The Great Divide in Scientific Productivity. Why the Average Scientist Does Not Exist

Stijn Kelchtermans and Reinhilde Veugelers

No 2009/01, Working Papers from Hogeschool-Universiteit Brussel, Faculteit Economie en Management

Abstract: We use a quantile regression approach to estimate the eects of age, gender, research funding, teaching load and other observed characteristics of academic researchers on the full distribution of research performance, both in its quantity (publications) and quality (citations) dimension. Exploiting the panel nature of our dataset, we estimate a correlated random-eects quantile regression model, accounting for unobserved heterogeneity of researchers. We employ recent advances in quantile regression that allow its application to count data. Estimation of the model for a panel of biomedical and exact scientists at the KU Leuven in the period 1992-2001 shows strong support for our quantile regression approach, revealing the dierential impact of almost all regressors along the distribution. We also .nd that variables like funding, teaching load and cohort have a dierent impact on research quantity than on research quality.

Keywords: economics of science; research productivity; quantile regression; count data; random effects (search for similar items in EconPapers)
JEL-codes: C14 C23 L31 O31 O32 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2009-01
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Journal Article: The great divide in scientific productivity: why the average scientist does not exist (2011)
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