Identifying excellent researchers: A new approach

Richard S J Tol

doi:10.1016/j.joi.2013.06.003

Identifying excellent researchers: A new approach

Richard S J Tol^*

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Quantile kernel regression is a flexible way to estimate the percentile of a scholar's quality stratified by a measurable characteristic, without imposing inappropriate assumption about functional form or population distribution. Quantile kernel regression is here applied to identifying the one-in-a-hundred economist per age cohort according to the Hirsch index.

Original language	English
Pages (from-to)	803-810
Number of pages	8
Journal	Journal of Informetrics
Volume	7
Issue number	4
DOIs	https://doi.org/10.1016/j.joi.2013.06.003
Publication status	Published - 2013

Keywords

A11
Economics
Hirsch index
Quantile kernel regression

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10.1016/j.joi.2013.06.003

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title = "Identifying excellent researchers: A new approach",

abstract = "Quantile kernel regression is a flexible way to estimate the percentile of a scholar's quality stratified by a measurable characteristic, without imposing inappropriate assumption about functional form or population distribution. Quantile kernel regression is here applied to identifying the one-in-a-hundred economist per age cohort according to the Hirsch index.",

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Identifying excellent researchers: A new approach

Abstract

Keywords

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