Endogenous Capital Utilization in CGE Models: A Mongolian Application with the PEP-1-1 Model
Bibliographic record
Abstract
This paper extends the PEP-1-1 model (a static computable general equilibrium, or CGE, model for small open economies) to incorporate variable capital utilization. It argues that CGE models with fixed sectoral capital may underestimate the impact of shocks in the short run by ignoring industries’ adjustment of their capital utilization rate (or intensity of use) in response to changes in their economic environment. The model is calibrated to a 2014 Mongolian social accounting matrix. An increase in the export price of coal is considered as a shock for demonstration purposes. Compared to the standard PEP-1-1 model the impact of the shock is larger in the expanded model. In addition, the results of the PEP-1-1 model are derived as a special case of the model involving capital utilization.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".