GENETIC ABILITY AND
INTERGENERATIONAL EARNINGS
MOBILITY
HAOMING LIU
JINLI ZENG
KENAN ERTUNC
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SURVEY
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INTRODUCTION
BASIC THEORETICAL MODEL
DATA COLLECTION
EMPIRICAL FINDINGS
SENSITIVITY ANALYSIS
CONCLUSION
INTRODUCTION
 It is a well known fact that earnings are highly correlated across
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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
BASIC THEORETICAL MODEL(1)
(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
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BASIC THEORETICAL MODEL(2)
(2)
(3)
Substituting Eq. (2) and (3) into Eq.(1)
(4)
(4.1)
a: adopted children
b: biological children
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(4.2)
Technology of the human
capital production
αs: Coefficients
g: genetic endowment
c: cultural endowment
: random variations
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.
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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
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DATA- US Panel Study of Income Dynamics(2)
 Adopted children tend to
grow up from more
favourable
family
backgrounds than nonadoptive 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
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EMPIRICAL FINDINGS(1)
(5)
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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.
EMPIRICAL FINDINGS (2)
 Childrens earnings and hourly wages are strongly correlated with those of their
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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)
EMPIRICAL FINDINGS(3)
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EMPIRICAL FINDINGS(4)
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SENSITIVITY ANALYSIS (1)
1. Life cycle bias(column (2) of Table 2)
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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)
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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
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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
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SENSITIVITY ANALYSIS (4)
 Argument:Ifparentsinvestmore onsmarter
5. Parental investment in human capital
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children ,then richparents will investmore 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 nonadoptedsiblings
 The probability of attending collegeisthe same
between adoptedandnon-adoptedchildren.
 Table 3 shows that non adopted children
don´t tendtobesmarterthanadoptedchildren
andreceivemorehuman capitalinvestment.
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
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