«Multiway data analysis» and the general problem of journals’ ranking

Alexander Rubinstein and Lev Slutskin

Applied Econometrics, 2018, vol. 50, 90-113

Abstract: The paper presents a principally new ranking algorithm (on the example of economic journals) which applies methods of multiway data analysis to a sociological survey of representatives of the economic community. The algorithm provides determination of the weight function for aggregation of private ratings, taking into consideration both statistically discovered differences between the respondents and the journals weights. It also reflects latent relationships between all the components of measurement process of journals characteristics. The algorithm central element is an iterative procedure of determination of the journals core and extracting on its basis a subset of experts, whose estimates allow determining the journals aggregated ratings with subsequent clustering. The research practical result is methodological and instrumental justification of Russian economic journals ranking and selection on its basis the five categories of periodical publications.

Keywords: ranking; rating; weights of indicators; aggregation of weights; principal component analysis; Tucker decomposition; multiway data analysis (search for similar items in EconPapers)
JEL-codes: A11 A12 A14 C38 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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