nep-sog New Economics Papers
on Sociology of Economics
Issue of 2011‒07‒02
four papers chosen by
Jonas Holmström
Swedish School of Economics and Business Administration

  1. The Merits of Using Citations to Measure Research Output in Economics Departments: The New Zealand Case By David L. Anderson; John Tresler
  2. Measuring the Value of Research: A Generational Accounting Approach By Robert Hofmeister
  3. Dominance relations when both quantity and quality matter, and applications to the\r\ncomparison of US research universities and worldwide top departments in economics By Nicolas CARAYOL (GREThA); Agenor LAHATTE (OST)
  4. Identifying the Effects of Co-Authorship Networks on the Performance of Scholars: A Correlation and Regression Analysis of Performance Measures and Social Network Analysis Measures By Alireza Abbasi; Jorn Altmann; Liaquat Hossain

  1. By: David L. Anderson (Queen's University); John Tresler (University of Waikato)
    Abstract: In this paper we explore the merits of utilizing citation counts to measure research output in economics in the context of a nation-wide research evaluation scheme. We selected one such system for study: the New Zealand government’s Programme-Based Research Fund (PBRF). Citations were collected for all refereed papers produced by New Zealand’s academic economists over the period 2000 to 2008 using the databases of the ISI/Web of Science and, to a limited extent, Google Scholar. These data allowed us to estimate the time lags in economics between publication of an article and the flow of citations; to demonstrate the impact of alternative definitions of ‘economics-relevant’ journals on citation counts; and to assess the impact of direct citation measures and alternative schemes on departmental and individual performance. Our findings suggest that the time-lags between publication and citing are such that it would be difficult to rely on citations counts to produce a meaningful measure of output in a PBRF-like research evaluation framework, especially one based explicitly on individual assessment.
    Keywords: citations; economics departments; journal weighting schemes; PBRF; research output
    JEL: A19 C81 J24
    Date: 2011–06–21
  2. By: Robert Hofmeister (Department of Economics, University of Konstanz, Germany)
    Abstract: This paper proposes a generational accounting approach to valuating research. Based on the flow of scientific results, a value-added (VA) index is developed that can, in principle, be used to assign a monetary value to any research result and, by aggregation, on entire academic disciplines or sub-disciplines. The VA-index distributes the value of all applications that embody research to the works of research which the applications directly rely on, and further to the works of research of previous generations which the authors of the immediate reference sources have directly or indirectly made use of. The major contribution of the VA-index is to provide a measure of the value of research that is comparable across academic disciplines. To illustrate how the generational accounting approach works, I present a VAbased journal rating and a rating of the most influential recent journal articles in the field of economics.
    Keywords: Research evaluation, research accounting, journal ranking, citations
    JEL: A13 A14 I23
    Date: 2011–05–02
  3. By: Nicolas CARAYOL (GREThA); Agenor LAHATTE (OST)
    Abstract: In this article, we propose an extension of the concept of stochastic dominance intensively\r\nused in economics for the comparison of composite outcomes both the quality and the\r\nquantity of which do matter. Our theory also allows us to require unanimity of judgement\r\namong new classes of functions. We apply this theory to the ranking of US research\r\nuniversities, thereby providing a new tool to scientometricians (and the academic\r\ncommunities) who typically aim to compare research institutions taking into account both\r\nthe volume of publications and the impact of these articles. Another application is provided\r\nfor comparing and ranking academic departments when one takes into account both the size\r\nof the department and the prestige of each member.
    Keywords: Ranking, dominance relations, citations.
    JEL: D63 I23
    Date: 2011
  4. By: Alireza Abbasi; Jorn Altmann (Technology Management, Economics, and Policy, College of Engineering, Seoul National University); Liaquat Hossain
    Abstract: In this study, we develop a theoretical model based on social network theories and analytical methods for exploring collaboration (co-authorship) networks of scholars. We use measures from social network analysis (SNA) (i.e., normalized degree centrality, normalized closeness centrality, normalized betweenness centrality, normalized eigenvector centrality, average ties strength, and efficiency) for examining the effect of social networks on the (citation-based) performance of scholars in a given discipline (i.e., information systems). Results from our statistical analysis using a Poisson regression model suggest that research performance of scholars (g-index) is positively correlated with four SNA measures except for the normalized betweenness centrality and the normalized closeness centrality measures. Furthermore, it reveals that only normalized degree centrality, efficiency, and average ties strength have a positive significant influence on the g-index (as a performance measure). The normalized eigenvector centrality has a negative significant influence on the g-index. Based on these results, we can imply that scholars, who are connected to many distinct scholars, have a better citation-based performance (g-index) than scholars with fewer connections. Additionally, scholars with large average ties strengths (i.e., repeated co-authorships) show a better research performance than those with low tie strengths (e.g., single co-authorships with many different scholars). The results related to efficiency show that scholars, who maintain a strong co-authorship relationship to only one co-author of a group of linked co-authors, perform better than those researchers with many relationships to the same group of linked co-authors. The negative effect of the normalized eigenvector suggests that scholars should work with many students instead of other well-performing scholars. Consequently, we can state that the professional social network of researchers can be used to predict the future performance of researchers.
    Keywords: Collaboration, citation-based research performance, co-authorship networks, social network analysis measures, regression, correlation.
    JEL: C02 C13 C25 C43 C51 C52 D02 D85 H81 L25 M11 M12 O31 O33
    Date: 2011–06

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