Using the Web to Predict Regional Trade Flows: Data Extraction, Modeling, and Validation.
Despite the importance of interregional trade for building effective regional economic policies, there are very few hard data to illustrate such interdependencies. We propose here a novel research framework to predict interregional trade flows by utilizing freely available Web data and machine learn...
| Publicado en: | Annals of the American Association of Geographers Vol. 113; no. 3; pp. 717 - 740 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Taylor & Francis Ltd
2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=162238165&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 162238165 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 24694452 JRMH jtl: Annals of the American Association of Geographers issn: 24694452 maglogo: N pubinfo: dt: 2023 vid: 113 iid: 3 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 162238165 10.1080/24694452.2022.2109577 ppf: 717 ppct: 23 formats: tig: atl: Using the Web to Predict Regional Trade Flows: Data Extraction, Modeling, and Validation. aug: au: Tranos, Emmanouil Carrascal-Incera, André Willis, George affil: School of Geographical Sciences, University of Bristol, UK and The Alan Turing Institute, UK Department of Economics, University of Oviedo, Spain School of Geography, University of Birmingham, UK su: United Kingdom Commerce Economic policy Regional economics Interregionalism Websites Machine learning Random forest algorithms sug: subj: Commerce Economic policy Regional economics Interregionalism Websites United Kingdom Internet Publishing and Broadcasting and Web Search Portals Machine learning Random forest algorithms keyword: interregional trade machine learning prediction random forest Web archives Web data aprendizaje automático archivos web bosque aleatorio comercio interregional datos web 区域间贸易 机器学习 网站存档 网络数据。 随机森林 预测 interregional trade machine learning prediction random forest Web archives Web data aprendizaje automático archivos web bosque aleatorio comercio interregional datos web 区域间贸易 机器学习 网站存档 网络数据。 随机森林 预测 ab: Despite the importance of interregional trade for building effective regional economic policies, there are very few hard data to illustrate such interdependencies. We propose here a novel research framework to predict interregional trade flows by utilizing freely available Web data and machine learning algorithms. Specifically, we extract hyperlinks between archived Websites in the United Kingdom and we aggregate these data to create an interregional network of hyperlinks between geolocated and commercial Web pages over time. We also use existing interregional trade data to train our models using random forests and then make out-of-sample predictions of interregional trade flows using a rolling-forecasting framework. Our models illustrate great predictive capability with R greater than 0.9. We are also able to disaggregate our predictions in terms of industrial sectors, but also at a subregional level, for which trade data are not available. In total, our models provide a proof of concept that the digital traces left behind by physical trade can help us capture such economic activities at a more granular level and, consequently, inform regional policies. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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