Sinning in the Basement: What are the Rules? The Ten Commandments of Applied Econometrics
Bibliographic record
Abstract
Unpleasant realities of real‐world data force applied econometricians to violate the prescriptions of econometric theory as taught by our textbooks. Leamer (1978) vividly describes this behavior as wanton sinning in the basement, with sinners’ metamorphizing into high priests as they ascend to the third floor to teach econometric theory. But this sinning is not completely wanton — applied econometricians do (or should) follow some unwritten rules of behavior, in effect bounding the sinning and promoting a brand of honor among sinners. This paper exposits these rules, and culls from them an unauthorized list of the Ten Commandments of applied econometrics.
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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 | 0.030 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".