Stranded Fossil Fuel Reserves and Firm Value
Bibliographic record
Abstract
Do capital markets reflect the possibility that fossil fuel reserves may become "stranded assets" in the transition to a low carbon economy?We examine the relation between oil firms' value and their proved reserves.Using a sample of 600 North American oil firms for the period 1999 to 2018, we document that while reserves are an important component of oil firm value, the growth of these reserves has a negative effect on firm value.This negative effect on value is stronger for oil producers with higher extraction costs.When we decompose total reserves into developed and undeveloped reserves, we show that the negative effect of reserves growth on value is due to firms growing their undeveloped oil reserves.Unlike developed, undeveloped reserves require major capital expenditures and longer time before they can be extracted.We also document that the negative effect is stronger for undeveloped oil reserves located in countries with strict climate policies.Our evidence is consistent with markets penalizing future investment in undeveloped reserves growth due to climate policy risk.High level of institutional ownership, stock market liquidity and analyst coverage do not change the negative effect of undeveloped reserves growth on firm value.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".