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Incidence and extent of co-authorship in environmental and resource economics: evidence from the Journal of Environmental Economics and Management

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Abstract

We examine the incidence and extent of co-authorship in environmental and resource economics by investigating the leading journal of environmental and resource economics: the Journal of Environmental Economics and Management. Previous studies of general economic journals have offered empirical evidence for the fact that intellectual collaboration is most prevalent in the field of environmental and resource economics. However, no previous study has examined this finding more carefully. This is a gap in the literature we hope to fill. Accordingly, we investigate all 1,436 papers published in JEEM from 1974 until 2010 with respect to potential drivers of co-authorship. We start with a descriptive analysis in order to depict the most important trends in the past 36 years. We then employ empirical methods to test several hypotheses that are commonly used to analyze the structure of co-authorship. However, we do not stick to hypotheses but investigate also other potentially relevant drivers of co-authorship as e.g. external funding. We find empirical support for a relation between the number of authors and key characteristics of an article like the number of equations, tables or the presence of external funding. Research in environmental and resource economics is demanding in terms of both disciplinary and interdisciplinary skills, so the likelihood of collaboration and jointly written publications is present and significant.

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Notes

  1. Lovell (1973) notes that the cumulative stock of journal articles in economics doubles every 14 years.

  2. According to the ISI Web of Knowledge, JEEM was ranked number 17 of all economic journals and number one among environmental economics journals with an impact factor of 2.989 in 2010. Rousseau et al. (2009) offer evidence that JEEM “is the leading publication in the field” (Rousseau et al. 2009, p. 283). Auffhammer (2009) states that “JEEM is the most highly ranked journal in the environmental and resource economics field” (Auffhammer 2009, p. 254). Moreover, the journal was the sole official journal of the Association of Environmental and Resource Economists (AERE) and has a long publication history which makes it the ideal journal for our purpose. We have analyzed three other leading publications in the field, Ecological Economics, Environmental and Resource Economics and Energy Economics. Energy Economics started publishing in 1981, Ecological Economics in 1993 and Environmental and Resource Economics in 1995. We have compared the figures for number of authors and single-authored publications in JEEM and the other three journals from 1981 onwards. The pattern is similar for number of authors. In 1981, the number of authors was 1.52 in JEEM and 1.5 in Energy Economics. This number increased until 2009 to 2.49 in JEEM and 2.51 in the other three journals. Additionally, the first issue of JEEM was published in 1974 and our sample allows us therefore to determine important trends in environmental and resource economics over a longer timespan.

  3. Resources for the Future, the University of British Columbia, the University of Maryland, the University of California, Berkeley, and the University of Wyoming all had more than 10 papers published in JEEM. Canada, the United Kingdom, Israel, Norway, and Australia were the top foreign contributing countries.

  4. See Acedo et al. (2006) for management and organizational studies and Hilmer and Hilmer (2005) for agricultural economics. Hollis (2001) uses a panel of 339 economists in order to evaluate the relationship between co-authorship and output, and Acedo et al. (2006) investigate co-authorship in management and organizational studies using network analysis.

  5. Piette and Ross (1992) investigate the 15 leading economic journals between 1984 and 1986 and find general evidence that co-authorship in economics depends on the field of specialization. In their probit estimation, the effect for “natural resources” was the most influential. Laband and Tollison (2000) have also estimated a probit model for the timespan from 1885 to 1995 using the old Journal of Economic Literature (JEL) classification. The marginal effect for the “JEL 700—Agriculture and natural resources” variable was both statistically highly significant and most influential (with a marginal effect of 0.0885).

  6. According to Kalaitzidakis et al. (2003, p. 1349), The American Economic Review, Econometrica, The Journal of Political Economy, Journal of Economic Theory, and The Quarterly Journal of Economics. To keep a balance between US and European journals we have also included the British Economic Journal.

  7. Similar to Hudson (1996) we conduct a linear spline analysis for the average fraction of single-authored papers for each year in order to figure out whether trends were more or less steady or spasmodic. We find that the slope of the timeseries changes significantly at the 5 percent level in 1977, 1989, and 1999 (see Appendix 2 for the estimation and a graphic representation).

  8. However, the magnitude for articles published in JEEM was significantly higher. A standard mean-comparison test over the whole sample period revealed a t value of −9.96. In this way, the mean number of authors was statistically significantly higher for JEEM than for the core journals.

  9. We are thankful for this comment provided by an anonymous referee. In practice, however, it is hard to distinguish between the different effects acknowledgements could measure.

  10. Unfortunately, 31 articles could not be analyzed, since we could not determine the gender of the author(s) because only the surname and the first initial were given.

  11. While the mean for 1974 was ≈570 words per page, this number has risen to ≈1,050 words per page in 2010. If we did not take into account these layout changes the coefficient for pages would be significantly biased downwards.

  12. Due to the fact that programming of bootstrapping routines or simulation studies require demanding computer skills and hence fosters potential collaboration, the coefficient on THEORY would be even higher if we were to treat artificial data and simulation methods as quantitative work.

  13. Of course citations are only one possible alternative for measuring impact or influence. But as Medoff (2007) aptly writes about the findings of Leibowitz and Palmer (1983), “if an article (or an economist) with few citations is considered to be a significant scientific contribution, then why has it not generated more citations?” (Medoff 2007, p. 305).

  14. Alternative measures include the ordinal inclusion of citations or interpreting the articles as “TOP” that were cited by a core journal at least once (≈10 %). In an older version of the paper, we have considered the 10 % of the most cited articles as being the leading publications. This approach favored older articles. We are thankful to a referee for this comment.

  15. Laband and Tollison (2000) investigate a sub-sample of 439 articles published in The American Economic Review, the Journal of Political Economy, and The Quarterly Journal of Economics and compare it to articles in three biology journals. They find that “in both disciplines, the presence of funding increases the average number of coauthors by 0.3, which implies that there is some relationship between funding and co-authorship” (Laband and Tollison 2000, p. 637).

  16. However, distinguishing between both effects is not possible with our dataset.

  17. As our data is significantly underdispersed we have chosen the Poisson count data model (Cameron and Trivaldi 2013).

  18. We obtain a χ 2 of 216.96 in a Breusch-Pagan test (p = 0.00).

  19. We have chosen to use only the numbered equations in order to ensure comparability between articles.

  20. An inclusion of this variable for all 1,426 articles would not have made any sense, since this variable can only be 1 if the article is co-authored. An inclusion would have resulted in multicollinearity.

  21. The partial correlations for e.g. a theoretical article and the number of equations was 0.43 and −0.63 for the number of tables.

  22. The results are available upon request.

  23. We thank Dan Phaneuf, the editor of JEEM, for the delivered data on paper submissions for the period from 2000 to 2010. Unfortunately, this results in a restricted sample of 517 articles and the empirical analysis loses some meaning and explanatory power. However, the results are available upon request.

  24. We are thankful to a referee for pointing this out.

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Acknowledgments

The authors gratefully acknowledge comments provided by two anonymous referees. We express our thanks to Sascha Rexhäuser and to the participants of the 19th Annual Conference of the European Association of Environmental and Resource Economists (EAERE) in Prague for inspiring discussions. The usual disclaimers apply.

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Authors and Affiliations

  1. Centre for European Economic Research (ZEW), Mannheim, L7,1, 68161, Mannheim, Germany

    Michael Schymura & Andreas Löschel

  2. University of Heidelberg, Heidelberg, Germany

    Andreas Löschel

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  1. Michael Schymura
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Correspondence to Michael Schymura.

Appendices

Appendix 1: Summary statistics

See Table 6.

Table 6 Descriptive statistics of important variables
Full size table

Appendix 2: Linear spline analysis

See Table 7 and Fig. 8.

Table 7 Linear spline regression for single-authored papers
Full size table
Fig. 8
figure 8

Linear spline regression

Full size image

Appendix 3: Classification of articles

To validate our classification we estimate three similar probit models j with the type of article as the dependent variables (\(j \in (THEOR, QUALI, QUANTI, QUANTITHEOR))\) and our variables for quantitative content and other potentially relevant characteristics as regressors.

$$ \begin{aligned} \hbox{Probit}_{ji} =\,& \beta_0 + \beta_1 \cdot \hbox{PAGES}_i + \beta_2 \cdot \hbox{FEMALE}_i + \beta_3 \cdot \hbox{EXTERNALFUND}_i \\ & + \beta_4 \cdot \hbox{EQUAT}_i + \beta_5 \cdot \hbox{TABLES}_i + \beta_6 \cdot \hbox{FIGURES}_i + \beta_7 \cdot \hbox{APPENDIX}_i \\ & + \gamma_{i} \\ & \hbox{with}\; j \in \left(THEOR, QUALI, QUANTI, QUANTITHEOR\right) \\ \end{aligned} $$

See Table 8.

Table 8 Probit estimates for article category
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Schymura, M., Löschel, A. Incidence and extent of co-authorship in environmental and resource economics: evidence from the Journal of Environmental Economics and Management . Scientometrics 99, 631–661 (2014). https://doi.org/10.1007/s11192-014-1248-0

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