Home equity, fiscal policy and the demand for housing
Notice bibliographique
Résumé
There is strong evidence of a seasonal pattern in Dutch house prices; prices tend to increase stronger in the second quarter of the year. This is reported both in popular reports from banks (e.g. Rabobank, the largest mortgage supplier of the Netherlands) and in academia (e.g. De Wit & Van der Klaauw, 2010). One of the potential explanations for this pattern is that households are timing their purchase of a new house before the summer holiday, such that they can move in (and do some DIY) during the summer holiday. By planning the move in a holiday the transition from one house to the next should be as smooth as possible: plenty of time to pack and move, do refurbishing et cetera. More specifically, by moving in the summer holiday kids are able to enter gently into their new schools. This argument leans on a large body of scientific research that proves that certain predictable changes in lifeís course trigger residential mobility (e.g. Clark & Huang, 2003). Alternative explanations have been suggested as well, such as Ngai et. al. (2009) market matching explanation. In this study we seek if we can explain the commonly reported Q2-peak in transaction prices of residential housing according to the life course hypothesis. We specifically focus on the potential influence of the summer holiday on the housing market. Especially to households with children it is beneficial to purchase a new house before the start of the summer holiday: households without children are less stringently tied to the summer holiday. Moreover, households without children are less stringently tied to house types (or at least to size). These two results of the life course hypothesis therefore leads us to expect that housing that is not suited for households with children (i.e. small multi-family dwellings) displays less seasonality. We use the database of the Dutch Association of Real Estate Agents and Real Estate Experts (henceforth: NVM) for our study. This database contains roughly 70% of all residential housing transactions in the Netherlands from 1985 onwards. The information we have on transactions includes dates (on and off the market), price and numerous characteristics. In the Netherlands schools are free to set most holidays. The summer holiday is the only holiday prescribed by the government. In setting the dates of the summer holiday the government distinguishes three regional areas for spreading holiday peaks (thus seeking to avoid congestion on roads and lengthening the holiday season for e.g. the catering industry). The summer holiday starts and ends at different dates for each area with a time gap of 3 weeks between the early and the late area. Our initial analysis focuses on the general holiday season and national patterns of seasonality using the common hedonic and seasonality dummy approach. We will then try to further exploit our extensive database and venture into a natural experiment where we try to find small shifts in seasonal patterns given the above described holiday spreading policy.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».