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The Anti-Social Effects of Legalizing Same-Sex Marriage: Fact or Fiction?

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Abstract

Introduction

Previous research examines the effects of same-sex marriage on many child and family outcomes, but only a small subset examines the effects of laws on those outcomes. We evaluate the effects of same-sex marriage legalization in the USA on four socio-familial outcomes.

Methods

We use currently available public data from the U.S. Census and CDC to analyze changes in state-level legalization of same-sex marriage on rates of child poverty, divorce, marriage, and children living in single-parent households within each state from 2011 to 2016. The estimators use traditional cross-sectional time-series methodologies, along with adjusting for high-dimensional fixed-effects (HDFE) clustering to account for both spatial and temporal dependence of state-time observations.

Results

We find no evidence to validate claims of negative ramifications from same-sex marriage legalization on these outcomes.

Discussion

With respect to the arguments articulated in Supreme Court amici briefs, we show that assertions of negative social effects of legalized same-sex marriage are largely unsupported.

Conclusion

In addition to illustrating the gains from HDFE estimators, we conclude that warnings of likely negative effects from same-sex marriage, such as disallowing adoption by same-sex couples, are not credible.

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Notes

  1. There are extensive discussions that critique (e.g., Marks, 2012) and defend the validity (e.g., Amato, 2012) of these studies. One major study that found negative impacts of same-sex parents on child outcomes (Regnerus, 2012) was criticized when a replication did not come to the same conclusion (Cheng & Powell, 2015)

  2. Louisiana, Utah, Texas, Alaska, Arizona, Arkansas, Georgia, Idaho, Kansas, Montana, Nebraska, North Dakota, Oklahoma, South Dakota, and West Virginia (listed here in same order as listed on the legal brief).

  3. In economics, non-price entry barriers (such as refusing to hire based on race or gender) are inefficient: they impose costs not only on the excluded group but also on consumers or employers, while conferring smaller benefits (higher wages) on the privileged group. There are no social benefits.

  4. Considerable research shows that marriage in general benefits both the two parents and the children, partly due to scale economies along with more income. In addition to within family benefits, external benefits of marriage include reduced demand for many social services (e.g, welfare and other income supports; police) that might otherwise be required if there were more single-parent families. See Ribar (2015); Sawhill and Thomas (2005); Thomas and Sawhill (2002); Sawhill and Haskins (2016); McLanahan and Sawhill (2015); Zissimopoulos, Karney, and Rauer (2015).

  5. The early adopter control states include the 2013 legalizers (CA, DE, HI, MD, MN, NJ, NM and RI) and the earliest adopters (MA, 2004; CT, 2008; IO, V, 2009; NH, DC, 2010; NY, 2011; ME, WA, 2012). The treated states, forced to adopt by Windsor (except IL, which voluntarily adopted after Windsor) include OR, ID, MT, WY, NV, UT, AZ, CO, OK, WI, IL, IN, PA, WV, VA, NC, and SC. Omitted states (the late legalizers, forced to legalize by Roe in 2015) include ND, SD, NE, KS, TX, MO, AR, LA, MI, OH, KY, TN, MS, AL, GA, FL)

  6. However, as a robustness check, we also provide a secondary model specification that drops all states from our “control” group which did not have same-sex marriage for multiple years prior to 2014. The results in Tables 1, 2, 3, and 4 do not change.

  7. Note that Illinois was the only state post-Windsor to voluntarily legalize same-sex marriage.

  8. For ease of interpretation, we use state-year levels in the dependent variables. However, because we use state fixed effects, the focal coefficient B represents the average within state difference in the dependent variable between treatment and control state (Ludwig & Cook, 2000); it is not a between state difference. As a robustness check, when we use difference-in-difference estimates of the relation between state-year changes in the policy adoption variable to state-year changes in dependent variables, along with the control variables and state fixed effects, the results do not change appreciably.

  9. The SUR estimates show that the residuals are correlated:

    Correlation matrix of residuals:

    childpov divorce marriage sglpar

    childpov 1.0000

    divorce 0.0259 1.0000

    marriage − 0.1606 0.5399 1.0000

    sglpar 0.3548 0.0124 0.0768 1.0000

    Breusch-Pagan test of independence: chi2(6) = 246.067, Pr = 0.0000.

    We also estimated an xtreg with state-level fixed effects (Cameron & Trivedi, 2009; Wooldridge, 2010). Similar to Ludwig and Cook’s (2000) assessment of the Brady bill, we also performed a specification of ordinary least squares analysis with controls, heteroskedasticity-robust standard errors, and state and year fixed effect regressors. We do not show the results, but they do not differ from the results that we present.

  10. Excluding 2013 legalizing states is a robustness check to provide a model where all the “control” states had same-sex marriage legalization for more than just 1 year. The results do not change.

  11. These findings are robust to replacing rates in the dependent variables with log of rates. Neither the statistical nor substantive results changed. Data available upon request.

  12. Opponents prefigured adverse effects of legalized same-sex marriage; therefore, we used directionally one-sided tests.

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Authors and Affiliations

  1. Department of Public Administration & Policy, American University, 4400 Massachusetts Avenue NW, Kerwin Hall, Washington, DC, 20016, USA

    Laura Langbein

  2. Department of Political Science, Winthrop University, Rock Hill, SC, USA

    Brandon Ranallo-Benavidez

  3. Department of Justice, Law & Criminology, American University, Washington, DC, USA

    Jane E. Palmer

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  1. Laura Langbein
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Correspondence to Laura Langbein.

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Research Involving Human Data

This is an observational study that uses publicly available aggregate data on humans. Specifically, as noted in the abstract of the manuscript, “we use currently available public data from the U.S. Census and CDC to analyze changes in state-level legalization of same-sex marriage on rates of child poverty, divorce, marriage, and children living in single-parent households within each state from 2011 to 2016.”

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Langbein, L., Ranallo-Benavidez, B. & Palmer, J.E. The Anti-Social Effects of Legalizing Same-Sex Marriage: Fact or Fiction?. Sex Res Soc Policy 18, 1060–1077 (2021). https://doi.org/10.1007/s13178-020-00509-y

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