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Chinese Housing Market Sentiment Index: A Generative AI Approach and An Application to Monetary Policy Transmission
Author:
Kaiji Chen
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and
Yunhui Zhao
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Series:
IMF Working Papers
Volume/Issue:
Volume 2024: Issue 264
Language:
English
Publication Date:
23 Dec 2024
DOI:
https://doi.org/10.5089/9798400293160.001
ISBN:
9798400293160
ISSN:
1018-5941
Pages:
68
Keywords:
Chinese Housing Market Sentiment; Generative AI; Monetary Policy Transmission; Consumption; Crowding-Out; sentiment index; housing sentiment; C. predicting housing price; housing market sentiment; Housing prices; Housing; Mortgages
Legal-disclaimer:
IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
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We construct a daily Chinese Housing Market Sentiment Index by applying GPT-4o to Chinese news articles. Our method outperforms traditional models in several validation tests, including a test based on a suite of machine learning models. Applying this index to household-level data, we find that after monetary easing, an important group of 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, whereas for homebuyers in other age-education groups, such a pattern does not exist. This suggests that current monetary easing might be more effective in boosting non-housing consumption than in the past for China due to weaker crowding-out effects from pessimistic housing sentiment. The paper also highlights the need for complementary structural reforms to enhance monetary policy transmission in China, a lesson relevant for other similar countries. Methodologically, it offers a tool for monitoring housing sentiment and lays out some principles for applying generative AI models, adaptable to other studies globally.
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Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund