›› 2016, Vol. 28 ›› Issue (12): 145-154.

• 组织行为与人力资源管理 • 上一篇    下一篇

就业状态对家庭消费隐含碳排放的影响——来自中国城市家庭的微观证据

徐新扩1,2, 韩立岩1   

  1. 1. 北京航空航天大学经济管理学院, 北京 100191;
    2. 首都经济贸易大学金融学院, 北京 100070
  • 收稿日期:2014-08-26 出版日期:2016-12-28 发布日期:2017-03-15
  • 通讯作者: 韩立岩(通讯作者),北京航空航天大学经济管理学院教授,博士生导师,博士,北京航空航天大学金融学科责任教授
  • 作者简介:徐新扩,北京航空航天大学经济管理学院,博士,首都经济贸易大学金融学院讲师。
  • 基金资助:

    国家自然科学基金面上项目(71173008;71371022);国家自然科学基金青年项目(71603174)。

Employment Status and Indirect Household Carbon Emissions:Micro Evidence from Urban China

Xu Xinkuo1,2, Han Liyan1   

  1. 1. School of Economics and Management, Beihang University, Beijing 100191;
    2. School of Finance, Capital University of Economics and Business, Beijing 100070
  • Received:2014-08-26 Online:2016-12-28 Published:2017-03-15

摘要:

节能减排影响就业,反过来,就业影响节能减排吗?本文基于STIRPAT模型,采用中国城市家庭的调查数据,分析就业状态及其变动对家庭消费隐含碳排放的影响。结果表明:受雇、失业和退休对家庭消费隐含碳排放的影响系数分别为0.0927、-0.233和-0.157,就学的影响不显著;就业状态影响的差异说明就业状态变动会导致家庭消费隐含碳排放的变动;具体而言,受雇通过衣着、家用设备、家居、通讯、交通和文教娱乐等多类消费增加家庭的隐含碳排放,退休增加家庭医疗保健消费的隐含碳排放,就学人员食品消费的隐含碳排放较高。研究结果能够为家庭节能减排政策的制定提供参考。

关键词: 隐含碳排放, 就业, 家庭消费, 节能减排, STIRPAT 模型

Abstract:

Climate policies have impacts on employment. Conversely, does employment affect carbon emissions? Using the survey data from households in urban China and based on the STIRPAT model, this paper analyzes the impact of employment status on household carbon emissions resulting from consumption. The findings include:the affecting coefficients of employment, unemployment and retirement are 0.0927, -0.233 and -0.157 respectively; this implies that the changes of employment status will induce the changes of household carbon emissions resulting from consumption. Specifically, employment increases household carbon emissions through consumptions in clothing, equipment, housing, communications, transportation, education or recreation; retirement increases household carbon emis-sions by means of healthcare; students produce more carbon emissions through food consumption. These findings are helpful for household emission mitigation policies.

Key words: indirect carbon emissions, employment, household consumption, emission mitigation, STIRPAT model