Cover Image

A new method of identifying key industries: A principal component analysis

This article using the principal components analysis identifies key industries and groups them into particular clusters. The data come from the US benchmark input-output tables of the years 2002, 2007, 2012 and the most recently published input-output table of the year 2019. We observe some intertemporal switches of industries both between and within the top clusters. The findings further suggest that structural change is a slow-moving process and it takes time for some industries to move from one cluster to the other. This information may be proved important in the designation of effective economic policies by targeting key industries and also for the stability properties of the economic system.
Year of publication:
2022
Authors: Tsoulfidis, Lefteris ; Athanasiadis, Ioannis
Published in:
Journal of Economic Structures. - Heidelberg : Springer, ISSN 2193-2409. - Vol. 11.2022, p. 1-23
Publisher: Heidelberg : Springer
Subject: Clusters | Dimensionality reduction | Networks | Principal components | Structural change
Type of publication: Article
Type of publication (narrower categories): Article
Language: English
Other identifiers:
10.1186/s40008-022-00261-z [DOI]
1797437208 [GVK]
hdl:10419/261630 [Handle]
Classification: B24 - Socialist; Marxist ; B51 - Socialist; Marxian; Sraffian ; C67 - Input-Output Models ; D46 - Value Theory ; D57 - Input-Output Analysis ; E11 - Marxian; Sraffian; Institutional; Evolutionary ; E32 - Business Fluctuations; Cycles
Source:
Persistent link: https://ebvufind01.dmz1.zbw.eu/10013288360
Similar items by subject
Similar items by person