FijiParticipation Is the Gap
Strong job quality for women who work. A sharp gap in who enters the labour force.
Fiji scores a GEVI of 56.2 (90% interval 51.6 to 60.2), in the Partial band. Fiji has the sharpest participation gap in the group: 38.5% of women are in the labour force against 76.5% of men, yet women who do work are as likely as men to hold wage jobs. All 13 inputs are measured (blind-spot ratio 0.00).
Source: the attached country paper. Animation reveals the reported measures; it does not show change over time.
Abstract
Fiji scores a GEVI of 56.2 (90% interval 51.6 to 60.2), in the Partial band. Fiji has the sharpest participation gap in the group: 38.5% of women are in the labour force against 76.5% of men, yet women who do work are as likely as men to hold wage jobs. All 13 inputs are measured (blind-spot ratio 0.00).
Job quality is Fiji's strongest dimension (D2 = 0.899) while participation is its weakest labour dimension (D1 = 0.572), so the problem is getting women into the labour force, not the quality of jobs once there; the weakest dimension overall is institutional visibility (D4 = 0.310). Youth unemployment is 19.7% for young women against 12.7% for young men, and 26.9% of young women are outside education, work and training. Raising I1 from 0.503 to 0.70, which means about 15 more women in every 100 taking part, would lift the index by 1.5 points to 57.7.
The paper prioritises target the participation gap with data, not assumption; refresh the enterprise survey; publish sex-disaggregated income tax filers.
Fiji's main use case is analytical: because job quality is high, the binding question is why participation is low, and the data to answer it (linked survey and PAYE records) already exists in principle.
Download the paper PDFHeadline result
Strong job quality for women who work. A sharp gap in who enters the labour force.
90% interval 51.6–60.2.
Rank 4 of 15 · Blind-spot ratio 0.00.
versus D2 at 0.899
Fiji's main use case is analytical: because job quality is high, the binding question is why participation is low, and the data to answer it (linked survey and PAYE records) already exists in principle.
How the index is built
Each dimension is the simple mean of its indicators. GEVI is the weighted geometric mean of the five dimension scores.
| Dimension | Score D | Weight w | D^w |
|---|---|---|---|
| D1 Labour participation | 0.572 | 0.25 | 0.8697 |
| D2 Job quality and seniority | 0.899 | 0.20 | 0.9790 |
| D3 Enterprise and legal rights | 0.647 | 0.20 | 0.9165 |
| D4 Institutional visibility | 0.310 | 0.15 | 0.8389 |
| D5 Statistical and political voice | 0.466 | 0.20 | 0.8584 |
= 56.2
Product of the five terms = 0.5619, so GEVI = 100 × 0.5619 = 56.2, rank 4 of 15. Dimension values and the index 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 (12 grade A at 0.02, 1 grade B at 0.06) and draws dimension weights from a Dirichlet distribution centred on the base weights. Median 55.8, 5th to 95th percentile 51.6 to 60.2; blind-spot ratio 0/13 = 0.00. Under 5,000 random weight sets alone, the rank has a median of 4 with a range of 3 to 4.
Input interpretation
I4 and I6 are capped at 1 because women's vulnerable employment is lower, and wage employment higher, than men's.
Where the gap is
Each dimension is raised to full parity while holding the others fixed.
| Dimension raised to 1.0 | GEVI | Gain |
|---|---|---|
| D1 | 64.6 | +8.4 |
| D2 | 57.4 | +1.2 |
| D3 | 61.3 | +5.1 |
| D4 | 67.0 | +10.8 |
| D5 | 65.5 | +9.3 |
Single-indicator scenarios
Each scenario lifts one indicator to the upper quartile of countries with data.
| Indicator lifted | From | To | GEVI | Gain |
|---|---|---|---|---|
| I1 Labour force participation | 0.503 | 0.911 | 59.3 | +3.1 |
| I2 Youth NEET | 0.569 | 0.907 | 58.8 | +2.6 |
| I12 Women MPs | 0.182 | 0.382 | 58.4 | +2.2 |
| I11 Women ministers | 0.210 | 0.373 | 58.2 | +2.0 |
Values and gains are reproduced as printed in the paper; rounding can cause differences between displayed gains and subtraction of displayed index values. These conditional scenarios are not forecasts or causal estimates.
Reading the result
Job quality is Fiji's strongest dimension (D2 = 0.899) while participation is its weakest labour dimension (D1 = 0.572), so the problem is getting women into the labour force, not the quality of jobs once there; the weakest dimension overall is institutional visibility (D4 = 0.310). Youth unemployment is 19.7% for young women against 12.7% for young men, and 26.9% of young women are outside education, work and training. Raising I1 from 0.503 to 0.70, which means about 15 more women in every 100 taking part, would lift the index by 1.5 points to 57.7.
The 2009 firm-ownership figure (I7) is old enough to be graded B and should be refreshed before it is quoted.
Priorities and practical use
The priorities connect the index to actions and named users.
Target the participation gap with data, not assumption. Link household survey records to the PAYE register to see where women exit formal work after childbirth, using survival models on the merged panel.
Refresh the enterprise survey. I7 rests on a 2009 observation; a new round would tighten the interval.
Publish sex-disaggregated income tax filers. Employer PAYE returns record who earns wages; adding a sex field and publishing the counts would turn the survey-based I6 into an administrative statistic and lift D4.
Who uses the data, and for what decision?
| Data product | Primary user | Decision it informs | Cadence |
|---|---|---|---|
| I1, I2 and I3: participation and youth outcomes by sex | Labour ministry, national statistics office | Where to target youth employment and re-entry programmes, given 26.9% of young women are outside education, work and training against 15.3% of young men | Each survey round |
| I4 and I6 from PAYE returns with a sex field | Revenue authority, Treasury | Whether tax thresholds and withholding rules discourage women's entry, tested against the I1 gap (0.503); who receives refunds | Annual |
| I7 firm ownership, refreshed | Trade ministry, statistics office | Replace a 2009 observation before any enterprise-support programme is targeted on it | Next enterprise survey |
| D4 gap (+10.8 points) and I10 supportive frameworks (41%) | Ministry for women, Treasury | A costed list of missing mechanisms and a gender budget statement | Budget cycle |
Fiji's main use case is analytical: because job quality is high, the binding question is why participation is low, and the data to answer it (linked survey and PAYE records) already exists in principle.
Series: GEVI Research Series