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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">LNE</journal-id><journal-title-group><journal-title>Lecture Notes in Education, Arts, Management and Social Science</journal-title></journal-title-group><issn>TBA</issn><eissn>2705-053X</eissn><publisher><publisher-name>WHIOCE PUBLISHING PTE. LTD.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18063/LNE.v3i10.1100</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Real-time Forecasting of Business Climate Index in Cultural, Sports, and Entertainment Industries of China: A Mixed-Frequency Dynamic Factor Model Approach</title><url>https://artdesignp.com/journal/LNE/3/10/10.18063/LNE.v3i10.1100</url><author>HuangLina,ChenQiwen,JinHouzhong</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>3</volume><issue>10</issue><history><date date-type="pub"><published-time>2025-11-26</published-time></date></history><abstract>Since China&amp;rsquo;s economic reform, the cultural, sports, and entertainment (CSE) industries have experienced significant growth. Currently, there is a lack of effective high-frequency indicators to help policymakers and industry practitioners monitor CSE developments in real time. This study constructs a Mixed-Frequency Dynamic Factor Model to provide real-time forecasting of the Prosperity Index of Enterprises (PIE) in China&amp;rsquo;s CSE industries, utilizing a dataset consisting of 26 macroeconomic indicators from 2010 to 2024. The results revealed that the model effectively captured fluctuations in PIE, successfully distinguishing economic situation before and after the COVID-19. Compared to existing macroeconomic forecasting models, this model exhibits superior predictive accuracy.</abstract><keywords>Dynamic factor model, Cultural industry, Sports industry, Entertainment industry, China, Mixed-frequency data, Real-time forecasting</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] Yin X, 2005, New Trends of Leisure Consumption in China. Journal of Family and Economic Issues, 26(1): 175.
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