Real Option Valuation in a Gollier/Weitzman World: The Effect of Long-Run Discount Rate Uncertainty
Bibliographic record
Abstract
Large-scale investment projects face significant long-run uncertainty in interest rates. However, little is known about the effect of long-term discount rate uncertainty on capital investment real option values. This paper bridges the long-run discount rate uncertainty literature developed in climate change economics with the financial literature on interest rate models and real options. First, we derive an Ingersoll-Ross real option model under the assumption of a declining discount rate model (DDR) following Gollier and Weitzman, and show how optimal investment timing is affected. Second, we study the problem of an open oil field with an abandonment option. We find that, compared with DDR, standard models using constant or mean-reverting interest rates undervalue projects and their real options to wait or to abandon. Indeed, results under DDR are more consistent with recent evidence on corporate decision-making under incomplete preferences or ambiguity. The results have implictions for both energy investment under uncertainty and climate finance.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".