GENETIC ABILITY AND INTERGENERATIONAL EARNINGS MOBILITY

1. GENETIC ABILITY AND INTERGENERATIONAL EARNINGS MOBILITY HAOMING LIU JINLI ZENG KENAN ERTUNC

2. SURVEY • INTRODUCTION • BASIC THEORETICAL MODEL • DATA COLLECTION • EMPIRICAL FINDINGS • SENSITIVITY ANALYSIS • CONCLUSION

3. INTRODUCTION • It is a well known fact that earnings are highly correlated across generations but we still have little knowledge about the factors which are responsible for the strong correlation • Several studies find that parents´ money per se does not have any significant impact on childrens earnings •  Key question: If it is not parents money, can it be parents´ ability? • Objective of the paper: Examining the role of genetic ability in generating the strong positive intergenerational earnings correlation observed in the USA •  Main measure: Comparison of the intergenerational wage and earnings elasticity of adopted children with non adopted children

4. BASIC THEORETICAL MODEL(1) Individuals earnings equation y: the log of long-run earnings h: individual`s human capital : :luck in the labour market h is a function of : I: parential investment g: genetic endowment c: cultural endowment : : random disturbances : l:log of parent`s long run earnings (1)

5. BASIC THEORETICAL MODEL(2) Technology of the human capital production αs: Coefficients g: genetic endowment c: cultural endowment : random variations (2) (3) Substituting Eq. (2) and (3) into Eq.(1) (4) a: adopted children (4.1) (4.2) b: biological children

6. BASIC THEORETICAL MODEL(3) Adopted and biological children are compared in the model under the following assumptions: Results: The Authors find that the difference between the estimated earnings elasticity of adopted biological children overstates the contribution of genetic endowment to the intergenerational earnings transmission.

7. DATA- US Panel Study of Income Dynamics(1) • Data from the PSID, a national representative sample, is extracted to conduct empirical analyses • Dataset contains the following characteristics: Multi-years´ earnings information for both fathers(period of 1967-1983) and their children(period of 1984-2000)  2 income measures: hourly wage and annual earnings- hourly wage meassures the transmission of earnings ability while the intergenerational correlation of annual earnings reveals the transmission of both, earnings ability and preferences to work Adjustment of both, earnings and wage for life cycle and time effects by regressing the log of hourly wage and earnings on age, age squared and year dummies because current earnings are a poor proxy for lifetime earnings if they are observed at the age of 20s Childrens wages and earnings are averaged over a span of 8 years and fathers´wages and earnings are averaged over 13 years separation between biological and adopted children of parents  consideration of any potential genetic link between adoptees and their adoptive fathers

8. DATA- US Panel Study of Income Dynamics(2) • Adopted children tend to grow up from more favourable family backgrounds than non-adoptive children • Adoptive fathers earn more than non adoptive fathers, due to the income requirement for adoptive parenthood • Adopted children have few siblings than non adopted children • Adopted children earn less than non adopted children in their adulthood

9. EMPIRICAL FINDINGS(1) Estimation of the following equation: Ai equals 1 if i is an adoptee and 0 otherwise is individual i’s average wage (earnings) over the period of 1984 –2000 is the average wage (earnings) of i’s father over the period of 1967–1984. (5) 9

10. EMPIRICAL FINDINGS (2) • Childrens earnings and hourly wages are strongly correlated with those of their biological fathers, but only weakly correlated with their adoptive fathers • The estimated intergenerational elasticities with respect to biological fathers´ wage is 0.345 (SD = 0.018) and fathers´ earnings is 0.369(SD=0.021) • The earnings relationsship between fathers and their adopted children is much weaker The intergenerational wage elasticity of adopted children is 23.2 (significant at the 2.2% level) percentage points lower than that of non-adopted children, and their earnings elasticity is 27.3 (significant at the 2.4% level) percentage points lower • These results suggest that, while a 1% increase in father’s hourly wage raises his biological child’s hourly wage by 0.345%, it only raises his adopted child’s wage by 0.113% • Earnings correlation between fathers and children would be halfed if their biological link was removed • Fathers´wages(earnings) have a strong impact on their biological children´s wages(earnings) but a weaker impact on their adopted children´s wages(earnings)

11. EMPIRICAL FINDINGS(3)

12. EMPIRICAL FINDINGS(4)

13. SENSITIVITY ANALYSIS (1) 1. Life cycle bias(column (2) of Table 2) • Can the age difference between adopted and non adopted children be responsible for the difference in the estimated earnings elasticity? • Reestimation of Eq.5 by restricting children´s sample to those who were at least 30 years old when their earnings were last observedthe average age raised to 36.97 for adopted children and to 38,42 for non adopted children good proxy for lifetime income increase of the estimated intergenerational wage elasticity to 0.386(SD=0.022) and earnings elasticity to 0.395(SD= 0.025), increase of the average age of non adopted children by almost 4 years but the estimated wage elasticity raised only by 0.041 • Differences in ages between adopted and non adopted children cannot be the major contributor to the differences in the intergenerational wage(earnings)

14. SENSITIVITY ANALYSIS (2) 2. Gender differences in intergenerational mobility • comparison of column(1)(3) and(4) shows that the results are not sensitive to whether men and women are pooled togheter 3. The impact of the number of siblings(column (5 )of Table 2) • Parents with fewer children have a stronger incentive to adopt children than these with many children. This explains why adopted children tend to have fewer siblings. • There is no trade off between children´s quality and quantity, so that the difference in the number of siblings between adopted and non adopted children don´t bias the estimation results

15. SENSITIVITY ANALYSIS(3) 4. Differences in father´s characteristics(column (6) and (8) of Table2 • Does father´s characteristics have an impact on the difference in intergenerational wage earning elasticity? If it is father´s characteristics that cause the differences, then the intergenerational elasticity would be lower for non adoptive children from adoptive families as well. To examine this, the authors are reestimating Equation 5 using 2 subsamples: • The first subsample consists of fathers and their biological children. In the regression, wages (earnings), adoptive father dummy and its interaction with father´s wage(earnings) as independent variables are used. The difference is insignificant either economically or statistically • The second subsample consists of both families with adopted and non adopted children  Difference in intergenerational wage earnings elasticity of adopted children is significantly lower than that of their non- adopted siblings  Difference in intergenerational wage (earnings) elasticity between adopted and non adopted children is not due to differences in the fathers characteristics

16. SENSITIVITY ANALYSIS (4) • Argument: If parents invest more on smarter children , then rich parents will invest more on their biological children, but poor parents will invest more on their adoptive children. This is because the former expects that their own children are more able than their adopted children, but poor parents would expect the opposite. • Examination of this argument  Comparison of the education attainment of adopted children with that of their non-adopted siblings • The probability of attending college is the same between adopted and non-adopted children. • Table 3 shows that non adopted children don´t tend to be smarter than adopted children and receive more human capital investment. 5. Parental investment in human capital

17. CONCLUSION • The genetic ability of adopted children is not correlated with that of their adoptive fathers but with those of their biological fathers • The intergenerational wage earnings transmission of adopted children is largely caused by the impact of other factors such as parential income and education • The intergenerational wage earnings elasticity of adopted children is much smaller than that of non-adopted children • The transmission of genetic ability across generations can account to a large proportion of the intergenerational earnings correlation, passing parents´earnings ability on to their children