI 0.204
 8. Mng 0.322
 9. SECPT 0.447
10. SECFT 0.481
11. Tech 0.628
12. OASS 0.56
13. GASS 0.623
14. CASS 0.598
15. Prass 0.626
16. T. cut 0.354
17. Refbin 0.548
Variance 8.9748
% Var 0.528

TABLE 3

Ranking of Economic Journals Principal Component Method on Production
Characteristics

Rank Variables (Excluding Variables (Including Compensation)
Compensation)

 1. Am. Journal of Agri. Econs. J. Economic Perspectives
 2. Small Business Econs. J. Regulatory Economics
 3. J. Scient. Beh. and Org. Finance Practice and Education
 4. J. Urban Economics Eastern Economic Journal
 5. Science and Society Journal of Env. Econs. and
 Management
 6. Review of RPE Journal of Urban Economics
 7. The Antitrust Bulletin Journal of Macroeconomics
 8. J. Human Resources Review of Black Political Economy
 9. J. Public Economics Small Business Economics
10. Review of Social Economy J. of Economics
11. J. World Business Economic Perspective
12. J. Multinational Fin. The Accounting Review
 Management
13. J. Cultural Economics Regulation
14. Review of Political Economy FRB Richmond Quarterly
15. J. Intl. Fin. Markets, Inst. Industrial Relation
16. The Energy Journal J. Future Markets
17. Regulation Canadian Public Policy
18. J. Env. Econs. and Management J. Public Economics
19. Finance Practice and Education Review of Regional Studies
20. Marketing Science Atlantic Economic Journal
21. J. Consumer Affairs Review of Social Economy
22. Car. Rochester Conf. Series on Growth and Change: AS. of Urb/Reg.
 Pub. Policy
23. Social Science Quarterly The Energy Journal
24. Int. Trade and Public Finance J. Scientific Beh. and Org.
25. J. of Regulator Econs. Review of Radical Poll Econ.
26. Review of Agri. Economics Economics of Education Review
27. Rand Journal of Economics Intl. Adv. in Economic Research
28. Economics of Education Review J. Development Economics
29. Growth and Change: a J. of Am. J. of Agricultural Economics
 Urb/Reg.
30. Ecological Economics J. Empirical Economics
31. Explorations in Economic Intl. Trade and Public Finance
 History
32. J. of Health Economics Economic Development Qrt.
33. Economic Development Qrt. Resource Policy
34. Review of Black Political J. Intl. Fin. Markets, Institutions
 Economy
35. Industrial Relations Agri. Economics
36. Economic Policy Review J. Multinational Fin. Management
37. J. Asian Economics Exploration in Economic History
38. J. Transnational Mgt. Journal of Cultural Economics
 Development
39. Review of Industrial Russian and East European Finance
 Organization and Trade
40. Papers in Regional Science Journal of Health Economics
41. J. Health Policies Policy and Review of Industrial Organization
 Law
42. Human Resource Development Qrt.
43. J. of Macroeconomics
44. J. Labor Economics
45. Russian and E. European Fin.
 and Trade
46. Population and Dev. Review
47. Resource Policy
48. J. Futures Markets
49. Canadian Public Policy
50. J. of Policy Modeling
51. National Tax Journal
52. Canadian Public Policy
53. J. of Development Economics
54. The Canadian J. Regional
 Science
55. The Accounting Review
56. Economic Development and Cull
 Change
57. Agri. Resource Econ. Review
58. J. Intl. Business Studies
59. Economic Perspectives
60. Review of Regional Studies
61. J. of Economic Perspectives
62. FRB Richmond Econ. Qrt.
63. Intl. J. of Qual. and Rel.
 Mgmt.
64. J. Empirical Finance
65. Atlantic Economic Journal
66. Intl. Advances in Economic
 Research
67. J. Money Credit and Banking
68. J. of Political Economy
69. J. of Economics, MVEA
70. Eastern Economic Journal
71. Economic Inquiry
72. Finance and Development

TABLE 4

Generalized Method of Moments: Simultaneous Equation Results

 Log (Compensation)

Description Equation 1 t-Values

Constant Terms 5.04 (4.71)
Log (Circulation) 0.64 (4.42)
Part-Time Secretaries -0.31 (-1.82) **
Graduate Assistants -0.21 (-5.08)
Proofreaders 0.38 (3.25)
Copy Editors 1.07 (3.94)
Log (Invited Articles)
Log (Associate Editors)
Full-Time Secretaries
Referees
Compensation
Index of Assistants
Proofreaders
Observations 47
R-Square .28
D-W 2.62

 Technical Journals Number of Issues

Description Equation 2 t-Values Equation 3 t-Values

Constant Terms 0.80 (4.24) 1.31 (24.60)
Log (Circulation)
Part-Time Secretaries
Graduate Assistants
Proofreaders
Copy Editors
Log (Invited Articles) -0.15 (-2.92)
Log (Associate Editors) 0.11 (1.63) *
Full-Time Secretaries -0.34 (-2.48)
Referees 0.18 (2.06)
Compensation
Index of Assistants 0.058 (2.13)
Proofreaders -0.11 (-2.53)
Observations 44 80
R-Square .15 .06
D-W 2.42 1.47

Note: * t values are at the 90% confidence interval

** t values are at the 95% confidence interval

All the other t values are significant at the 99% confidence interval

Notes

(1.) The American Economist was excluded from the survey to avoid any appearance of biasing the estimates.

(2.) A negative loading should be interpreted with a negative connotation, i.e., with the preamble that the "respondent tends not to..." As a general rule though, "...it is customary to 'reflect' (change all) the signs of a factor on which the highest loadings are negative. As long as all the signs in the column are changed, it is the absolute size of the loadings, rather than the signs, that count" (Wells and Sheth, 1974, 2-458). The columns with the three asterisks are so adjusted.

References

Becker, William E. (1998). "The Use of Mathematics and Statistics in the Teaching and Learning of Economics." in William B. Walstad and Phillip Saunders, eds., Teaching Undergraduate Economics: A Handbook for Instructors. New York, NY: Irwin-McGraw Hill.

Dusansky, Richard, and Clayton J. Vernon. (Winter 1998). "Ranking of U.S. Economics Departments," Journal of Economic Perspectives, Volume 12(1), 157-170.

Greene, William H. (2000). Econometric Analysis, Fourth Edition. Upper Saddle River, NJ: Prentice Hall.

Goffe, William L., and Robert P. Parks. (Summer 1997). "The Future Information Structure in Economics," Journal of Economic Perspectives, Volume 11(3), 75-94.

Laband, David N., and Michael J. Piette. (June 1994). "The Relative Impacts of Economics Journals: 1970-1990," Journal of Economic Literature, Volume 32(2), 640-666.

Liebowitz, Stanley J., and John C. Palmer. (1984). "Assessing the Relative Impacts of Economics Journals," Journal of Economic Literature, Volume 22(1), 77-88.

Lee, Eric Youngkoo, and Michael Szenberg. (Fall 1988). "Analysis of Factors Determining the Compensation of Editors of Economics Journals," The American Economist, Volume 32(2), 76-78.

"Report of the Commission on Graduate Education in Economics" (September 1991). Journal of Economic Literature, Volume 22(3), 1035-53.

Snedecor, George W., and Cochran, William G. (1959). Statistical Methods. Chapter 17. Ames, Iowa: The Iowa State College Press.

Varian, Hal R. (Summer 1997). "The American Economic Association's Electronic Publishing Plans: A Progress Report," Journal of Economic Perspectives, Volume 11(3), 95-104.

Wells, William D., and Jagdish N. Sheth. (1974). "Statistical Analysis of Relationships: Factor Analysis" in Robert Farber, ed., Handbook of Marketing Research. New York, NY: McGraw Hill.

Lall B. Ramrattan * and Michael Szenberg **

* University of California, Berkeley

** Lubin School of Business, Pace University, New York, NY 10038, Email: mszenberg@pace.edu