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

Abstract Purpose In recent decades, with the availability of large-scale scientific corpus datasets, difference-in-difference (DID) is increasingly used in science and bibliometrics studies. DID method outputs unbiased estimation on condition that several hypotheses hold, especially common trend assumption. this paper, we gave a systematic demonstration science, potential ways to improve accuracy method. Design/methodology/approach At first, reviewed statistical assumptions, model specification, application procedures Second, necessary assumptions before conducting regression estimation, introduced some matching techniques serving as pre-selecting step for design by control individuals who are equivalent those treated ones observational variables intervention. Lastly, performed case study estimate effects prizewinning performance Nobel laureates, comparing yearly citation impact after year between laureates their prizewinning-work coauthors. Findings We conduct demonstrated effectiveness use results. As study, found there no significant increases citations compared Research limitations This ignored rigorous mathematical deduction parts DID, while focused practical parts. Practical implications work gives experimental practice guidelines Originality/value gains insights into usage econometric tools science.