Increased Income Inequality in OECD Countries and the Redistributive Impact of the Government Budget
Bibliographic record
Abstract
Abstract The recent rise in inequality in the distribution of disposable income in many, although not all, countries has led to a search for explanations, particularly since for much of the postwar period falling income inequality has been the norm. In the OECD countries, on which this chapter concentrates, the cause has been identified as rising wage dispersion, coupled with persistent unemployment in Europe. However, a number of factors need to be brought into any explanation of the extent and timing of changes in income distribution, including movements in factor shares, changes in real interest rates, and the impact of the government budget. This chapter focusses on the last of these. It has five sections: Introduction; Redistributive Impact of the Government Budget in selected OECD countries—a review of the statistical evidence from five OECD countries where a time series of studies covering the 1980s and the 1990s is available (UK, Canada, West Germany, Finland, Sweden; The Government Budget in Principle and Policy Reaction to Demographic Shifts—a simple framework within which the distributional implications of different government policy responses to changes in economic conditions and the different elements influencing the choice of response are explored; Policy Changes in Redistributive Taxes and Transfers: Case Studies of Unemployment Benefit and Personal Taxation—in the five European countries already studied, and in the US; and Summary of Conclusions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".