Rethinking evolutionary economic geography through a gender lens

Abstract Evolutionary Economic Geography (EEG) explores how industries cluster, networks evolve, and regions grow, yet often overlooks gender. This study introduces a gender-sensitive framework, extending Related and Unrelated Variety (RV and UV) measures through a three-stage entropy decomposition. Findings reveal that RV and UV respond differently as women’s employment share increases, showing increasing returns when women are underrepresented. Thus, promoting women’s participation in male-dominated industries can more effectively enhance labor market dynamics than concentrating them in already female-dominated sectors. This underscores the importance of not only encouraging women’s labor market participation but also considering the sectors in which they are employed.