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Heterogeneous Impacts of Policy Sentiment with Different Themes on Real Estate Market: Evidence from China

Author

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  • Diandian Ma

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Benfu Lv

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Xuerong Li

    (Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China)

  • Xiuting Li

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China)

  • Shuqin Liu

    (School of Management, Minzu University of China, Beijing 100081, China)

Abstract

This paper empirically investigates the heterogeneous impacts of the media sentiment about policies with different themes on the real estate market in China. Based on the policy texts collected from both official and unofficial sources, we construct sentiment indices to capture the sentiment about policies with different themes, including real estate policies, fiscal policies, monetary policies, land policies, healthcare policies, household registration policies, and education policies, using text mining methods. Mediation models and GARCH models are then established to examine the impact of these sentiment indices on the real estate market. The E-GARCH model is established to examine the asymmetric effect of positive and negative sentiment on real estate market. The results show the following: (1) The real estate market in China is more affected by the policy sentiment on official media compared with the unofficial ones. (2) Policy sentiment affects the real estate price through the mediating variables of interest rate, real estate construction area, and real estate sales. (3) The impacts of sentiment with different themes on the volatility of the real estate market are heterogeneous. (4) The impacts of policy sentiment on official media are more pronounced in a tight government-policy environment than those in a loose one. (5) The effect of negative unofficial media policies sentiment on real estate price is bigger than the positive unofficial media policies sentiment.

Suggested Citation

  • Diandian Ma & Benfu Lv & Xuerong Li & Xiuting Li & Shuqin Liu, 2023. "Heterogeneous Impacts of Policy Sentiment with Different Themes on Real Estate Market: Evidence from China," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1690-:d:1037103
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    as
    1. Walter Dolde & Dogan Tirtiroglu, 2002. "Housing Price Volatility Changes and Their Effects," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 30(1), pages 41-66.
    2. Shleifer, Andrei & Summers, Lawrence H, 1990. "The Noise Trader Approach to Finance," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 19-33, Spring.
    3. Dennis R. Capozza & Patric H. Hendershott & Charlotte Mack, 2004. "An Anatomy of Price Dynamics in Illiquid Markets: Analysis and Evidence from Local Housing Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(1), pages 1-32, March.
    4. Levon Goukasian & Mehdi Majbouri, 2010. "The Reaction of Real Estate–Related Industries to the Monetary Policy Actions," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 38(2), pages 355-398, June.
    5. Xing Su & Zhu Qian, 2020. "State Intervention in Land Supply and Its Impact on Real Estate Investment in China: Evidence from Prefecture-Level Cities," Sustainability, MDPI, vol. 12(3), pages 1-15, January.
    6. Clive B. Walker, 2014. "Housing booms and media coverage," Applied Economics, Taylor & Francis Journals, vol. 46(32), pages 3954-3967, November.
    7. Aymen Belgacem & Anna Creti & Khaled Guesmi & Amine Lahiani, 2015. "Volatility spillovers and macroeconomic announcements: evidence from crude oil markets," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2974-2984, June.
    8. Norman Miller & Liang Peng, 2006. "Exploring Metropolitan Housing Price Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 33(1), pages 5-18, August.
    9. Gordon W. Crawford & Michael C. Fratantoni, 2003. "Assessing the Forecasting Performance of Regime‐Switching, ARIMA and GARCH Models of House Prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(2), pages 223-243, June.
    10. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    11. Yunchu Huang & Chang-Gyu Yang & Heon Baek & Sang-Gun Lee, 2016. "Erratum to: Revisiting media selection in the digital era: adoption and usage," Service Business, Springer;Pan-Pacific Business Association, vol. 10(1), pages 261-261, March.
    12. Esin Cakan & Nadia Doytch & Kamal P. Upadhyaya, 2015. "Does U.S. macroeconomic news make emerging financial markets riskier," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 15(1), pages 37-43, March.
    13. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2017. "Macro News and Commodity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 68-80, January.
    14. Walter Dolde & Dogan Tirtiroglu, 1997. "Temporal and Spatial Information Diffusion in Real Estate Price Changes and Variances," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 25(4), pages 539-565, December.
    15. Liu, Peipei & Xia, Xinping & Li, Antai, 2018. "Tweeting the financial market: Media effect in the era of Big Data," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 267-290.
    16. Verma, Rahul & Soydemir, Gökçe, 2009. "The impact of individual and institutional investor sentiment on the market price of risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 1129-1145, August.
    17. Arjun Chatrath & Hong Miao & Sanjay Ramchander, 2012. "Does the price of crude oil respond to macroeconomic news?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(6), pages 536-559, June.
    18. Bahloul, Walid & Bouri, Abdelfettah, 2016. "Profitability of return and sentiment-based investment strategies in US futures markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 254-270.
    19. repec:dau:papers:123456789/15049 is not listed on IDEAS
    20. Zhang, Xiaoyu & Pan, Fanghui, 2021. "Asymmetric effects of monetary policy and output shocks on the real estate market in China," Economic Modelling, Elsevier, vol. 103(C).
    21. Liu, Crocker H. & Nowak, Adam & Rosenthal, Stuart S., 2016. "Housing price bubbles, new supply, and within-city dynamics," Journal of Urban Economics, Elsevier, vol. 96(C), pages 55-72.
    22. Zhang, Chengsi, 2013. "Money, housing, and inflation in China," Journal of Policy Modeling, Elsevier, vol. 35(1), pages 75-87.
    23. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    24. Jun Cai & Yan‐Leung Cheung & Michael C. S. Wong, 2001. "What moves the gold market?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(3), pages 257-278, March.
    25. Irfan Ahmed & Claudio Socci & Ali Medabesh & Francesca Severini & Jacopo Zotti, 2021. "Economic impact of monetary policy: Focus on real estate sector in Italy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1256-1269, January.
    26. Scott W. Barnhart, 1989. "The Effects of Macroeconomic Announcements on Commodity Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 389-403.
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