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| Title | A data mining analysis of the Chinese inland-coastal inequality |
| Creator | 陳樹衡 Chen, Shu-Heng Lin, Hung-Wen Bucciarelli, Edgardo Muratore, Fabrizio Odoardi, Iacopo |
| Contributor | 經濟學系 |
| Key Words | Chinese provinces ; Inland/coastal income inequality ; MARS |
| Date | 2018 |
| Date Issued | 18-Sep-2017 15:40:12 (UTC+8) |
| Summary | 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. |
| Relation | 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 |
| Type | 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-Heng | en_US |
| dc.creator (作者) | Lin, Hung-Wen | en_US |
| dc.creator (作者) | Bucciarelli, Edgardo | en_US |
| dc.creator (作者) | Muratore, Fabrizio | en_US |
| dc.creator (作者) | Odoardi, Iacopo | en_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 96-104 | en_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 193359 | en_US |
| dc.subject (關鍵詞) | Chinese provinces ; Inland/coastal income inequality ; MARS | en_US |
| dc.title (題名) | A data mining analysis of the Chinese inland-coastal inequality | en_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 |