Estimating the Level and Distribution of Global Wealth, 2000–2014
Bibliographic record
Abstract
This paper estimates the level and distribution of household wealth globally, as well as for regions and countries, for the period 2000–2014. The data used are mainly from household surveys and national accounts balance sheets, covering about two thirds of the world's population and over 95% of global household wealth. Lists of the most wealthy published in the media are used to adjust the upper tail. Wealth levels and distributions are imputed for countries without data. Estimated global household wealth stood at USD 251 trillion in 2014, having grown from USD 117 trillion in the year 2000. Wealth per adult in 2014 was USD 53,000. The estimated Gini coefficient of global wealth was 92.2% in 2014 and the share of the top 10% was 88.3%. Wealth inequality fell from 2000 to 2007, with the share of the top 10% falling from 89.4% to 86.5%, before rising steadily to 2014. From 2000 to 2008 the share of financial assets in gross wealth, an important driver of wealth inequality, fell from 55.2% to 50.2%, before climbing to 55.0% in 2014. Household debt rose from 13.6% of gross assets in 2000 to 16.0% in 2008, and has since fallen to 13.9%.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".