A New Decomposition Method for Multiregional Economic Equilibrium Models
Bibliographic record
Abstract
This paper discusses decomposition of a multiregional economic equilibrium model that is characterized by a cost minimizing, linear programming (LP) model of the supply side and a vector-valued function that gives demand prices as functions of the quantities demanded. Our motivation is to ease model development and maintenance by a solution method that links separately developed regional models only when a consistent multiregion solution is desired. A heuristic strategy is described to extend any existing (LP) decomposition principle to a procedure for decomposing an equilibrium model by region. This strategy is applied to extend Dantzig-Wolfe decomposition to the multiregional economic equilibrium model, and several theoretical results are derived for the resulting algorithm. The central result is a proof of asymptotic convergence, under usefully general conditions. The extended Dantzig-Wolfe procedure is illustrated with an existing, two-region model of Canadian energy supplies and demands.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".