Arguments that rise in public school funding provides few
significant benefits for pupils, contrast other evidences on the school
quality. First, some studies have found significantly positive relationship
between school quality and earnings.[1]
Second, the development of black-white relative earnings during the past
century has been attributed to growth in the relative black school quality. [2]
There are various explanations for such evidences.
Researches on earnings and school quality are mainly centered on the
correlation between school attributes (such as per capita expenditure) and the
mean earnings of students in a school district. With the argument that family
background variables have an impact on both education expenditures and labor
market earnings, the correlation of school quality and earnings is likely
specious. On the contrary, some can claim that test scores are a lacking
measure of school performance, since earnings and test scores are not identical
though they may be correlated. Those having an impact on following labor market
achievement may have an insignificant effect on test scores.
This research deals with the analysis
on the link between earnings and school quality for men born between 1920 and
1949 using samples from the 1980 census.
The findings imply a significant variation in the rate of
return to education across individuals with varying states and times of birth.
A great deal of these differences is related with the disparities in the school
quality. Those who are educated in schools having lower student-teacher ratios
and greater relative teacher wages have higher rates of return. Furthermore,
returns are found to be related to higher teacher education. However, with
school quality measure constant, there is no evidence that the returns to
education are linked to income or levels of schooling of the parents'
generation.
The focal point of the paper is the relation between school
quality and the education rate of return. Increase in the earnings and
schoolings relationship does not essentially boost mean earnings, for instance,
earnings gained by more educated employees might be at the expense of the less
educated. Meanwhile, variations in school quality have an impact on the mean
education level and on the marginal return to additional school years.
Furthermore, holding constant the permanent discrepancies among individuals
born in different states, there is a significant positive school quality impact
on both the mean school years and mean student earnings. Also by augmenting the
years of completed education, as well as each school year return, changes in
school quality have an effect on succeeding income.
I. An Empirical
Framework for Modeling Returns to Schooling
The goal here is to link the returns to education of
individuals attended schools in various states to the public school system
attributes. It is assumed that individuals are educated in their state of birth
and private schooling is ignored.
The equation used for earnings is a linear combination of
the effects of birth of state and region of residence, which allow the observed
rates of return to schooling to differ due to variation in the return to
education across various regional labor markets and due to variation in the
rate of return to education gained by individuals in a certain state of birth
and cohort in any labor market.[3]
By including the relations between state of birth and schooling and another set
of relations between region of residence and education, the state of
birth-specific input to the return to education is determined by individuals
who attended school in one state and transferred to another region. In
addition, it was assumed that the state of birth components in the return to
education relies on the public school quality, and also potentially on a series
of state-specific constants, which is a linear function of the quality of
education in a certain state during the period that a specific cohort went to
school and the state of birth effects. In this condition, the latter absorbs
any variations in the returns to education such as those from discrepancies in
the distributions of ability across states.
The paper first estimates the mean rate of return to
education for individuals of a specific cohort born in a particular state, while
holding constant state of birth, state of residence, and any regional
dissimilarity in the return to education. Afterwards, a second-step regression
is used to link the estimated rates of return to the quality variables. The
procedure has quite a few significant advantages:
1. It
offers convenient cut of the data and the demonstration of the diversity in the
returns to education and their connection to measures of school quality.
2. It
aids the general models of the earnings function
3. The
simple correction for the interstate movement of children can be included.
It also comes with certain a disadvantage. Particularly with
the two-step procedure the cohorts should be defined quite generally to acquire
reliable estimates of the state- and cohort-specific returns to education.
A. Functional
Form
The linear schooling-(log) earnings relation is broadly used
in applied studies of earnings. Such relation is more or less linear in pooled
samples (of individuals coming from various states and birth cohorts) but is
nonlinear for certain subsamples. Also, changes in the public school quality
alter the returns to elementary or secondary education more (or less) than the
returns to college. Hence, the return to education function condition should
allow for curves at 12 years of schooling.
Simple evidence on these issues was
attained through estimation of a set of unrestricted earnings-schooling models
from narrowly defined subsamples of individuals in the 1980 census.
Three general results were obtained:
1. For a specific cohort and state of birth
group, the earnings-education relation is roughly log-linear for education
level over the minimum threshold.
2. The threshold
differs broadly across states and over time within states, for instance, it is
fairly low for older cohorts and for individuals belonging in states having
lower mean educational attainment.
3. There is a
positive correlation between the mean educational attainment of a state of
birth and cohort group and the threshold point in their return to education
function. From this, and through additional estimation and comparison, a simple
empirical relation was observed: across various cohorts and states of birth and
various race groups, the threshold point correspond roughly to the grade level
achieved by the lower 20 percent of the
education distribution of employees.
Due to the pattern of the nonparametric
estimates of the return to education function for the bigger states, the rest
of the paper focuses on estimating the return to education for years of
education over the second percentile of the education distribution of an
individual's state of birth and cohort. It is important to mention that the
estimated rates of return to years of schooling over the threshold prove to be
rather comparable to the estimated returns from a conventional log-linear
earnings-schooling model.
II. Measures of the
Quality of Public Schooling
Data on the public school system
attributes in each state are available on a semi-yearly basis from 1918 to 1958
in the Biennial Survey of Education and yearly since 1960 in the Digest
of Education Statistics. The Office of Education tabularizes the
outputs of questionnaires submitted to the education state offices, concerning
the statewide enrollment, revenues, number of teaching positions, length of
school term, mean teacher wages, and other variables.
The available data provided information
on three main attributes: enrolled student to teacher ratio in the state, the
mean length of the school term, and mean yearly teacher wages. The three
hypotheses made were:
1. The rise in term
length raises the quantity of materials dealt in a school year, thus boosting
the economic value of extra years of education.
2. The decline in
the student-teacher ratio enhances the classroom instruction quality which
leads to greater returns for each completed school year.
3. Higher teacher
wages allows schools to draw in and retain more qualified and highly motivated
teachers, which results to better classroom instruction and greater returns to
education.
Previous authors, such as Morgan and
Sirageldin (1968), Johnson and Stafford (1973), Wachtel (1976), and Rizzuto and
Wachtel (1980), have applied total expenditures per student as an index of
school quality. However, it seems that the schooling quality is more directly
related to indexes of student-teacher ratios and teacher wages than to total
expenditures per student. This finding was also implied in Welch (1966).
Nonetheless, approximately 60 percent of total education spending is from
teacher salaries. Since the per capita spending on teaching wages is just the
ratio of the mean teacher salary to the student-teacher ratio, the gap in teacher wages and student-teacher
ratios account for a majority of the differences in total spending per student.
Also, with the geographic deviations in
the cost of living and in the level of alternative salaries accessible to
possible teachers, it appears unlikely that the level of teacher salaries is a
proper index of teacher quality in different states. Therefore teacher salaries
are normalized in each state by the level of mean state salaries. In addition,
the changing scope of the social security salary index and with the need for
index-linking unequal salary series, the trend in the mean relative teacher
wages during the sample period is removed. In particular, the relative teacher
salary in each state is divided by the national mean of this ratio in the same
year. By doing so any time-series inconsistency in the mean value of relative
teacher wages are eliminated, while the interstate variation in relative
teacher wages is preserved at a point in time.
The three school quality measures are
reported for three cohorts of students born:
a.
between
1920 and 1929;
b.
between
1930 and 1939;
c.
between
1940 and 1949.
The assumptions for the means are that
each individual goes into public school for 12 years and that the number of
annual birth in any cohort is constant. By assuming 12 years of schooling, the
potential quality of the education accessible to individuals in a particular
cohort and abstract from the likely endogeneity of school quality and mean
schooling are measured. However, the quality measures are found to be nearly
equal when the averages are estimated by means of individual-specific schooling
years for the men in each group.
Further results indicate considerable
difference in school quality across states, while there is a much lesser
interstate difference in the school quality measures for the later cohorts. The
latter mainly applies in the term length variable, which is observed in a
narrow range for individuals born in the later cohort. Meanwhile, the trends in
school quality during the sample period differ extensively across states.
III. Returns to
Education by Cohort and State of Birth for White Men
Presented in this section are the estimates of the mean
education rates of return for white men born in the 48 mainland states and the
District of Columbia from 1920 to 1949. The samples are divided into three
10-year birth groups and estimated rates of return for 147 individual states
and age groups were obtained
A. Rates
of Return to Education by State and Cohort
The estimated education rates of return
are derived from three age group-specific regressions fitted to separate data
on log weekly earnings for 1979. The explanatory variables in each regression
comprise a set of indicator variables for an individual's current state of
residence and individual’s state of birth, and hold for possible experience and
its square, marital status, and residence within a standard metropolitan
statistical area (SMSA)). The models also include interactions among nine
present region-of-residence dummies and completed schooling in order to manage
the differences in the education rate of return across various labor markets.
Lastly, the models contain state of birth-specific interactions with individual
schooling. Such interactions are viewed as estimates for the education rate of
return for individuals belonging to certain cohort and state. Regardless of having
the estimates attained from highly parameterized models, having 158 explanatory variables in the
regression equation for each group, the estimates are fairly accurate, with
standard errors ranging from 0.1-0.3
percent in the majority of states. The resulting patterns indicate
that the mean rates of return to education are much lower for older employees: 5.1 percent annually for age
group of 50-59, in contrast to 7.4 percent for the age group of 30-39 in 1979. Meanwhile, the interstate distribution in returns
(adjusted for sampling error) suggests an opposing trend, in which it is
largest for the oldest group and smallest for the youngest.
Also, the estimated correlations imply
that returns to education are significantly related to all three school quality
measures. On the other hand, by dividing the states into three groups,
according to student-teacher ratio, the output shows that returns are greater
among states having lower student-teacher ratio provided that teacher wages are
controlled for, and greater among states having higher relative teacher salary,
holding the student-teacher ratio constant.
Another finding, as implied by the
resulting sampling error, suggest that
the inter-cohort variations in the returns to education are inaccurately
estimated for some of the smaller states. Hence, further observations show that
the rates of return to education increased more rapidly between the 1920-29 group and the 1940-49 group in states that
had a greater decline in student-teacher ratios.
B. Rates
of Return and the Quality of Schools
The models in this section rely on the
interstate co-variation between rates of return to education and measured
school quality in estimating the impact of the quality variables. The estimated
coefficients suggest significantly greater returns for the later cohorts:
roughly 1.2 percent per
decade. All three variables, student-teacher ratio, term length, and the
relative teacher salary are robustly correlated with education return. However,
when the three quality variables are jointly included, the impact of term
length and the student-teacher ratio is smaller and less accurately determined.
This is most likely due to the multi-collinearity across the quality variables.
The sizes of the estimated school
quality coefficients suggest a quantitatively significant school quality impact
on the return to education. For instance, a reduction in the student-teacher
ratio by 10 pupils is related to a 0.9 percent rise in the return to years of
education beyond the threshold level. If the threshold is 8 years of education
and is impervious to the variation in school quality, then the decrease in the
student-teacher ratio will increase the earnings by 3.6 percent of high school
graduates. Likewise, a 30 percent raise in relative teacher pay is expected to
increase the rate of return to education by about 0.3 percent and the high
school graduates earnings by 1.2 percent, given that the threshold level of
schooling is constant at 8 years.
Regardless the joint significance of
the quality variables, they have a rather small contribution in explaining the
inter-cohort trend in returns to education. Models with consideration of state
effects, in comparison to those without, show that the quality variables
explain more of the inter-cohort trend in returns to education. However, the
cohort dummies are highly significant, and their exclusion results to a
considerable exaggeration of the quality effects.
Meanwhile, the larger mean rates of
return for younger employees do not essentially imply true cohort effects. If
relation between age and the return to education does exist, the estimated
cohort dummies baffle cohort and age.
In addition to the results showing
school quality variables explain somewhat little of the cohort effects, such
findings indicate that majority of the higher return to education noticed for
younger employees can be credited to age effects.
Lastly, in considering the estimated
state effects, they are found to be largely significant. The output also
implies that there is absence of several significant state-specific
determinants of the return to education in the analysis. Assessment of the
estimated state effects shows that returns to education are rather low for men
from South and in the North Central/Northwest regions and rather high for those
from Midwest and Northeast.
Such
finding for white men born in the southern states is quite unexpected, given
that the quality measures in the analysis pertains to the whole school system
for each state. States that functioned in an unintegrated school systems prior
to 1954 usually had lower student-teacher ratios, longer term lengths, and
higher teacher pay in white schools than in black schools (Card and Krueger,
1992). Thus, the mean quality measures with regards to entire student
enrollments understate the
quality of the white schools in these states. Nonetheless, when a dummy
variable for the segregated states is included in the model, the results are
not in agreement with a simple mismeasurement hypothesis for the quality of
white schools in the South and instead, they indicate that other measures of
quality were considerably lower in the South or that other attributes of the
southern states have an effect on the returns to education.
C. Other
Characteristics of Schools and States
In each case in analyzing the impact of other school and
state-level attributes on the returns to education, three basic school quality
measures and state-specific fixed effects are included. An observation is that
the estimated coefficients of the school quality variables are greatly unchanged
by the inclusion of controls for other attributes, such as teacher and private
school characteristics, mean income in the state, and educational
accomplishment.
Meanwhile, several prior studies have
observed a strong relationship between aspects of family background, such as
parental schooling and earning, and the student performance on standardized
tests. If these family background attributes are associated with school quality
and if such characteristics eventually vary significantly within states, the
estimates of the school quality effect may be perplexed by the impact of family
background variables.
Finally, the estimated impacts of the
three major school quality variables are impervious to the addition of such
family background variables.
a. Teacher
Characteristics
In assessing the role of teacher
attributes on the returns to education, the portion of male teachers is
considered since controlling for the level of teacher wages, one might predict
the teaching staff quality to differ given the percentage of male teachers. Presumably,
if female teachers were paid lower compared to identical males for the period
of 1926-66, one can
perceive the fraction of male teachers as an alternative for lower-quality
teachers. On the other hand, the percentage of male teachers can be taken as an
indicator of higher nonwage return or better working environment within the
schools, which would potentially draw in relatively more men into teaching,
provided that the relative wages are controlled for.
The findings suggest that a rise in the
portion of male teachers in the state has a significant negative effect on
students' return to schooling. Also, a rise in the percentage of male teachers
(in 1966) is linked to a 0.8-percentage-point decline in the return to years of
schooling beyond the threshold. Moreover, it is difficult to determine whether
the percentage of male teachers affects the return to education because males
are less efficient teachers, or via some other channel.
Meanwhile, the estimated coefficient of
average teacher education is positive and statistically significant, while the
estimated impact of teachers' experience is insignificant. On the other hand
the student-teacher ratio and relative teacher salary remain in being
significant indicators of the return to education when such teacher quality
variables are added. Furthermore, the study’s estimated coefficients are barely
influenced by the inclusion of the teacher quality variables. Lastly, the
inclusion of controls for the mean education and experience of teachers
scarcely alters the estimated coefficient of the percentage of male teachers.
b. Educational
Distribution
In an another model the estimates of
the high school and college completion rates per state of birth and cohort
group are included as to control for portion of a given cohort. For instance,
assuming that more schools are established in a state, this leads to a
reduction in the travel time for pupils and in the student-teacher ratio.
Assuming further that individuals
differ in their expected returns to education and that as more schools are
constructed several students having lower expected returns to education remain
in school longer. Hence, improvements in school quality can be considered to be
correlated with lower returns
to education, suggesting a negative correlation between the mean return rate to
education and the percentage of individuals having higher education. In
addition, mean educational attainment and measures of education quality are
strongly and positively correlated. This indicates that if rates of return
differ systematically across the population and if individuals having higher
expected returns opt for further education, there exist a potential downward
bias in the estimates of the impact of schooling quality on returns to education.
This can be managed partially by including measures of the proportion of
individuals at higher education levels in each cohort.
Moreover, high school graduation rate
and the college graduation rate do not have a statistically significant impact
on the return to education. Also, the former holds a negative coefficient,
while the college graduation rate has a little, positive coefficient. These
findings, however, offer no evidence that students enter themselves into
various levels of schooling based on different expected returns to education.
Meanwhile, with regards to the impact
of the dispersion in educational achievement in a state on the return to
schooling, increases in school quality are linked with lower dispersion in the
schooling distribution.
c. Private
Schools
Although not all attends public school,
the school quality measures are based on the public school system attributes in
each state. For the period 1920 to 1960, the percentage of students attending
private schools increased, however, this range of the fraction of private
enrollments differs across states. The existence of private schools brings in
two possible sources of unobserved difference in school quality:
1. Private schools
may be relatively more effective than public schools
2. Private schools
may possibly have different employment levels, teacher wages, and term lengths
in comparison to public schools.
To deal with these issues, data on
private school enrollments and student-teacher ratios by state and cohort are
gathered. The student-teacher ratio data in private schools is constrained to
Catholic schools.
The findings show that when
student-teacher ratios, term length, and relative teacher wages in the public
schools are held constant, the private school enrollment variable coefficient
is numerically small and statistically insignificant. These imply that
increases in private school enrollment do not by themselves impact returns to
schooling.
Meanwhile, with the exemption of the
term length variable, the school quality variables are statistically
significant. On the contrary, the variables measuring family background
attributes, student educational attainment, and private school attendance
typically have small and insignificant effects.
d. Evidence
for Black and White Men Born in the South
Regardless the limited evidence of
family background effects in the return to schooling, the wide disparity in
school quality for men belonging to different states and cohorts seemingly
reveals gaps in salaries and preferences for schooling over time and across
states. A possibly more appropriate test of the school quality effects is based
on the earnings experiences of blacks, since swift school quality developments
that happened from 1920 and 1960 for black schools of the
segregated southern states present an arguably exogenous experiment for
assessing the impacts of school quality.
The findings from assessing the impact
of school quality on the returns to education for southern-born black and white
men were employed in northern cities. Itseems to be qualitatively and
quantitatively similar to those in the previous sections. This gives additional
evidence for an underlying interpretation of the school quality effects in
previous sections.
D. Adjustments
for Mobility of Preschool and School-Age Children
So far, the analyses have implicitly
assumed that an individual goes to the public school in his state of birth.
Interstate mobility of preschool and school-age children poses a concern
comparable to measurement error in the interpretation of the returns to schooling
for those born in a particular state. It is practical to focus on a single
cohort and to consider that individuals are enrolled in only one state.
The results of interstate
mobility-adjusted model seem to have minor impact on the qualitative and
quantitative conclusions of the previous section. This also implies somewhat
low mobility rates of preschool and school-age children and the lack of a
strong link between interstate mobility and the geographic pattern of the
measured quality of schooling.
E. Log-Linear
Specification
A log-linear specification is broadly
used in the literature, and it is useful in verifying the sensitivity of the
estimates to the functional form assumptions. However, regardless of
specification, the school quality variables have statistically significant and
considerable impacts on the return to schooling. Such findings imply that the
connection between school quality and the return to schooling is not primarily
sensitive to the specification used to estimate the return to education.
IV. The Effects of
School Quality on Education and Earnings
On one hand the advantage of analyzing
the relationship of school quality and the return to schooling is being able to
control for overlooked differences across state of birth groups and cohorts. Background factors that augment income of
individuals of a certain group are absorbed by the cohort-specific state of
birth impacts included in initial equation. On the other hand, the disadvantage of focusing on the return to
schooling is that variations in school quality may just expand the earnings
distribution with no increase in the mean income. It is even possible that
changes in school quality modify the schooling distribution, and the slope of
the earnings-schooling relation, without impact on the earnings distribution.
In exploring these concerns, there are
two considerations:
1. Analysis on the
effect of changes in school quality on the location and shape of the
earnings-schooling relationship.
2. Presentation of
simple reduced-form evidence on the relationship between school quality and the
levels of education and earnings.
However in interpreting the result, it
must be kept in mind that as opposed to the analysis of the returns to
schooling, the influences of school quality on the distribution of education
and on the levels of earnings cannot be determined in models having
unrestricted cohort-specific state of birth effects..
A. Location
and Shape of the Earnings-Education Relationship
Given the assumption that the
educational distribution is not affected by a decline in class size, there are
two considerations,
1.
The
schooling level attained by those belonging in the second percentile of the
education distribution rises as class size decreases.
2.
A
decline in the student-teacher ratio is linked with a small and statistically
insignificant upward shift in the intercepts of the earnings-education
relationship.
A regression of the state of
birth-specific intercepts of the earnings-schooling relation on state of birth
effects, cohort effects, and the three school quality variables produces
negative coefficients for the student-teacher ratio and for term length
variable, and positive for the relative teacher salary. The coefficients for
all three are small and statistically insignificant. Meanwhile, the quality
variables are found to be jointly insignificant.
The finding reflects that a decline in
the student-teacher ratio turns and shifts out the earnings-education relation,
with an intersect point about the twelfth or thirteenth grade level. Indeed,
narrowing the sample to those who have precisely 12 years of education, the
school quality seems to have an insignificant impact on earnings, indicating
that the intersection is around the twelfth grade. At a fixed education level, those with postsecondary schooling seem
to gain from enhanced school quality, while individual having below high school
education seem to earn less. On the other side, a rise in school quality
increases levels of education, mainly in the lower tail of the education
distribution. These returns to education compensate for the apparent losses due
to the shift in the earnings-schooling function, leading those in the lower
tail of the earnings distribution roughly as wealthy and those in the mid and
upper parts of the earnings distribution wealthier.
The result of the regression aimed
to further analyze the impacts of changes in school quality on those belonging
in the lower tail of the earnings distribution, showed little but generally positive and marginally significant
impacts of higher school quality on earnings of the tenth and twenty-fifth percentiles.
B. Reduced-Form
Estimates
In summarizing the school quality
effect on average income, several simple reduced-form estimates of the school
quality impact on log earnings and schooling were computed. These reduced-form
models consist of measures of school quality, state of residence and state of
birth effects, and demographic variables such as age, age squared, and marital
status indicators and residence in an SMSA).
The results indicate that improvements
in school quality are due to increases in both average income and mean years of
schooling. Meanwhile, each of the quality variables is a significant
determinant of earnings and mean education, when each are included
individually. On the other hand, jointly, the pattern of coefficient estimates
is comparable to that in previous sections: the student-teacher ratio and the
relative teacher salary remain significant, and the term length variable is
insignificant. For the model wherein (log weekly earning as the dependent
variable) the exclusion of state of birth dummies yields greater school quality
effects. Meanwhile the exclusion of current state of residence effects lowers
the goodness of fit of the earnings model but has a small effect on the
magnitude of the school quality coefficients.
According to the estimates of the
majority of models, a decline in the student-teacher ratio by 10 pupils is
expected to increase mean earnings by about 4 percent and increase mean
schooling by 0.6 years. However, the 0.6-year rise in mean education is likely
to be perceived to raise earnings by 3.2 percent.
Meanwhile, the total gain in earnings
from a decline in the student-teacher ratio is somewhat 30 percent greater than
would be predicted on the basis of the rise in mean schooling alone. While, the
gain in earnings is approximately 40 percent greater than would be predicted
basing on the increase in schooling alone.
Finally two conclusions can be drawn
from the reduced-form relations between earnings, education, and school
quality.
1. Improvements in
school quality for the past century are due to rise in years of education and
average salary.
2. Increases in
earnings seem to show both a gain for the extra years of schooling and a rise
in the return for each existing year of schooling.
Both results must be adjusted by
inability to control for overlooked cohort-specific factors that may increase
the earnings of those from states having better schools in the reduced-form
models. Taking these considerations together with the evidence assembled on the
returns to schooling, there is strong support for the conclusion that
improvements in school quality lead to bigger earnings.
V. Conclusion and
Discussion
Men who attended schools in states
having better-quality school systems earn higher economic returns for their
years of education. Even though the evidence is essentially non-experimental,
the findings are perceived to be consistent with a causal interpretation of the
role of school quality, since:
1. The findings
were based on statistical models that hold constant any variations across state
of birth and cohort groups in the total earning levels.
2. Differences in
the rates of return to schooling gained by present residents in various regions
of the country were controlled for.
3. Any permanent
dissimilarity across states in the return to schooling gained by different
cohorts of men and for variations in family background measures (schooling and
parents' generation income) that may have an effect on subsequent labor market
performance is also controlled for.
4. The reduced-form
analysis verifies that improvements in school quality raise the mean student
earnings.
Hence the school quality effects are
not just redistributive, nor are they an artifact of shift in the distribution
of educational attainments.
The findings emphasize the paradox that
school quality seems to have a vital impact on labor market performance but is
generally assumed to have no effect on standardized achievement tests. However,
two current experimental studies of school attributes and test scores are
consistent with positive school quality effects.
1. A study suggests
that decline in the student-teacher ratio for elementary school pupils
significantly raise test scores on reading and math exams (Finn and Achilles
1990).
2. Another
randomized study shows that increasing the school term by offering additional
instruction during the summer has a positive impact on disadvantaged students'
test scores (Sipe, Grossman, and Milliner 1988).
Even though more is needed to be done
to resolve the available evidence, still, the success in the labor market is at
least as significant measurement in assessing the performance of the schooling
system as success on standardized tests. At the very least, the result of a
positive relationship between school quality and the economic returns to
schooling must have silenced those who claim that investments in the public
school system have no advantages for the pupils.
Source:
David Card and Alan Krueger, “Does School Quality Matter? Returns
to Education and the Characteristics of Public Schools in the United States”, Journal of Political Economy, Vol. 100,
No. 1. (February, 1992), pp. 1-40.
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