Credit Where Credit's Due: Accounting for Co-Authorship in Citation Counts
Richard Tol ()
No WP387, Papers from Economic and Social Research Institute (ESRI)
I propose a new method (Pareto weights) to objectively attribute citations to co-authors. Previous methods either profess ignorance about the seniority of co-authors (egalitarian weights) or are based in an ad hoc way on the order of authors (rank weights). Pareto weights are based on the respective citation records of the co-authors. Pareto weights are proportional to the probability of observing the number of citations obtained. Assuming a Pareto distribution, such weights can be computed with a simple, closed-form equation but require a few iterations and data on a scholar, her co-authors, and her co-authors' co-authors. The use of Pareto weights is illustrated with a group of prominent economists. In this case, Pareto weights are very different from rank weights. Pareto weights are more similar to egalitarian weights but can deviate up to a quarter in either direction (for reasons that are intuitive).
Keywords: data (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-sog
References: Add references at CitEc
Citations: View citations in EconPapers (14) Track citations by RSS feed
Downloads: (external link)
Journal Article: Credit where credit’s due: accounting for co-authorship in citation counts (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:esr:wpaper:wp387
Access Statistics for this paper
More papers in Papers from Economic and Social Research Institute (ESRI) Contact information at EDIRC.
Bibliographic data for series maintained by Sarah Burns ().