Gender & Inclusion
Gender Economic Visibility in Developing Economies
A Data Framework for Inclusive Economic Policy
Overview
Gender Economic Visibility Index (GEVI)
Short explanation
This framework measures the extent to which women are represented in economic and data systems across five dimensions: financial inclusion, labor participation, enterprise visibility, data representation, and policy inclusion.
The pilot application to Papua New Guinea shows that women participate actively in the economy while remaining weakly visible in formal systems, creating policy blind spots and missed fiscal opportunities.
Index Explorer
Papua New Guinea
Pilot country score based on proxy measures across five visibility dimensions.
Dimension Breakdown
Explore each visibility dimension.
Financial Visibility
Women are economically active but largely outside formal financial systems.
- • Low formal banking penetration among women
- • High reliance on informal savings groups
- • Limited access to credit
Policy Insights Panel
Dynamic interpretation for governments and development institutions.
Top 3 gaps
- • Data invisibility remains the core constraint, not participation.
- • Informal sector dominance weakens institutional recognition of women’s contribution.
- • Tax and financial systems undercapture economically active women.
Recommended interventions
- • Expand inclusive banking and fintech channels
- • Integrate women-focused financial visibility metrics into government reporting
- • Invest in integrated data infrastructure that supports gender tagging across systems.
Classification
Limited Visibility Economy
PNG shows high real participation but low statistical visibility, leading to underestimated GDP contribution, inefficient policy targeting, and missed tax base opportunities.
Executive Summary
The paper proposes a visibility-based framework for assessing how women appear, or fail to appear, inside formal data systems.
This research examines the consequences of partial visibility in economic data systems. Women are often active in labor, enterprise, and informal markets while remaining weakly represented in official datasets.
The paper argues that visibility is not just a statistical issue. It is a policy constraint that affects targeting, taxation, financial inclusion, and the design of public interventions.
Maitras.ai frames visibility as a measurable policy problem and lays groundwork for composite indices such as GEVI.