Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/113067


Title: A data mining analysis of the Chinese inland-coastal inequality
Authors: 陳樹衡
Chen, Shu-Heng
Lin, Hung-Wen
Bucciarelli, Edgardo
Muratore, Fabrizio
Odoardi, Iacopo
Contributors: 經濟學系
Keywords: Chinese provinces;Inland/coastal income inequality;MARS
Date: 2018
Issue Date: 2017-09-18 15:40:12 (UTC+8)
Abstract: 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
Data Type: conference
DOI 連結: https://doi.org/10.1007/978-3-319-60882-2_12
Appears in Collections:[經濟學系] 會議論文

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