Essays on dynamics of the housing market : a thesis presented in fulfilment of the requirement for the degree of Doctor of Philosophy in Finance at Massey University, Albany, New Zealand
Notice bibliographique
Résumé
As the largest proportion of a household's wealth is invested in houses, a household's saving and consumption is highly likely to be affected by the movement of housing markets.Economists are also very interested in housing price movements, due to its significant impact on general economic wellbeing and business cycles.The US housing collapse is commonly referred to as the trigger of the global financial crisis (GFC), leading to stronger demand from both the public and policymakers for in-depth analysis of housing markets.This thesis provides three empirical studies that aim to explore the dynamics of housing markets.The first essay analyses the relationship between immigration and housing markets with a focus on the regional differences within a country.Among the three housing market indicators studied (prices, rents, and price-to-rent ratios), the impact of immigration is found to be most strongly associated with rents and most weakly associated with prices.A negative relationship is reported between immigration and price-to-rent ratios, implying that in an overvalued housing market, the extent of deviation from equilibrium would have been even greater without immigration.Increased global financial integration as a result of improvements in the specification of trade, innovations in finance, and advances in information technology has led to increased connectedness between financial markets.Against this backdrop, the second essay measures the equicorrelation and connectedness between housing and oil markets.The results provide robust evidence of the existence of strong connectedness between these markets.The results also indicate that the connectedness is time variant, reaching its peak during the financial crisis.Among the studied markets, the US housing market is found to be the dominant shock transmitter, spreading shocks to the other markets.During the GFC period, the oil market operated as an information transmission mediator, conveying shocks from the US housing market to other OECD housing markets, particularly in the net oil importing OECD countries.The third essay focuses on whether capital gain in housing markets smooths consumption.The results indicate that the appreciation of house prices is an effective channel of risk sharing.Furthermore, the analysis of the consumption response to long-run output shocks in three developed countries (Australia, Canada, and New Zealand) provides evidence that Canadian residents are the most sensitive to permanent domestic output shocks and that the consumption patterns of Australian residents remain unchanged.
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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 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».