Consumption smoothing in Russia<sup>1</sup>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Using a panel from the Russian Longitudinal Monitoring Survey (1994–2004), this paper investigates to what extent Russian households have been able to maintain their living standards while suffering income shocks. Consumption smoothing is modelled by means of an equilibrium correction mechanism, which disentangles short‐run dynamics and long‐run equilibrium adjustments. GMM estimation is used to control for individual household effects in the presence of dynamics. Additionally, we differentiate between food and non‐food consumption, positive and negative shocks, rural and urban areas, and several levels of poverty risk. We find that dynamics are important in the consumption equation, and that estimates are sensitive to imputation errors in home food production. No strong claims can be made regarding heterogeneity in smoothing behaviour.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it