New evidence on son preference among immigrant households in the United States

We begin the analysis within the following econometric framework:

where i denotes married women between the age of 18 and 40 with at least one child, AllGirls_i is a dummy variable indicating the gender of previous children as being all female, X_i are control variables, ε_i is the error term, β s are the coefficients, and, specifically, β₁ is the parameter of interest.

We consider two dependent variables of interest: Fertility_i, indicating whether family i had additional children within 6 years, and Male child_i, indicating whether the next child is a son.

We obtain similar results using five-year or seven-year window and present results for 6 years to be consistent with previous literature on son preference.

The parameter of interest is the coefficient on AllGirls_i, an indicator variable assigned 1 when the previous children are all girls in family i. The coefficient indicates the difference in Y_i between families with all girls and those with at least one son. Arguably, it should provide an upper bound of the effects of son preference on family size because some families may have additional children simply to balance the gender pool of their children—an effect which may not be due to son preference. To isolate bias for sons from gender balancing preferences, in third birth order children analysis, we additionally include another specification that also controls for Mix_i, which indicates that the gender of the two previous children contains both a boy and girl, in the following regression equation:

Once this additional indicator is included, the omitted category becomes families with only boys. Thus, the coefficients on AllGirls_i and Mix_i indicate the difference between families with all girls or families with children of both sexes in comparison to the fertility of those with only sons. The coefficient on AllGirls_i then isolates son preference effects from any other preferences relating to gender balancing effects.

The vector of control variables, X_i, are standard to the literatures on fertility and son preference in general and contain variables that relate to the mother, household variables, and geographic variable.

Haughton and Haughton (1998) demonstrate that these factors also affect families’ fertility and should be controlled for in regression analysis.

Table 2 reports the influence of son preference on fertility for the full sample of families with an oldest child 12 years of age or younger in the United States, as well as for the sample of families where the mother is either native-born, or a first-generation immigrant, a non-SESE Asian immigrant, or a SESE Asian immigrant.

The complete regression results with coefficients on all covariates are shown in Table A2 of Appendix.

First, looking at the full sample of the US population, the coefficient of interest in front of all girls for mothers in Column (1) is close to zero and insignificant, indicating no strong influence of initial child gender on the decision to have a second child. The estimates in Column (2) suggest that those with two daughters are 3.2% points more likely to have a third child, but as can be seen in Column (3), this impact is entirely driven by a motivation among households for gender balancing.

Among the sample of only native-born mothers, the coefficient on all girls is actually negative and significant in both Columns (1) and (3). This suggests that the probability of having a second child within the next 6 years is 0.4% points lower if the first child of the family is a daughter. For the decision to have a third child, once accounting for gender balancing effects this rise to 0.8% points in Column (3). In both cases, there is no evidence of son preference in the United States when focusing on fertility choices and looking at these aggregate populations.

However, when we limit the sample to first-generation immigrants, this pattern is reversed. Focusing on the results in Columns (1) and (3), we see that having only a girl or girls leads to a positive and significant increase in the odds of a mother having another child, even after controlling for gender-balancing preferences. Disaggregating by region, we see that the overall effects observed in the immigrant population are driven by migrants from South East Asia. Among this population, mothers are 2.3% points more likely to have a second child if their first was a girl. Comparatively, the coefficient on all girls for immigrants from other countries is negative and not significant. While there is again strong evidence of gender-balancing desires in immigrant populations, as well as among SESE Asian migrants, there is an even larger 3.1% point increase in the odds of having a third child if the first two are female.

Columns (4–6) replicate this strategy for another dependent variable, whether the next child is male.

Coefficients on covariates are shown in Table A2 of Appendix for the fertility regressions for interested readers but are otherwise excluded for brevity.

We conclude that there is little evidence for son preference among native-born mothers as well as most immigrant mothers through either fertility stopping decisions or from gender selection in the United States. At the same time, however, mothers who migrate from SESE Asian countries do exhibit behavior that is consistent with son preference. They are both more likely to have additional children if the previous children are all girls, and they appear to influence the gender of the third child if the first two are female.

It is also possible that son bias could manifest in other weaker forms of son preference than fertility timing and gender selection. Dahl and Moretti (2008) provide survey evidence that male parents prefer sons and demonstrate an effect that can be seen in parents’ marital status, with marriage between parents more commonly occurring both before (only for those who may have learned the gender before birth) and after male births.

In Table 3, we present regressions in which the dependent variable is an indicator equal to 1 if a mother with at least one child is divorced, separated, or never married. As before, this is regressed on the gender of the previous children with the complete set of covariates from equation 3 as well as controls for number of children and for families with one child or more. Again, the coefficient of interest is the indicator variable All Girls, which is equal to 1 if the previous children are all daughters. The estimated coefficients on all girls in this linear probability model indicate the change in the probability of not being married for mothers of girls in comparison to those with a son. Here, the coefficients are all positive, and for the full sample, natives, as well as first-generation immigrants and non-SESE Asian immigrants they are significant at between 1% and 5% levels of significance. Consistent with the previous analysis, mothers are either more likely to marry or less likely to separate after having sons. Even though the magnitudes seem small, the percentage effects are actually very large, at 9.5%, 11%, 6.4%, 5.9%, and 5.3%, respectively, and are thus quite non-negligible.

Of all mothers, 5.28% with at least one child are divorced, separated, or never married in the United States. This figure is 5.47% for native-born mothers, 4.69% for first-generation immigrants, 5.1% for non-SE Asian immigrants, and 3.77% for SE Asian immigrants.

An important caveat of this alternative approach to assessing son preference is that while consistent with Dahl and Moretti (2008), lacking more detailed records and panel data, we cannot rule out the alternative possibility that extraneous factors are driving the change in marriage patterns. For instance, sons could simply require more parental attention or resources to raise, and increased paternal childcare responsibilities may drive the lower levels of divorce in households with sons relative to those with daughters. Although this could still be classified as son preference, it is a much weaker version than that which shows up in the previous sections. We restrict the analysis to fertility timing and gender selection for the remainder of our paper, as our focus is on the development and persistence of son preference among immigrant populations, and there is less potential for these more stringent manifestations of son preference effects to be confounded by unobservables than the marital status results.

To better understand the sources of son preference among Southeast Asian immigrants, we decompose the sample into families who migrate from a specific country of origin as shown in Table 4. In order to achieve a larger sample, we now extend the analysis back to include Census and all ACS data since 1980. We also focus only on countries with large number of migrants to the United States so that we have sufficient samples to identify the effects should they exist. As discussed, we now run regressions on the sample of immigrant mothers who are from China, Japan, Korea, the Philippines, Vietnam, and India, respectively.

Several things immediately stand out. For families in which a mother is migrated from China and India, they are more likely to have a second child if the family had a girl first relative to having a boy first, unlike the opposite pattern among US natives. These effects dramatically strengthen when we turn to the third child. As can be seen in Column (3), they are indeed more likely to reflect son preference in this case, as they exist even when controlling for gender balancing. Chinese, Indian, Korean, Philippine, and Vietnamese migrant mothers all exhibit a noticeably higher propensity to have a third child when they have two daughters. These patterns are most clearly seen in Figure 1A, which plots the coefficients of interest and confidence intervals for each of the sets of regressions presented in Columns (1) and (3).

As can be seen on the right-hand side of Table 4, there is some evidence of gender selection among immigrant groups in the United States. Only Indian households demonstrate this effect for two-child households, but when we look at three-child households and control for balancing in Column (6), immigrant mothers from China, Korea, the Philippines, and India show some degree of male biased child sex ratios. Figure 1B graphically replicates the exercise of Figure 1A for the percentage of births which are male, making clear the patterns just described. We also construct a category for all other SESE Asian immigrants in the ACS not from the countries listed in Table 4, but the coefficients are not significant although it is unclear whether this is simply due to the small sample of these individuals.

These results suggest that there is a large degree of child gender preference both in fertility timing and in terms of skewed birth ratios among these populations in the United States, consistent with the studies discussed in the introduction—although decomposing across groups reveals a larger degree of heterogeneity. Another interesting result of this decomposition is that Japanese migrants exhibit some degree of daughter preference. This can be seen in the outcomes for both fertility and child gender of second child births and for the third child births in fertility stopping behavior.

We replicate Table 4 using only the 2012–2016 ACS sample to get a sense of the idea whether these patterns continue today in the United States (results are presented in Table A3 of Appendix). The findings are largely similar with two exceptions. Korean households exhibit some son preference in the full sample but not in the recent year ACS samples, and there is no evidence of daughter preference among Japanese migrants in the most recent window either.

Figure 1A

Figure 1B

In Table 5, we undertake a novel exercise that sheds some new light on the durability of son preference among immigrants in the United States. We re-estimate our main exercise— examining fertility effects and male birth ratios for third children (accounting for gender- balancing preferences), and further partition the sample of immigrant households in the United States. Specifically, we reproduce our previous estimates in Columns (1) and (5), and then in Columns (2) and (6) we contrast them with households in which parents are assortatively matched in that both are immigrants from the same country of origin. For clarity, it is worth reminding readers that our sample includes households with married mothers between the age of 18 and 40 with an eldest child at the age of 12 or younger living in the household. In our previous analysis, some of these mothers were married to other immigrants from their own country of origin, some from other countries, and some from the United States.

As can be seen from Table 5, the degree of child gender preference strengthens in magnitude in every case when we look at couples paired from the same country of origin in SE Asia. In the case of Japanese migrants that exhibited daughter preference in the overall sample, households where both parents are immigrants are significantly more likely to have daughters than sons and more likely to have a third child after two boys.

In Columns (3) and (7), we restrict the sample to include households where the mother is a migrant from SE Asia but the father is native-born. In this case, we see no robust evidence of son preference among any of the households we examine. In Columns (4) and (8) we restrict to native-born mothers who marry immigrant fathers. Although this is our smallest sample, we observe several interesting things. First, we see some evidence of son preference among migrants from India and the Philippines as well as stronger fertility and sizeable gender effects in favor of daughters among the sample with Japanese dads.

Comparing the role of mothers and fathers is potentially interesting for a number of reasons, including the fact that fertility outcomes result from an intrahousehold bargaining process in which either spouse may have a greater degree of certain dimensions of influence or control (such as income or control over contraception). Unfortunately, just as migrants are a selected sample of individuals, these new grouping should be interpreted with caution, as there is likely a large amount of selection in the marriage market among individuals who migrate to the United States and they choose to marry either another immigrant or a native-born individual. For example, mothers and fathers from the same country are likely to have similar preferences and thus more likely to exhibit a cultural trait in their home country such as son preference.

In spite of this, at a minimum, our results are suggestive of a situation in which fathers exhibit at least some responsibility for son preference outcomes—as in the case of assortative matching the impact is strengthened, and some of the son preference manifests even when only the father is a migrant. Causal analysis to uncover the degree of maternal and paternal influence in driving son preference is likely a valuable avenue for future research.

We first consider the development of son preference and assimilation at the individual level, exploiting variation in an immigrant’s age at arrival to the United States. The younger an individual is, the less time they will have had to grow up in a society where the son preference is the norm. In order to do this, we estimate a differences-in-differences regression according to the following equation to capture the difference in son preference across immigrants arriving before and after age 9. We adopt age 9 because it has been shown to be a critical age period for both individual’s fertility decision and for the acquisition of gender norms of behavior. Critical period hypothesis, developed by cognitive scientists, states that individuals learn languages more easily at a critical age range, between years 3 and 10 (Lenneberg, 1967), than older children. This hypothesis is supported and applied by Bleakley and Chin (2004, 2010) by exploiting variation in the age of immigrants at their time of immigration to the United States. They argue that timing of immigration is critical to a variety of social outcomes of immigrants such as wages, marriage status, and fertility decisions via the effects of English language skills and knowledge of American culture and institution. Age 9 is found to be the cutoff of the critical period. We set age 9 as the cutoff to be consistent with previous studies.

Hicks et al. (2015) also use age 9 as cutoff and find that immigrants’ gender identities are acquired in early life.

Age_Arrival_i is a dummy variable, indicating whether or not mother i migrated to the Unites States after the cutoff age of 9.

We obtain similar results when we select 8 or 10 years of age as the cutoff.

Table 6 provides results for fertility timing decisions and gender selection behavior, respectively, using the differences in the approach described in equation (3). Here we look at the population of migrants from South East Asia, excluding Japanese migrants given that the daughter preference we uncovered in the previous samples should attenuate any impact among other populations. As can be seen from Table 6, the estimated coefficients on arrived at age 9+ are significantly negative in both cases. This suggests that families who migrate at an older age tend to have fewer children than families who arrived at earlier age. One explanation for this could be the pressure from migration at these ages or selection into age of migration on the basis of economic outcomes not captured by our set of controls.

For example, maybe initially they spend more time and money on surviving in the new countries. They get married later, spend less time on children, and have stronger incentive to integrate into local community. Alternatively, individuals who migrate at older ages may experience different levels of familial pressure via communication and relationship structure with relatives than those who arrive at younger age.

As can be seen, the coefficients of interest, those on the interaction term of all girls and arrived at age 9+, are both positive and significant for the dependent variable fertility decision, both for the decision to have a second and third child for the broad sample of immigrants from Southeast Asia. The effect is strongest for third children. These effects are statistically significant and economically meaningful. To get a sense of the effect sizes, the estimates suggest that SESE Asian immigrant mothers who arrived in the United States after age 9 are 6.5% points more likely to have a third child when their first two children are girls.

The implications of this test can be most clearly seen in the two left panels of Figure 2, which flexibly plots regression adjusted coefficient estimates on all girls across mothers’ age of migration within first-generation immigrants from SESE Asian countries.

Figures 2 and 3 plot the coefficient of interest on the basis of individual age of migration in an effort to shed light on when son preference is formed and whether it is persistent. For each graph, we run a sequence of regressions using a moving window for a sample of migrants within 6 years (3 years on either side of each age). We then store the specified coefficients and SE from the model for each sample that are then plotted in the figures.

These results are remarkably consistent with previous research on gender norm acquisition and justify the choice of the critical period in the regression analysis—the coefficient on the interaction of interest becomes positive and significant only among mothers who migrate at later stages of their life. These flexible plots suggest that ages between 7 and 11 are a critical period in life during which individuals acquire preferences regarding the gender of their offspring, consistent with the formation of gender norms of behavior found in previous work.

When we turn to male births as our measure of son preference in Column (2), the coefficient on the interaction term in families with at least one child is 0.027 and with two children is 0.28, both significant at 1%. As seen in Figure 2, the two right panels, we again see results consistent with there being a critical period in which individuals acquire son bias early in life for the gender of second children. When the first child is a girl, South East Asian mothers are significantly more likely to have male sons, but only if they migrated after age 10. When they arrived at their early ages, they would be more likely to have a second daughter.

Figure 2

We also observe a negative and significant coefficient (−0.018**) on the indicator for all girls in Column 2 of Table 6, which provides suggestive evidence that there may be some degree of serial correlation in the gender of the second child. Impacts for the gender outcome of a third child, conditional on the first two being girls are, however, less precisely estimated. Noise in the estimates make it impossible to rigorously say whether younger age immigrants exhibit higher rates of male births for their third child, although it does appear that there is more robust evidence of a significant increase in the male share of births for SESE Asian migrants who arrive after age 9.

These results suggest that individuals form preferences for having a son early in life. A natural next question is whether son preference, once developed, is resilient in the face of exposure to a culture where son preference is not the norm, such as the United States. Figure 3 plots the coefficient on the indicator for all girl children as a function of the duration of time spent in the United States before the birth of the first child. The sample is the full set of mothers who have migrated from SESE Asia. In these specifications, we additionally control for age of migration as we have already shown that it matters for the formation of son preference. As can be seen from the figures, if longer duration of residence in the United States has any bearing on the degree of son preference exhibited in these households, it is a weak one. This suggests that either US cultural norms are not influential enough to shift migrants to US norms of child gender preferences. As a cultural trait, bias in favor of sons or daughters is persistent among individuals once they have developed it. Stated differently, the results suggest that those who have arrived earlier and thus spent more time in the United States exhibit less son preference. After the critical age, more time in the United States does not appear to diminish son preference.

Figure 3

A nice feature of the ACSs is that it provides information on an individual’s language spoken in the home and their country of ancestry. Using these pieces of information, we run another set of analysis to examine fertility stopping and the sex ratio of births for higher-order generation immigrants who are from Southeast Asian countries. These results are presented in Table 7.

It is evidently apparent that there is no significant change in the probability of having a second child for families with a first child who is a girl in comparison to families with a first child who is a boy. When looking at larger size families and controlling, we observe an impact for several of the population groups—but this effect appears to be driven by a desire for gender-balancing in most cases. There is one exception that stands out starkly, families whose ancestors are from India are 6.2% and those from Korea are 5.9% points more likely to have a third child if the previous children are all girls than all boys. While the results for fertility stopping from China appear anomalous, we find no similar impact among second- and higher-order generation children from China when we use only recent ACS waves (Table A4 of Appendix). Those from other countries analyzed show no clear evidence of son preference.

At first blush, these results are quite surprising. Estimates of son preference for first-generation immigrants from China and Vietnam were even larger than those of India and Korea. Why do some of these populations assimilate more rapidly than others? Why are immigrants of Indian descent such an outlier? Indeed, when we look at only more recent immigrants, the effect for Korean migrants dissipates much as it has in previous analysis, but the impact for higher-order Indian migrant generations is even larger than that for first generations and highly significant. Although we are limited to the pieces of information we can observe in the ACS, we posit two hypotheses for the case of Indian households as an outlier; however, there may be other explanations beyond the scope of our analysis.

First, because we cannot discern second generation from higher-generation immigrants—one possibility is that immigrants from India in our sample are more likely to be second-generation migrants than those from other South East Asian countries such as China or Vietnam, which showed son preference in the first generation. If migrants on average from China arrived further in the past, and son preference assimilates to US norms, then the results could be a quirk of the epoch of migration different populations around the world have faced. While we cannot observe these dates in the ACS for second- and higher-order generation migrants, we can observe the average year of migration for first-generation migrants. This value is 1995 for Vietnam, 1998 for Korea, 1999 for the Philippines, 2002 for China and Japan, and 2004 for India, which is not decisively supportive evidence of this explanation for the patterns we observe.

A second plausible explanation may be the higher proportion of homogamous marriages among Indian migrants. A high proportion of marriages among Indian immigrants could facilitate traditional social norms from an origin country, potentially reinforcing son preference in the home. As can be seen in Table A3 of Appendix, 92% of first-generation Indian immigrants marry other first-generation Indian immigrant fathers, significantly higher than for Chinese and Vietnamese mothers.

For first-generation immigrant Chinese and Vietnamese, the proportions are 72% and 75%, respectively.