News sentiment and housing market dynamics: Evidence from wavelet analysis

IF 6.5 1区经济学 Q1 DEVELOPMENT STUDIES

Habitat International Pub Date : 2025-05-21 DOI:10.1016/j.habitatint.2025.103441

Jin Shao , Jingke Hong , Xianzhu Wang

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Abstract

This paper investigates the time-varying relationships between news sentiment and housing market dynamics in China. By using the natural language processing (NLP) model, the News Sentiment Index (NSI) is constructed through the textual content of over 54,000 news narratives from January 2011 to May 2024. Wavelet analysis is employed to explore the co-movement between NSI and the housing market from the frequency domain. The empirical results reveal that: 1) The movement of NSI is ahead of house prices but lags behind housing investment and demand for the short term, while driving both for the mid-term period. 2) News narratives are closely related to real estate stocks, with daily NSI exhibits a leading relationship with real estate stocks over the long run. 3) House prices in second-tier, third-tier, and western cities show greater sensitivity to NSI compared to other regions. 4) Negative sentiment index plays a leading role to house prices during the whole period, the asymmetric effects of sentiment are confirmed. These findings may serve as fresh evidence that could contribute to the discussion of the power of news narratives for the housing market.

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新闻情绪与房地产市场动态：来自小波分析的证据

本文研究了新闻情绪与中国房地产市场动态之间的时变关系。通过使用自然语言处理（NLP）模型，通过2011年1月至2024年5月的54,000多篇新闻叙事的文本内容构建新闻情感指数（NSI）。利用小波分析从频域探讨NSI与房地产市场之间的共同运动。实证结果表明：1)NSI的变动在短期内领先于房价，但滞后于住房投资和需求，而在中期对两者都有推动作用。2)新闻叙事与地产股密切相关，每日NSI与地产股长期表现出领先关系。3)与其他地区相比，二线、三线和西部城市的房价对NSI的敏感度更高。4)负面情绪指数在整个时期对房价起主导作用，情绪的不对称效应得到证实。这些发现可以作为新的证据，有助于讨论新闻叙事对房地产市场的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Habitat International Multiple-

CiteScore

10.50

自引率

10.30%

发文量

151

审稿时长

38 days

期刊介绍： Habitat International is dedicated to the study of urban and rural human settlements: their planning, design, production and management. Its main focus is on urbanisation in its broadest sense in the developing world. However, increasingly the interrelationships and linkages between cities and towns in the developing and developed worlds are becoming apparent and solutions to the problems that result are urgently required. The economic, social, technological and political systems of the world are intertwined and changes in one region almost always affect other regions.