Mutual Granger “causality” between scientific instruments and scientific publications

Chunjuan Luan (), Siming Deng () and John R. Allison ()
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Chunjuan Luan: Dalian University of Technology
Siming Deng: Dalian University of Technology
John R. Allison: University Texas Austin

Scientometrics, 2022, vol. 127, issue 11, No 9, 6209-6229

Abstract: Abstract In this paper, we aim at examining whether there is a two-way interactive effect between scientific instruments (si) and scientific publications (sp) by employing the Granger Causality Test. As scientists explore the world, and indeed the universe, more and more deeply, new demands are constantly made for innovations in scientific instruments. More advanced scientific instruments, in turn, promote greater advances in the underlying science. Although the relationship between developments in scientific instruments and advances in science is intuitive, it has not been estimated statistically. Gaining a better empirical understanding of this relationship is, therefore, important to the science of science. Previous studies have not revealed whether there is a measurable interactive effect between them. To fill this gap in the research, we collected 42 years of data on the number of global scientific instrument patents and 42 years of data on the number of scientific research papers, both during the period 1980–2021. We take the logs of these counts (lnsi and lnsp) and perform time-series analyses of the two data sets. The Granger Causality Test is then employed to ascertain whether there exists an observable mutual association between the two time-series. The Granger Causality Test reveals, with a very high degree of confidence, a mutual predictive relationship between them. Stated differently, each time-series appears to “forecast” the other, with different time lags. A number of the Granger Causality Tests based on the characteristics of si/ sp disclose that the interaction between si and sp also applies to the mutual effect between the characteristics of si and sp, with different lag lengths.

Keywords: Scientific Instruments; Scientific Publications; The Granger Causality Test; Time-series Analysis; Co-integration (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11192-022-04516-1

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