Motherhood Penalties, Referral Networks, and Labor Market Outcomes

This thesis consists of three separate papers: The first paper, titled “How Does Fertility Relaxation Policy Affect the Motherhood Wage Penalty?”. This chapter examines the impact of China’s two-child policy on the motherhood wage penalty using CFPS and the DiD approach. The study reveals that, post-policy, one-child mothers face a 9% increase in wage penalty, as employers anticipate higher maternity costs. In contrast, two-child mothers experience an 8% reduction in wage penalty due to the policy legitimizing their status. Moreover, the study identifies statistical discrimination against one-child mothers and taste-based discrimination relief for two-child mothers as the main mechanisms. The second paper, titled “how do different types of referrals affect inequality?”. This paper examines the effect of referral on labor outcomes by distinguishing between the information transmission and screening mechanisms. Using the SCE dataset, we isolate these effects and find that referral significantly increase job-finding probability through the information transmission mechanism, while improve matching quality and starting wages only through the screening mechanism. To further examine the screening mechanism, we define two types of referrals engage the different roles, namely screening ability and reputational cost. For low-noise signal job seekers, employee referrals improve outcomes, while co-worker referrals benefit high-noise signal job seekers. The third paper, title “The Role of Networks Size and Quality in Labor Market Outcomes”. This paper addresses these gaps by examining both the direct and indirect effects of network size and quality on starting wages. We find that larger networks significantly raise starting wages, especially for low-ability job seekers through higher hiring probability. Additionally, while network quality alone does not increase wages, its interaction with referrals significantly boosts starting wages and wage growth, especially for high-ability job seekers in network-dependent occupations like sales.