Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries
In this study, the effect of freight and passenger transport in different modes on economic growth is determined for 28 selected countries. The Westerlund cointegration test is used to reveal the long-term relationship between freight and passenger transportation and growth. According to the cointe...
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| Format: | Article |
| Language: | English |
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TU Delft OPEN Publishing
2025-03-01
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| Series: | European Journal of Transport and Infrastructure Research |
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| Online Access: | https://journals.open.tudelft.nl/ejtir/article/view/7715 |
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| author | Esme Isik Ayfer Ozyilmaz Yüksel Bayraktar Metin Toprak Mehmet Fırat Olgun Nazli Keyifli Senturk |
| author_facet | Esme Isik Ayfer Ozyilmaz Yüksel Bayraktar Metin Toprak Mehmet Fırat Olgun Nazli Keyifli Senturk |
| author_sort | Esme Isik |
| collection | DOAJ |
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In this study, the effect of freight and passenger transport in different modes on economic growth is determined for 28 selected countries. The Westerlund cointegration test is used to reveal the long-term relationship between freight and passenger transportation and growth. According to the cointegration analysis, all transportation modes (road, rail, and air) are cointegrated with growth. Additionally, machine learning models were used to predict growth based on each transportation mode for each country for the upcoming four years and to determine the importance of the input parameters. According to the importance of the parameter analysis, for the entire panel, rail transport is the most effective transport mode for economic growth. On a country-by-country basis, the findings differ. Rail transport is the strongest transport mode for growth in high-income countries. However, although it is not the dominant mode, the relative impact of air passenger transport is strong. In upper middle-income countries, there generally is not a dominant mode of transport, but in general, freight transport is important to economic growth. In passenger transportation, air passenger transport is the most prominent mode in these countries. In lower middle-income countries, rail freight is the strongest transport mode for economic growth.
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| format | Article |
| id | doaj-art-23ee4bd2bcb6413e9859c6010d10fded |
| institution | Kabale University |
| issn | 1567-7141 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | TU Delft OPEN Publishing |
| record_format | Article |
| series | European Journal of Transport and Infrastructure Research |
| spelling | doaj-art-23ee4bd2bcb6413e9859c6010d10fded2025-08-20T03:44:21ZengTU Delft OPEN PublishingEuropean Journal of Transport and Infrastructure Research1567-71412025-03-0125110.59490/ejtir.2025.25.1.7715Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 CountriesEsme Isik0Ayfer Ozyilmaz1https://orcid.org/0000-0001-9201-2508Yüksel Bayraktar2https://orcid.org/0000-0002-3499-4571Metin Toprak3https://orcid.org/0000-0001-9217-6318Mehmet Fırat Olgun4https://orcid.org/0000-0002-2728-0714Nazli Keyifli SenturkMalatya Turgut Ozal UniversityKırıkkale UniversityAnkara UniversityHalic UniversityKastamonu University In this study, the effect of freight and passenger transport in different modes on economic growth is determined for 28 selected countries. The Westerlund cointegration test is used to reveal the long-term relationship between freight and passenger transportation and growth. According to the cointegration analysis, all transportation modes (road, rail, and air) are cointegrated with growth. Additionally, machine learning models were used to predict growth based on each transportation mode for each country for the upcoming four years and to determine the importance of the input parameters. According to the importance of the parameter analysis, for the entire panel, rail transport is the most effective transport mode for economic growth. On a country-by-country basis, the findings differ. Rail transport is the strongest transport mode for growth in high-income countries. However, although it is not the dominant mode, the relative impact of air passenger transport is strong. In upper middle-income countries, there generally is not a dominant mode of transport, but in general, freight transport is important to economic growth. In passenger transportation, air passenger transport is the most prominent mode in these countries. In lower middle-income countries, rail freight is the strongest transport mode for economic growth. https://journals.open.tudelft.nl/ejtir/article/view/7715TransportationLogisticsEconomic GrowthArtificial Neural Network |
| spellingShingle | Esme Isik Ayfer Ozyilmaz Yüksel Bayraktar Metin Toprak Mehmet Fırat Olgun Nazli Keyifli Senturk Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries European Journal of Transport and Infrastructure Research Transportation Logistics Economic Growth Artificial Neural Network |
| title | Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries |
| title_full | Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries |
| title_fullStr | Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries |
| title_full_unstemmed | Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries |
| title_short | Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries |
| title_sort | assessing the impact of multimodal transportation on economic growth a machine learning and cointegration approach in 28 countries |
| topic | Transportation Logistics Economic Growth Artificial Neural Network |
| url | https://journals.open.tudelft.nl/ejtir/article/view/7715 |
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