Economic Modelling at thirty-five: A retrospective bibliometric survey
Debidutta Pattnaik (),
Bruce Burton and
Weng Marc Lim
Economic Modelling, 2022, vol. 107, issue C
Economic modelling (EM) is a premier journal for policy-relevant economic models. However, so far, no retrospective studies exist for the journal. This study addresses this gap using a machine learning n-gram (bigram and trigram) analysis. The survey results find that the journal has contributed to 9517 topics, with 69 topics covered in at least 10 studies between 1984 and 2019. Through a co-occurrence analysis of bigram and trigram terms, this study reveals that the major topics in the journal converge to nine themes: international economics, development economics, regional and real estate economics, economic growth and development, financial economics, monetary economics, general economic equilibrium, international finance, and non-conventional finance and macroeconomics. This study concludes with key takeaways and suggestions for prospective authors intending to publish their best papers in EM.
Keywords: Economic modelling; Bibliometrics; Machine learning; N-gram analysis; Co-occurrence analysis (search for similar items in EconPapers)
JEL-codes: C00 E44 F31 N01 O1 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:107:y:2022:i:c:s0264999321003011
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().