178 P. Christie, M. Shannon Economics of Education Review 20 2001 165–180
Table 9 Oaxaca decomposition of the gender earnings gap, full-time year workers in 1990 and 1985
a
With industryoccupation Without industryoccupation
Gap Explained
Residual Gap
Explained Residual
1990 Results: Total
0.387 0.125
0.261 0.386
0.062 0.324
Due to: Educational attainment
20.003 20.007
Field of study 0.025
0.037 Location
20.004 20.004
Maritalfamily 0.013
0.015 Occupation
0.014 –
Industry 0.053
– Hours
0.019 0.012
Age 0.005
0.005 Other personal
0.004 0.005
1985 Results: Total
0.434 0.155
0.279 0.433
0.079 0.354
Due to: Educational attainment
20.004 20.008
Field of study 0.017
0.034 Location
20.004 20.004
Maritalfamily 0.024
0.028 Occupation
0.028 –
Industry 0.064
– Hours
0.015 0.012
Age 0.010
0.012 Other personal
0.005 0.007
a
Oaxaca decomposition: see Eq. 2.
the Oaxaca decomposition, the explained component is smaller in all years and specifications. However, in all
other respects the results are quite similar. The explained component is smaller when industry and occupational
dummies are left out, educational attainment remains an unimportant contributor to the explained component
while field of study contributes positively and is especially important in the absence of industry and occu-
pational dummies. The major new insight provided by the Cotton decomposition is its breakdown of the
residual into a male advantage and female disadvantage component. The latter term accounts for most of the
residual term in all years and specifications. Over time the fall in the combined residual term reflects a decline
in the female disadvantage term.
Projections of future and past log-wage levels, along the lines of those presented in Section 3, were made
based upon the earnings regression estimates. Under the assumption that in the future educational attainment and
field of study patterns of older workers converge to that of 25–34 year olds, the 1990 gap changes from 0.387 to
0.361 when industryoccupation dummies were present or 0.350 when the latter were absent. If, projecting back-
wards in time, the 55–64 year old patterns were to pre- vail for workers age 25 and older, the gap would be
0.386 with industryoccupation or would climb to 0.406 no industryoccupation. As in Section 3, these
changes are driven by the changes in educational attain- ment.
6. Comparison with previous studies
How important is the extra educational detail provided in the Census to the decomposition of the gender gap?
The results clearly suggest that having data on field of study aids in explaining the gap. In both years, differ-
ences by gender in field of post-secondary qualification account for a significant part of the earnings gap. The
highest estimate the 1990 results with no industry and occupation dummies is nearly 10 of the total gap and
over half of the explained component. Field of study was typically either unavailable or not controlled for in earl-
ier Canadian studies.
A comparison with earlier studies suggests that the additional detail on educational attainment alone does
not add much to the explanation of the gap. Gunderson 1979 using Census data for 1970, and Shapiro and
179 P. Christie, M. Shannon Economics of Education Review 20 2001 165–180
Table 10 Cotton decomposition of the gender earnings gap, full-time year workers in 1990 and 1985
a
With industryoccupation Without industryoccupation
Gap Explained
Male Female
Gap Explained
Male Female
residual residual
residual residual
1990 Results: Total
0.387 0.085
0.142 0.159
0.386 0.040
0.149 0.197
Due to: Educational attainment
20.002 20.006
Field of study 0.018
0.029 Location
20.004 20.005
Maritalfamily 0.006
0.006 Occupation
0.002 –
Industry 0.042
– Hours
0.017 0.008
Age 20.003
0.004 Other personal
20.011 0.004
1985 Results: Total
0.434 0.117
0.140 0.177
0.433 0.058
0.151 0.224
Due to: Educational attainment
20.002 20.005
Field of study 0.013
0.026 Location
20.004 20.004
Maritalfamily 0.014
0.016 Occupation
0.016 –
Industry 0.053
– Hours
0.014 0.009
Age 0.009
0.010 Other personal
0.004 0.006
a
Cotton decomposition: see Eq. 3.
Stelcner 1987 and Miller 1987, using Census data for 1980 all find that differences in educational attainment
explain virtually none of the gap — consistent with our results. Estimates by Doiron and Riddell 1994 for 1984
Survey of Union Membership and Kidd and Shannon 1995 for 1981 Survey of Work History and 1989
LMAS suggest the same result for gender differences in average log-hourly wages.
24
The apparent unimport- ance of the additional detail on educational attainment is
confirmed by re-estimating our earnings equations using a simpler 7-category attainment variable differences in
attainment account for 20.003 to 20.008 of the gap depending on year and specification.
Our results largely parallel those for the US. Education variables used in the US literature are often quite simple.
Years of schooling, sometimes augmented by a dummy for college degree are common. Consistent with Canad-
ian results, differences in the quantity of schooling appear to play little role in explaining gender differences
in wages, see for example Blau, Ferber and Winkler
24
The result is derived from the 1984 regression results and means table reported in Doiron and Riddell 1994.
1998, p. 190 who report that educational attainment differences accounted for only 0.3 of the 27.6 percentage
point gap in 1988.
25
The US literature also provides evi- dence of the importance of field of study. Brown and
Corcoran 1997 find that field of study accounts for 0.08–0.09 of the 0.21 gender wage gap for a sample of
college educated workers. They also note that, as for our results, the importance of field of study declines with
the inclusion of industry and occupational dummies. An earlier study of recent college graduates by Daymont and
Andrisani 1984 gave similar results with field of study explaining 0.045–0.058 of a 0.129 gap. These effects are
somewhat larger than those obtained on our subset of university educated workers see
23
.
25
The authors’ own calculations based on means and coef- ficients reported in the US studies Macpherson and Hirsch
1995, Sorenson 1989 and Neumark 1988 all imply a small role for schooling attainment differences.
180 P. Christie, M. Shannon Economics of Education Review 20 2001 165–180
7. Conclusions
