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the SER may, in fact, be biased down by even more than
would be the case with comparable survey data. It also
suggests that the possibility of upward bias from correlated
measurement error between fathers and children when using
SER data is more than offset by the overall attenuation bias.
Otherwise the estimates using the SER would have been
higher than those found when using the SIPP. It is also
apparent from table 4 that on the whole, the IGE is only
slightly lower when the imputed noncovered fathers are
added to the sample.
The most striking ﬁnding is that the IGE rises dramatically as the fathers’ earnings are increasingly averaged over
more years. Indeed, the estimated father-son elasticity is
0.613 when the fathers’ earnings are averaged over 16 years.
The father-daughter elasticity is a bit lower at 0.570. When
the sample of fathers is restricted to private-sector, non-selfemployed workers, however, the father-daughter elasticity
is estimated at 0.754. Such a high degree of transmission is
rather surprising and may be due to the possible positive
correlation between fathers’ earnings and daughters’ labor
force participation among this group, as discussed earlier.
C. Does Excluding Years of Nonemployment Matter? Couch and Lillard (1998) argue that the results of Solon
(1992) and Zimmerman (1992) are sensitive to the inclusion Fortin – Econ 560 Lecture 5B Using detailed information on wealth from the SIPP, he finds an higher IGE for
families with low net worth, offering some empirical support for theoretical models
that predict differences in IGE due to borrowing constraints, but again small sample
sizes are involved. How much difference does it really make if the IGE is 0.6 rather than 0.4? With an
IGE of 0.6, it will take the descendants of a family, initially at the poverty threshold
(roughly 75% below the national average) 5 to 6 generations (125 to 150 years)
before their income would be within 5% of the national average. With a...
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- Fall '13