This research sheds light on the link between social norms and economic development. It explores the determinants of inheriting the mother’s surname in China and its implications for children’s health status and education outcomes. It establishes that children whose mothers are younger, more educated, and from regions with a lower sex ratio are more likely to be named after their mother. Moreover, these children have superior health and education outcomes, reflecting predominantly the impact of women’s higher bargaining power on children’s human capital accumulation.
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Again, such tendency should be stronger for a mother born in a family with a higher socioeconomic status.
Data is from the Annual Statistical Report of Social Service Development by the Ministry of Civil Affairs.
The Census dataset does not contain information about family members who do not live together, which is very frequent among adult children. Thus, the examination of the human capital outcomes of adult children would suffer from severe sample selection problem, and this is another major reason why we focus on children younger than 18. Nonetheless, we present results on adult children in the appendix (Table 11) and they are consistent with our main finings
The observation numbers before each of these steps are 327,329, 171,458, 76,620, 70,980, and 68,804.
Unfortunately, the dataset does not provide information to infer whether the mother has any sibling.
Data is from the National Bureau of Statistics.
Sex ratio for cohort 1975–1989 is calculated using data from the 2000 Population Census. Sex ratio for cohort 1990–1999 is calculated using data from the 2000 Population Census. Sex ratio for cohort 2000–2004 is calculated using data from the 2005 Inter-Census Population Survey.
Johnson and Scheuble (2002) study a US sample of 600 married women and find that women with unconventional marital surnames were more likely to include their birth surname in their child’s name. Their study also suggests that the relative frequency of father’s and mother’s surnames could be a potential impact factor for the children’s surname.
Our results are robust to the using of alternative models, including the logit model, the rare events logit model (King and Zeng 2001; “relogit” in STATA), and the penalized maximum likelihood logit model (Firth 1993; “firthlogit” in STATA). In fact, according to Allison (2012), our sample size is large enough and the rarity of un-healthy and not-enrolled-in-school cases should not pose a problem in estimation.
We also conduct additional weak identification tests and weak-instrument-robust inference test. For the whole sample, the Cragg-Donald Wald F statistic (equals 387.24) is larger than the critical value of Stock-Yogo weak ID test (which is 16.38).
Detailed information about the survey and data download is available at www.isss.pku.edu.cn/cfps/EN/.
Due to privacy protection reasons, we are not able to get information on the exact surname of each survey respondent and thus cannot conduct the IV estimation. All results using CFPS are obtained with OLS.
WAZ is defined as (a person’s weight minus the median weight of a reference population of the same age and gender)/standard deviation of weight of a reference population of the same age and gender. HAZ is defined as (a person’s height minus the median height of a reference population of the same age and gender)/standard deviation of height of a reference population of the same age and gender. The reference data is from the magazine of China Journal of Pediatrics (Issue 7, 2009) and provided by the Department of Growth and Development, Capital Institute of Pediatrics. Because the reference group of height for age and weight for age is only available for children aged between 0 and 15, we restrict the sample to children aged younger than 15 years.
The kid’s rank in class is constructed based on the survey question “What is your rank (%) in your class in the recent midterm or final exam?” The rank variable takes a value from 1 to 5, corresponding to the answer of “bottom 24%,” “bottom 25–49%,” “top 26–50%,” “top 11–25%,” and “top 10%.” The degree of excellence is a self-reported outcome and takes a value from 1 to 5, where 1 indicates the lowest and 5 indicates the highest.
Lower Yangzi Region includes the following cities: Shanghai, Suzhou, Wuxi, Changzhou, Nanjing, Jiaxing, Hangzhou, Huzhou, Shaoxing, and Ningbo.
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The authors would like to thank the anonymous referees for helpful comments and suggestions.
We thank financial support from the National Natural Science Foundation of China (No. 71673314) and the Humanities and Social Science Fund of Ministry of Education of China for Youth Scholars (No. 19YJC840064).
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Li, L., Wu, X. & Zhou, Y. Intra-household bargaining power, surname inheritance, and human capital accumulation. J Popul Econ 34, 35–61 (2021). https://doi.org/10.1007/s00148-020-00788-0
- Surname inheritance
- Intra-household bargaining
- Human capital