Analysis of the impact of research output on economic growth with using a multivariate random effects model

Arman Pourghaz, Ehsan Bahrami Samani () and Babak Shokri
Additional contact information
Arman Pourghaz: Shahid Beheshti University
Ehsan Bahrami Samani: Shahid Beheshti University
Babak Shokri: Shahid Beheshti University

Scientometrics, 2023, vol. 128, issue 4, No 9, 2259-2282

Abstract: Abstract The purpose of this paper is to investigate the simultaneous effect of research outputs such as the number of articles indexed in Scopus on economic indicators such as inflation rate, unemployment rate and GDP of selected countries in the period of 2016 and 2020. Many articles have been studied in this regard, but none of them have focused on the simultaneous examination of research achievements on economic indicators. In some articles, research outputs on each of the economic growth indicators have been examined separately. Furthermore, separate analysis give biased estimates for the parameters and misleading inference. Consequently, we need to consider a method in which these variables can be modelled jointly. For this study, a random sample of 39 countries has been collected from the World Bank data to extract the economic index and Scopus data to extract the number of articles. In this paper, a joint model with random effects for longitudinal economic growth indicators is proposed. For these data, the simultaneous effects of some covariate for example the number of articles indexed in Scopus on the economic growth indicators as three mixed correlated responses are explored. There are main findings. Firstly, in the simultaneous examination of the effect of research outputs on economic indicators, some latent influencing factors related to each country under the title of random effects that have significant on economic indicators. Secondly, research achievements on economic indicators are significant at the same time. This significance is due to the simultaneous examination of economic indicators and appropriate statistical models are obtained with the least error compared to separate analysis.

Keywords: Joint modelling; Economic growth indicators; Longitudinal studies; Maximum likelihood; Research output; Random effect (search for similar items in EconPapers)
JEL-codes: C10 C13 C30 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-023-04638-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:128:y:2023:i:4:d:10.1007_s11192-023-04638-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-023-04638-0

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().