The Important Role of Equivalence Scales: Household Size, Composition, and Poverty Dynamics in the Russian Federation
Bibliographic record
Abstract
Hardly any literature exists on the relationship between equivalence scales and poverty dynamics for transitional countries. This paper offers a new study on the impacts of equivalence scale adjustments on poverty dynamics in the Russian Federation, using equivalence scales constructed from subjective wealth and more than 20 waves of household panel survey data from the Russia Longitudinal Monitoring Survey. The analysis suggests that the equivalence scale elasticity is sensitive to household demographic composition. The adjustments for the equivalence of scales result in lower estimates of poverty lines. The study decomposes poverty into chronic and transient components and finds that chronic poverty is positively related to the adult scale parameter. However, chronic poverty is less sensitive to the child scale factor compared with the adult scale factor. Interestingly, the direction of income mobility might change depending on the specific scale parameters that are employed. The results are robust to different measures of chronic poverty, income expectations, reference groups, functional forms, and various other specifications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".