Optimal Population and Sustainable Growth Under Environmental Constraints
Bibliographic record
Abstract
This paper develops a dynamic optimal growth model integrating population, economic activity, and environmental constraints to investigate sustainable long-run development. The model incorporates capital accumulation, consumption, pollution abatement, and an endogenous demographic equation in which population growth responds negatively to pollution. A critical environmental threshold is imposed beyond which population growth collapses. Calibrating the model with plausible parameter values indicates that a sustainable steady state can support a global population of approximately 5 billion, a level consistent with high per capita consumption and stable environmental conditions. The optimal policy entails devoting roughly one-third of output to pollution abatement, which is sufficient to stabilize pollution below the safe threshold without imposing excessive economic cost. In this equilibrium, the economy achieves high consumption per person, a stable capital stock, and environmental balance, thereby avoiding overshoot and collapsing scenarios. The results highlight the trade-off between economies of scale and environmental limits. Larger populations can stimulate production and innovation but risk unsustainable pollution levels, whereas smaller populations allow higher per capita welfare within ecological boundaries. These findings suggest that achieving global sustainability requires balancing population size, consumption, and ecological limits through effective pollution abatement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".