2006
DOI: 10.1007/s11113-006-0001-7
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Marriage form and fertility in rural China: an investigation in three counties

Abstract: Using data from two surveys in three counties where the prevalence of uxorilocal marriage differs greatly, this paper analyzes impact of marriage form, individual, family, and social factors on fertility and its regional differences. The results show that, under the Chinese patrilineal joint family system, uxorilocal marriage does not universally increase fertility, which is likely to be determined by other factors. It is further found that fertility differs greatly in the three regions, and is significantly l… Show more

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Cited by 9 publications
(5 citation statements)
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“…2-5). These are caused mainly by the fertility of each county: Since the 1980s, the fertility in Lueyang is very close to that in Sanyuan, while that in Songzi is the lowest of the three counties (Jin, Li, and Feldman 2006). In Lueyang, the underdeveloped economy and harsh living environment increase the demand for male labor to improve household economy.…”
Section: Marriage Form Regional Differences and Sex Ratios At Birthmentioning
confidence: 99%
“…2-5). These are caused mainly by the fertility of each county: Since the 1980s, the fertility in Lueyang is very close to that in Sanyuan, while that in Songzi is the lowest of the three counties (Jin, Li, and Feldman 2006). In Lueyang, the underdeveloped economy and harsh living environment increase the demand for male labor to improve household economy.…”
Section: Marriage Form Regional Differences and Sex Ratios At Birthmentioning
confidence: 99%
“…Therefore, the ethical necessity of heterosexual monogamous marriage and procreation is also denied. He/she no longer regarded marriage and family as destiny, but integrated his/her love and desire, retrospectively recognized his/her sexual orientation, and threw himself/herself into the embrace of civil society [6].…”
Section: Historic Factormentioning
confidence: 99%
“…For example, Li [12] used the number of children ever born and the number of children expected as the dependent variable, and applied multiple regression to study the influence of women's employment level and employment type on women's individual reproductive behavior. Jin & Li [13] chose the number of children ever born as the dependent variable, and used OLS regression to analyze the impact of rural marriage on fertility levels. Chen & Wu [14] used the original data of 0.95% of the 2000 national census to use the two categorical variables of "whether they gave birth to children in the year before the census" as the dependent variable, and used logistic regression to investigate the impact of mobile migration on individual fertility rate of women.…”
Section: Literature Reviewmentioning
confidence: 99%