Chinese Housing Market Sentiment Index: A Generative AI Approach and An Application to Monetary Policy Transmission
IMF Working Papers, December 23, 2024
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- Chinese Housing Market Sentiment Index: A Generative AI Approach and An Application to Monetary Policy Transmission
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Bibliographic details
- Authors: Kaiji Chen, Yunhui Zhao
- Published: December 23, 2024
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798400293160.001
Methodology and Data
- Constructed a daily Chinese Housing Market Sentiment Index by applying GPT-4o to Chinese news articles.
- Validation: the GPT-4o-based method outperforms traditional models in several validation tests, including a test based on a suite of machine learning models.
- Application: index linked to household-level data to study responses to monetary easing.
- Publication metadata:
- Authors: Kaiji Chen, Yunhui Zhao
- Publication date: December 23, 2024
- Series: Working Paper No. 2024/264
- Issue: 264
- Volume: 2024
- Pages: 68
- DOI: https://doi.org/10.5089/9798400293160.001
- Stock No: WPIEA2024264
- ISBN: 9798400293160
- ISSN: 1018-5941
Key Findings
- Heterogeneous household responses after monetary easing:
- Homebuyers who have a college degree and are aged between 30 and 50 in cities with more optimistic housing sentiment have lower responses in non-housing consumption.
- For homebuyers in other age-education groups, such a pattern does not exist.
- Policy effectiveness implication:
- Current monetary easing might be more effective in boosting non-housing consumption than in the past for China because of weaker crowding-out effects from pessimistic housing sentiment.
Policy Recommendations and Implications
- Highlights the need for complementary structural reforms to enhance monetary policy transmission in China.
- Notes that this lesson is relevant for other similar countries seeking stronger monetary transmission mechanisms.
Methodological Contributions and Tools
- Offers a tool for monitoring housing sentiment using generative AI.
- Lays out principles for applying generative AI models that are adaptable to other studies globally.
Subject Areas and Keywords
- Subject: Consumption, Financial institutions, Housing, Housing prices, Mortgages, National accounts, Prices
- Keywords: C. predicting housing price, Chinese Housing Market Sentiment, Consumption, Crowding-Out, Generative AI, Housing, housing market sentiment, Housing prices, housing sentiment, Monetary Policy Transmission, Mortgages, sentiment index
Source: IMF Working Papers — "Chinese Housing Market Sentiment Index: A Generative AI Approach and An Application to Monetary Policy Transmission" by Kaiji Chen and Yunhui Zhao, December 23, 2024.
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