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    <journal-meta>
      <journal-title-group><journal-title>SET Proceedings</journal-title></journal-title-group>
      <issn pub-type="epub">2978-4387</issn>
      <publisher><publisher-name>Caravel Press</publisher-name></publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.65582/set.2018.215</article-id>
      <article-id pub-id-type="publisher-id">2018.215</article-id>
      <title-group><article-title>Study on the evolution of living energy consumption structure for urban residents in China under the background of low-carbon</article-title></title-group>
    <contrib-group>
      <contrib contrib-type="author">
        <name><surname>Peng</surname><given-names>Fangchun</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Shen</surname><given-names>Yuxi</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Xu</surname><given-names>Hao</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
      </contrib>
      <aff id="aff1">School of Economics and Management, Hubei University of Technology</aff>
    </contrib-group>
      <pub-date publication-format="electronic" date-type="pub"><day>28</day><month>02</month><year>2019</year></pub-date>
      <volume>17</volume>
      <issue>4</issue>
      <isbn publication-format="electronic">978-0-85358-327-1</isbn>
      <fpage>237</fpage>
      <lpage>245</lpage>
      <self-uri xlink:href="https://caravelpress.com/proceedings/set/papers/2018.215"/>
      <history>
        <date date-type="received"><string-date>28 February 2019</string-date></date>
      </history>
      <permissions>
        <copyright-statement>© 2018 Copyright WSSET</copyright-statement>
        <copyright-year>2019</copyright-year>
      </permissions>
      <abstract><p>The proportion of urban residents' living energy consumption in total energy consumption is increasing, and its structural evolution is related to the sustainable development of China's energy structure and the green development. Based on 1997-2016 as samples, this paper analysis the spatial and temporal evolution of energy consumption structure for urban residents in China. After building the vector autoregressive model containing information entropy of energy consumption structure, the per capita consumer expenditure of urban residents and urbanization rate, the influence of per capita consumer expenditure and urbanization rate on the evolution of urban residents' living energy consumption structure was studied by impulse response analysis and variance decomposition. The result shows: in terms of time, the information entropy presents the &quot;inverted U&quot; tendency, namely the energy consumption for urban residents has gradually evolved from disorder to order and from low order to high order; in terms of space, there are significant differences in the living energy consumption structure in eastern, central and western regions of China. The impact of per capita consumer expenditure and urbanization rate on the living energy consumption structure is significantly different. The structure has obvious lag effect on the impact of per capita consumer expenditure and less fluctuation. And the response to the impact of urbanization rate has repeated fluctuations. Under the background of low-carbon, the optimisation of China's living energy structure needs not only give full play to the role of the market in energy structure adjustment, but also give full play to the role of the government in macro-control.</p></abstract>
      <kwd-group kwd-group-type="author">
        <kwd>living energy consumption structure</kwd>
        <kwd>the information entropy</kwd>
        <kwd>per capita consumer expenditure</kwd>
        <kwd>vector autoregressive model</kwd>
      </kwd-group>
      <conference>
        <conf-date>21 to 23 August 2018</conf-date>
        <conf-name>17th International Conference on Sustainable Energy Technologies</conf-name>
        <conf-acronym>SET2018</conf-acronym>
        <conf-num>17</conf-num>
        <conf-loc>Wuhan, China</conf-loc>
      </conference>
    </article-meta>
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