Estimation of an Efficient Production Frontier with Increasing Marginal Product: The Case of the Canadian Oil and Gas Industry
Why this work is in the frame
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Bibliographic record
Abstract
The convexity axiom in conventional DEA models requires non-increasing marginal product (Banker et al., 1984, BCC). Banker and Maindiratta (1986, BM) suggest a DEA model with log-transformed input and output values that allow for both increasing and decreasing marginal products. By using simulated data and the Canadian oil and gas industry data, we document that the BM model outperforms the BCC model in estimating the efficiency frontier when the production function exhibits increasing marginal product. The BM model also reduces biases in the second-stage analysis of efficiency, providing additional insights that are not available from using the BCC model. Our analysis suggests that relatively small O&G companies may forego efficiency gains by not scaling up their businesses and that using the BM model is desirable when the production function is believed to exhibit increasing marginal product.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it