A new method of identifying key industries: a principal component analysis
Abstract 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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-03-01
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| Series: | Journal of Economic Structures |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40008-022-00261-z |
| _version_ | 1818917943124164608 |
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| author | Lefteris Tsoulfidis Ioannis Athanasiadis |
| author_facet | Lefteris Tsoulfidis Ioannis Athanasiadis |
| author_sort | Lefteris Tsoulfidis |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-20T00:42:05Z |
| format | Article |
| id | doaj.art-a614dfd1f2dd4874b2b3030d5a23b515 |
| institution | Directory Open Access Journal |
| issn | 2193-2409 |
| language | English |
| last_indexed | 2024-12-20T00:42:05Z |
| publishDate | 2022-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Economic Structures |
| spelling | doaj.art-a614dfd1f2dd4874b2b3030d5a23b5152022-12-21T19:59:31ZengSpringerOpenJournal of Economic Structures2193-24092022-03-0111112310.1186/s40008-022-00261-zA new method of identifying key industries: a principal component analysisLefteris Tsoulfidis0Ioannis Athanasiadis1Department of Economics, University of MacedoniaDepartment of Economics, University of MacedoniaAbstract 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.https://doi.org/10.1186/s40008-022-00261-zPrincipal componentsStructural changeDimensionality reductionClustersNetworks |
| spellingShingle | Lefteris Tsoulfidis Ioannis Athanasiadis A new method of identifying key industries: a principal component analysis Journal of Economic Structures Principal components Structural change Dimensionality reduction Clusters Networks |
| title | A new method of identifying key industries: a principal component analysis |
| title_full | A new method of identifying key industries: a principal component analysis |
| title_fullStr | A new method of identifying key industries: a principal component analysis |
| title_full_unstemmed | A new method of identifying key industries: a principal component analysis |
| title_short | A new method of identifying key industries: a principal component analysis |
| title_sort | new method of identifying key industries a principal component analysis |
| topic | Principal components Structural change Dimensionality reduction Clusters Networks |
| url | https://doi.org/10.1186/s40008-022-00261-z |
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