Bibliographic record
Abstract
Building an understanding of the complex dynamics between housing, finance, policy and the wider economy is a critical step towards the development of a strategy that permits policy makers to leverage resources and enable the housing market to function better in the pursuit of economic, financial and social objectives. Powerful real, legislative and financial circuits suggest that an enabling strategy for housing can support societal progress and wellbeing. By summarizing the key findings in the existing theoretical and empirical literature, this study helps to explain the complex interrelations between housing, finance, policy and the wider economy by using a simple model; it also deals with housing-related policies and their effects, examines the rational for housing market regulation, investigates whether housing market corrections threaten financial and macroeconomic stability, and asks whether policies are efficacious at controlling housing market outcomes. The important takeaways from this study are: (i) policy setting should be evidence-based, which necessitates further efforts to address existing data deficiencies; (ii) finance trends are in flux and policy effects can be asymmetric, which necessitates regular and critical housing market reviews to identify misallocation, dislocation and reform needs; (iii) improvement in the functioning of the housing market requires a coordinating authority that takes steps to reconcile the various housing market stakeholders’ mutually incompatible interests and arrange for concerted policy and institutional reforms. The study closes with an outlook on future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".