{"title":"Do Chinese Photovoltaic Products Have Trade Potential in RCEP Countries? A BP Neural-Network-Improved Trade Gravity Model Analysis","authors":"Qing Guo, Zishan Mai","doi":"10.3390/su15010463","DOIUrl":null,"url":null,"abstract":"China plays an important role in the global trade of photovoltaic products, and the RCEP agreement provides more opportunities and possibilities for China. This paper develops an improved trade gravity model with BP neural networks to estimate trade potentials, and the following conclusions are obtained: (1) The BP neural network is a more effective estimation method than traditional pooled regression, fixed effects, and random effects, and the combination of multiple neural networks for prediction can lead to higher robustness and accuracy. (2) The potential of China’s trade in PV products to RCEP countries is relatively mature, but the scale of trade in PV products between China and Japan and other countries may still be further expanded. (3) China’s trade potential for different regions in the RCEP agreement changed historically in different processes, with China’s trade potential for the Oceania region declining, while its trade potential for the East and Southeast Asia region increased in recent years.","PeriodicalId":22183,"journal":{"name":"Sustainability","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainability","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3390/su15010463","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 5
Abstract
China plays an important role in the global trade of photovoltaic products, and the RCEP agreement provides more opportunities and possibilities for China. This paper develops an improved trade gravity model with BP neural networks to estimate trade potentials, and the following conclusions are obtained: (1) The BP neural network is a more effective estimation method than traditional pooled regression, fixed effects, and random effects, and the combination of multiple neural networks for prediction can lead to higher robustness and accuracy. (2) The potential of China’s trade in PV products to RCEP countries is relatively mature, but the scale of trade in PV products between China and Japan and other countries may still be further expanded. (3) China’s trade potential for different regions in the RCEP agreement changed historically in different processes, with China’s trade potential for the Oceania region declining, while its trade potential for the East and Southeast Asia region increased in recent years.
期刊介绍:
Sustainability (ISSN 2071-1050) is an international and cross-disciplinary scholarly, open access journal of environmental, cultural, economic and social sustainability of human beings, which provides an advanced forum for studies related to sustainability and sustainable development. It publishes reviews, regular research papers, communications and short notes, and there is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research relating to natural sciences, social sciences and humanities in as much detail as possible in order to promote scientific predictions and impact assessments of global change and development. Full experimental and methodical details must be provided so that the results can be reproduced.