NauruUpdate the Youth Picture
The new measured inputs move the score in two directions.
Nauru's provisional GEVI is 48.1 (90% interval 40.4 to 53.9), 12th of 15 and in the Hidden band. This paper replaces an earlier version scoring 42.3, which had only one measured input; it now uses labour, youth and management data from Nauru's 2019 Mini-Census and related surveys as compiled by UN Women, so 6 of 13 inputs are measured and 7 are imputed (blind-spot ratio 0.54). Because more than half of the inputs are still imputed, the score remains provisional.
Source: the attached country paper. Animation reveals reported measures; it does not show change over time.
Abstract
Nauru's provisional GEVI is 48.1 (90% interval 40.4 to 53.9), 12th of 15 and in the Hidden band. This paper replaces an earlier version scoring 42.3, which had only one measured input; it now uses labour, youth and management data from Nauru's 2019 Mini-Census and related surveys as compiled by UN Women, so 6 of 13 inputs are measured and 7 are imputed (blind-spot ratio 0.54). Because more than half of the inputs are still imputed, the score remains provisional.
The new measured inputs move the score in two directions. Labour participation is now a real weakness: women's participation is 52% against 75% for men, and D1 falls from 0.809 (imputed) to 0.644, among the lowest labour scores in the series alongside Fiji, Samoa and Tonga. D5 rises from 0.105 to 0.272 because data coverage is no longer zero. The largest remaining gain is still in D5 (+14.3) and D4 (+10.8), both of which rest on imputed or single measured inputs.
Priorities include Publish an update of the 2013 youth labour data from the next census or survey, and report NEET on the same definition each time; Use public payroll by sex as an administrative measure of formal employment; it would replace two imputed inputs (I4 and I6) at almost no cost; Record women in ministerial posts annually so I11 is measured; Publish sex-disaggregated account counts from the banking agency, since no financial-access indicator by sex currently exists.
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Nauru's provisional GEVI is 48.1 (90% interval 40.4 to 53.9), 12th of 15 and in the Hidden band. This paper replaces an earlier version scoring 42.3, which had only one measured input; it now uses labour, youth and management data from Nauru's 2019 Mini-Census and related surveys as compiled by UN Women, so 6 of 13 inputs are measured and 7 are imputed (blind-spot ratio 0.54). Because more than half of the inputs are still imputed, the score remains provisional.
90% interval 40.4–53.9.
Rank 12 of 15 · Blind-spot ratio 0.54.
versus D2 at 0.789
How the index is built
Dimensions are simple means of their indicators. The index uses a weighted geometric mean. Imputed inputs use the series medians; these are placeholders, not observed country outcomes.
| Dimension | Score D | Weight w | D^w |
|---|---|---|---|
| D1 Labour participation | 0.644 | 0.25 | 0.8959 |
| D2 Job quality and seniority | 0.789 | 0.20 | 0.9538 |
| D3 Enterprise and legal rights | 0.569 | 0.20 | 0.8932 |
| D4 Institutional visibility | 0.260 | 0.15 | 0.8170 |
| D5 Statistical and political voice | 0.272 | 0.20 | 0.7706 |
= 48.1
Product of the five terms = 0.4805, so GEVI = 100 × 0.4805 = 48.1, rank 12 of 15. Values are rounded as reported in the source.
Uncertainty and rank sensitivity
The simulation samples each score with the standard deviation of its grade (4 grade A at 0.02, 2 grade B at 0.06, 7 grade C at 0.12) and draws dimension weights from a Dirichlet distribution centred on the base weights. Median 47.6, 5th to 95th percentile 40.4 to 53.9; blind-spot ratio 7/13 = 0.54. Under 5,000 random weight sets alone, the rank has a median of 11 with a range of 9 to 13.
Source and indicator caveats
Sources: the UN Women Gender Equality Brief for Nauru (I1, and I5 at 33% in 2021, both confirmed against the brief) and the IPU ranking (I12). The NEET and youth unemployment figures are taken from the Nauru paper supplied for review, which attributes them to the 2019 Mini-Census and the Pacific Community (2013); I did not open those sources separately. I5 is graded B because the brief measures a ten-organisation sample of chief-executive, finance and operating roles, not the standard senior and middle management definition. Informal-employment (57.6% of women's and 91.2% of men's non-agricultural jobs, 2013) and formal-employment (42% of the female and 69% of the male labour force, 2012-13) figures exist but do not match the definitions of I4 and I6, so they are not used.
A separate Nauru paper using a five-dimension, judgement-scored framework reports 43.0. The two indices differ in design and are not interchangeable.
Where the gap is
Each scenario raises one dimension to full parity, holding the others fixed.
| Dimension raised to 1.0 | GEVI | Gain |
|---|---|---|
| D1 | 53.6 | +5.6 |
| D2 | 50.4 | +2.3 |
| D3 | 53.8 | +5.7 |
| D4 | 58.8 | +10.8 |
| D5 | 62.4 | +14.3 |
Single-indicator scenarios
Single-indicator scenarios, each lifting one measured or coverage indicator to the upper quartile of countries with data (imputed indicators excluded):
| Indicator lifted | From | To | GEVI | Gain |
|---|---|---|---|---|
| I13 Data availability | 0.333 | 0.750 | 53.8 | +5.8 |
| I12 Women MPs | 0.210 | 0.382 | 50.8 | +2.7 |
| I3 Youth unemployment | 0.557 | 0.802 | 49.5 | +1.5 |
| I2 Youth NEET | 0.682 | 0.907 | 49.4 | +1.3 |
Scenario values and gains are reproduced as printed; rounding can affect the subtraction of displayed values. These are conditional model scenarios, not forecasts or causal estimates.
Reading the result
The new measured inputs move the score in two directions. Labour participation is now a real weakness: women's participation is 52% against 75% for men, and D1 falls from 0.809 (imputed) to 0.644, among the lowest labour scores in the series alongside Fiji, Samoa and Tonga. D5 rises from 0.105 to 0.272 because data coverage is no longer zero. The largest remaining gain is still in D5 (+14.3) and D4 (+10.8), both of which rest on imputed or single measured inputs.
The youth figures are stark but old: 37.5% of young women were unemployed against 20.9% of young men in 2013, and 44% of young women were outside education, work and training against 30% of young men in 2019. The public sector matters for interpretation. As reported in the paper supplied for review, government provides about 34% of all jobs and 45% of women's jobs, and women hold 54% of government posts, so formal women's work in Nauru is largely visible in public payroll records.
Priorities and practical use
The priorities connect the index to actions and named users.
Publish an update of the 2013 youth labour data from the next census or survey, and report NEET on the same definition each time.
Use public payroll by sex as an administrative measure of formal employment; it would replace two imputed inputs (I4 and I6) at almost no cost.
Record women in ministerial posts annually so I11 is measured.
Publish sex-disaggregated account counts from the banking agency, since no financial-access indicator by sex currently exists.
Who uses the data, and for what decision?
| Data product | Primary user | Decision it informs | Cadence |
|---|---|---|---|
| Public payroll by sex and grade | Finance department, public service commission | Whether the 52% participation and 54% government share translate into equal pay and promotion; measured I4 and I6 | Annual |
| Youth labour and NEET series | Statistics office, education and labour ministries | Where the 2013 to 2019 youth gaps persist; lifting either youth indicator to the upper quartile is worth 1.3 to 1.5 points | Each census or survey |
| Account counts by sex from the banking agency | Finance department | A first financial-access indicator; today none exists | Annual |
| I13 coverage (4 of 12 rows) | Statistics office, Pacific Community | Which of the seven applicable missing rows (wage employment, vulnerable employment, firm ownership, account ownership, savings, unpaid care time, top managers) to collect first; the agricultural-employment row does not apply to Nauru | Survey plan |
Nauru remains provisional. Its use is to show that a small state's existing national data changes the picture materially, and to set a baseline against which the next update can be judged.
Series: GEVI Research Series · Paper 11 · DOI: 10.5281/zenodo.23209110