The Market for Publications in Top Economics Journals.

Transcription

1 Institute of Public Economics Discussion Paper 2000/1 The Market for Publications in Top Economics Journals. Concentration and Export Ratios of Authors Current and Ph.D.- Affiliations for the Last Two Decades and Power Laws of Scientific Productivity * Martin G. Kocher, Matthias Sutter Institute of Public Economics University of Innsbruck Universitaetsstrasse 15/4 A-6020 Innsbruck martin.kocher@uibk.ac.at matthias.sutter@uibk.ac.at Abstract: This paper addresses the concentration of the market for publications in top economics journals. Our database consists of 15 journals with the highest average impact factor in the period 1977 to We select every fifth year within the chosen period in order to detect possible shifts in the distribution of authors current and Ph.D.-affiliations. Our findings confirm that the concentration of Ph.D.-affiliations is much higher than the concentration of current affiliations. By applying population weighting to our data we find that the USA s dominance is considerably reduced whereas Israel and the UK come out excellently. We can identify typical exporters and importers of Ph.D.s among universities. Concentration ratios like the Herfindahl-Index lack a clear time trend. Nevertheless, we dare to conclude that the position of the USA has been weakening during the last five to ten years. Finally, our data satisfy both Lotka s law for individuals and Zipf s law for institutions. JEL classification: A11, A14, D4 Keywords: economics journals, market for publications, concentration ratios, Lotka s law, Zipf s law January 2000 Comments on this paper are gratefully acknowledged. * We would like to thank Hans-Werner Holub and participants of the research seminar at the University of Innsbruck for valuable comments on this paper. Of course, we bear the sole responsibility for the content. We are especially indebted to around 400 economists around the world who kindly responded to our inquiry concerning their Ph.D.-affiliation.

2 1. Introduction Attempts to assess the status of economic publications, of economic journals and authors have been increasing, lately. One strand of this literature, concentrating on the market for economic publications, has intensively analysed the contributions to core economic journals and the relative impact of various countries and/or single institutions, either from a viewpoint stressing the output measurement of institutions or from a perspective expressing concerns about scientific progress and the variety of ideas, methods and approaches of articles in leading journals. Serious apprehension has been raised for example that the market for economic publications might be an institutional oligopoly (Hodgson and Rothman, 1999), as a few, mostly American institutions dominate those journals considered to be of highest visibility and quality by a majority of economists, henceforth simply referred to as top journals. Even more severe, the aggregate concentration of authors origins appears to be extremely high when the argument is applied on the country level instead of the institutional level. Hodgson and Rothman (1999) report for 1995 that 79.9 % of authors in 15 leading journals (ranked by the impact factor in the Journal Citation Reports 1 ) state an institution located in the United States as their current affiliation. Ten American universities (namely, Harvard, Chicago, U Pennsylvania, Stanford, Northwestern, U Michigan, MIT, Princeton, U Cal Berkeley, U Cal San Diego) account for no less than 26.2 % of all authors current affiliations in these top 15 journals. Similar results with partly different journals and different methods have been presented by Kalaitzidakis et al. (1999) who report shares of North American (USA and Canada) economists for ten core journals between 69 and 90 %. 2 In a word, the market for economic publications in top journals is highly concentrated. Furthermore, the concentration increases intriguingly if the Ph.D. origins of authors are considered. These results as well as those of similar studies (Bairam, 1994; Bommer and Ursprung, 1998; Elliott et al., 1998; Kirman and Dahl, 1994, 1996) are astonishing and have evoked diverse interpretations and comments on the status of economic research. 1 See section 2 for more information on the Journal Citation Reports. 2 They count AER-standardised pages for The majority of publications in the Economic Journal and in the European Economic Review originate from European authors, although about one third of the contributions is classified as non-european. The same results, in substance, are provided by Elliot et. al (1998) for

3 Specifically, the fear of an American domination in economics or of an institutional oligopoly have been expressed. 3 Surprisingly, one aspect of the whole issue has not been addressed adequately to our mind, hitherto. All empirical studies we are aware of remain amazingly vague on the development of the market for economic publications within the last decades, which is even more astonishing as examinations on the contestability of a market clearly require a dynamic view. The most comprehensive study, conducted by Hodgson and Rothman (1999), covers only one year, namely 1995, causing them to urge for further studies of institutional concentration... for years in addition to to discern a picture of the trend of developments (p. F182). Elliott et al. (1998) compile data for , but display their results only for the whole period and not disaggregated for single years to get an idea of the time trend. Given the lack of research on time trends concerning the relative impact of different countries in top economics journals one is forced to remain rather speculative on the current status and possible future scenarios. This article is designed to shed light on that black spot, namely the time path of the impact of different countries and institutions through contributions in top economics journals from The starting date was chosen since it is the first year the Journal Citation Reports for the Social Sciences were published. The remainder of the paper is organised as follows. Section 2 deals with the selection of 15 top journals which build the data basis for this study. Section 3 reports on the origins of our data set as well as the methodology we applied to compute the results. To highlight possible problems in comparability with related studies we reveal differences to their methods and the implications for the results. Section 4 presents the results on concentration ratios of current and Ph.D.-affiliations of authors in 15 top journals. Additionally, it tries to give a rough estimate of scientific productivity in different countries, it investigates which institutions are the main exporters and importers of Ph.D.s and it applies some power laws of scientific productivity to our data. Section 5 concludes the paper. 3 Frey and Eichenberger (1993), e.g., do not share the pessimism of most European commentators on this subject insofar as they highlight the different objective functions of European and American economists. According to them European researchers in economics are much more involved in politics and political consulting than their American counterparts. Therefore, it seems obvious that Europeans do not appear competitive in a simple comparison of scientific output in the form of articles published in top journals. 3

4 2. Top 15 Journals Efforts in identifying top, leading or core journals have been numerous. It is obvious that there is no universally agreed upon method of labelling a few of the increasing number of journals in economics top. 4 Despite this fact one can detect a considerable correspondence between the leading journals in the Journal Citation Reports (JCR), the top journals in other compilations with different methods (e.g., Liebowitz and Palmer, 1984; Diamond, 1989; Laband and Piette, 1994; Burton and Phimister, 1995; Stigler et al., 1995) and those journals on which most economists would agree upon the label core or high-quality. According to this argument we decided to choose the 15 economics journals in the Journal Citation Reports with the highest average impact factor over the time period The impact factor is an objective measure to assess a journal s visibility over the whole time period. 6 It is part of the yearly published JCR, based on the Social Sciences Citation Index (SSCI) and edited by the Institute for Scientific Information (ISI) since Specifically, the impact factor is a measure of citations relative to citable items published, including a time lag. Take for instance the impact factor of the Journal of Economic Literature (JEL) in 1998 (see Table 1). Let N be the number of citations in all SSCI journals in 1998 citing an article published in the JEL either in 1997 (N 97 ) or 1996 (N 96 ) and A be the number of articles appearing in the JEL in 1997 (A 97 ) and 1996 (A 96 ). The impact factor for 1998 is then (N 97 +N 96 )/(A 97 +A 96 ). 7 Table 1 shows the correspondence between the journals selected in our study and those in related ones. A majority of economists should meet our choice of journals with approval, since the flagships of the American Economic Association, the Econometric Society and the Royal Economic Society are included as are other widely accepted journals. Contrary to the JCR we do not include The Economist with the second highest average impact factor, because it is normally not considered a scientific journal. A 4 Hodgson and Rothman (1999) mention a compilation of The Judge Institute (1994) stating 1,431 journals in social science and management. The Journal Citation Reports of the Institute for Scientific Information (ISI) for 1998 list 161 journals in the economics section. Most of them are international journals published in English so that a lot of journals are, of course, omitted. 5 When we started to compile our data the JCR for 1998 was not available, yet. Each journal assigned to the economics section of the JCR for 1997 was considered for selection. In the meantime we could review our selection for the average impact factor from 1977 to 1998, resulting in the expected finding that the top 15 journals would have remained the same. 6 Laband and Piette (1994, p. 641) describe citations as the scientific community s version of dollar voting by consumers for goods and services. 7 See Garfield (1972) for further details and other ways of calculating journal impact. 4

5 number of high ranked journals did not exist long enough to be taken into account for this study 8, other well-known journals were very close to being included, namely, the Journal of International Econonomics, the Journal of Economic Theory, the Journal of Economic History, the Review of Economics and Statistics, the Journal of Environmental Economics and Management, Economica and Explorations in Economic History (with average ranks 16-22, respectively). The development of the impact factors is amazingly stable over the past two decades, allowing us to conclude that the selected journals in this paper stand for foremost visibility of publications in the field of economics. In particular, the twelve journals with the highest average impact factors could not be excluded in any conceivable weighting and calculation method or sensitivity analysis of our choice. 9 Finally, we decided to rely on the average impact factor as decision variable because other possible ones (e.g., the rank in the JCR) clearly exhibit shortcomings. 10 It is remarkable that twelve of the 15 journals would have been included in our study if we had neglected all previous years of the JCR and only relied on the impact factors of , with the remaining three on places 16, 17 and 18. One of the possible caveats of our selection method is that we neglect a vast majority of the scientific output by economists. Kirman and Dahl (1996, p. 33) report that all articles published in journals included in the JCR amount to two percent of the total production of scientific articles. It is obvious that we can cover only a very tiny (though, admittedly, very important) portion of all economic publications. However, the aim of our study is to address the top edge of the market for economic publications. Furthermore, without being able to proof this conjecture, we believe that the overall picture and the qualitative results of this study would not have been altered if we had included another, say, 15 journals, which would still have been a negligible portion of all economic publications J Econ Perspect (8 listings), Health Econ (2), Contrib Polit Econ (1), Bus Lawyer (2), Sov Econ (5), Am Bankrupt Law J (1), J Account Econ (14), J Risk Uncertainty (6), J Health Econ (13), Econ Soc (3), J Law Econ Organ (7), Ecol Econ (5), NBER Macroecon Ann (3), Probl Communism (18), Post-Sov Aff (4), J Labor Econ (13) and J Econometrics (16) would have to be considered if this study had not required publication since The results are available from the authors upon request. 10 Note that not all journals were always listed in the economics section of the JCR. E.g., J Monetary Econ was included only in the business section for some years, or J Hum Resour was listed in the category sociology for three years. 11 For 1998 eleven out of 15 would have remained in our selection. 12 The results of Hodgson and Rothman (1999) support this conjecture. They report concentrations for 30 as well as for 15 journals with qualitatively the same results. 5

6 Table 1 Selection of Journals Average IF a ( ) IF (1998) Hodgson, Rothman Top 15/30 On Diamond list? On Burton, Phimister list? Kalaitzidakis et al. Elliott et al. Bairam J Econ Lit top 15 Yes Yes No No No Brookings Pap top 15 Yes Yes No No No J Financ Econ b top 15 Yes Yes No No No J Polit Econ top 15 Yes Yes Yes Yes Yes Econometrica top 15 Yes Yes Yes No Yes Q J Econ top 15 Yes Yes Yes Yes Yes Am Econ Rev top 15 Yes Yes Yes Yes Yes J Law Econ top 15 Yes Yes No No No J Monetary Econ b top 15 Yes Yes Yes No No Rand J Econ c top 30 Yes Yes No No No Rev Econ Stud top 15 Yes Yes Yes Yes No Econ J top 30 Yes Yes Yes Yes Yes J Hum Resour top 30 No Yes No No No Econ Geogr top 15 No Yes No No No Econ Hist Rev top 30 No No No No No a IF: Impact factor. Source: Journal Citation Reports ( ), published by Institute for Scientific Information. b Only 20 instead of 21 observations due to lacking listing in the JCR c Rand J Econ comprises three titles that followed each other: Bell J Econ Manage S, Bell J Econ and Rand J Econ. Due to overlapping periods we obtained 22 observations instead of 21. Sources and journals selected: - Hodgson and Rothman (1999): selection based on impact factors for 1995 (30 journals): J Econ Lit, Econometrica, J Econ Perspect, J Account Econ, J Financ Econ, Q J Econ, Brookings Pap, J Polit Econ, Econ Geogr, Am Econ Rev, Rev Econ Stud, J Envir Econ Manag, J Monetary Econ, Post-Soviet Affairs, J Law Econ (1-15), J Labor Econ, J Econometrics, J Law Econ Organ, Ecol Econ, J Risk Uncertainty, J Health Econ, J Hum Resour, Econ Hist Rev, Work Employ Soc, Rand J Econ, Econ J, Land Econ, J Comp Econ, Game Econ Behav, B Indon Econ Stud (16-30); time period: one year (1995). - Kalaitzidakis et al. (1999): selection based on market share with respect to citations, inclusion in the Diamond list and a few other qualitative arguments (ten journals): Am Econ Rev, Econometrica, J Polit Econ, Q J Econ, J Monetary Econ, J Econ Theory, Rev Econ Stud, Rev Econ Stat, Econ J, European Econ Rev; time period: six years ( ; no time trend indicated). - Elliott et al. (1998): selection based on no evident criterion except the label core (eight journals) Am Econ Rev, J Polit Econ, Q J Econ, Rev Econ Stat, Econ J, Oxford Econ Pap, European Econ Rev, Rev Econ Stud; time period: 25 years ( ; no time trend indicated). - Bairam (1994): selection based on no evident criterion (five journals): Am Econ Rev, Econometrica, Econ J, J Polit Econ, Q J Econ; time period: six years ( ; no time trend indicated). 6

7 3. Data sources and methodology Data sources and the applied methodologies play, of course, a crucial role in determining the results. To avoid misinterpretations we present the methodology applied in this study in comparison to related investigations by highlighting the differences in compiling data and weighting articles. In contrast to Hodgson and Rothman (1999), the most comprehensive study of this kind, we focus only on authors current and Ph.D.-affiliations and not on editors. Theoretically, there is a great deal to be said in favour of taking top journals editors into account. Although the institutional origins of editors may probably influence the concentration of authors origins, including editors in the investigation creates some daunting problems. First, it is impossible to distinguish between editors who participate in the processing and selection of papers for publication and those who are mainly concerned with administration or production of a journal. This is first and foremost due to distinct terminologies in different journals. 13 Furthermore, as also noted by Hodgson and Rothman (1999, p. F167), same terminologies do not mean same responsibilities in different journals, causing them not to distinguish between different kinds of editors and, therefore, counting all stated editors equally. Second, some journals do or did not always list all editors; a problem being most pronounced in statements such as in cooperation with other members of the Department of Economics of the University of Chicago (Journal of Political Economy) or in association with the Harvard Department of Economics and Invited Readers (Quarterly Journal of Economics, 1977). In such cases a considerable number of editors would have to be neglected. Third, one runs the risk of getting a false picture due to entirely different sizes of editorial boards. Take, for instance, Econometrica or the American Economic Review, both journals stating over 40 editors in 1997, and compare it to the Journal of Law and Economics with two editors in 1977 and not more than five editors in Clearly, the relative impact of journals with numerous editors would be overestimated unless sophisticated weighting measures were applied. 13 We found, among many others, Consulting Members, Senior Editorial Associates, Statistical Associates, Assistant Editors, Editorial Associates, Research Verifiers, Research Fellows, Editorial Consultants, Research Assistants, Administrative Assistants, Production Editors, Founding Editors, Managing Editors, Advisory Editors, Foreign Editors, Coordinating Editors. 7

8 Bearing in mind the lack of differences between concentrations of authors and editors affiliations in Hodgson and Rothman (1999) and the arguments mentioned above we abstained from surveying editors institutional origin. 14 We also refrained from detecting home journals and assigning journals to countries because of methodological caveats. E.g., in Hodgson and Rothman (1999), the Journal of Monetary Economics is classified as European because of its publishing company Elsevier (in the Netherlands) despite the fact that there is not a single European member on the editorial board in Origin of data Our data of authors and their current affiliations do not stem from electronic data bases, but have been ascertained directly from the journals in question. 15 We consider all authors of a paper and all institutional affiliations they state. In gathering data on authors Ph.D.-affiliations we relied mainly on the data bases of the American Economic Association, the European Economic Association, the Economic History Association, the Royal Economic Society, further on numerous websites of universities and colleges and on correspondence with around 400 economists all over the world who kindly answered our inquiry concerning their Ph.D.-affiliations. As we were not capable of collecting the necessary information for 21 years due to the enormous effort which would have been required (approximately articles in the 15 journals selected 16 ), we restricted ourselves to five years, equally distributed over the time horizon, namely 1977, 1982, 1987, 1992 and For the top 15 journals this yields 3250 articles with 5014 entries for authors and a total of 3415 different contributors. No articles have been disregarded except editorial notes, obituaries, book reviews and similar non-scientific contributions % of authors current affiliations 18 and 89.24% of Ph.D.-affiliations 19 could be collected. A few authors do not hold a Ph.D., forcing us to rely on their other highest degree. 14 The high institutional concentration of editors reported by Hodgson and Rothman (1999), though, seems to be conducive to the notion of an institutional oligopoly. 15 The electronic database EconLit, e.g., does not indicate authors affiliations before 1990 and, generally, states no more than three authors of a publication. 16 This figure excludes about 1500 contributions to the Papers and Proceedings of the American Economic Association. 17 Like Bairam (1994) we exclude the Papers and Proceedings of the American Economic Association, because generally papers published therein do not undergo the standard reviewing process, but are invited contributions. The conference volumes of the ECONOMIC JOURNAL are included on account of their being fully refereed. 18 With current affiliation(s) we denote the affiliation(s) stated by the author(s) in the article. 8

9 3.2 Applied methodology There are numerous different methodologies applied in various papers on the market for publications in economics journals, clearly having an adverse effect on comparability. Distinct weighting approaches are manyfold and do not always reflect intuition, particularly when rankings of departments or single economists are concerned and the aim is to push the ranking of one s own institution by means of more or less inventive weighting (see Feinberg, 1998, or Griliches and Einav, 1998). Nevertheless, on closer inspection, it becomes obvious that the results are surprisingly stable in general, especially when one is concerned with the leading institutions in the field. 20 As to the weighting of the number of authors, we employed a straightforward and comprehensive method, in line with most other studies. Let N i be the number of authors of article i, then the weight assigned to each author is simply 1/N i. Some other possible methods 21 are actually designed to reward cooperation among scientists, but are counterintuitive and not appropriate for this kind of study. Hodgson and Rothman (1999) treat all authors equally, leading to an overestimation of contributions in multiauthored papers. Given the steadily increasing number of articles that have multiple authors (Hudson, 1996), applying the methodology of Hodgson and Rothman would have clearly biased our results in favour of authors and their respective affiliations in the most recent years of our sample. 22 The results for single institutions are derived by aggregating over all authors who state this institution as their current affiliation. When multiple institutions for a single author come into play the weighting scheme is analogously applied. Take, e.g., a paper with four authors, one of whom is affiliated with MIT and NBER, then the weight assigned to the MIT for this article is To get summary statistics for countries the results for institutions located in the respective countries are simply summed up. International organisations like the IMF, World Bank or OECD are treated separately throughout the paper, contrary to many other studies. 19 This is remarkable compared to the 44.2% of Hodgson and Rothman (1999). Despite difficulties in obtaining information on authors Ph.D.-affiliations in the early years of our sample, the distribution of obtained information on Ph.D.s is surprisingly equal over the five years. We succeeded in obtaining Ph.D.-affiliations of 86, 90, 91, 89 and 89% of all entries on authors in 1977, 1982, 1987, 1992 and 1997, respectively. With respect to current geographical location we succeeded in obtaining information on Ph.D.-affiliations for 91.37% of authors currently affiliated in the USA and 84.34% of authors currently affiliated outside the USA. 20 We did some sensitivity analyses which confirmed that different weighting methods than the one introduced below lead to essentially the same results. Results are available upon request. 21 de Vries (1995) and Bommer and Ursprung (1998) assign each author a weight 2/(N i +1). 22 Also the restriction on the first author like in Kirman and Dahl (1994, 1996) would not be suitable for us. 9

10 Most differences concerning weights and counting appear in connection with article length and type of article. We put the same value on every article in our sample. Our data base would allow to distinguish between full papers and shorter papers (comments, replies etc.), but the assignment is more or less arbitrary; a fact which prevented us from processing this information. Kalaitzidakis et al. (1999) count pages per article and convert them to American Economic Review standardised pages. 23 The standardised pages are then allocated to the affiliations stated by the author. The adjustment procedure of Kalaitzidakis et al. implies that longer papers require more research resources (time, effort etc.) and, therefore, assigns higher values to longer papers. We do not subscribe to that point of view. The correlation between the length of a paper and the resources used to obtain its scientific content is, at best, poor due to the fact that the time of writing generally constitutes only a small fraction of the entire resources employed. Also controversial is the issue of quality weighting of single articles. Contrary to, e.g., Kirman and Dahl (1994, 1996) we apply standard US-practice by weighting articles with the impact factor of the relevant year. 24 As mentioned by Kalaitzidakis et al. (1999) it would be more precise to employ the actual citation impact of each article for quality adjustments. Though, irrespective of the huge amount of information which would have to be compiled, this method would clearly undervalue recently published papers, creating a bias against the contributions in Hence, we adjust articles with the impact factor of the respective year. 25 Methodologies to obtain the results for authors Ph.D.-affiliations are in general analogous. The adjustment procedure is actually easier, because multiple institutional affiliations are very rare and in case of authors with more than one Ph.D. we decided to regard only the one granted first. If authors were not holding a Ph.D. we considered any other highest scientific degree. Students in Ph.D.-programs were supposed to obtain the degree from the institution where they were enrolled. 23 One page of this JOURNAL would correspond to 0.14 American Econ Rev pages. 24 The only missing weight is the impact factor for the J Financ Econ in 1977, in which the journal was not included in the JCR. We employed the figure for 1978 instead. 25 However, the correlation between the data with and those data without impact factor-weighting is overwhelmingly high. Specifically, the correlation coefficient is in any case larger than Even rank correlations are not less than 0.94 for any listing in this paper. 10

11 4. Empirical results This section presents the main results of our study. On the aggregate level, without displaying years separately, we can confirm some results of prior studies. In calculating export- and import-ratios for Ph.D.s we extend existing findings. Likewise, we try to address the difficult question of productivity measures in contrast to descriptive ones, which yields some surprising results and permits further insights. Time trends of institutional concentration are not easy to interpret, but concentration seems to decrease within the last decade. 4.1 Authors current and Ph.D.-affiliations Table 2 displays the weighted scores and shares of contributions to the top 15 journals for different countries and/or institutions. The USA alone accounts for 72.2% of all contributions, followed by the U.K. with 10.2% and Canada with 4.7%. All other countries account for less than the highest ranked US-institutions, namely Harvard (3.8%), MIT (3.7%) and Chicago (3.6%). Israel, the country ranked fourth, contributes approximately as much as the University of Pennsylvania, and the number one in continental Europe, France, can just beat New York University, number 13 in the US institutional ranking. The highest ranked European university, the LSE, would occupy rank 11 (rank 10 if the NBER is excluded) in an overall institutional ranking. Institutions in English speaking countries account for no less than 88.9% (90.1% if international organisations are included) of contributions, clearly indicating the dominance of the English language in economics. The concentration is even more severe, as expected, with regard to authors Ph.D. origins. Table 3 shows that the shares of the USA and U.K. increase to 80.6% and 11.4%, respectively. Institutions in English-speaking countries account for 93.9% of weighted Ph.D. scores. Most striking is the comparatively huge share of single American institutions. The MIT s share of weighted Ph.D.-affiliations is larger than any other country s share with the exception of the USA, of course. MIT, Chicago and Harvard account for one third of weighted Ph.D. scores. The enormous impact of the top economics departments of the USA becomes obvious when concentration ratios of 11

12 authors current and Ph.D.-affiliations are compared. The market share of the top 10 USinstitutions for Ph.D.s is nearly double what it is for current affiliations. 26 Table 2 Current affiliation of 'Top 15' Economics Journal Authors: total for five selected years; weighted scores country/institution score a % of total country/institution score a % of total Argentina 0.9 Canada subtotal Australia subtotal Western Ontario Australian National U Toronto Austria 11.2 UBC Belgium 19.7 Israel subtotal Bermuda 0.6 Hebrew Brazil 1.8 Tel Aviv Chile 0.3 UK subtotal China 2.1 LSE Cote d'ivoire 0.8 Cambridge Denmark 7.9 Oxford Ethiopia 0.9 U London Finland 0.8 USA subtotal France Harvard Germany MIT Greece 2.9 Chicago Hong Kong 3.5 NBER Iceland 0.5 Princeton India 6.4 Stanford International Organisations Northwestern subtotal U Pennsylvania World Bank Rochester Ireland 14.5 Yale Italy 21.3 U Cal Berkeley Japan Columbia Korean Republic 8.2 NYU Malaysia 1.0 U Michigan Mexico 5.1 Fed Res Board Netherlands UCLA New Zealand 1.9 U Wisconsin Norway 20.3 U Virginia Poland 0.5 U Minnesota Portugal 2.0 U Cal San Diego Puerto Rico 0.2 U Maryland Russia 6.4 Cornell Singapore 5.6 Carnegie Mellon Slovenia 0.6 Ohio State U Spain 14.7 Brookings Inst Sweden subtotal Stockholm Switzerland 17.3 Subtotal: Known affiliation Taiwan 6.9 (weighted scores) Tansania 0.9 Not known 16.5 Thailand 0.4 (weighted scores) Ukraine 4.2 TOTAL a weighting includes number of authors and stated affiliations per article as well as the journal s impact factor of the relevant year. 26 Further details will be given in section

13 Table 3 Ph.D.-affiliation of 'Top 15' Economics Journal Authors: total for five selected years; weighted scores country/institution score a % of total country/institution score a % of total Australia subtotal USA subtotal Australian National U 10.9 MIT Austria 19.3 Chicago Belgium 17.8 Harvard Canada subtotal Stanford UBC 19.5 Yale Toronto 13.3 Princeton Western Ontario 4.0 U Cal Berkeley Denmark 4.3 Rochester Finland 0.8 Columbia France Northwestern Germany U Wisconsin India 3.9 U Minnesota Ireland 4.5 U Pennsylvania Israel subtotal UCLA Hebrew U Michigan Tel Aviv 4.9 Carnegie Mellon Italy 16.0 Johns Hopkins Japan 13.7 Brown Netherlands Cornell New Zealand 3.3 Purdue Norway 9.8 U North Carolina South Africa 1.3 Cal I Tech Spain 1.7 Ohio State U Sweden subtotal U Washington Stockholm NYU Switzerland 15.8 UK subtotal Subtotal: Known affiliation LSE (weighted scores) Oxford Not known Cambridge (weighted scores) U London TOTAL a weighting includes number of authors and stated affiliations per article as well as the journal s impact factor of the relevant year. So far, there was no kind of productivity consideration involved in our results. It would clearly be desirable from an economic point of view not to regard output solely, but to have an eye on inputs such as manpower or financial resources devoted to economics research in different countries. Unfortunately, data comparable across different countries in our sample are missing. 27 Kirman and Dahl (1996) compile data for some countries of the European Union, however, they themselves admit inaccuracies. Besides, they report no data for the USA, which would be most interesting for comparisons. 28 Therefore, we apply a rather crude method for obtaining a broad-brush 27 We do not intend to measure department productivity, because a vast literature addressing this topic already exists (e.g. Scott and Mitias, 1996). Instead we concentrate on productivity at the country level. 28 Dividing current or Ph.D. affiliation scores by figures on manpower from Kirman and Dahl (1996) results in more or less the same ranking of European countries as the one reported in Table 4. Results are available upon request. 13

14 picture of a country s productivity in producing publications in top economics journals by dividing a country s current or Ph.D. affiliation scores by its population. 29 Nevertheless, the results, summarised in Table 4, are insofar remarkable as they reveal further interesting aspects and level off the big differences between the USA and European countries. Particularly striking is the fact that concentration appears much less severe when weighted scores are standardised per inhabitant. The USA and U.K. do not nearly fare as good as in Table 2 or Table 3, whereas Canada, the Scandinavian countries and some smaller European countries benefit. With respect to current affiliations on the left hand side of Table 4 it was a big surprise that Israel takes the lead, putting the USA in second position. Referring to Ph.D.-affiliation scores per inhabitant on the right hand side of Table 4 the USA is still number one, but the differences are also less alarming than when scores are not adjusted for population. Table 4 Scores and population Current affiliations Ph.D. affiliations country a population (in 1000s) b weighted score per inhabitant ( 10 6 ) country population (in 1000s) b weighted score per inhabitant ( 10 6 ) Israel USA USA UK UK Israel Canada Sweden Sweden Austria Norway Norway Ireland Switzerland Australia Canada Switzerland Belgium Netherlands Australia Belgium Netherlands Singapore Ireland Iceland France Denmark New Zealand Austria Denmark France Germany Germany Italy New Zealand Finland Spain Japan Italy Spain Japan South Africa Taiwan India Slovenia Greece Portugal Korean Republic Finland a The following countries' scores per inhabitant for current affiliations are less than 0.10 (in descending order): Ukraine, Mexico, Cote d'ivoire, Malaysia, Russia, Tansania, Argentina, Chile, Ethiopia, Poland, Brazil, India, Thailand, China. b Figures are for Source: Der Fischer Weltalmanach Frankfurt am Main, October Although countries scores are based on their performance from 1977 through 1997, population figures are for 1997 only. This method somehow favours relatively slow growing countries. 14

15 We are aware of the shortcomings of our approach to measure productivity, since it implies that the resources involved in economics are highly correlated with countries inhabitants. This may be not entirely wrong for highly developed, but is certainly disadvantageous for populous developing countries. Other possible proxies for manpower and financial resources like the number of universities in a country or GDP and/or per capita GDP exhibit similar problems and caveats. Our approach should be understood as a first, incomplete attempt to discern a comprehensive picture of concentration in publications. Further research, especially in connection with productivity statements, remains necessary. top exporters Table 5 Export- and import-ratios: unweighted entries exportratio c [1]/[2] top importers a importratio c [2]/[1] Institution Ph.D. b [1] Current b [2] Institution Ph.D. b [1] Current b [2] Johns Hopkins Tel Aviv MIT Western Ontario Purdue U Texas Chicago Boston Brown U Florida Oxford U Cal Santa Barbara U Wisconsin U Cal Davis Harvard U Arizona U Minnesota U Cal San Diego U London NYU a We report only importers with at least 5 Ph.D. entries. A complete list of ratios is available upon request. b Total unweighted entries c Export (import) ratios rise (decline) if they are calculated by dividing shares of total Ph.D. scores by shares of total current affiliation scores (see Fig. 1). However, the order of the listed institutions would remain exactly the same. This also holds true if weighted scores instead of unweighted entries are applied. Table 5 relates the unweighted entries for current affiliations to unweighted entries for Ph.D. affiliations of single institutions. 30 This relation enables us, on the one hand, to identify universities which are successful in attracting other universities Ph.D.s who contribute very much to the hiring university s standing as current affiliation. On the other hand, there are universities that educate more highly talented Ph.D.s than they have academic positions to fill, resulting in a ratio of Ph.D. entries to current entries of greater than one. We call institutions with many Ph.D. entries and relatively few current entries exporters and the ratio between Ph.D. and current entries export ratio. 30 We rely on unweighted entries (not adjusting for number of authors or affiliations or impact factors), because an institution s reputation (due to its members publication records in top journals) seems to be better accounted for by the mere number of entries than by fully weighted scores. 15

16 Accordingly, institutions with few Ph.D. and relatively many current entries are denoted importers and the corresponding ratio import ratio. 31 In addition to MIT, Chicago, Harvard and Oxford, which were expected to be exporters, the left hand side of Table 5 identifies Johns Hopkins, Purdue and Brown Universities as large exporters. The right hand side of Table 5 shows the most successful importing institutions, on top Tel Aviv and Western Ontario with remarkably high import ratios MIT 0.08 Chicago Harvard 0.06 Stanford 0.04 Berkeley Princeton Yale Oxford Wisconsin LSE 0.02 Northwestern NYU share of total current affiliation (unweighted) scores Fig. 1. Exporters and importers of Ph.D.s (N = 95) Figure 1 addresses the relation between Ph.D. and current affiliation entries in a different way. The vertical axis represents an institution s share of total unweighted Ph.D. affiliation scores, whereas the horizontal axis shows its share of total unweighted current affiliation scores. Exporters lie to the north-west of the straight 45 -line, importers are located to the south-east. The best 95 institutions with respect to current affiliation scores have been included. 33 institutions are exporters, the remaining 62 being importers. 10 institutions to the north-west of the 45 -line account for more than 31 Our results give a first impression of the relative importance of Ph.D. education at different institutions. For a more thorough understanding of the driving forces involved in the creation of the patterns we found it would be desirable to have a full matrix of Ph.D. exports and imports of single institutions. 16

17 half of total Ph.D. entries. These institutions are MIT, Harvard, Chicago, Stanford, Princeton, Berkeley, Yale, Oxford, LSE and Wisconsin. The bulk of institutions near the origin but south-east to the 45 -line results from the trickle-down process of economists moving to other, less prestigious universities after being granted a Ph.D. from highly ranked institutions (Ehrenberg, 1999). Some of those, like NYU, seem to be quite successful in attracting Ph.D.s from other top universities. 4.2 Time trends in concentration Since we have chosen five years out of the last two decades we are able to present a time trend of authors current and Ph.D. affiliations. Figure 2 displays the time trends for current affiliation weighted scores. The figure on the right hand side is an enlargement of the lower part of the full scale figure on the left hand side. The results suggest that there is no clear cut development within our sample years, although the relative impact of the United States seems to decline a little bit and the contributions of continental European and British economists appear to increase in recent years. The peak of concentration in 1987 may well be accidental. Generally, the findings seem to support the intuition that the dominance of the USA was quite stable during the 15 years from 1977 to 1992, but is declining in the second half of the nineties USA 0.10 UK Europe (excl. UK) UK 0.05 Israel Rest Canada International Organisations Australia Fig. 2. Current affiliation origins for selected years 17

18 The results for Ph.D. affiliations in Figure 3 can be interpreted in a similar vein. However, comparing Figures 2 and 3 one can see that the USA s share of Ph.D. affiliation scores is considerably higher than its share for current affiliation scores. Similar to the time trend for current affiliation scores there is a large decline of the USA s share of Ph.D. affiliation scores from 1992 to Conversely, the U.K. s share as well as the share of continental Europe has risen sharply in the same period which is best seen in the right hand side of Figure USA UK UK Rest Europe (excl. UK) Canada Israel Australia Fig. 3. Ph.D. affiliation origins for selected years Tables 6 and 7 are related to Figures 2 and 3 and report concentration indices for the publication market in top journals. The decline of the Herfindahl-Index from 1987 to 1997 both at the institutional and country level with respect to current affiliations (see Table 6) confirms the graphical impression for the country level in Figure 2. The market share of the top 10 institutions ranges from 26.3% (1982) to 30.2% (1987). 18

19 Table 6 Concentration indices of current affiliations of 'Top 15' Economics Journal Authors year Institutional level Herfindahl-Index a, b number of institutions as current affiliations b market share of top 10 institutions (in %) Country level Herfindahl-Index a number of current affiliation-countries market share (in %) c USA UK Canada Israel Australia Europe (excl. UK) International Organisations Rest a = ( ) 2 H j q j Q /, where q j is the weighted score of institution or country j and Q is the total weighted score of all (known) affiliations. b For calculating the Herfindahl-Index at the institutional level we took only q j 's of institutions which had at least five (unweighted) entries as current affiliations in our whole data set ( ; with a total of 5535 unweighted entries for current affiliations). However, institutions with at least five entries account for 88% (1977), 88% (1982), 87% (1987), 87% (1992) and 85% (1997) of weighted scores in respective years. From that we conclude that the Herfindahl-Index for all institutions as current affiliations could at most be higher than the one indicated in the table. c Figures may not add up to due to rounding. Table 7 refers to Ph.D. affiliations. The Herfindahl-Indices as well as market shares of top 10 institutions are considerably higher than for current affiliations. Note though that there is again a sharp decline in concentration from 1992 to 1997 which is associated with a declining impact of the United States in that period. The notion of a declining dominance of the USA, therefore, appears to hold for authors current as well as Ph.D. affiliations. The top 10 institutions have a market share between 50.5% (1997) and 57.8% (1977), double what we obtained for current affiliations. There is ample evidence that such high concentration in the second-generation production of economists is not conducive to innovation as well as variety and has possibly contributed to an inbreeding of the economics profession (Pieper and Willis, 1999). 19

20 Table 7 Concentration indices of Ph.D.-affiliations of 'Top 15' Economics Journal Authors year Institutional level Herfindahl-Index a number of Ph.D.-granting institutions market share of top 10 institutions (in %) Country level Herfindahl-Index a number of Ph.D.-granting countries market share (in %) b USA UK Canada Israel Australia Europe (excl. UK) Rest a = ( ) 2 H j q j Q /, where q j is the weighted score of institution or country j and Q is the total weighted score of all (known) affiliations. b Figures may not add up to due to rounding. 4.3 Power laws of the economics publication market We found a quite asymmetric distribution of publications on the institutional and country levels, with a few institutions or countries contributing most of all articles. Do our findings also apply on the individual level? Lotka (1926) was the first to discover a relationship between the number of authors and the frequency of their contributions, which is known as Lotka s law. In its general form, it states that the relative frequency y of persons making x contributions can be derived by the following formula (where c is a constant): x n y = c (1) Lotka found for Auerbach s Historical Tables and the Chemical Abstracts that n = 2 and called it inverse square law of scientific productivity, which means that the proportion of all contributors who contribute just a single article should empirically be near 60% (being equivalent to c in this case). The number of authors making k contributions is about n 1 / k of the fraction of authors with only 1 contribution. In its general form, Lotka s law seems to hold for many scientific fields, for econometrics it was already confirmed by Leavens (1953) 32. We report the data for our sample in Table 8, indicating the absolute and relative frequency y of authors with x 32 Leavens (1953) does not refer to Lotka, but to Zipf (1949), another power law examined below, but his application of Zipf s law clearly exhibits Lotka properties. 20

21 contributions. For our data we could reject Lotka s inverse square law where n = 2. However, we found a good fit by the following regression (indicating standard errors in parenthesis): ln( y) = ln( x) R ² = (2) (.31) (.17) number (x) of contributions in whole database (unweighted) Table 8 Authors and contributions absolute frequency of authors with x contributions relative frequency (y) of authors with x contributions Our data support n 3, meaning that the fraction of authors with only one contribution is larger than expected under the inverse square law. Our data base contains 3415 different authors, of which 2531 appear only once. This corresponds to 74.1% in comparison to the theoretical 60.8% predicted by Lotka s inverse square law. Our data corroborate the notion that the market for publications is quite competitive on the individual level since more than 3000 out of 3415 authors in our data base contributed either one or two articles. We consider this a substantial finding in the face of concerns on the variety and innovative potential in economics. Although the concentration on the institutional and country levels is high, competition between individuals irrespective of their institutional origin seems to work well at least for the top 15 journals. Stemming from the intuitive notion that institutions growth may exhibit similar properties like local growth we tested if our data fits another power law, namely Zipf s law (Zipf, 1949). Basically, it says that the number of cities with population exceeding S is proportional to 1/S. Zipf s law can be reformulated as predicting a linear relationship with slope 1 between the natural log of a city s rank and the natural log of its population. Substitute cities by institutions and population by publication 21