Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis
Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrali...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ramírez-Álvarez, José [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2023 |
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| Übergeordnetes Werk: |
Enthalten in: Networks and spatial economics - Dordrecht [u.a.] : Springer Science Business Media B.V., 2001, 24(2023), 1 vom: 14. Dez., Seite 131-164 |
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| Übergeordnetes Werk: |
volume:24 ; year:2023 ; number:1 ; day:14 ; month:12 ; pages:131-164 |
| Links: |
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| DOI / URN: |
10.1007/s11067-023-09605-z |
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SPR05483421X |
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| 520 | |a Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. | ||
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| 650 | 4 | |a Input–output analysis |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Montenegro-Rosero, Nathaly |4 aut | |
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10.1007/s11067-023-09605-z doi (DE-627)SPR05483421X (SPR)s11067-023-09605-z-e DE-627 ger DE-627 rakwb eng Ramírez-Álvarez, José verfasserin aut Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. Social Network Analysis (dpeaa)DE-He213 Centrality (dpeaa)DE-He213 Heterogeneity (dpeaa)DE-He213 Intersectoral links (dpeaa)DE-He213 Input–output analysis (dpeaa)DE-He213 Chungandro-Carranco, Vanessa aut Montenegro-Rosero, Nathaly aut Guevara-Rosero, Carolina aut Enthalten in Networks and spatial economics Dordrecht [u.a.] : Springer Science Business Media B.V., 2001 24(2023), 1 vom: 14. Dez., Seite 131-164 (DE-627)325570701 (DE-600)2037373-9 1572-9427 nnns volume:24 year:2023 number:1 day:14 month:12 pages:131-164 https://dx.doi.org/10.1007/s11067-023-09605-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2023 1 14 12 131-164 |
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10.1007/s11067-023-09605-z doi (DE-627)SPR05483421X (SPR)s11067-023-09605-z-e DE-627 ger DE-627 rakwb eng Ramírez-Álvarez, José verfasserin aut Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. Social Network Analysis (dpeaa)DE-He213 Centrality (dpeaa)DE-He213 Heterogeneity (dpeaa)DE-He213 Intersectoral links (dpeaa)DE-He213 Input–output analysis (dpeaa)DE-He213 Chungandro-Carranco, Vanessa aut Montenegro-Rosero, Nathaly aut Guevara-Rosero, Carolina aut Enthalten in Networks and spatial economics Dordrecht [u.a.] : Springer Science Business Media B.V., 2001 24(2023), 1 vom: 14. Dez., Seite 131-164 (DE-627)325570701 (DE-600)2037373-9 1572-9427 nnns volume:24 year:2023 number:1 day:14 month:12 pages:131-164 https://dx.doi.org/10.1007/s11067-023-09605-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2023 1 14 12 131-164 |
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10.1007/s11067-023-09605-z doi (DE-627)SPR05483421X (SPR)s11067-023-09605-z-e DE-627 ger DE-627 rakwb eng Ramírez-Álvarez, José verfasserin aut Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. Social Network Analysis (dpeaa)DE-He213 Centrality (dpeaa)DE-He213 Heterogeneity (dpeaa)DE-He213 Intersectoral links (dpeaa)DE-He213 Input–output analysis (dpeaa)DE-He213 Chungandro-Carranco, Vanessa aut Montenegro-Rosero, Nathaly aut Guevara-Rosero, Carolina aut Enthalten in Networks and spatial economics Dordrecht [u.a.] : Springer Science Business Media B.V., 2001 24(2023), 1 vom: 14. Dez., Seite 131-164 (DE-627)325570701 (DE-600)2037373-9 1572-9427 nnns volume:24 year:2023 number:1 day:14 month:12 pages:131-164 https://dx.doi.org/10.1007/s11067-023-09605-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2023 1 14 12 131-164 |
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10.1007/s11067-023-09605-z doi (DE-627)SPR05483421X (SPR)s11067-023-09605-z-e DE-627 ger DE-627 rakwb eng Ramírez-Álvarez, José verfasserin aut Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. Social Network Analysis (dpeaa)DE-He213 Centrality (dpeaa)DE-He213 Heterogeneity (dpeaa)DE-He213 Intersectoral links (dpeaa)DE-He213 Input–output analysis (dpeaa)DE-He213 Chungandro-Carranco, Vanessa aut Montenegro-Rosero, Nathaly aut Guevara-Rosero, Carolina aut Enthalten in Networks and spatial economics Dordrecht [u.a.] : Springer Science Business Media B.V., 2001 24(2023), 1 vom: 14. Dez., Seite 131-164 (DE-627)325570701 (DE-600)2037373-9 1572-9427 nnns volume:24 year:2023 number:1 day:14 month:12 pages:131-164 https://dx.doi.org/10.1007/s11067-023-09605-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2023 1 14 12 131-164 |
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10.1007/s11067-023-09605-z doi (DE-627)SPR05483421X (SPR)s11067-023-09605-z-e DE-627 ger DE-627 rakwb eng Ramírez-Álvarez, José verfasserin aut Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. Social Network Analysis (dpeaa)DE-He213 Centrality (dpeaa)DE-He213 Heterogeneity (dpeaa)DE-He213 Intersectoral links (dpeaa)DE-He213 Input–output analysis (dpeaa)DE-He213 Chungandro-Carranco, Vanessa aut Montenegro-Rosero, Nathaly aut Guevara-Rosero, Carolina aut Enthalten in Networks and spatial economics Dordrecht [u.a.] : Springer Science Business Media B.V., 2001 24(2023), 1 vom: 14. Dez., Seite 131-164 (DE-627)325570701 (DE-600)2037373-9 1572-9427 nnns volume:24 year:2023 number:1 day:14 month:12 pages:131-164 https://dx.doi.org/10.1007/s11067-023-09605-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2023 1 14 12 131-164 |
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Ramírez-Álvarez, José |
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Ramírez-Álvarez, José misc Social Network Analysis misc Centrality misc Heterogeneity misc Intersectoral links misc Input–output analysis Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis |
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Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis Social Network Analysis (dpeaa)DE-He213 Centrality (dpeaa)DE-He213 Heterogeneity (dpeaa)DE-He213 Intersectoral links (dpeaa)DE-He213 Input–output analysis (dpeaa)DE-He213 |
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Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis |
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Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis |
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Ramírez-Álvarez, José |
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Ramírez-Álvarez, José Chungandro-Carranco, Vanessa Montenegro-Rosero, Nathaly Guevara-Rosero, Carolina |
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central industries in the ecuadorian input–output network. an application of social network analysis |
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Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis |
| abstract |
Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. © The Author(s) 2023 |
| abstractGer |
Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. © The Author(s) 2023 |
| abstract_unstemmed |
Abstract The present study identifies the most influential industries in Ecuador according to the Input–Output Table for 2019. For this purpose, four weighted centrality indices are used from Social Network Analysis: Degree Centrality, Closeness Centrality, Betweenness Centrality, and Alpha Centrality. The results suggest that wholesale and retail trade, transportation, and professional activities are the most influential in the Ecuadorian economy due to their high centrality in commercial relationships. According to Chenery and Watanabe's methodology, all are base sectors, that is, they mainly are supply-driven. So, these centrality measures highlight the relevance of sectors based on their forward linkages. This result is not surprising. The theory of shock diffusion suggests that productive shocks on high centrality sectors can spread cascading effects downstream and generate aggregate fluctuations. © The Author(s) 2023 |
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Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis |
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https://dx.doi.org/10.1007/s11067-023-09605-z |
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Chungandro-Carranco, Vanessa Montenegro-Rosero, Nathaly Guevara-Rosero, Carolina |
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Chungandro-Carranco, Vanessa Montenegro-Rosero, Nathaly Guevara-Rosero, Carolina |
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| doi_str |
10.1007/s11067-023-09605-z |
| up_date |
2024-07-04T03:11:53.615Z |
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