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    <identifier>10.57760/sciencedb.08175</identifier>
    <datestamp>2023-09-04T09:48:58Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2023-09-04</dc:date>
  <dc:title>External Earnings Pressure, Management Tone and Stock Price Crash Risk</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.08175</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This study uses panel data on Chinese A-share listed companies in Shanghai and Shenzhen covering 2014 to 2020 selected through the following screening: first, we exclude listed companies in the finance and insurance sectors; second, we exclude listed companies in ST and *ST (Special Treatment); finally, we exclude samples that lack important data. This approach generates 8,658 valid research sample observations. The data are obtained from several official websites, such as those for CSMAR (China Stock Market &amp;amp; Accounting Research Database), CNRDS (Chinese Research Data Services), and the Shanghai and Shenzhen stock exchanges.In this study, the descriptive and relevance of the final data was tested using Stata software, and baseline regression, threshold regression, and robustness and heterogeneity tests were performed. The&amp;nbsp;final&amp;nbsp;data&amp;nbsp;were&amp;nbsp;tested&amp;nbsp;for&amp;nbsp;descriptiveness&amp;nbsp;and&amp;nbsp;correlation&amp;nbsp;using&amp;nbsp;Stata&amp;nbsp;software,&amp;nbsp;and&amp;nbsp;baseline&amp;nbsp;regression,&amp;nbsp;threshold&amp;nbsp;regression,&amp;nbsp;and&amp;nbsp;robustness&amp;nbsp;and&amp;nbsp;heterogeneity&amp;nbsp;tests&amp;nbsp;were&amp;nbsp;performed.</dc:description>
  <dc:subject>threshold regression; china;  A-share listed companies in Shanghai and Shenzhen</dc:subject>
  <dc:creator>Kuang-Cheng Chai</dc:creator>
  <dc:creator>Jia-Hui Zhang</dc:creator>
  <dc:creator>Zi-Lu Wang</dc:creator>
  <dc:creator>Ke-Chiun Chang</dc:creator>
  <dc:creator>Yang-Yang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
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  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1080/00036846.2023.2273233</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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