Formulating research policy on expert advice |
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| Institution: | 1. Department of Economics, Monash University, Clayton, VIC 3800, Australia;2. Charles Reeves School of Business, Methodist University, Fayetteville, NC 28311-1498, USA;1. Department of Economics, University of Messina, Italy;2. School of Economics, Nottingham University, United Kingdom;1. Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia;2. Department of Microbiology, Graduate School of Medical Science, Kanazawa University, Takara-machi Kanazawa, Ishikawa, Japan;1. Owen Graduate School of Management, Vanderbilt University, USA;2. Department of Economics, Santa Clara University, USA;1. School of Mathematical Sciences, Monash University, Clayton, Victoria 3800, Australia;2. Institute of Applied Physics of the Russian Academy of Sciences, Nizhny Novgorod, Russia;3. University College London, UK;4. Nizhny Novgorod State Technical University n.a. R.E. Alekseev, Nizhny Novgorod, Russia;5. University of Southern Queensland, Toowoomba, QLD, 4350, Australia;1. Department of Mathematics and Statistics, University of Massachusetts, Amherst MA 01003-4515, USA;2. Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA;3. Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15260, USA;4. Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15260, USA |
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| Abstract: | National Research Assessments represent the principal policy used by countries with public university systems to improve the quality of their universities׳ research. They typically employ expert panels of local academics to assess journal quality, and use such assessments to reward publications. We propose a model of how experts assess quality and test this model using data from the recent Australian assessment. Controlling for objective quality, we show that experts׳ cognitive biases dominate their assessments. Consequently, such assessments exaggerate the quality of the experts׳ research and understate that of their colleagues. Our model can explain 95% of the variation in assessments. |
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| Keywords: | Cognitive bias Interested experts Voting Linked decisions Research policy |
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