Differential heritability? Directory UMM :Data Elmu:jurnal:E:Economics of Education Review:Vol20.Issue3.2001:
221 P. Miller et al. Economics of Education Review 20 2001 211–224
Table 3 IV estimates of DeFries and Fulker model of educational attainment, Australian twins sample
a
Variable OLS
IV OLS
IV Constant
9.333 13.94 5.121 4.60
10.123 15.15 6.346 5.80
Co-twin’s educational attainment S
j2i
0.222 4.03 0.573 6.34
0.092 1.75 0.455 5.09
Coefficient of genetic relationship R
ji
2 5.864 7.34
2 5.503 3.70
2 5.511 7.23
2 5.050 3.59
S
j2i
R
ji
0.485 7.26 0.459 3.79
0.474 7.43 0.430 3.75
Age –
b
–
b
2 0.023 5.64
2 0.009 1.93
Father’s education level –
b
–
b
0.094 4.83 0.035 1.65
Mother’s education level –
b
–
b
0.087 3.97 0.035 1.47
Number of siblings –
b
–
b
2 0.056 2.50
2 0.024 1.03
Father’s occupational status –
b
–
b
0.007 3.12 0.003 1.78
Female –
b
–
b
2 0.632 7.33
2 0.457 4.67
Sample size 2478
478 2478
2478 R
2
0.3557 0.2733
0.4204 0.3833
a
Heteroscedasticity-consistent “t” statistics in parentheses.
b
Variable not entered.
tin 1978 reduces the estimate of c
2
to between 0.3 and 0.4 and again raises the estimate of h
2
to around 0.65. But even with this adjustment for the extra additive gen-
etic component due to assortative mating, the IV esti- mates ascribe a stronger role to common environmental
factors. Ashenfelter and Krueger 1994 also find that the empirical findings in their study of wages are sensitive
to the treatment of measurement errors in self-reported schooling data.
5. Differential heritability?
The analyses above have shown that the major factor in accounting for variance in educational attainments is
genetic endowments. Cherny et al. 1992 argue that heritability may differ as a function of the phenotype and
that such differences have important consequences for attempts to estimate heritability and for the policy impli-
cations derived from estimates. The first issue is easily interpreted in terms of model specification. Thus, Cherny
et al. 1992 suggest that Eq. 8 may be written as:
S
ji
5 b
1 b
3
S
j −
i
1 b
4
R
ji
1 b
5
S
j −
i
R
ji
1 b
6
S
2 j
− i
1 b
7
S
2 j
− i
R
ji
10 1
g
ji
where b
6
estimates the change in common environmen- tality as a function of S
2 i
.
25
and b
7
estimates the change in heritability as a function of S
2 i
. Higher order interac- tion terms may also be considered for inclusion in the
estimating equation. Exclusion of the S
2 j
− i
and S
2 j
− i
R
ji
terms thus amounts to a misspecification of the estimat- ing equation, and resulting parameter estimates may be
25
This was measured in Eq. 8 as b
3
=∂ S
ji
∂ S
j2i
, net of zygos- ity influences R
ji
.
biased. If b
6
is non-zero, then it implies that the impact of shared environment differs across educational attain-
ments. A negative parameter, for example, would indi- cate that education policy would be more efficacious at
lower levels of educational outcomes than at the tertiary level. Similar reasoning holds with respect to heritability.
Relevant estimates are presented in Table 4. Column i presents estimates obtained when the data are pooled
across males and females, column ii lists results for males only while column iii lists results for females
only.
The coefficient on S
2 j
− i
R
ji
, which records differential heritability, is insignificant in each of the equations in
Table 4. Hence, there is no evidence of differential heri- tability with respect to educational attainment in these
data. In other words, while the evidence in this paper suggests that heritability is important in that h
2
is sizeable, the degree of its importance does not vary
across educational attainments for either males or females.
The coefficient on S
2 j
− i
, which records differential environmentality, is significant for males and for the total
sample but is insignificant for females. The negative coefficient for males indicates that shared family effects
are more important among males at the earlier edu- cational attainments. Therefore, the totality of our evi-
dence suggests that the family environment is important and approximately equally so for males and females in
that c
2
is of the same order of magnitude for these groups in the basic model of DeFries Fulker, 1985, and that
the degree of its importance varies across educational attainments, at least for males. The sensitivity of this
effect to level of education, whereby shared family effects are more important among males at the earlier
educational attainments, would be expected to accentuate the inter-generational transmission of inequality. In this
222 P. Miller et al. Economics of Education Review 20 2001 211–224
Table 4 OLS estimates of Cherny et al.’s model of educational attainment, Australian twins sample
a
Variable Total sample
Males
b
Females
b
Constant 5.530 2.15
2 1.973 0.32
6.805 1.72 Co-twin’s educational attainment S
j2i
0.857 2.05 1.889 1.97
0.536 0.81 Coefficient of genetic relationship R
ji
2 1.803 0.58
3.816 0.54 2
3.710 0.83 S
j2i
R
ji
2 0.156 0.30
2 1.077 0.97
0.219 0.29 Age
2 0.021 5.01
0.003 0.26 2
0.024 4.70 Father’s education level
0.093 4.76 0.094 2.24
0.082 3.20 Mother’s education level
0.085 3.90 0.090 1.98
0.074 2.51 Number of siblings
2 0.052 2.36
2 0.025 0.51
2 0.050 1.74
Father’s occupational status 0.007 3.19
0.006 1.31 0.006 2.19
Female 2
0.631 7.33 –
c
–
c
S
2 j2i
2 0.031 1.84
2 0.068 1.85
2 0.016 0.60
S
2 j2i
R
ji
0.026 1.23 0.059 1.38
0.009 0.30 Sample size
2478 592
1313 R
2
0.4221 0.3720
0.4461
a
Heteroscedasticity-consistent “t” statistics in parentheses.
b
Mixed sex twin pairs are omitted from separate analyses of males and females.
c
Variable not entered.
regard it is well recognised in the educational attainment literature that the important thresholds with respect to
educational attainments occur at an early stage in the spectrum of levels of education. For example, James
1988, p. 11 notes:
It is also clear that aid alone will not bring about equal access. For example, until their earlier edu-
cational environments are equalised, disadvantaged groups will continue to have lower participation in
higher education, particularly in the most selective schools.