Empirical Research on the Determinants of House Price Behaviour in China, From January Quarter 2000 to December Quarter 2008
Notice bibliographique
Résumé
Abstract \n \nThe house prices in China have increased dramatically after the housing finance market reform since 1998. The housing market boom has contributed to domestic consumption, investment and rapid economic growth. But at the same time, many Chinese people have experienced increasing difficulties to purchase a house as the run-up house prices become too expensive relative to household income, rents and it seems will never fall. This problem became more severe in metropolitan areas, such as Beijing, Shanghai, Hangzhou and Shenzhen. As the housing problem is not only highly related to family life, but also to the economic growth and financial stability, it turns out to be a concern nationwide. Some academics argue the high house price is contributed by the development of macroeconomic fundamentals, while others believe the house price growth is due to speculation. The People’s Bank of China (PBC), which is China’s central bank, has implemented policies, for example, rising personal housing mortgage rate and benchmark lending rate to control the growth of house prices, but has received limited effects (Shang, 2009). Those complex phenomena raise the question about what are the key determinants of house price growth in China. In order to find answers to this question, this paper is going to explore the relationship between housing price and a series of variables by four time series regression models using the Ordinary Least Square (OLS) technique based on empirical data from 1st quarter 2000 to 4th quarter 2008. The tested variables include GDP, CPI, land price, bank lending, real benchmark lending rate, real effective exchange rate, and Shanghai Composite Index. It is found that in general, China’s house price growth is highly associated with the improvements of its macro-economic fundamentals. In particular, GDP growth, CPI growth, land price growth, expansion in bank lending and rise in equity prices are positively correlated with the house price growth, while the real benchmark lending rate and the growth in RMB appreciation are negatively correlated with house price growth. Beside, the limited supply of cheap housing, a lack of competition in the land transfer market, and political incentives to local governments also contribute to the increase in house price. Therefore, it is suggested that the Chinese government should not only implement monetary instruments, but policy measures to stabilize house price growth and maintain sustainable development of the domestic housing market.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».