Journal of Data and Information Science (Mar 2023)

Practical operation and theoretical basis of difference-in-difference regression in science of science: The comparative trial on the scientific performance of Nobel laureates versus their coauthors

  • Huang Yurui,
  • Tian Chaolin,
  • Ma Yifang

DOI
https://doi.org/10.2478/jdis-2023-0003
Journal volume & issue
Vol. 8, no. 1
pp. 29 – 46

Abstract

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In recent decades, with the availability of large-scale scientific corpus datasets, difference-in-difference (DID) is increasingly used in the science of science and bibliometrics studies. DID method outputs the unbiased estimation on condition that several hypotheses hold, especially the common trend assumption. In this paper, we gave a systematic demonstration of DID in the science of science, and the potential ways to improve the accuracy of DID method.

Keywords