PalauLeadership Needs Institutions
D4 (0.190) is the binding constraint.
Palau scores a GEVI of 51.6 (90% interval 44.2 to 58.0), 7th of 15 and in the Partial band. Palau combines some of the strongest political and management outcomes among the small island states (25.0% women in the lower house, 45.5% of senior and middle management) with the weakest supportive institutions in the series: only 13% of the mechanisms that implement equality laws are in place. Five of 13 inputs are imputed (blind-spot ratio 0.38).
Source: the attached country paper. Animation reveals reported measures; it does not show change over time.
Abstract
Palau scores a GEVI of 51.6 (90% interval 44.2 to 58.0), 7th of 15 and in the Partial band. Palau combines some of the strongest political and management outcomes among the small island states (25.0% women in the lower house, 45.5% of senior and middle management) with the weakest supportive institutions in the series: only 13% of the mechanisms that implement equality laws are in place. Five of 13 inputs are imputed (blind-spot ratio 0.38).
D4 (0.190) is the binding constraint. Raising the supportive-frameworks score from 13% to 50% would lift the index by 5.5 points to 57.1, more than any political or legal change tested; lifting the legal score from 0.438 to 0.60 adds only 1.0. Restoring data coverage to 9 of 12 rows would add 6.9 points, to 58.5.
Priorities include Build supportive institutions before legal reform; Publish labour indicators by sex; Track the two chambers separately.
Download the paper PDFHeadline result
Palau scores a GEVI of 51.6 (90% interval 44.2 to 58.0), 7th of 15 and in the Partial band. Palau combines some of the strongest political and management outcomes among the small island states (25.0% women in the lower house, 45.5% of senior and middle management) with the weakest supportive institutions in the series: only 13% of the mechanisms that implement equality laws are in place. Five of 13 inputs are imputed (blind-spot ratio 0.38).
90% interval 44.2–58.0.
Rank 7 of 15 · Blind-spot ratio 0.38.
versus D2 at 0.873
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 | 0.846 | 0.25 | 0.9590 |
| D2 Job quality and seniority | 0.873 | 0.20 | 0.9731 |
| D3 Enterprise and legal rights | 0.538 | 0.20 | 0.8834 |
| D4 Institutional visibility | 0.190 | 0.15 | 0.7795 |
| D5 Statistical and political voice | 0.333 | 0.20 | 0.8027 |
= 51.6
Product of the five terms = 0.5159, so GEVI = 100 × 0.5159 = 51.6, rank 7 of 15. Values are rounded as reported in the source.
Uncertainty and rank sensitivity
The 10,000-draw simulation samples each score with the standard deviation of its grade (8 grade A at 0.02, 5 grade C at 0.12) and draws dimension weights from a Dirichlet distribution centred on the base weights. Median 50.9, 5th to 95th percentile 44.2 to 58.0; blind-spot ratio 5/13 = 0.38. Under 5,000 random weight sets alone, the rank has a median of 6 with a range of 5 to 8.
Source and indicator caveats
I2 is capped at 1 because young women are less often outside education, work and training than young men. I12 uses the lower house; the Senate share is 13.3%.
Where the gap is
Each scenario raises one dimension to full parity, holding the others fixed.
| Dimension raised to 1.0 | GEVI | Gain |
|---|---|---|
| D1 | 53.8 | +2.2 |
| D2 | 53.0 | +1.4 |
| D3 | 58.4 | +6.8 |
| D4 | 66.2 | +14.6 |
| D5 | 64.3 | +12.7 |
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 | 0.167 | 0.750 | 58.5 | +6.9 |
| I10 WBL supportive frameworks | 0.130 | 0.315 | 54.7 | +3.2 |
| I11 Women ministers | 0.250 | 0.373 | 53.8 | +2.2 |
| I8 WBL legal frameworks | 0.438 | 0.551 | 52.3 | +0.7 |
The upper-quartile target for I10 (0.315) is lower than the 50% used in the reading below, so the two scenarios give different gains (+3.2 and +5.5); both are shown because they answer different questions.
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
D4 (0.190) is the binding constraint. Raising the supportive-frameworks score from 13% to 50% would lift the index by 5.5 points to 57.1, more than any political or legal change tested; lifting the legal score from 0.438 to 0.60 adds only 1.0. Restoring data coverage to 9 of 12 rows would add 6.9 points, to 58.5.
The pattern is a small high-income economy where women are visible in leadership but the institutional scaffolding (policies, services, budget lines, data) is thin. Because the labour dimension is partly imputed, D1 and D2 should be read with the caveat that they reflect regional medians as well as Palau's own outcomes.
Priorities and practical use
The priorities connect the index to actions and named users.
Build supportive institutions before legal reform. A costed inventory of missing mechanisms (equal-opportunity body, data unit, budget tagging) is worth more index points than the next statutory amendment.
Publish labour indicators by sex. As a high-income economy with a formal labour market, Palau is the most likely of the imputed group to move to measured values quickly.
Track the two chambers separately. The 25.0% and 13.3% figures differ enough that both should be reported.
Who uses the data, and for what decision?
| Data product | Primary user | Decision it informs | Cadence |
|---|---|---|---|
| I10 supportive frameworks (13%, the lowest measured) | Ministry responsible for women, finance ministry | A costed inventory of missing mechanisms: an equal-opportunity body, a data unit, budget tagging | Budget cycle |
| I1, I3, I4, I6 and I7 by sex from the formal labour market | Statistics office, revenue authority | Replace five imputed inputs; Palau's formal economy makes administrative payroll counts feasible | Annual |
| I12 women in the two chambers (25.0% and 13.3%) | Congress, women's organisations | Report both chambers; the gap is a candidate-pipeline question | After each election |
| I11 women ministers (12.5%) | Cabinet office | Annual appointments series | Annual |
Palau is a clear example of index-guided sequencing: build the institutions (D4) first, because that is where the gain is largest (+14.7), then add the missing labour data.
Series: GEVI Research Series · Paper 12 · DOI: 10.5281/zenodo.23209257