186 M. Binder Economics of Education Review 18 1999 183–199
vocational programs. Of all students at the upper-second- ary level, eighteen per cent are enrolled in vocational
programs. The majority of these vocational students- about 70 per cent—study in public institutions.
5. Data sources and implementation
5.1. Schooling indicators The schooling data are drawn primarily from annual
data published by the Secretary of Public Schooling SEP in Mexico between 1976 and 1994 SEP, 1983,
1984–1994.
11
The data include national and state-level enrollments by grade level at the start and finish of the
school year for all public and private schools. These data provide the basis for calculating retention, continuation
and efficiency rates, which measure the flow of students through the schooling system. The retention rate is the
number enrolled at the close of the school year divided by the number who started the school year. The continu-
ation rate is the number of students beginning a given school level divided by those who graduated in the pre-
vious school year from the earlier school level. The efficiency rate is the number of students who graduated
from a particular school level divided by those who entered the school g-1 years earlier, where g is the num-
ber of grades for that school. For example, primary school consists of six grades. Students graduating in the
1993–94 cycle would have entered first grade in the 1988–89 cycle, if they successfully completed one grade
a year. The efficiency rate captures leakages from the system as students drop out of school as well as the
prevalence of grade repetition. Figs 2a, b, c and d plot the time-series for these indicators.
The SEP enrollment figures can also be combined with population censuses to determine enrollment rates, which
give the fraction of all age-appropriate children that attends school. Since Mexico conducts a decennial cen-
sus, population counts between censuses must be extrapolated. Primary and secondary enrollment data are
drawn from the World Bank WorldData country data series, which in turn rely on UNESCO estimates. I also
estimate state secondary enrollment rates for the census years of 1980 and 1990. Enrollment rates give a broad
measure of the population’s participation in the school- ing system, while retention, continuation and efficiency
rates measure the progress of those who have already entered the system.
11
SEP data for the school years 1970–71 to 1975–76 report student enrollments for only one undetermined point in the
school year. Thus none of the schooling indicators can be calcu- lated before the 1976–77 school year.
Fig. 2. a Retention rates, academic sequence b Retention
rates, vocational levels c Continuation rates d Efficiency rates. Source: Secretary of Public Education, derived from pub-
lished data.
187 M. Binder Economics of Education Review 18 1999 183–199
5.2. Economic indicators The human capital framework calls for measures of
income and the costs and benefits of schooling. For income, I use GDP in constant U.S. dollars from the
World Bank WorldData series.
12
Since annual data on direct school costs are not available, the price of school-
ing is determined by opportunity costs alone.
13
The stud- ies of United States and British enrollment use unem-
ployment rates to proxy opportunity costs. In Mexico, however, official unemployment rates are quite low
usually under 4 per cent for the time period studied here and not considered a reliable indicator of job mar-
ket conditions, since all those who worked at least one hour in any income-generating activity in the week pre-
ceding the survey are considered employed. I therefore use GDP growth rates as measures of the expansion and
contraction of the economy to proxy opportunity costs.
14
I will refer to the relationship between the growth rates and schooling as the price effect.
Another data issue concerns a mismatch in timing between the calendar year, for which economic variables
are reported, and the school year. The school year runs from September through June and thus spans two calen-
dar years. I use growth rates from both years spanned and GDP for the year in which the school year ends.
15
The growth rate for the year in which the school year ends is included in the schooling series in Fig. 2a, b, c
and d. Note that the schooling indicators appear to move counter-cyclically, especially in Fig. 2b and c.
Unfortunately, I could locate no data that provide wage differentials by schooling level on an annual basis
for the period covered. Thus the estimated effects of the income and price measures may also include effects of
changes in schooling wage differentials. As noted earlier, these differentials tend to move counter-cyclically. Thus
the negative schooling impact of falling income during a recession may be underestimated and the positive
schooling impact of falling opportunity costs may be
12
Specifications which used per capita income gave similar results to those reported below.
13
The bias introduced by this omission cannot be charac- terized a priori, since the correlation between direct and opport-
unity costs is unknown.
14
It is a stylized fact that unemployment rises in the downsw- ing of a business cycle and falls with a lag in upswings Lilien
and Hall, 1986. The mapping between economic contraction and expansion and opportunity costs is therefore not exact.
15
I also experimented with an alternative specification for addressing the time mismatch, using the average of the GDP
and GDP growth rates for the two calendar years spanned by the school year. This specification gave similar results to those
reported here.
overestimated depending on the correlation of these vari- ables with the omitted wage-differential variable.
16
Finally, a trend variable is needed to control the possi- bility that the schooling indicators trend independently
from the economic variables included.
17
The following reduced-form equation provides a start- ing point for the analysis:
logs 5 b 1
b
1
logGDP 1 b
2
DGDP
BEGIN
1 1
b
3
DGDP
END
1 b
4
TREND 1 m where s is a schooling indicator retention, continuation,
efficiency or enrollment rate for a given school level, GDP measures income, DGDP
BEGIN
and DGDP
END
measure the opportunity cost or price effect for the calen- dar years in which the school year begins and ends, and
TREND is a time-varying trend variable. The bs are coefficients and m is an error term. The semi-log form
allows b
1
to be interpreted as the income elasticity of the schooling indicator and b
2
and b
3
to be read directly as per cent changes in the schooling indicator.
18
6. Economic conditions and national schooling indicators
