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題名 A data mining analysis of the Chinese inland-coastal inequality
作者 陳樹衡
Chen, Shu-Heng
Lin, Hung-Wen
Bucciarelli, Edgardo
Muratore, Fabrizio
Odoardi, Iacopo
貢獻者 經濟學系
關鍵詞 Chinese provinces ; Inland/coastal income inequality ; MARS
日期 2018
上傳時間 18-Sep-2017 15:40:12 (UTC+8)
摘要 As in many countries, even in China the socio-economic changes have affected income inequality in recent decades. The various economic opportunities have led to different paths of development causing severe disparities in GDP per capita level. In addition to the well-known Chinese rural/urban inequality, in this work we study the inland/coastal differences. There are many known causes of inequality, but we aim to discover the actual determinants of the local GDP and, therefore, of income in a period that includes the international economic crisis started in 2007. With this aim, we use different variables to obtain clusters of the Chinese provinces in the period 2004–2015 and, subsequently, we investigate the determinants of income with a multivariate adaptive regression splines (MARS). There is an extensive economic literature on the Chinese case: MARS allows us to integrate this literature enabling us to find which GDP determinants are the most relevant in the certain areas of China.
關聯 Advances in Intelligent Systems and Computing, olume 618, Pages 96-104
14th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2017; Porto; Portugal; 21 June 2017 到 23 June 2017; 代碼 193359
資料類型 conference
DOI https://doi.org/10.1007/978-3-319-60882-2_12
dc.contributor 經濟學系zh_TW
dc.creator (作者) 陳樹衡zh_TW
dc.creator (作者) Chen, Shu-Hengen_US
dc.creator (作者) Lin, Hung-Wenen_US
dc.creator (作者) Bucciarelli, Edgardoen_US
dc.creator (作者) Muratore, Fabrizioen_US
dc.creator (作者) Odoardi, Iacopoen_US
dc.date (日期) 2018
dc.date.accessioned 18-Sep-2017 15:40:12 (UTC+8)-
dc.date.available 18-Sep-2017 15:40:12 (UTC+8)-
dc.date.issued (上傳時間) 18-Sep-2017 15:40:12 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/113067-
dc.description.abstract (摘要) As in many countries, even in China the socio-economic changes have affected income inequality in recent decades. The various economic opportunities have led to different paths of development causing severe disparities in GDP per capita level. In addition to the well-known Chinese rural/urban inequality, in this work we study the inland/coastal differences. There are many known causes of inequality, but we aim to discover the actual determinants of the local GDP and, therefore, of income in a period that includes the international economic crisis started in 2007. With this aim, we use different variables to obtain clusters of the Chinese provinces in the period 2004–2015 and, subsequently, we investigate the determinants of income with a multivariate adaptive regression splines (MARS). There is an extensive economic literature on the Chinese case: MARS allows us to integrate this literature enabling us to find which GDP determinants are the most relevant in the certain areas of China.en_US
dc.format.extent 181 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Advances in Intelligent Systems and Computing, olume 618, Pages 96-104en_US
dc.relation (關聯) 14th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2017; Porto; Portugal; 21 June 2017 到 23 June 2017; 代碼 193359en_US
dc.subject (關鍵詞) Chinese provinces ; Inland/coastal income inequality ; MARSen_US
dc.title (題名) A data mining analysis of the Chinese inland-coastal inequalityen_US
dc.type (資料類型) conference
dc.identifier.doi (DOI) 10.1007/978-3-319-60882-2_12
dc.doi.uri (DOI) https://doi.org/10.1007/978-3-319-60882-2_12