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11
Table 1: Relationship Between IQ and Schooling
Coefficient
of IQ
Other Controls
Pooled
Sample
(1)
(2)
Near
College
(3)
(4)
Not Near
College
(5)
(6)
0.075
0.068
(0.003) (0.003)
0.081
0.072
(0.003) (0.004)
0.059
0.058
(0.005) (0.006)
No
Yes
No
Yes
No
Yes
R-squared
0.260
0.348
0.294
0.375
0.175
0.299
Number of
Observations
2,061
2,061
1,460
1,460
601
601
Note: Table reports coefficient of IQ in a linear regression model
for completed education in 1976. Models in odd columns include no
other controls.
Models in even columns include both parents’
education, age and age-squared, indicators for race, family
structure at age 14, and region in 1966. Near College subgroup are
those whose county of residence in 1966 had a local 4-year college
(public or private).
Sample includes men in the NLS Young Men
sample who were interviewed in 1976 and who have valid education
data for their parents and an IQ score obtained from their school
records.
Table 2:
OLS and IV Estimates of the Return to Education with Instruments Based on Features
of the School System
Schooling Coefficients
Author
Sample and Instrument
OLS
IV
1. Angrist and
Krueger (1991)
2. Staiger and
Stock (1997)
3. Kane and
Rouse (1993)
4. Card (1995b)
5. Conneely and
Uusitalo
(1997)
1970 and 1980 Census Data, Men.
Instruments are quarter of birth
interacted with year of birth.
Controls include quadratic in
age and indicators for race,
marital status, urban residence.
1920-29 cohort in 1970
0.070
(0.000)
0.101
(0.033)
1930-39 cohort in 1980
0.063
(0.000)
0.060
(0.030)
1940-49 cohort in 1980
0.052
(0.000)
0.078
(0.030)
1980 Census, Men. Instruments are
quarter of birth interacted with
state and year of birth. Controls
are same as in Angrist and Krueger,
plus indicators for state of birth.
LIML estimates.
1930-39 cohort in 1980
0.063
(0.000)
0.098
(0.015)
1940-49 cohort in 1980
0.052
(0.000)
0.088
(0.018)
NLS Class of 1972, Women.
Instruments are tuition at 2 and
4-year state colleges and distance
to nearest college. Controls
include race, part-time status,
experience.
Note: Schooling measured in units
of college credit equivalents.
Models without test
score or parental
education
0.080
(0.005)
0.091
(0.033)
Models with test scores
and parental education
0.063
(0.005)
0.094
(0.042)
NLS Young Men (1966 Cohort)
Instrument is an indicator for
a nearby 4-year college in 1966,
or the interaction of this with
parental education. Controls
include race, experience (treated
as endogenous), region, and
parental education.
Models that use college
proximity as instrument
(1976 earnings)
0.073
(0.004)
0.132
(0.049)
Finnish men who served in the
army in 1982, and were working
full time in civilian jobs in
1994. Administrative earnings
and education data. Instrument
is living in university town in
1980. Controls include quadratic
in experience and parental
education and earnings.
Models that exclude
parental education
and earnings
0.085
(0.001)
0.110
(0.024)
Models that include
parental education
and earnings
0.083
(0.001)
0.098
(0.035)
0.061
(0.001)
0.153
(0.015)
Austrian Men
0.518
(0.015)
0.947
(0.343)
German Men
0.289
(0.031)
6. Harmon and
Walker (1995)
British Family Expenditure Survey
1978-86 (men). Instruments are
indicators for changes in the
minimum school leaving age in
1947 and 1973. Controls include
quadratic in age, survey year,
and region.
7. Ichino and
Winter-Ebmer
(1998)
Austria: 1983 Census, men born
before 1946. Germany: 1986 GSEP
for adult men. Instrument is
indicator for 1930-35 cohort.
(Second German IV also uses dummy
for father’s veteran status).
Controls include age, unemployment
rate at age 14, and father’s
education (Germany only). Education
measure is dummy for high school
or more.
Models that use college
proximity × family background as instrument
--
Notes: see text for sources and more information on individual studies.
Table continues.
0.097
(0.048)
0.590 / 0.708
(0.844) (0.279)
Table 2:
OLS and IV Estimates of the Return to Education with Instruments Based on Features
of the School System, Continued
Schooling Coefficients
Author
Sample and Instrument
OLS
IV
8. Lemieux and
Card (1998)
9. Meghir and
Palme (1999)
Canadian Census, 1971 and 1981:
French-speaking men in Quebec
and English-speaking in Ontario.
Instrument is dummy for Ontario
men age 19-22 in 1946.
Controls include full set of
experience dummies and Quebecspecific cubic experience profile.
1971 Census:
0.070
(0.002)
0.164
(0.053)
1981 Census:
0.062
(0.001)
0.076
(0.022)
Swedish Level of Living Survey
(SLLS) data for men born 1945-55,
with earnings in 1991, and
Individual Statistics (IS) sample of
men born in 1948 and 1953, with
earnings in 1993. Instrument is
dummy for attending “reformed”
school system at age 13. Other
controls include cohort, father’s
education, and county dummies.
Models for IS data also include
test scores at age 13.
SLLS Data
(Years of education)
0.028
(0.007)
0.036
(0.021)
IS Data
(Dummy for 1-2 years
of college relative
to minimum schooling)
0.222
(0.020)
0.245
(0.082)
10. Maluccio (1997) Bicol Multipurpose Survey (rural
Philippines): male and female wage
earners age 20-44 in 1994, whose
families were interviewed in 1978.
Instruments are distance to nearest
high school and indicator for local
private high school. Controls
include quadratic in age and
indicators for gender and residence
in a rural community.
Models that do not
control for selection
of employment status
or location
0.073
(0.011)
0.145
(0.041)
Models with selection
correction for
location and employment
status
0.063
(0.006)
0.113
(0.033)
11. Duflo (1999)
Model for hourly wage
0.078
(0.001)
0.064 / 0.091
(0.025) (0.023)
Model for monthly wage
with imputation for
self-employed.
0.057
(0.003)
0.064 / 0.049
(0.017) (0.013)
1995 Intercensal Survey of Indonesia: men born 1950-72. Instruments are interactions of birth year
and targeted level of school building
activity in region of birth. Other
controls are dummies for year and
region of birth and interactions
of year of birth and child
population in region of birth.
Second IV adds controls for year of
birth interacted with regional
enrollment rate and presence of
water and sanitation programs in
region.
Notes: see text for sources and more information on individual studies.