Topological structures in women’s digital and financial empowerment: A TDA

Many women in Malawi continue to face limited access to finance, digital tools, and formal labour mar-

kets, despite policy efforts and donor support. Conventional gender metrics and monitoring frameworks

frequently overlook the intricate, multidimensional, and non-linear dynamics of women’s empowerment,

resulting in a fragmented understanding of both progress and enduring inequalities. Motivated by this

gap, we apply topological data analysis (TDA) to gender-disaggregated national data from 2011 to 2024,

including indicators such as account ownership, Internet use, primary education, salaried wage employ-

ment, and political representation. Through the application of the Mapper algorithm, we uncover different

groups of empowerment, recurring structural patterns, and isolated regions within the data that illumi-

nate shifts over time, embedded inequities, and areas of stagnation in Malawi’s empowerment path.

Our analysis reveals that improvements in education or digital connectivity are not reliably associated

with enhanced financial autonomy or integration into the labor market, underscoring the asynchronous

and nonlinear progression of empowerment. Furthermore, statistical tests confirm that key indicators

such as primary education, parliamentary representation, account ownership, and female unemploy-

ment differ significantly across the identified regimes, providing quantitative support for the topological

patterns. We contend that structurally grounded topology-based approaches offer a valuable comple-

ment to traditional aggregate indicators, allowing policymakers to formulate more nuanced and targeted

strategies that simultaneously leverage emerging opportunities and confront persistent systemic barriers

to women’s empowerment.