Almost all studies of same-sex parenting have concluded there is “no difference” in a range of outcome measures for children who live in a household with same-sex parents compared to children living with married opposite-sex parents. Recently, some work based on the US census has suggested otherwise, but those studies have considerable drawbacks. Here, a 20 % sample of the 2006 Canada census is used to identify self-reported children living with same-sex parents, and to examine the association of household type with children’s high school graduation rates. This large random sample allows for control of parental marital status, distinguishes between gay and lesbian families, and is large enough to evaluate differences in gender between parents and children. Children living with gay and lesbian families in 2006 were about 65 % as likely to graduate compared to children living in opposite sex marriage families. Daughters of same-sex parents do considerably worse than sons.
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For example, it forms the basis for the American Psychological Association’s position supporting gay marriage.
Economists have written a considerable amount on gay and lesbian issues outside of child development, and generally find differences in behavior. For example, Negrusa and Oreffice (2011) on savings rates, Oreffice (2010) on labor supply, Black et al. (2007) on labor markets, Jepsen and Jepsen (2009) on home ownership, and Carpenter and Gates (2008) on family formation. Indeed, The Review of Economics of the Household devoted its 2008 December issue to gay and lesbian households. Those papers examined wage differentials [Zavodny (2008), Booth and Frank (2008)], household formation [Badgett et al. (2008)], and bank deposits [Klawitter (2008)]. This is the first paper in economics to examine differences in child performance.
This is often a characteristic of a nascent field. These measures include self reports on attitudes, awareness, and adjustments [e.g., McNeill and Rienzi (1998)]; self reports on parenting quality and socio-emotional child development [e.g., Golombok et al. (1997)]; self reports on psychological well-being, identity, and relationships [e.g., Tasker et al. (1995)]; self reports on family closeness, parental legitimacy, child bonding [e.g., Gartrell et al. (1999)]; and self reports on stigma and self-esteem [e.g., Gershon et al. (1999)].
“Snowballing” is the practice of asking individuals within a study to recruit their friends and associates to join the study.
The first Canadian same-sex marriages took place on January 14, 2001 at the Toronto Metropolitan Community Church. These became the basis of a successful legal challenge which ended at the court of appeal on June 10, 2003. On July 20, 2005, the Federal government passed the Civil Marriage Act that made Canada the fourth country in the world to legalize same-sex marriage. Thus, different people date the arrival of same-sex marriage in Canada as 2001, 2003, or 2005.
Biblarz and Savci, p. 490, 2010.
Unfortunately, it also lumps married and common law same-sex couples together, and I am unable to separate them.
The census is not a panel, and provides only a snap shot of the population. As a result, this paper does not study the effect of growing up in a same-sex household, but rather examines the association of school performance for those children who lived with same-sex parents in 2006.
Rosenfeld (2010) stressed the importance of controlling for a child’s home life stability. He restricted the sample to households that remained in one place for the past 5 years. Here mobility is controlled for with a fixed effect on whether or not the child has remained in the home for 1 year. Results reported in the text all refer to this mobility control. The "Appendix" shows the results of the alternative control: did the child move residences in the past 5 years.
Golombok et al. (2003) uses a random sample from the Avon Longitudinal Study of Parents and Children—a local British study—and comes up with 18 lesbians. They then use snowball methods to bring their numbers up to 39 lesbians.
The 2000 US Census does not directly identify same-sex couples. Rosenfeld, like others, did the best he could by indirectly identifying them. He did this by selecting those couples who indicated they were a couple and who identified their sex as being the same. This procedure requires the correct answer of three questions, and a small chance of error on the part of heterosexuals can lead to a large measurement error for the same-sex couple sample, given the large size of the former and the small size of the latter. Black et al. (2006) suggest a procedure for correcting this statistical problem; however, there is no indication in the Rosenfeld paper that he followed it.
The Regnerus study (2012) also used a random sample; however, it was still too small to identify a sufficient sample of same-sex parents. To increase his sample size he decided to use a broader definition of same-sex parent.
Of the fifty-three studies examined here, only a few dealt with gay male parents. Almost all of the studies are done on lesbians. This is another source of bias that warrants caution in drawing any conclusions about non-lesbian families.
Often the problem of small sample size comes from low response rates. Many of the fifty-two studies are silent on the question of response rates to their surveys, but when information is provided it often shows that response rates are very low. For example, in Bos (2010) the gay males were recruited from an Internet mail list for gay parents. Although the list had 1,000 names, only 36 replied and participated in the study. This amounts to a 3.6 % response rate. Other studies (e.g., Chan et al. and Fulcher et al.) have reductions in their samples similar in relative size to Rosenfeld. Response rates lower than 60 % are usually taken to mean the presence of a strong selection bias—even when the initial list is random.
This file is not a public use data set. To use the data, a proposal is screened by the Social Sciences Research Council of Canada, an RCMP criminal check is conducted, and the researcher becomes a deemed employee of Statistics Canada subject to the penalties of the Statistics Act. Empirical work was conducted at the SFU Research Data Center, and all results were screened by Statistics Canada before release. Statistics Canada does not allow any unweighted observations or descriptives to be released, nor any maximums or minimums of weighted estimates, nor sample sizes for the weighted regressions.
Because the procedure starts by selecting the children, and then matches the parents of the child to the file, the problem of having a non-biological parent not report a child in the household who is biologically related to their spouse is avoided.
Statistics Canada does not allow the sample sizes to be released; however, there are approximately ten million children in Canada, and so the sample has close to two million children in it.
There’s no reason to believe this selection bias would be correlated with family type, however. All regressions were run with various restrictions on the child’s age within the sample, including keeping everyone, and none of the gay or lesbian family results in the paper change, in terms of magnitudes or levels of significance, in an important way.
Many children in Canada who live with a gay or lesbian parent are actually living with a single parent. About 64 % of children in gay homes have a single father, and about 46 % of children in lesbian homes have a single mother (see Allen and Lu, “Marriage and children: differences across sexual orientations,” (unpublished, 2013). The number of gay and lesbian single parent homes is so small compared to all other single parent homes, however, that it likely causes little bias. In any event, the children analyzed here are a distinct subset of all children raised by a gay or lesbian parent.
The census identifies many visible minorities, but only has a broad based question on race. Hence, the same race variable likely contains significant measurement error.
This control is lacking in other large sample studies on same-sex parents. It is important because a previous marriage disruption is likely to have a negative impact on high school performance. This is particularly important with same-sex couples given the evidence that their relationships are less stable [see Andersson et al. (2006)].
Using current parental marital status is a decent control for family history (as used here), but the coefficients estimated are biased measures of the correlation of parental marital history on child school performance. For this reason, and to keep the tables to one page, these coefficients are not reported.
Rosenfeld (2010), and Allen et al. (2013) use normal progress through school as their measure of child performance. The Canada census does not identify the grade of the student in 2006, and therefore, this measure is not possible. It does, however, identify if the child has graduated from high school or not.
Two mobility measures are used because of the important role mobility played in Rosenfeld (2010). He decided to restrict his sample by removing households that moved within the past 5 years. This procedure was also performed here. No qualitative difference was made in terms of the point estimates. Rather than controlling for whether or not the child had moved residences over the past one or 5 years, the regressions were also run controlling for whether or not the child changed census metropolitan areas over the past 1 or 5 years. No qualitative difference in the point estimates on type of household resulted, although they were estimated with more precision. All regressions cluster by province to provide robust standard errors.
The key to interpreting the odds ratio is to compare it to the odds of 1 (equally likely). Hence, an odds ratio of 1.2 means that a unit change in an independent variable, others held constant, increases the chance of a positive outcome by 20 %.
The odds are reduced to around 70–80 %, but keep in mind this variable contains measurement error.
They are also reasonably close to the unconditional estimated average graduation rates found in Table 3. The odds ratios are .71 and .64 for the 5 year mobility measure.
The reported odds ratios are relative to children from opposite sex married parents. Compared to children of opposite sex cohabitating parents, the children of same-sex parents do even worse. This can be seen indirectly from Table 5. If cohabitating parents are the left out category, the odds ratio (standard error) for high school graduation from a gay home is 0.61 (0.132), and 0.53 (0.138) from a lesbian home—when all controls are used.
In order to further test the idea that lower graduation rates for children of gay and lesbian parents may be the result of a negative environment, more controls were used for location. Rather than just control for the province of residence, in an alternative specification the census metropolitan area was also controlled for. For gay parents the odds ratio changes from 0.69 to 0.68 if the 1 year mobility control is used with all other controls, and remains unchanged if the 5 year mobility control is used. For lesbian parents the odd ration changes from 0.60 to 0.57, and from 0.64 to 0.58 depending on the mobility control. These estimates have slightly lower standard errors.
Within the literature, see Chrisp (2001), which addresses sons in lesbian homes. Within the popular culture, see Modern Family, Season 4, Episode 19, where the gay couple Cam and Mitchell decide their daughter Lily needs the input of aunt Gloria to discuss “girl issues.”
For school attendance only the results for the 1 year mobility control are reported. The results for controlling for 5 year mobility were virtually identical. An unreported regression on primary school attendance found no difference between the different household types.
It might seem odd that the effect of Age is positive. However, the dependent variable is 1 if the child ever attended school, or is now attending. Given that some students start school later than age 5, and that many children are home schooled in primary divisions, a positive effect of Age is expected. If the regression is run restricting the sample to students older than 12, the age effect is greatly removed. When the sample is restricted to various age ranges (e.g., starting at ages 6–12, or ending at ages 17–22, the odds ratios for the family type variables barely change at all and remain statistically indistinguishable.
As mentioned, the census data has an imperfect measure of marital status. Those “currently married” could be divorced from an earlier marriage. Given the higher marriage rate for opposite sex couples, the estimated odds ratio on graduation rates for children of same-sex families may be biased upwards. The true effect may be larger and more troubling.
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Thanks to Sonia Oreffice, Krishna Pendakur, and three journal referees for their comments. This project was funded by the Social Sciences Research Council of Canada.
See Table 8.
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Allen, D.W. High school graduation rates among children of same-sex households. Rev Econ Household 11, 635–658 (2013). https://doi.org/10.1007/s11150-013-9220-y
- Same sex households
- Same sex parents
- High school graduation