Have a personal or library account? Click to login
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 Cover

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

By: Yurui Huang,  Chaolin Tian and  Yifang Ma  
Open Access
|Mar 2023

Abstract

Purpose

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.

Design/methodology/approach

At first, we reviewed the statistical assumptions, the model specification, and the application procedures of DID method. Second, to improve the necessary assumptions before conducting DID regression and the accuracy of estimation, we introduced some matching techniques serving as the pre-selecting step for DID design by matching control individuals who are equivalent to those treated ones on observational variables before the intervention. Lastly, we performed a case study to estimate the effects of prizewinning on the scientific performance of Nobel laureates, by comparing the yearly citation impact after the prizewinning year between Nobel laureates and their prizewinning-work coauthors.

Findings

We introduced the procedures to conduct a DID estimation and demonstrated the effectiveness to use matching method to improve the results. As a case study, we found that there are no significant increases in citations for Nobel laureates compared to their prizewinning coauthors.

Research limitations

This study ignored the rigorous mathematical deduction parts of DID, while focused on the practical parts.

Practical implications

This work gives experimental practice and potential guidelines to use DID method in science of science and bibliometrics studies.

Originality/value

This study gains insights into the usage of econometric tools in science of science.

DOI: https://doi.org/10.2478/jdis-2023-0003 | Journal eISSN: 2543-683X | Journal ISSN: 2096-157X
Language: English
Page range: 29 - 46
Submitted on: Dec 30, 2022
Accepted on: Jan 4, 2023
Published on: Mar 5, 2023
Published by: Chinese Academy of Sciences, National Science Library
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Yurui Huang, Chaolin Tian, Yifang Ma, published by Chinese Academy of Sciences, National Science Library
This work is licensed under the Creative Commons Attribution 4.0 License.