The dynamics of the gender wage gap in late career: a theoretical model

Abstract

I examine the gender wage gap in the late career stage, utilizing data from the Turkish Household Labor Force Survey spanning 2005 to 2023. By integrating elements of contract theory and narratives, the study offers a novel perspective on discrimination that challenges the traditional statistical discrimination theory. The two-period career concerns model incorporates rational Bayesian updating and narrative-driven extremist updating mechanisms to explore how different belief systems affect wages. The findings reveal that narrative-driven belief updating exacerbates wage variance for women and reinforces gender wage gaps. Empirical analysis supports the model’s predictions, showing significantly higher wage variance for women and a widening gender wage gap in the late career stage, particularly in the service sector. The research underscores the critical role of sector-specific characteristics in shaping wage outcomes and highlights the importance of addressing biases formed by social expectations in labor markets.