Per Capita Income, Consumption Patterns, and CO₂ Emissions
Bibliographic record
Abstract
This paper investigates the role of income-driven differences in consumption patterns in explaining and projecting energy demand and CO 2 emissions.We develop and estimate a general-equilibrium model with non-homothetic preferences across a large set of countries and sectors, and trace embodied energy consumption through intermediate use and trade linkages.Consumption of energy goods is less than proportional to income in rich countries, and more income-elastic in low-income countries.While income effects are weaker for embodied energy, we find a significant negative relationship between income elasticity and CO 2 intensity across all goods.These income-driven differences in consumption choices can partially explain the observed inverted-U relationship between income and emissions across countries, the so-called environmental Kuznet curve.Relative to standard models with homothetic preferences, simulations suggest that income growth leads to lower emissions in high-income countries and higher emissions in some low-income countries, with only modest reductions in world emissions on aggregate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".