The effect of foreclosure in a downward spiraling housing market
Bibliographic record
Abstract
With significant declines in home prices since 2007, many U.S. households have found the balance of their mortgage exceeding the value of their property. These underwater homes leave owners with the dilemma of continuing to pay on their note or relinquishing their property either through foreclosure or a short sale. A number of studies have looked at discounts on foreclosed property. Discounts range from a low of 4 to 6 percent in Springer (1996) to a high of 24 percent in Shilling, et al (1990). More recently, Claretie and Daneshvary (2011) examine three forms of distressed sales in Las Vegas and estimate that, in 2008, the average discount from an armís-length transaction was 5.6 percent for a short sale, 10.3 percent for a home in default and 13.5 percent for an REO. Whereas Claretie and Daneshvary use multiple listing service (MLS) data, our study analyzes tax records from the Las Vegas metropolitan area over the period 2007 through the second quarter of 2011. By using tax record data and extending the period of analysis, we are able to investigate housing prices in a downward spiraling market. While the county utilizes a multi-category coding system to identify various types of property sales, three primary transactions are of interest in this analysis: a) an ìRî transaction, where the price reflects an arms-length sale between a willing buyer and seller, b) a ìTî designation refers to a price bid on the property at foreclosure during a trustee sale and c) , an ìFî transaction denotes the selling price of a property after foreclosure. For a given property, historical sequencing of transaction type designations allows us to infer the circumstances of the most recent sale. As home prices continue to fall and more homeowners find themselves underwater, distressed sales will make up a larger proportion of sales. Nevertheless, many of these transactions in the form of either a short sale or a home in default may be recorded by the county as an armís-length (R) transaction thereby changing its meaning over time. This has important implications for house price indexes and tax assessments as both utilize armís-length transaction prices. Given that armís length transactions could include distressed sales, the analysis will apply a form of propensity score matching to adjust the circumstances of the final sale. In this manner, it will be possible to measure the ìpure effectî of foreclosure and how this changes over time.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".