Using option value games with an embedded risk preference measure to study behavior of market participants faced with short and long term carbon offset choices
Bibliographic record
Abstract
This study uses economic experiments to examine agricultural producers' incentives to supply permanent and/or temporary credits to a carbon offset market.Their decision to partake in an investment project with an uncertain outcome and a flow of information about future conditions was mimicked through two types of games in the laboratory.The timing games consist of a three-period investment project in which subjects must decide if and when to invest, knowing that they can delay their decision until more information about the future outcomes is known.Their behavior was compared with the theoretical solution based on expected value calculations and an assumption of risk neutrality; further analysis then explores the possible causes of nonoptimal results.Next, bidding games tested the choice to delay the investment until the outcome was certain as both the expected value of the gamble and the variance between possible payoffs increase.Participants were also asked to state the minimum compensation they would be willing to accept to sell the gamble.The option value component was measured as the difference between the value of the game with an option to delay and the value of the game without the option to postpone investment.The last element of the experiment was a game to determine the risk preference of the subjects.The experimental results show non-optimal behavior in the timing and bidding games, although risk-aversion predictions fit the data quite well.Stated willingness-toaccept values observed in the bidding games were on average close to the predicted levels.Option values were found to be increasing as the risk level and expected value of the gambles increase, switching from a negative to a positive value.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".