Complex Dynamics Induced by Nonlinear Pollution Absorption, Pollution Emission Rate and Effectiveness of Abatement Technology in an OLG Model
Bibliographic record
Abstract
In this work, nonlinear pollution absorption, emission rate, and effectiveness of abatement technology are incorporated into the classic overlapping generation model. Within this framework, we analyze the macroeconomic effects of pollution emission and abatement technology on the economy. Our findings reveal that different levels of pollution emission rates from per capita income and the effectiveness of abatement technology could induce complex dynamical behavior, including the occurrence of a stable equilibrium, cycles, and chaos. Our analysis shows that either the pollution emission rate per capita income should be controlled to be small enough or the effectiveness of abatement technology should be large enough to maintain a stable system yielding high level of per capita income. A high level of pollution emission rate per capita income and a low level of effectiveness of abatement technology can lead to a stable economy, but with a low level of per capita income. In the case that the pollution emission rate and the effectiveness of abatement technology vary in a certain range, the economy would become unstable, and cycles and chaos would emerge.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".