A data-science study of how visible women's economic activity is: measurement model, uncertainty, sensitivity, scenarios and value of information - Palau

The Gender Economic Visibility Index (GEVI) asks whether women’s economic activity is present, measured and recognised in the systems that set policy, budgets and taxes. This paper applies the index to Palau as a data-science measurement problem: 13 inputs are converted to parity scores, aggregated into five dimensions by a weighted geometric mean, and run through a Monte Carlo model of 10,000 draws that varies indicator scores and dimension weights together.

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).

The strongest dimension is job quality and seniority (0.873) and the weakest is institutional visibility (0.190), which takes the largest Shapley share (38%) of the 48.4-point gap to full parity. Of the 13 inputs, 8 are grade A and 5 are grade C (imputed), and the imputed inputs act as placeholders that widen the interval. Across seven weighting schemes the rank runs from 4 to 10, and across ten alternative specifications from 5 to 12, with the score moving by up to 12.5 points. Raising data coverage to 9 of 12 rows is worth +6.9 points, and a greedy pathway of +0.10 steps on measured indicators reaches the 65-point Emerging threshold after 10 steps. Every number is reproducible from the accompanying Python scripts with a fixed random seed of 2026.