CAN HYSTERESIS AND REAL OPTIONS EXPLAIN THE FARMLAND VALUATION PUZZLE?
Bibliographic record
Abstract
This paper proposes that the common finding that land prices are systematically higher than their fundamental value as measured by the present value of future cash might be due to real options arising from uncertainty in cash flows. The paper posits a model in which the seller has a real option to postpone the sale of land. Because the value of land is measured as a present value, the buyer does not hold a similar option to postpone the purchase. It is argued that the seller's option offers a plausible explanation for the wedge between observed farmland prices and the present value model. The paper uses a Dixit and Pindyck (1996) real options framework. Using historical cash flow and land price information for Ontario, it is shown how real options can lead to a land price greater than that predicted by the present value model. The findings also suggest the existence of land price bubbles and shows how a real options framework can be used to detect bubbles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".