Measuring the Value of Research: A Generational Accounting Approach
AbstractThis 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.
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Bibliographic InfoPaper provided by Department of Economics, University of Konstanz in its series Working Paper Series of the Department of Economics, University of Konstanz with number 2011-07.
Length: 33 pages
Date of creation: 02 May 2011
Date of revision:
Find related papers by JEL classification:
- A13 - General Economics and Teaching - - General Economics - - - Relation of Economics to Social Values
- A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
- I23 - Health, Education, and Welfare - - Education - - - Higher Education and Research Institutions
This paper has been announced in the following NEP Reports:
- NEP-ACC-2011-05-14 (Accounting & Auditing)
- NEP-ALL-2011-05-14 (All new papers)
- NEP-SOG-2011-05-14 (Sociology of Economics)
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- Volij, Oscar & Palacios-Huerta, Ignacio, 2004.
"The Measurment of Intellectual Influence,"
Staff General Research Papers
10797, Iowa State University, Department of Economics.
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- Amavilah, Voxi Heinrich, 2011. "The Full Value of the Nobel Prize - Part 1: Mining “Data Without Theory”," MPRA Paper 33483, University Library of Munich, Germany.
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