Homebuilders Choice Behaviour analysis/Une Analyse Du Comportement Des Constructeurs Immobiliers Dans Leur Choix
Bibliographic record
Abstract
Abstract Research in housing supply is scarce. Even scarcer is the research on the location and housing-type choices of homebuilders. The academic literature is almost silent on the questions of what influences the location and housing type choices of homebuilders. Similarly, a small body of literature has addressed spatial autocorrelation in discrete choice models. The spatial homogeneity depicted by the typical cookie-cutter architecture of urban and suburban dwellings suggests the presence of spatial autocorrelation. However, empirical studies of the determinants of homebuilders' product type choices have completely ignored the presence of spatial correlation. This paper presents the derivation and development of a random parameter discrete choice model that accounts for spatial correlation in choice behaviour. A mixed spatial multinomial logit model is formulated that incorporates spatial dependencies to predict housing-type choices of new homebuilders. The results of the model suggest that housing-type choice of a homebuilder is influenced by other projects in adjacent zones, resulting in a spatially correlated choice behaviour. Heterogeneity effects were also found to be important in this model. The mixed spatial multinomial logit model offers a substantial improvement, in terms of model fit, over the multinomial logit and standard spatial logit models. Resume Il existe tres peu de recherche au sujet de l'offre immobiliere et encore moins sur le choix de la localisation et type de logements que les entrepreneurs construisent. De la meme facon, il n'y a que peu de recherche qui se penche sur la question de l'autocorrelation spatiale dans l'analyse des choix discrets. Par contre, l'homogeneite spatiale des banlieues suggere l'existence d'une autocorrelation spatiale. Les etudes empiriques des choix et comportements des entrepreneurs ignorent completement l'autocorrelation spatiale. L'article presente les choix de types de logements que les entrepreneurs construisent en tenant compte des parametres de dependance spatiale et d'heterogeneite en matiere de gouts. Cet article demontre et developpe un modele de choix discret avec des parametres aleatoires qui incorpore l'autocorrelation spatiale. Ces dernieres annees, un nombre limite de recherches a essaye d'analyser les dependances spatiales et temporales des decision-makers et les alternatives. Alors que les dependances temporales sont souvent considerees dans les modeles dynamiques, peu de recherche incorpore les dependances spatiales dans les variables dependantes qualitatives et les modeles de choix discret. L'idee de base presentee dans cet article est que les entrepreneurs qui construisent, influencent le choix de types de logement des autres entrepreneurs qui peuvent choisir de construire de nouveaux logements dans un espace proche, resultant en un choix lie au comportement dans l'espace. Les donnees sur les constructions de nouveaux types de logement et ses determinants ont ete compilees a partir de diverses sources. La base de donnees de construction de logement consiste en des nouveaux developpements de logements en incorporant le type, la localisation et le prix de nouveaux logements construits entre janvier 1997 et avril 2001 dans la grande region metropolitaine de Toronto (Greater Toronto Area, GTA). La base de donnees integre tous les nouveaux types de developpement de logements ayant un minimum de dix nouvelles unites de logement. L'echantillon final utilise dans cette etude consiste en 1384 nouveaux projets de developpement pour lesquels toutes les variables requises etaient disponibles. Chaque projet represente la decision des entrepreneurs de construire un type particulier d'unite de logement, incluant single detached houses, semi-detached (SD) houses, projets d'appartements, et autres developpements de type low riset (townhouses, row houses). Les 1384 projets de logement incluent la construction de 113000 nouvelles unites de logement. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".