Abstract
Using Korean data, this study investigates whether son-favoring ideas or the preference for sons affect fertility decisions. Son-favoring fertility behavior in Korea is of interest because the sex ratio at birth has recovered to a natural level after having been very skewed. To isolate the effects of the preference for sons from the effects of the surrounding environment, we compare the fertility behavior of individuals living in the same region but who were born in different regions or years. Exploiting the male-female gap in educational achievement at the parents’ time and place of birth as exogenous variation in the 2000 Census Korea 2% sample, we find that the strength of son preference formed at an early age is associated with the strength of son-favoring fertility behavior as adults. Our results indicate that parents are more likely to have a third child if they happen to have only daughters as their first two children. More importantly, this tendency is stronger if parents were born in a spatiotemporal region with more skewed gender gap in educational investment. These findings are robust against various alternative specifications, including endogenous migration issues.
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Data availability
Data are available from Statistics Korea at https://mdis.kostat.go.kr/.
Notes
The reasons for this change remain controversial. Some have identified changes in preferences based on survey data, whereas others have emphasized the change in the economic environment. See the upcoming section on related literature.
As Bachrach (2014) noted, behavior and decisions are distinct from beliefs and values. Son-favoring behavior is visible and can be quantified, but the preference for sons is an underlying variable. It has also been argued that ideas and values underpin these environmental factors. Although it is important to understand how preferences and the environment interact and which has the dominant role in their evolution, this is beyond the scope of this article.
Despite an overall downward trend in the sex ratio at birth across the 1990s and 2000s, there was substantial heterogeneity across the metropolitan cities and provinces of Korea, especially between the southeastern and southwestern regions. See the Background section for more details.
Some have attempted to explain the regional variation. For example, Suh (1995) argued that the southeastern region has stronger Confucian traditions. This region had more Seowon (Confucian schools) during the Chosun dynasty, and it has more Buddhist temples than Catholic or Protestant churches. In addition, using county-level variation, Kim and Song (2007) reported that the number of Buddhist temples was positively correlated with sex ratios in 1994, but the number of Protestant churches was negatively correlated.
Some of these studies, as well as an earlier version of this article, have used the term culture to indicate son preference. The term, however, seems to have broader meaning beyond preference, including patterned behaviors or norms as well as values and ideas, and it can refer to different meanings depending on the context (Bachrach 2014; Pollack and Watkins 1993). Thus, we choose to use the term son preference with clear definition.
Although these studies measured son preference using questionnaire-based survey data on the desire for a son, questions about how desirable it is for respondents to have a son are not necessarily an adequate measure of preference because the answers may already reflect respondents’ consideration of environmental factors. Our work aims to measure the effect of son preference but does not seek to directly measure son preference itself.
This approach is consistent with that of Guiso et al. (2004), who used domestic migrants in Italy to study other issues.
In the literature, preferences and utility functions are often used interchangeably. In this research, we use a common utility function v and assume that the individual heterogeneity of preferences beyond x is summarized by the parameter δ.
For details about potential outcomes, see Angrist and Pischke (2009), for example.
Because the existence of a common preference is meaningful only when it affects behavior, “the existence of a son preference” and “the effect of a son preference on fertility decisions” are used interchangeably in our discussion.
Although nonzero δ1 implies positive β1, δ1 is likely to be nonnegative in practice. First, θ2 ≥ 0 as a son-favoring environment induces higher \( {gap}_i^{birth} \). Second, \( \mathit{\operatorname{cov}}\left({PREF}_i^{birth},{ENV}_i^{birth}\right) \) ≥ 0 as a son-favoring environment is likely to influence the male-female gap in educational achievement, which is positively correlated with son preference formed at an early age. These two lead to δ1 ≥ 0.
Studies using census data restrict the ages of parents and children for the same reason. See, for example, Angrist and Evans (1998).
In the context of Manski (1993), the effect of the current residential area arising from the shared preference and that from the economic environment correspond to the peer effect and the correlated effect, respectively.
In addition to the main findings, we also analyze (1) whether the effects of son preference formed at an early age differ by cohort, (2) whether there is a complementary effect of father’s preference and mother’s preference, and (3) whether higher education leads to son preference having a weaker effect on fertility decisions. We do not find any statistically significant results; see section B of the online appendix.
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Acknowledgments
The authors have benefited from helpful comments made by Eleanor Jawon Choi, Chirok Han, Sok Chul Hong, and seminar participants at the T.S. Kim Bidecennial Memorial Workshop, the International Conference on Population Aging in Three East Asian Countries, the annual meeting of the Population Association of America, the annual meeting of Korea’s Allied Economic Associations, Sungkyunkwan University, and Seoul Labor Economics Working Group.
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Kim, S., Lee, SH. Son Preference and Fertility Decisions: Evidence From Spatiotemporal Variation in Korea. Demography 57, 927–951 (2020). https://doi.org/10.1007/s13524-020-00875-7
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DOI: https://doi.org/10.1007/s13524-020-00875-7