2019
DOI: 10.18520/cs/v116/i1/35-39
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A Granger Causality Test of the Causal Relationship Between the Number of Editorial Board Members and the Scientific Output of Universities in the Field of Chemistry

Abstract: Editorial board members, who are considered the gatekeepers of scientific journals, play an important role in academia, and may directly or indirectly affect the scientific output of a university. In this article, we used the quantile regression method among a sample of 1,387 university in chemistry to characterize the correlation between the number of editorial board members and the scientific output of their universities. Furthermore, we used time-series data and the Granger causality test to explore the cau… Show more

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Cited by 3 publications
(3 citation statements)
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“…The results differing from the hypothesis may be due to following reasons i) small sample size of secondary education or out-of-pocket expenditure ii) the two variables might be 'rigid'. In other words, an increase or decrease of one variable does not necessarily cause a significant increase or decrease of the other (Wang, 2019). Thus, no policy effect is expected to manifest between the two variables.…”
Section: Unit Root/stationarity Testmentioning
confidence: 97%
See 1 more Smart Citation
“…The results differing from the hypothesis may be due to following reasons i) small sample size of secondary education or out-of-pocket expenditure ii) the two variables might be 'rigid'. In other words, an increase or decrease of one variable does not necessarily cause a significant increase or decrease of the other (Wang, 2019). Thus, no policy effect is expected to manifest between the two variables.…”
Section: Unit Root/stationarity Testmentioning
confidence: 97%
“…The data for selected variables are obtained for the time period 1970-2018 and were sourced from the World Bank Development Indicator (2018) online Procedurally, the first step to Granger causality test is the determination of the optimal lag length using the relevant information criteria. Meanwhile, the choice of information criteria to be used is entirely the researchers' because no information criterion is superior to the other (Wang, 2019). However, while the Akaike Information criteria (AIC) is suitable for very large sample size.…”
Section: Model Specificationmentioning
confidence: 99%
“…We used a restricted regression model which says that variable Y can be described itself using its own lagged ("past") values (equation 2) 01 1 m is the number of lagged terms (Wang, 2019). The null hypothesis of the test says that the variable X does not affect the variable Y in Granger way (no lagged values of X are statistically significantly feasible for the regression model).…”
Section: Granger Causalitymentioning
confidence: 99%