Asset Prices and Armageddon: Do Evangelicals' 'End Times'Beliefs Aect U.S. House Prices?
Bibliographic record
Abstract
According to surveys, around a quarter of Americans expect the world to end as prophesied by the Bible during their own lifetime. This pa- per undertakes the …rst test of whether these 'end times' beliefs aect economic behavior, using a 10-year panel of house price data across 363 Metropolitan Statistical Areas (MSAs). It identi…es a causal eect by interacting a time-varying proxy for the perceived probability of the 'end times'occurring soon with a geographically-varying proxy for the propor- tion of believers in Biblical prophecy, both of which are exogenous with respect to changes in house prices, controlling for time and area …xed ef- fects. The paper uncovers a signi…cant positive eect that is robust across samples, speci…cations, and alternative data sources. One explanation for this positive eect is that believers in Biblical prophecy face a tension - between their belief that the end of the world is imminent and Biblical injunctions to behave responsibly in the meantime - that could be re- duced by holding illiquid or 'commitment'assets to lock in responsible behavior, generating a premium on such assets. Data on mortgage appli- cations support this interpretation. The paper therefore supports models -such as Laibson's (1997) 'golden eggs'model of hyperbolic discounting - that incorporate time inconsistent preferences and predict a commitment premium.
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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 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".