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

Round 1

Reviewer 1 Report

This is a very nicely written and executed paper that addresses an important topic and one that has particular relevance in the context of the Chinese market. The role of sentiment is important in the context of housing generally but this paper nicely makes the argument as to the specific issues relating to China. It is a nicely executed paper from a methodological viewpoint as well.

Author Response

Thanks for your comments.

Reviewer 2 Report

The paper investigates the heterogeneous impacts of the media sentiment about policies with different themes on the real estate in China. The paper is well structured and the reader can follow the rationale of the essay, also because of a very plain and easy English style and grammar. However, the manuscript can be further improved by considering the following suggestions. 

Line 58. It might be helpful for non-Chinese readers to have a brief definition of the Chinese city tier system.

Line 69. The words tight and loose sound vague. The reader needs to know the aspects considered to define a government-policy environment tight or loose.

Lines 91-93. Missing reference.

Line 135. Which policies have a positive impact? I guess the expansionary monetary policies, but it is not very clear. Perhaps you can write "these policies" to indicate the expansionary monetary policies you have just mentioned.

Line 136; 165. Slack is a vague adjective. It needs to be explained. More in general, it would be helpful to dedicate a paragraph to the definition of slack and tight policies. In addition, it is not clear what the government did in concrete terms to tighten real estate policy in 2016 (line 294).

Conlcusions should not introduce new information, instead it should clarify the intent and importance of the paper. For this reason, it is advisable to move tables 5, 6, 7 and 8 in a previous paragraph and to dedicate the conclusion section to restate the main ideas and arguments, pulling everything together to help clarify the thesis of the paper. 

When providing suggestions for future research, please specify you are referred to the Chinese context. If you are referred to the global context, please consider additional widespread social media, such as Facebook and Instragram.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

This study examines the heterogeneous impacts of media sentiment about policies with different themes on the real estate market in China. 99,272 policy announcements have been considered between January 2010 and December 2020. A standard GARCH model was utilised to assess the impact of these policies on real estate. Several key findings have been identified. This is an interesting study. I agree with the authors on the focus of housing price volatility and real estate sale volatility as this provides further insights than housing price itself. However, I have several comments.

The motivations of this study are not clear enough. How this study different from previous studies? The authors should articulate this more clearly. Lines 72 indicates that

“we provide a new perspective of sentimental analysis to policy evaluation which helps to get a better understanding of the underlying mechanism that how the policies would affect the market, by capturing the sentiment that indicates the potential response of the market to the policies.”

However, extensive studies have demonstrated the importance of sentiment, including Wang et al. (2022) in Buildings on the COVID-19 sentiment, Shen et al. (2022) in Journal of Real Estate Finance and Economics on local housing sentiment, as well as Li et al (2022) in International Journal of Strategic Property Management. These studies were from China.

Wang, S., Lee, C. L., & Song, Y. (2022). The COVID-19 Sentiment and Office Markets: Evidence from China. Buildings, 12(12), 2100. https://doi.org/10.3390/buildings12122100

Shen, S., Zhao, Y. & Pang, J. Local Housing Market Sentiments and Returns: Evidence from China. J Real Estate Finan Econ (2022). https://doi.org/10.1007/s11146-022-09933-w

Li, J., Wang, Y., & Liu, C. (2022). Spatial effect of market sentiment on housing price: evidence from social media data in China. International Journal of Strategic Property Management, 26(1), 72-85.

The literature review section should be improved as real estate/housing studies have been largely ignored. For instance, the key methodology is housing price volatility. However, the section does not review the importance of housing price volatility. The authors should be able to find vast numbers of papers on housing price volatility via google scholar. The following seminal papers have been revealed from the google scholar (housing price volatility papers that are widely cited more than 100 times).

Miller, N., & Peng, L. (2006). Exploring metropolitan housing price volatility. The Journal of Real Estate Finance and Economics, 33(1), 5-18.

Lee, C. L. (2009). Housing price volatility and its determinants. International Journal of Housing Markets and Analysis.

Dolde, W., & Tirtiroglu, D. (2002). Housing price volatility changes and their effects. Real Estate Economics, 30(1), 41-66.

Most recent papers are also available. For instance:

Ghosh, S. (2021). Housing price volatility: uncertainty, an asymmetric econometric analysis–some European country experiences. International Journal of Housing Markets and Analysis;

Yang, Y., Rehm, M., & Zhou, M. (2021). Housing Price Volatility: What's the Difference between Investment and Owner‐Occupancy? Economic Record, 97(319), 548-563).

Please have a more inclusive literature review.

Why we consider volatility (the second moment) instead of housing price level (the first comment)? The advantages of considering volatility should be considered and discussed. See the housing/real estate literature in this area. 

Asymmetric effect should be considered. Positive and negative sentiments would have different impacts on real estate prices. Can the authors consider using an E-GARCH to gauge the impacts of asymmetric effect? This would be an extension of a standard GARCH(1,1) model. Many studies have been devoted to the asymmetric effect on housing price volatility. These studies used an E-GARCH. Therefore, an E-GARCH is not a complex model. This can be easily done via software packages like Eviews and Stata. Some more complex GARCH-family models have been used in the housing literature (Component-GARCH, Spline-GARCH etc). Please see the related papers from Housing Studies and JEREF.

Volatility clustering effect. I am not sure whether the volatility clustering effect has been undertaken. This should be noted that no volatility modelling can be conducted if there is no volatility clustering effect. Please conduct the ARCH modelling to confirm this.

The role of COVID-19. The study period covered the shock of COVID-19. As such, I am wondering whether the COVID-19 shock would have an impact on the results. This is one of the significant health policies of the century. Major radical policies such as lockdowns were introduced in 2020. These should have some impact on real estate volatility. Can we conduct a robustness check on this? A dedicated study period to capture the impact of COVID-19.

The conclusion is too long. This can be condensed, yet the implications of the findings can be further highlighted.

I look forward a stronger revised version.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Thanks for the revision. The authors have addressed most of my previously raised comments satisfactorily. 

However, few minor comments:

1) Abstract- E-GARCH models were employed. Please revise this

2) Housing price volatility literature review. However, the importance of housing price volatility has not been discussed. Many studies discussed the policy importance of housing price volatility analysis (e.g. Stephens (2011) and Stephens and Williams (2012) in Joseph Rowntree Foundation Housing Market Taskforce; Lee and Reed (2014) in Housing Studies). Please discuss its policy importance, as this is highly relevant to this study. 

3) In addition, the volatility linkages of real estate assets (e.g. REITs, direct property, REIT futures) have also been widely discussed. This allows investors to make better-informed investment decisions. See Hoesli and Reka (2013) in the Journal of Real Estate Finance and Economics; Lee, Stevenson and Cho (2021) in the Journal of International Money and Finance. This practicality should be discussed. This also provides a solid foundation for examining real estate volatility. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf