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  • 徐 斌

    日期:2019-01-01 14:06:20   文章点击数: 稿源:

    统计学院教师个人简介情况表

    姓名

    徐斌

    性别


    出生年月

    1975.9

    职务/职称

    副教授


    学历/学位

    博士

    博导∕硕导

    博(硕)导


    所学专业

    统计学

    电子邮箱

    Xubin9675@163.com


    学术研究领域:

    计量经济学;能源经济学


    荣誉称号和社会团体兼职

    全国统计教学学会理事,20多个国际期刊通信审稿人。


    教 学 情 况

    主要承担《计量经济学》、《空间计量经济学》、《概率论与数理统计》等课程教学工作。

    科 研 情 况

    近几年来,以第一作者或通信作者在《Energy Economics, Applied Energy, Energy Policy, Energy, Renewable and Sustainable Energy Reviews》和《数理统计与管理》等重要期刊发表论文40余篇,其中SCI 二区以上18篇,SSCI论文10篇。主持完成国家社科基金项目1项、江西省自然基金项目3项,江西省科技厅软科学项目4项,江西省教育厅科技项目2项,江西省人文社科项目1项,国家统计局科研项目3项,江西省统计局科研项目3项。代表性科研成果如下:

    期刊论文:

    [1]    Xu, B., Lin, B., 2015. Factors affecting carbon dioxide (CO2)   emissions in China's transport sector: a dynamic nonparametric additive   regression model. Journal of Cleaner Production, 101, 311322.

    [2]    Xu, B., Lin, B., 2015. Carbon dioxide emissions reduction   in China's transport sector: A dynamic VAR (vector autoregression) approach. Energy, 83, 486495. (TOP期刊).

    [3]    Xu, B., Lin, B., 2015. How industrialization and   urbanization process impacts on CO2 emissions in China: evidence   from nonparametric additive regression models. Energy Economics, 48, 188202. (TOP期刊).

    [4]    Xu, B., Lin, B., 2016. Regional differences of pollution   emissions in China: contributing factors and mitigation strategies. Journal of Cleaner   Production, 112, 14541463.

    [5]    Xu, B., Lin, B., 2016. Assessing CO2 emissions   in China’s iron and steel industry: a dynamic vector autoregression model. Applied Energy, 161, 375386. (TOP期刊).

    [6]    Xu, B., Lin, B., 2016. Regional differences in the CO2   emissions of China's iron and steel industry: Regional heterogeneity. Energy Policy, 88, 422434. (TOP期刊).

    [7]    Xu, B., Lin, B., 2016. Differences in regional emissions in China's   transport sector: Determinants and reduction strategies. Energy, 95,   459470. (TOP期刊).

    [8]    Xu, B., Lin, B., 2016. Reducing CO2 emissions in   China's manufacturing industry: Evidence from nonparametric additive   regression models. Energy, 101, 161173.   (TOP期刊).

    [9]    Xu, B., Luo, L., Lin, B., 2016. A dynamic analysis of air   pollution emissions in China: Evidence from nonparametric additive regression   models. Ecological   Indicators, 63, 346358.

    [10] Xu, B., Lin, B., 2016. Reducing carbon dioxide emissions in   China's manufacturing industry: a dynamic vector autoregression approach. Journal of Cleaner Production. 131(9), 594606.

    [11] Xu, B., Lin, B., 2016. A quantile regression analysis of   China's provincial CO2 emissions: Where does the difference lie? Energy Policy, 98, 328342. (TOP期刊).

    [12] Xu, B., Lin, B., 2017. Does the high–tech industry consistently reduce CO2   emissions? Results from nonparametric additive regression model. Environmental Impact Assessment Review 63, 4458.

    [13] Xu, B., Lin, B., 2017. What cause a surge in China's CO2   emissions? A dynamic vector autoregression analysis. Journal of Cleaner Production, 143, 1726.

    [14] Xu, B., Lin, B., 2017. Assessing CO2 emissions   in China's iron and steel industry: A nonparametric additive regression   approach. Renewable   and Sustainable Energy Reviews, 72,   325-337. (TOP期刊).

    [15] Xu, B., Lin, B., 2017. Factors affecting CO2   emissions in China’s agriculture sector: Evidence from geographically   weighted regression model. Energy Policy, 104, 404-414. (TOP期刊).

    [16] Xu, R., Xu, L., Xu, B., 2017. Assessing CO2   emissions in China's iron and steel industry: Evidence from   quantile regression approach. Journal of Cleaner Production, 152, 259-270.

    [17] Lin, B., Xu, B., 2017. Which provinces   should pay more attention to CO2 emissions? Using the quantile   regression to investigate China's manufacturing industry. Journal of Cleaner Production, 164, 980-993.

    [18] Xu, B., Xu, L., Xu, R., Luo, L., 2017. Geographical   analysis of CO2 emissions in China's manufacturing industry: A   geographically weighted regression model. Journal of Cleaner Production, 166, 628-640.

    [19] Xu, B., Lin, B., 2017. What   cause large regional differences in PM2.5 pollutions in China? Evidence from quantile regression model.  Journal of Cleaner Production, DOI:S0959-6526(17)32657-4.

    [20] Xu, B., Lin, B., 2017.   Investigating the differences in CO2 emissions in the transport   sector across Chinese provinces: Evidence from a quantile regression model. Journal of Cleaner Production, PII:S0959-6526(17)   32952-9.

    [21] XU, B., XU, L., 2012. An Empirical Research on the Factors   Impacting the Development Scale of Chinese Higher Education. Physics Procedia, 24, 667-673. (SSCI).

    [22] XU, B., Xu R.J., 2012. An Empirical Analysis on the   Consumption Structure of Town Residents, Jiangxi Province—Based on the   Extended Linear Expenditure System Model (ELES). Physics Procedia, 24, 660-666.

    [23] Wan, Y.P., Xu, B., Li, S.D., 2011. An empirical analysis on   the factors affecting the loan size of the construction of new university   campus. In Advanced   Materials Research (Vol. 181, pp.   879-883). Trans Tech Publications.

    [24] 徐斌,陈建宝,2015. 财政支农支出、经济增长、收入差距与区域农村居民消费——基于非参数可加模型的实证研究.数理统计与管理,34(5),   769-783.

    [25] 夏杰长,徐斌,2014.人力资本与经济增长——基于非线性STR模型的实证研究.首都经济贸易大学学报,16(2),5-13.

    [26] 徐斌,夏杰长, 2014.地下经济与正规经济关系的再检验广东财经大学学报, 29(1),4-11.

    [27] 夏杰长,徐斌,2015. 农村居民消费对经济增长的非线性冲击——基于STR模型的研究.黑龙江社会科学,(1):60-68.

    主持科研课题:

    [1]    中国区域PM2.5污染的空间分布差异、影响因素及溢出效应研究, 国家社科基金一般项目(15BTJ022)

    [2]    江西制造工业碳排放增长驱动因素和减排路径选择:基于非线性计量方法的实证研究, 江西省自然基金项目(20171BAA208017)

    [3]    江西新能源产业发展区域差异和影响因素:基于非线性计量的理论和应用研究,江西省人文社科项目(TJ161001)

    [4]    江西雾霾污染区域差异、影响因素及减排策略研究,江西省科学技术研究项目(GJJ160441)

    [5]      江西碳排放空间分布差异、驱动因素及溢出效应研究,江西省软科学研究项目(20161BBA10042)

    [6]      江西工业化进程中碳排放增长的影响因素和减排策略——基于非线性模型和非参数方法的实证研究, 江西省自然基金项目(20132BAB201014)

    [7]      江西工业化进程中的碳排放增长影响因素和减排策略研究, 江西省教育厅科技项目(GJJ13324)

    [8]      江西城市化进程中碳排放增长的驱动因素和减排潜力——基于非线性计量的理论和应用研究, 江西省软科学项目(20151BBA10037)

    [9]      江西工业主要行业碳生产率测度研究,江西省博士后科研择优资助项目(2013KY26)

    [10] 农村房地产发展实证研究,国家统计局统计科研计划项目(Z009)

    [11] 江西省农村公共产品供给实证研究,江西省科技厅软科学项目(N13)

    [12] 政府电子信息资源的元数据模型理论与应用研究, 国家统计局统计科研计划项目(2013LY118)

    获 奖 情   况

    近几年发表的学术论文,有5篇成为ESI高被引论文(居世界前50%的国家/地区和居前0.1%的热点论文)

    [1]    Xu B, Lin B. Assessing CO2, emissions in China’s iron and   steel industry: A dynamic vector autoregression model[J]. Applied Energy,   2016, 161:375-386. [ESI高被引论文]

    [2]    Xu B, Lin B. Factors affecting carbon dioxide (CO2) emissions   in China's transport sector: a dynamic nonparametric additive regression   model[J]. Journal of Cleaner Production, 2015, 101: 311-322. [ESI高被引论文]

    [3]    Xu B, Lin B. How industrialization and urbanization process impacts on   CO2, emissions in China: Evidence from nonparametric additive   regression models[J]. Energy Economics, 2015, 48:188-202. [ESI高被引论文]

    [4]    Xu B, Lin B. Regional differences in the CO2 emissions of   China's iron and steel industry: regional heterogeneity[J]. Energy Policy,   2016, 88: 422-434. [ESI高被引论文]

    [5]    Xu B, Lin B. Regional differences of pollution emissions in China:   contributing factors and mitigation strategies[J]. Journal of Cleaner   Production, 2016, 112: 1454-1463. [ESI高被引论文]