The great divide in scientific productivity: why the average scientist does not exist
作者： S. Kelchtermans , R. Veugelers
DOI: 10.1093/ICC/DTQ074
关键词: Count data 、 Statistics 、 Quantile regression 、 Economics 、 Distribution (economics) 、 Dimension (data warehouse) 、 Quality (business) 、 Economics of science 、 Estimation 、 Econometrics 、 Random effects model
摘要: We use a quantile regression approach to estimate the eects of age, gender, research funding, teaching load and other observed characteristics academic researchers on full distribution performance, both in its quantity (publications) quality (citations) dimension. Exploiting panel nature our dataset, we correlated random-eects model, accounting for unobserved heterogeneity researchers. employ recent advances that allow application count data. Estimation model biomedical exact scientists at KU Leuven period 1992-2001 shows strong support approach, revealing dierential impact almost all regressors along distribution. also …nd variables like cohort have dierent than quality. JEL-classi…cation: C14 ; C23 L31 O31 O32
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