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    <identifier>10.57760/sciencedb.12748</identifier>
    <datestamp>2024-09-04T14:47:17Z</datestamp>
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  <dc:date>2024-09-04</dc:date>
  <dc:title>The panel data of 141 cities in China from 2019 to 2023</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.12748</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The research data sources mainly include the &amp;lsquo;China City Statistical Yearbook&amp;rsquo;, &amp;lsquo;China Building Statistical Yearbook&amp;rsquo;, the EPS, the PatYee, Legal Star, etc. Some missing data are filled out using the linear interpolation method. For the variables with large values in the original data, such as the number of patents and per capita GDP of each city, this paper uses logarithmic processing.&amp;nbsp;</dc:description>
  <dc:subject>panel data; 141 cities; 2019 to 2023</dc:subject>
  <dc:creator>Zhang Guanyang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
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  <dc:publisher>Science Data Bank</dc:publisher>
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