By David Ribar IZA Discussion Paper No. 998, 2004

1. What do Social Scientists Know About the Benefits of Marriage? A Review of Quantitative Methodologies By David Ribar IZA Discussion Paper No. 998, 2004

2. Central Question See title! Literature review that addresses: * Why do we care? * What does theory predict? * How might we go about answering it? * What methods have researchers tried, and what have they found? * What can/should be done next?

3. Why do we care? • Tremendous interest by both academics and the public. • Public policy implications: • Direct: Administration for Children and Family’s Healthy Marriage Initiative, waiting periods, covenant marriages • Indirect: welfare policy, tax policy • Ribar’s contribution: • Summarize and evaluate (not all studies are created equal!) • Compare across disciplines, who often ignore one another • Includes recent developments

4. What does theory predict? Aside: Defense of the Rational Choice Model Rational behavior: adults make conscious decisions that maximize their well-being subject to their constraints. *or* People do the best they can with what they have. Many different models/perspectives can be incorporated into this framework. “Rational choice is the worst assumption except for all those other assumptions that have been tried from time to time.”

5. What does theory predict? How might marriage affect child well-being? • Resources (time and money) • Stability and stress • Parents’ productivity (health, cooperation) Which of these require marriage (vs. cohabitation, for ex.)? When might marriage have a negative effect?

6. How might we answer this question? Great challenge to research in this area is establishing causality. The endogeneity problem: correlation between variable (marital status) and error term. * Reverse causality * Omitted variables (or the problem of selection into marriage) Endogeneity problems often arise when the independent variable of interest is a choice variable—in this case, marriage.

7. How might we answer this question? Review: Omitted Variable Bias Suppose true model is: Y = β0 + β1X1 + β2X2 + ε What if we leave out X2? Estimate of β1 will be biased if corr(X1,X2)≠ 0 ANDβ2 ≠ 0.

8. How might we answer this question? Review: Omitted Variable Bias Suppose true model is: Childhealth = β0 + β1Marriage + β2Parenthealth + ε What if we leave out Parenthealth?

9. How might we answer this question? We would like to do an experiment and randomize people into marriage, but usually can’t do that. So what to do? Acknowledge & interpret carefully Statistical techniques (Combined with) theory with testable implications

10. How might we answer this question? Cross-section strategies • Add omitted variables (duh), or proxies. Disadvantages: May not have, may not know what they are. Cannot address reverse causality. Issues with interpretation and over-controlling. • Natural experiments: look for ways in which the world runs the experiment we want to run. Examples: “shot-gun” marriages, parental death Disadvantage: hard to find, generalizability.

11. How might we answer this question? Cross-section strategies • Instrumental Variables (a type of natural experiment) Formally: need a variable Z that is correlated with X1 but not correlated with error term. We can then use Z as an “instrument” for X1, using two-staged least squares: 1. Regress X1 on Z and all other exogenous variables. Obtain the fitted values from this regression (X1-hat). 2. Regress Y on X1-hat and the exogenous variables. Provides consistent estimates of β1.

12. How might we answer this question? Cross-section strategies • Instrumental Variables (cont’d) Examples: child sex mix as IV for 3rd child; QOB as IV for education Disadvantages: hard to find, generalizability Potential IVs for marriage: state/local laws regarding marriage, like blood test requirements. • Matching, modeling selection, nonparametric approaches

13. How might we answer this question? Panel-data strategies • Fixed Effects Add dummies for each individual, so effectively comparing the same individual to him/herself at different points in time. Advantage: eliminates OVB caused by permanent unobserved characteristics (ex: innate ability level) Disadvantages: cannot address OVB caused by changing characteristics (ex: health) • Can also think of family, geographic, school fixed effects . . .

14. How might we answer this question? Panel-data strategies • Control for pre-existing characteristics • Ex: Child health before the divorce

15. What has been tried? What was found? Broadly: • Children with married parents have higher living standards, better health, better development, more education, better behavior, less risky behavior, and more success as adults. • Some structures may be better than marriage, e.g. single mom with grandparents • Marriage associated with bad outcomes for some groups Causal or not?

16. What has been tried? What was found? Studies that add controls to address selectivity often find that doing so reduces or eliminates the beneficial effect of marriage. What do you make of this?

17. What has been tried? What was found? Interesting studies/convincing methods? • Gruber (2000): uses variation in unilateral divorce laws to estimate effect of divorce on kids’ education & wages. • Finds divorce decreases schooling and income and increases likelihood of early marriage.

18. What has been tried? What was found? Summary: • Selectivity “more than a hypothetical concern” • May be small direct causal effects

19. What next? • Studies should more carefully address the selectivity issue. • Natural experiments, like IV, most promising. Use policy variation? • Relationship quality, rather than status

20. Mouseover text: Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'.