Bidding Behavior in the Housing Market under Different Market Regimes
Bibliographic record
Abstract
The aim of this paper is to investigate whether different market regimes affect bidding behavior in housing auctions. Taking advantage of special circumstances in the Norwegian housing market in 2015 and 2016, we conduct a survey involving 1803 respondents in three of Norway’s largest cities, Oslo, Stavanger and Trondheim. In the Norwegian housing market 90 percent of dwellings are sold after an English auction. Norway has a rather homogeneous market, with the same laws, traditions, interest rates and approximately the same tax rates applying across the country. However, in December 2016, the two-year nominal house price increase was 34.8 percent in Oslo and 14.8 percent in Trondheim, whereas prices fell 7.8 percent over the same period in Stavanger. We find that households in booming housing markets appear to believe that a more aggressive bidding strategy is advisable to obtain a dwelling at the lowest possible price, compared with households in bust markets. Evidence suggesting that bidders in booming markets are less likely to decide on a maximum price limit before an auction commences substantiates this finding. In addition, we find that bidders in booming markets have a weaker reliance on real estate agents.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".