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Gender pay gap and Employment choice in Nigeria

Ekpeyong, Paul (2023): Gender pay gap and Employment choice in Nigeria.

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This study investigates the intricate interplay between gender pay gap and employment choices, specifically focusing on the distinctions between the private and public sectors. Employing a comprehensive dataset spanning various industries and professions, we employ an array of analytical methods to uncover the nuanced factors contributing to observed wage disparities between men and women, by employing Blinder decomposition analysis, this research reveals the presence of gender-based wage disparities in both private and public sectors. However, when accounting for selection bias inherent in employment choices, the dynamics of the gender wage gap shift, underlining the significance of considering the role of employment decisions. This study delves into the explained and unexplained components of the wage gap. Surprisingly, corrected results showcase women out earning their male counterparts in the private sector. This unexpected finding highlights the importance of analyzing employment choices for a comprehensive understanding of gender-based wage disparities. In addition to Blinder decomposition, we undertake an estimation of the conditional wage gap, shedding light on how the wage gap evolves over different percentiles of the wage distribution. This multifaceted approach provides deeper insights into the complexities of gender pay discrepancies. Moreover, the study employs multinomial Logit regression analysis to explore the influence of various factors on the employment choices between private and public sectors. By considering variables such as education, experience, and industry, we unveil the intricate determinants impacting individuals' decisions, contributing to the overall gender wage gap. The research's robustness is validated through the application of the Ramsey Reset test, confirming the integrity of the regression model. This study's contribution lies in its comprehensive analysis, combining Blinder decomposition, conditional wage gap estimation, and multinomial Logit regression to offer a holistic understanding of gender pay gap dynamics and employment choices. The findings have implications for policy formulation and future research aiming to create a more equitable labor market.

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