Housing Price Volatility: What's the Difference between Investment and Owner‐Occupancy?*

Yang, Yang; Rehm, Michael; Zhou, Mingquan

doi:10.1111/1475-4932.12639

Cited by 6 publications

(3 citation statements)

References 41 publications

(40 reference statements)

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“…Concerning housing price volatility, substantial fluctuations, particularly during boomand-bust cycles, challenge conventional explanations based on standard macroeconomic fundamentals or models with fully rational expectations (Abildgren et al, 2018;Granziera and Kozicki, 2015;Piazzesi and Schneider, 2016). Instead, the widely accepted driver of housing price volatility is market sentiment, especially evident after property market crises (Lin Lee, 2009;Yang et al, 2021). During periods of high sentiment, higher expectations of future housing returns lead to an influx of home buyers into the property market (Dong et al, 2021), and a rapid increase in transaction volumes (Fischer and Stamos, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

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Persistent trends and inefficiencies in the Greek housing market: a sentiment based approach

Vasileiou,

Hadad,

Oikonomou

2024

JERER

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PurposeWe examine the aggregate price trend of the Greek housing market from a behavioral perspective.Design/methodology/approachWe construct a behavioral real estate sentiment index, based on relevant real estate search terms from Google Trends and websites, and examine its association with real estate price distributions and trends. By employing EGARCH(1,1) on the New Apartments Index data from the Bank of Greece, we capture real estate price volatility and asymmetric effects resulting from changes in the real estate search index. Enhancing robustness, macroeconomic variables are added to the mean equation. Additionally, a run test assesses the efficiency of the Greek housing market.FindingsThe results show a significant relationship between the Greek housing market and our real estate sentiment index; an increase (decrease) in search activity, indicating a growing interest in the real estate market, is strongly linked to potential increases (decreases) in real estate prices. These results remain robust across various estimation procedures and control variables. These findings underscore the influential role of real estate sentiment on the Greek housing market and highlight the importance of considering behavioral factors when analyzing and predicting trends in the housing market.Originality/valueTo investigate the behavioral effect on the Greek housing market, we construct our behavioral pattern indexes using Google search-based sentiment data from Google Trends. Additionally, we incorporate the Google Trend index as an explanatory variable in the EGARCH mean equation to evaluate the influence of online search behavior on the dynamics and prices of the Greek housing market.

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Section: Literature Reviewmentioning

confidence: 99%

“…, 2018; Granziera and Kozicki, 2015; Piazzesi and Schneider, 2016). Instead, the widely accepted driver of housing price volatility is market sentiment, especially evident after property market crises (Lin Lee, 2009; Yang et al. , 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Persistent trends and inefficiencies in the Greek housing market: a sentiment based approach

Vasileiou,

Hadad,

Oikonomou

2024

JERER

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“…The asymmetric analysis of housing price volatility in European country experiences are vetified [16]. The GARCH-M model are used to estimate the housing price volatility of these two groups of transactions: leveraged investment and leveraged owner occupancy [17].…”

Section: The Volatility In Real Estate Marketmentioning

confidence: 99%

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

et al. 2023

Sustainability

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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.

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The estimation of house bubbles during the time of pandemic: a study of Australia

Yang

Zhou

2022

Applied Economics

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Housing Price Volatility: What's the Difference between Investment and Owner‐Occupancy?*

Cited by 6 publications

References 41 publications

Persistent trends and inefficiencies in the Greek housing market: a sentiment based approach

Persistent trends and inefficiencies in the Greek housing market: a sentiment based approach

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

The estimation of house bubbles during the time of pandemic: a study of Australia

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