Timor-LesteThe Next Threshold
Timor-Leste's lead comes from D1 (0.913) and D5 (0.729), the latter the highest of any economy.
Timor-Leste scores a GEVI of 63.7 (90% interval 59.1 to 68.2), the highest in the series and at the top of the Partial band. It combines near-parity youth outcomes, the highest legal-rights score (68.2%) and the highest share of women in parliament (35.4%), and every input is measured (blind-spot ratio 0.00). Even so, no PITAA member reaches the 65-point Emerging threshold.
Source: the attached country paper. Animation reveals reported measures; it does not show change over time.
Abstract
Timor-Leste scores a GEVI of 63.7 (90% interval 59.1 to 68.2), the highest in the series and at the top of the Partial band. It combines near-parity youth outcomes, the highest legal-rights score (68.2%) and the highest share of women in parliament (35.4%), and every input is measured (blind-spot ratio 0.00). Even so, no PITAA member reaches the 65-point Emerging threshold.
Timor-Leste's lead comes from D1 (0.913) and D5 (0.729), the latter the highest of any economy. Its shortfalls sit in the middle of the index: women hold 22.4% of senior and middle management, among the lowest measured in the series, and 26.9% of firms have a female owner, the lowest measured share. Raising women's management share to 40% (I5 to 0.80) would lift the index by 2.2 points to 65.9, crossing the Emerging threshold; the same gain follows from lifting the supportive-frameworks score from 32% to 50%.
Priorities include Convert political representation into institutions; Track women in management through administrative data; Protect the D1 lead.
Download the paper PDFHeadline result
Timor-Leste scores a GEVI of 63.7 (90% interval 59.1 to 68.2), the highest in the series and at the top of the Partial band. It combines near-parity youth outcomes, the highest legal-rights score (68.2%) and the highest share of women in parliament (35.4%), and every input is measured (blind-spot ratio 0.00). Even so, no PITAA member reaches the 65-point Emerging threshold.
90% interval 59.1–68.2.
Rank 1 of 15 · Blind-spot ratio 0.00.
versus D1 at 0.913
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 | 0.913 | 0.25 | 0.9776 |
| D2 Job quality and seniority | 0.638 | 0.20 | 0.9140 |
| D3 Enterprise and legal rights | 0.543 | 0.20 | 0.8851 |
| D4 Institutional visibility | 0.360 | 0.15 | 0.8579 |
| D5 Statistical and political voice | 0.729 | 0.20 | 0.9387 |
= 63.7
Product of the five terms = 0.6370, so GEVI = 100 × 0.6370 = 63.7, rank 1 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 (13 grade A at 0.02) and draws dimension weights from a Dirichlet distribution centred on the base weights. Median 63.6, 5th to 95th percentile 59.1 to 68.2; blind-spot ratio 0/13 = 0.00. Under 5,000 random weight sets alone, the rank has a median of 1 with a range of 1 to 2.
Where the gap is
Each scenario raises one dimension to full parity, holding the others fixed.
| Dimension raised to 1.0 | GEVI | Gain |
|---|---|---|
| D1 | 65.2 | +1.5 |
| D2 | 69.7 | +6.0 |
| D3 | 72.0 | +8.3 |
| D4 | 74.2 | +10.5 |
| D5 | 67.9 | +4.2 |
Single-indicator scenarios
Single-indicator scenarios, each lifting one indicator to the upper quartile of countries with data:
| Indicator lifted | From | To | GEVI | Gain |
|---|---|---|---|---|
| I7 Firm ownership | 0.538 | 0.986 | 66.9 | +3.2 |
| I5 Senior and middle management | 0.448 | 0.746 | 65.6 | +1.9 |
| I6 Wage and salaried employment | 0.689 | 0.984 | 65.5 | +1.8 |
| I4 Non-vulnerable employment | 0.777 | 0.989 | 65.1 | +1.4 |
Under weight changes alone Timor-Leste ranks first or second, but its interval (59.1 to 68.2) overlaps those of Samoa, FSM and Fiji, so its lead over them is not statistically firm.
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
Timor-Leste's lead comes from D1 (0.913) and D5 (0.729), the latter the highest of any economy. Its shortfalls sit in the middle of the index: women hold 22.4% of senior and middle management, among the lowest measured in the series, and 26.9% of firms have a female owner, the lowest measured share. Raising women's management share to 40% (I5 to 0.80) would lift the index by 2.2 points to 65.9, crossing the Emerging threshold; the same gain follows from lifting the supportive-frameworks score from 32% to 50%.
The result also shows how far a country can go on political voice and still trail on institutions: D4 is 0.360 because supportive frameworks are only 32% in place.
Priorities and practical use
The priorities connect the index to actions and named users.
Convert political representation into institutions. A costed programme to raise supportive frameworks (policies, services, budget lines and data) from 32% is worth as much as any single labour market change tested.
Track women in management through administrative data. The 22.4% management share and 26.9% firm-ownership share are survey values; company registry and PAYE data by sex would show the trend annually.
Protect the D1 lead. Near-parity youth NEET (0.997) is worth keeping under review with each new survey round.
Who uses the data, and for what decision?
| Data product | Primary user | Decision it informs | Cadence |
|---|---|---|---|
| I7 firm ownership (26.9%) by owner sex from the company register | Registry, revenue authority, small-business agency | Whether women-owned firms are under-registered or under-formed; the largest single-indicator gain available (+3.2) | Annual |
| I5 and I6: women in management (22.4%) and wage work (20.2% of women) from payroll data | Labour ministry, revenue authority | Where women are missing from formal senior roles, using administrative counts rather than survey estimates | Annual |
| I10 supportive frameworks (32%) and the D4 gap (+10.5) | Ministry of finance, women's ministry | Convert a strong legal and political position into funded institutions and budget lines | Budget cycle |
| I12 women in parliament (35.4%) as a benchmark | Other Pacific parliaments, UN Women | Evidence of what a quota-supported political outcome looks like | After each election |
Timor-Leste is the series' benchmark case: its policy question is not whether women take part, but why formal, senior and owner roles lag behind participation, and administrative data can answer that.
Series: GEVI Research Series · Paper 7 · DOI: 10.5281/zenodo.23206703