I. Introduction
The dissatisfaction over the inability of school policy to
enhance practice in education is directly linked to the knowledge regarding the
educational production process and underlying research on schools. While such
process has been thoroughly researched, definite policy recommendations flowing
from the research have been difficult to derive.[1]
The consistent result from the various studies that has a
direct application to school policy is that schools do differ significantly in
“quality”. However the variations in quality do not appear to reflect the
differences in the commonly measured school and teacher characteristics,
rather, they seem to stem from the disparities in teacher “skills” that defy
detailed description, but that possibly can be observed directly.
The economics research on schooling is empirical in nature,
and an understanding of its results should start with a basic conceptual
educational process model. Economic models of production theory and firm
behavior are natural starting points. However, little direct assistance is
given by the standard textbook formulations or classic industry and aggregate
production function specifications since they’re rarely designed to handle
detailed policy queries that have been the focal point to investigation of
schooling. After adjusting the standard framework to account for the policy
purposes, the measurement issues, the schools incentive structures and so on,
the resulting models may be amply different that a new nomenclature is
practical. The most crucial modification involves interpretations of economic
efficiency.
A. Limits
of the Study
Focusing on the schools’ production and efficiency features
in contrast to the vital uses of education, the study deals with the research
on the economics of education and schooling and investigate past results and
the major gaps in it. On the other hand, due to the excellent reviews of “human
capital”, such area is particularly understated regardless the fact that human
capital investment and economics of educations are at time treated
synonymously. Note that the review focuses on public education in the United
States.
Economic reviews of elementary and secondary education have
focused on production processes, public finance questions on governmental
support and to a lesser degree, labor markets for teachers, cost-benefit
analyses of specific programs, and public-private choices. Meanwhile, higher
schooling economic reviews have been greatly centered on distributional questions
with regards to access and costs experienced by various groups with
governmental subsidy policies, and with attendance decisions. Furthermore, no
interest has been provided to production processes or the analysis of specific
programs.
B. The
Elementary and Secondary School Sector
1. Expenditures
The total spending on elementary and
secondary education in the United States is presently (in 1983) roughly about 4
percent of gross national product. The rise in the expenditure percent of GNP
peaked in 1970 with 4.6 percent (from a 3.6 percent in 1960), and followed by a
steady rise of per student expenditure for the succeeding years. This trend has
pushed up the resources entering into elementary and secondary schools.
Two major changes over the past quarter
of a century in the schools’ funding source:
a. Federal
funding doubled from 1960 going to 1970, and followed by a slow growth before a
decline during the 1980s.
b. Due to
a series of legal and legislative challenges to the use of local property taxes
as the main funding source in the 70s, the funding of local schools was changed
extensively. This caused a stable rise
in the level of support from the state revenue sources, but with a
corresponding drop in the support of schools from local revenues.
In addition, while there is a small
amount of governmental support for private schools, there is also a small
amount of nongovernmental support for the public schools.
2. Enrollments
There are about roughly 45 million
students attending schools. Elementary school enrollment peaked in the late
1960s, while the height of high school enrollment was in the mid-1970s. From
1970 and 1980 the enrollment in total dropped by about 10 percent, however, at
the same time the number of classroom teachers actually rose by roughly 7 percent.
Private school enrollments had a
decrease in the 1960s and since then remained at a steady proportion of total
enrollment. The decline hugely reflects the decrease of enrollment in Catholic
schools. In the 1960, Catholic schools represented roughly 90 percent of
private school enrollment, yet the rate declined to 63 percent in the 1980s, as
21 percent is accounted by schools affiliated with other religion, and the 16
percent to schools with no religious affiliation.
3. Performance
Since the 1960s, there seems to be
little changes with regards to rates of graduation and going to college.
Many have noted the consistent rise in
educational attainment of the labor force without recognizing that since before
1970 there is a steady graduation and college attendance behavior.
Most of the attention provided to
schools links performance to standardized tests such as Scholastic Aptitude
Test (SAT). Since the absolute scores have little significance, the evaluations
are done in terms of standard deviations of student performance, wherein it can
be viewed as percentile comparisons by means of normal distribution.
Although it has been observed that over
the last 15 years there has been constant narrowing of the gap in test scores
between blacks and nonminority pupils, with such trend being apparent on almost
all tests, including SATs, the spread between minority and nonminority students
remain sizable.
4. Public
School Inputs
The most remarkable change in the
school operation that came along with the changes in student performance is the
increase in spending per pupil. The 1983 spending for current services per
public school student enrolled was 135 percent in real terms greater than in
1960. This equates to a compound annual growth rate of real expenditure of 3.8
percent. Aggregate expenditures (inclusive of capital spending, and interest on
debt) had a rather lower growth due to capital spending was declining share of
the total.
A crucial factor of the growth in the
expenditure per pupil is the total drop in student-teacher ratios – recall that
there was a rise in the number of classroom teachers at the same time when
there were a decreasing number of enrollments.
Though it is sometimes emphasized that
the drop in student-teacher ratios is simply a manifestation of the effort to
sustain overall teacher employment amidst the decline in enrollments, this
appear somewhat conflicting with the fact that class size wanes prior to total
enrollment gets smaller.
Additionally, teacher attributes have
also changed remarkably, example (and most notable) is the aging of the current
teacher force. On average teachers reached 13 years of experience, from a low
of 8 years.
Recognizing this stability in the
teacher force and the state regulations and financial incentives of teacher
salary schedules, the fraction of teachers having a master’s degree or higher
doubled between 1966 and 1983. In 1983, more than half of public school
teachers held at least a master’s degree.
However, the case is different for the
teachers’ salaries in which after dramatically rising during the 1960s it later
fell in real terms throughout the 1970s. Such decline in mean wages is more
striking when combined with the rise in experience and amount of graduate
training of teachers since both components will boost wages.
5. The
Puzzle
The most significant puzzle is that the
consistently increasing costs and “quality” of the school inputs seem to be
unsurpassed by the progress in the student performance.
C. Overview
Input-output or “cost-quality” analyses are alternative
terms for the studies of educational production functions which observe the
link among the various inputs into and output of the educational process.
Understanding of the functions of production and the prices
for each of the inputs provides a solution of the “least cost” set of inputs
which would yield any given output at minimum cost.
Although the production function is a powerful pedagogical
tool which in its basic form seems to be applicable to various industries, its
assumptions differ in the realities of education (for other field as well). In contrast
to the assumptions, the production function is unknown and ought to be
estimated using imperfect data; some significant inputs cannot be altered by
the decision maker; and any production function estimates will be subject to
considerable ambiguity. However, unlike in other industries, using production
function to education has its immediate application to policy consideration.
The roots of educational production function analysis is
usually traced to Equality of Educational
Opportunity, known as the “Coleman Report” (James Coleman et al. 1966),
which showed that for the differences in student’s performance, it is not the
differences in schools that seems to be important, but the family background
and the characteristics of other students in the school. Such finding received
extensive criticism, policy discussion and further research. Even though the
report has been cited in several present studies it is held to be seriously
flawed and its significance is more with regards to intellectual history and
not in the insights into school educational process.
Overall, the production function approach shows a general
feedback against using quantitative education and school evaluations. In
addition, it shows the concern about legitimate analytical problems or
misinterpretations of the outputs of specific studies.
II. Conceptual and
Specification Issues
The underlying model of the analysis:
- the
output of the educational process which is the achievement of the individual
students is directly related to a set of inputs
- some
of the inputs such as the school, teachers, and curricula attributes are
directly controlled by policy makers
- other
inputs such as those of families and friends or innate bequest of pupils are
not generally controlled
In addition, though the achievement may be discretely
measured, the educational process is cumulative and some of the past inputs
affect current levels of achievement.
A. Specification
and Measurement of Output
Educational studies focus on “quality” differences.
Most studies on educational production relationships assess
output commonly though standardized achievement test scores, and some use
student attitudes, school attendance rates, and college continuation or dropout
rates. On the other hand, the measures used are generally proxies for more
essential outcomes.
Concern about the
school performance is directly related to the seeming school significance in
having an impact on students’ ability to perform in and cope with society after
they exit the school. Although it was not frequently articulated the theory is
that more education makes people more healthy, wealthy and wise. Still,
overall, empirical studies substantiate the correlation between higher levels
of education and positive characteristics after schooling. However the analytic
predicament is that post education outcomes cannot be contemporaneously
assessed with the schooling. Considerably the typical approach in schooling is
to analyze cross-sectional differences in measures that can act as proxies for
future performance.
A common starting point is an examination of how education
impacts labor market performance and other post schooling operations.
The two fundamental difficulties with existing studies on
post schooling outcomes for the production function analyses point of view are:
1. Focus
on quantity differences (time spent in schooling activities) in contrast to
quality differences makes hard to link the analysis directly.
2. The
conceptual foundation of the assumed improved performance of the more educated
is still uncertain, thus making the attempts complicated in directly measuring
any quality differences among pupils due to the little guidance on what to look
for.
The efforts in incorporating qualitative factors of
schooling into labor market research have been severely restricted by the
availability of data and the strict assumptions on school processes.
In previous studies, years of education and measures of
cognitive ability shows independent impact on earnings.
Another broad line of examination has been to include
measures of the attributes of individual schools directly into earnings
function. Two classes of such data include:
1. average
school expenditure data
2. measures
of specific school resources or teacher attributes in the earnings model
However such studies must assume that variations in spending
or in definite resources give an index of differences in quality.
Furthermore if the models also include measures of other
inputs into the educational process such as family or school attributes they
will attain biased estimates of the impact of school differences. Other studies
have considered:
- the
schooling’s impact on the political socialization and voting behavior
- the
connection between schooling and criminality
- the
input of education to economic growth
- the
impact of education on marriage and divorce
However these researches have not yet dealt with the
question: How do such outcomes vary in reaction to the variety in school
programs and processes?
As an overall strategy, one might unconventionally approach
the issues by considering what schooling characteristics were significant for
later success and then producing direct measures that could be attained during
the same time period with education. However the flaw of this strategy is the
superficiality of the conception of ideas of the mechanism by which schooling
influence productivity and subsequent experiences. Through various standardized
tests, cognitive skills were found to be chief contemporaneous measure of
schooling quality presently available. However it is not seen to be the only
and most important result of education in shaping the students’ success. Less
schooling may even be an advantage in occupations that are repetitive or may
only require manual skills.
The ambiguity of the source of education-earnings
relationships is also a focus of the “screening” facet of schooling, as the
educational sector may not necessarily enhance the students’ skills but may
simply recognize the more able. Screening entails that the social value of
schooling may be substantially less than the private value if schools are just
pinpointing the more gifted rather than actually modifying their skills.
The screening model has direct implications for measuring
school outcomes and examining educational production relationships. The school
output in a screening model is information about the relative student skills.
This would suggest that more interest should be given to distribution of
observed educational outcomes (rather than just the average) and their
relationship to the distribution of core skills. Moreover it might even
completely change the interpretation of some studies – schools with higher
dropout rates may actually provide better information.
B. Standardized
Test Scores
The most commonly used gauge in examining the educational
process is the standardized test scores, however, considerable ambiguity exists
about the suitability of using such test as outcome measures. Nonetheless,
performance on tests is being used to assess educational programs, and even
distribute funds.
Some additional arguments for the use of test scores as
outcome measures:
1. Test
score seems to be valued in and of themselves – educators tend to consider that
they are significant, albeit incomplete, measure of educations. In addition,
parents and decision makers seem to value higher test scores.
2. The
use of test scores links to continuation in education.
However, the variety of potential outcomes of schooling
implies that educational process may have numerous outputs - which some may be
poorly measured by test scores. In addition, the effectiveness of test scores
in gauging the contribution of schooling to later performance most likely
varies at different points in the educational process. Particularly, test
scores might be more suitable in the earlier levels, where the focus tends to
be on fundamental cognitive skills such as reading and arithmetic, than in the
subsequent levels.
The aim in gauging outputs of schooling is to find a
quantitative measure that is both readily available and linked to long-run
objectives of education.
C. Empirical
Formulation
Regardless the efforts to provide more details on the input
differences, studies are still bombarded with criticism on the specifications
of the factors. Portion of the criticism is brought about by the fact that the
choice of inputs is guided by the availability of data rather than by any
concepts of how the study is best conceived. However, most of the criticism
arises from the desire to apply findings to actual policy decisions.
The general conceptual model reflects the success of a given
student at a specific point in time as a function of the cumulative inputs of
family, friends, or other students, schools, and teachers. These “contributors”
also relate with each other and with the natural skills of the students.
Two points to be emphasized:
1. Inputs
must be significant to the student being analyzed
2. Educational
process must be considered as cumulative (inputs in the past have some lasting
impact, although their value diminishes over time)
Failure in realizing these points has most likely caused the
greatest problems in interpreting studies.
Empirical conditions have varied in details but they have
much in common:
1. Family
inputs: tend to be gauged by sociodemographic attributes (parental education,
salary, and family size)
2. Peer
inputs: normally aggregate summaries of the sociodemographic characteristics of
other pupils in the school
3. School
inputs: involves measures of the:
o teachers
(education level, experience, race, and so on);
o school
organization (class sizes, facilities, administrative spending, and so on)
o district/community
factors (average spending level)
Research has both focused on distinctions within a single
system and on distinctions across districts.
The focus of this study is on two essential options in
analysis:
1. whether
estimation is carried out in “level” form or “value-added” form
2. whether
the teacher variations are measured implicitly or explicitly
Two persistent problems occur when an achievement measure is
simply regressed on an available set of inputs. These problems result to biases
in the estimated effects of school inputs:
1. Sufficient
measures of natural abilities have never been available
2. While
education is cumulative, normally only contemporaneous measures of inputs are
available, which leads to measurement and specification errors
The imprecise depiction of the stream of educational inputs
is likely the more severe in terms of biased estimation of school policy
factors.
In addition both cases may be aided if one uses the
“value-added” versus “level” form in estimation. So if the achievement
relationship holds at different points in time, it is likely to focus on
exactly what happened educationally between those points when outcomes are
measured.
Likewise the significance of the omitted factors is reduced
if the model is estimated in value-added form since any “level” impacts have
already been included by entering accomplishment and only “growth” impacts of
innate abilities have been removed.
In general, the value-added
estimation has been possible only when outcomes have been gauged through
standardized test scores – this arises merely from data availability since a
one-time data collection attempt using school record can still provide
intertemporal information through the history enclosed in normal records.
Another “strategic” issue in
estimation is the method of characterizing teacher and school inputs. The most
common approach is to recognize a parsimonious set of variables reflecting the
central inputs and policy decision in the schools. Possible school signifiers
include class sizes, backgrounds and experiences of teachers, curricula used,
spending on administration and so on. This however faces a plausibly rigorous
problem, typical example is that if the choice of inputs does not involve the
most significant ones or if the inputs have an inconsistent impact on
performance, the regression estimates will be hard to interpret.
On the other side having large
sample data that allows multiple observations of students given the same
teachers, it is possible to estimate the teachers’ impacts implicitly rather than
explicitly. For example, if there is a sample of “otherwise identical” pupils
who varied only in the teachers they had, a direct estimate of the efficiency
of each teacher would be the mean performance of all the students each teacher
taught. Although attaining such sample of identical students is evidently
implausible, statistical analysis can be used to adjust for the differences
among students.
The study of “total teacher effects”
is the approach wherein teacher-specific intercepts, which can be estimated by
using a dummy variable for each teacher, and are interpreted as the average
achievement of students of a given teacher after allowing for other differences
among the students.
Problem of this approach:
- The
estimation is found to present less information than a completely specified
explicit model, since it is not possible to distinguish the kinds of teachers
or teaching that are most efficient.
- It
needs large data requirements, which are only rarely met.
- For
the case wherein all students for a given teacher are together in the same
class, the estimates specify the joint impact of the teacher and the certain
classroom composition – thus the estimate’s interpretation is solely on the
effectiveness of teachers, but further interpretation requires additional
information or estimation work.
As for other areas of empirical studies, compromises are
often necessary between what is conceptually attractive and availability of
data.
III. Results
A. Do
Teachers Differ?
Since the publication of the Coleman Report, intense
discussion has surrounded the fundamental question of whether schools and
teachers are significant to the student educational performance. This idea
naturally follows from the Coleman Report, which is typically taken as result
in which differences in school resources explain a negligible portion of the
variation in students’ success. If this is true it would mean that it is not
significant which teacher a pupil had – something parents would have a
difficulty in accepting.
A number of studies’ unequivocal result is that teacher and
schools vary radically in their efficiency. Such finding provides a very
different impression from that left by the Coleman report and other later
studies – and the faulty notions have mainly resulted from a confusion between
the difficulty in explicitly measuring components of efficiency and true
effectiveness. Hence the existing measures of teacher and school attributes are
flawed thus are poor indicators of the schools’ true impact.
B. Summary
of Expenditure Relationships
It is desirable to be able to identify the teacher and
school aspects and attributes that are significant. Scholars have opposed the
factors that should be explicitly measured and included as inputs in the
educational production process. On the other side, in determining the basic
spending, there is a “core” set of factors that is almost generally observed.
About two-thirds of the total school expenditures are primarily instructional
spending, wherein its basic determinants in a district are teacher salaries
(teacher experience, teacher education), and class size.
According to the conventional knowledge (for the part of the
teacher) more education and more experience cost more and are assumed to be
beneficial; also, smaller classes (more teachers per pupil) must enhance
individual student learning. However the result of the study showed that at a 5
percent level, out of the 112 estimates of the impact of class size, merely 23
were statistically significant, and only 9 had the expected positive
significance.
In addition for the estimates for teacher experience, the
majority of the coefficients are found to be statistically insignificant.
However it at least has the large portion of its estimated coefficients having
the expected positive sign. However, if experience is a strong aspect in
teaching the results above are hardly overwhelming. Furthermore, due to likely
selection impacts they are faced with additional interpretative uncertainties.
Particularly, such positive correlation may stem from more senior teachers
having the ability to choose schools and classrooms with better students. Thus causality may move away from achievement
to experience and not the other way around.
A study that examined a single urban school system in the early 1970s
found that students’ race and socioeconomic background were systematically
related to the selection and transfer of teachers with different education and
level of experience.
The findings are remarkably consistent in seeing no strong
evidence that teacher student ratios, teacher education, or teacher experience
have a positive expected impact on student achievement. In addition, most data
do depict a strongly positive simple correlation between school spending and
achievement, but the strength of this relation vanishes when the differences in
family background are regulated.
Despite the inconsistencies, there is also a consistency to
the findings: there seems to be no strong or systematic relationship between
school spending and student performance.
However there are reasons to be cautious in interpreting
such evidence. For any individual
research, incomplete information, poor data quality, or flawed investigation could
distort the statistical result. Lastly, as in any research efforts, any of the
studies is open to some sort of dispute.
C. Other
Results
Various other school and nonschool aspects have been
studied:
1. Family
background: clearly crucial in explaining the discrepancies in success.
o More
educated and wealthier parents have children who on the average perform better.
o However
the extensive changes in birth and divorce rates have caused a concern on their
possible impacts on learning and achievement.
2. Peer
(or other student) attributes: this is important in taking into account school
desegregation where the concern is on the racial composition of the schools.
3. Wide
range of additional school and teacher measure:
a. Organizational
aspects of schools
b. Curricula
or educational process decisions
c. Time
spent by pupils on various subject matter
d. Teacher
information such as their cognitive abilities, family background, schooling,
majors, attitudes toward education and so on
e. Information
on school facility and school administrator and other employees
The closest thing to a consistent result among the research
is that “brighter” teachers – who perform well on verbal ability tests – do
better in the classroom; however there is no strong evidence to support this.
D. Teacher
Skill Differences
In the study of production relationships beyond education,
measures of organization and process are perceived to be irrelevant in
estimation. Production functions are deduced as the relation between inputs and
outputs mutatis mutandis. Information
on production potentials is seen as being publicly accessible in the form of
scientific and engineering knowledge, and production methods are reproducible
through blueprints and machinery. The likelihood of the players in the
production function making dynamic decisions on the process is not considered;
and the selection of the “best” course is assumed to be automatically made
after the choice of inputs. However the appropriateness of this framework is
questionable in the case of education.
Some facets of the educational process are innately hard to
separate from the attributes of individual teacher (for instance, classroom
management, methods of presenting abstract ideas, communication skills, and
etc.). From this, a serious problem arises both in the use of the overall
conceptual production theory model and in the interpretation of any estimated
impacts. Many educational decisions are made mainly by teachers and are
difficult to study, measure and replicate. Moreover, such decisions relate with
the attributes and skills of the individual teacher – such factors will be
referred to as “skill” differences.
Once the likelihood of skill differences is introduced,
defining just what “maximum probable output” may mean becomes problematic due
to the difficulty in determining the homogenous inputs. In other words it is
hard if not impossible to identify a few objective or subjective teacher
attributes that capture the systematic differences of both teacher backgrounds
and their idiosyncratic teaching style and methods. The empirical connotations
are that individual variables describing definite partial characteristics of
teacher skill are not likely to display systematic relations with student
performance (which is the measure of the teacher performance).
Although teacher skill differences are quite significant,
ability of teachers is not systematically correlated with the available
explicit measures of the teacher attributes. To reiterate, the effects of not
measuring teacher inputs explicitly should not be confused with teachers’
inefficiency.
An important sub-result of such study is that decision
makers might be able to determine with fair accuracy implicit differences in
skills among teachers. In a study it was found that principal’s teacher
assessments were highly correlated with total spending estimates – which for
many purposes, is nearly as good as the ability to determine differences among
teacher ex ante.
Although identification of skill differences does change the
interpretation of teacher and school inputs, it is still rational to take into
account the effect of measured teacher characteristics since many school
decisions such as hiring and wages are based on a set of these attributes. On
the other side, the nearly universal result that teacher’s graduate education
carries no systematic relationship to achievement, which may be interpreted as
an implication that current teacher training institutions, do not typically
change the skills of teachers. Likewise, the usual result that class size
doesn’t impact achievement may stem from complex (and unobserved) interactions
with the methods and instructional processes that teachers select. Hence,
though it is may be likely that smaller classes could be beneficial in specific
circumstances, it is also true that, in the context of school and teacher
operations, there is no evident gain.
E. Efficiency
in Schools
If schools are considered as institutions that maximize
student achievement, the earlier proof suggest that schools are economically
ineffective, since they pay for traits that are not systematically related to
achievement (assuming that schools are attempting to optimize student
performance). Such assumption may seem reasonable; however, complex objectives
of school official would lead to tempering this judgment.
The implication of public school inadequacy is not
surprising for two reasons:
1. Educational
decision makers are actually not guided by incentives to maximize profits or to
save on costs.
2. They
may not comprehend the production process, thus cannot be expected to be on the
production frontier.
Hence much of the maximization part of the theory of the
company and competitive markets is debatable in the case of governmental supply
in quasi-monopoly situations.
In addition, in terms of current school operation, it may be
concluded that school spending is unrelated to school performance. Large school
spending per student gives little information on whether or not it performs
well with respect to value added to students.
Past education debates have distorted any differences
between economic effectiveness (the proper choice of combination of inputs
given its prices and the production function) and technical efficiency
(operating in the production frontier). Taking into account technical
efficiency is more complex.
The idea of skill differences recognizes that individual
having the same measured attributes make a series of crucial production
decision that are tricky to identify, measure, and model; consequently, this
explains same measured inputs yielding a variety of outputs.
IV. Some Policy
Implications
The finding that schools function in an economically
ineffective manner has clear implications for school policy. The most obvious
is that raised spending alone offers no universal promise for enhancing
education. Hence a simple proposal would be to stop obliging and paying for
things that do not matter.
Furthermore, there is little obvious merit for schools to
follow their ubiquitous attempt for reduced class sizes. Teachers shouldn’t
also be required to take graduate course just to satisfy occupancy conditions
or to get an additional wage increase as more teacher experience alone does not
appear to have much value.
However each of the statements has its limitations as there
is no evidence of such to be universally applicable.
Teacher salary provides another set of policy issues:
1. Level of pay
o Many
have argued that the rewards of teaching are so low that it is not surprising
that the best graduates are not interested in teaching
2. Distribution
of pay
o In
most school system, salary schedules are tightly related to the education
levels accomplished by the teachers and years of teaching experience. Wage is
not linked to specialty (Math teachers have the same income as English
teachers), nor to grade level.
Linking pay to performance is a crucial element of some of
the comprehensive reforms, and previous evidence recommends that a “merit pay”
system is appropriate since there are substantial differences among teachers.
However the main stand against merit pay is that objective assessment is tricky
and hence there is always a chance that political and other influences may
affect pay determination.
The more difficult problem is to take into consideration
such system and actually implement it because:
1. The
current pay system might be a standard depiction of the inflexible rules that
are said to distinguish internal labor markets, and they definitely possess the
impact of lowering any direct competition among teachers.
2. Principals
appear to be able to distinguish good teachers when nothing is at stake, but
whether they would make such conclusion if their assessment mattered is
unknown.
3. Restructuring
of salary would cause a direct clash with teachers’ unions.
There is no absolute standard for setting teachers’
salaries; still raising all wages would almost undoubtedly draw more able
people into teaching. However, three factors must be remembered:
1. The
ability to change the teaching force is controlled by vacancies at schools
o If
there is a delay between choosing a profession in college and becoming trained
for it and if future turnover stays at current levels, it would take long after
alterations in general wages took place before any crucial change in the
teacher force could be determined
2. Current
constraints imposed by state certification requirement, hinder the entry of new
people into the profession (Murnane, 1985).
3. If the
pay structure considers no information about competing demands for specialties,
substantial inadequacy must always be present:
o Those
in the “low demand” areas will be overpaid in comparison to what is needed to
cover sufficient supply into teaching or people in “high demand” field will
tend to be of lesser quality comparing it to low demand field.
The whole area of state certification and educational
regulations is exposed to considerable question, specifically given the facts
above. States pressure teachers to pursue graduate degrees – an uncertain
restriction as evidences show lack of efficiency and costly since school
systems then give higher salaries to these teachers.
Many limitations in hiring, promotions, and so forth are
found in contracts and local regulations. These have similar restraining
impacts yet it seems likely that the more harmful ones can be eliminated
through the bargaining process. However, the union’s influence on salaries and
spending and other employment requirements is still uncertain.
Lastly, it is helpful to take in to account the financing of
local school systems, as there are many great different funding schemes by
which states support local schools.
Much of the discussion is based fully on a conjecture that
per student spending is the appropriate focus for policy.
One may argue that altering current financing formulae would
simply have distributional results since spending variations do not relay to
the performance of different school systems. Moreover, the politics of
redistribution tend to increase total expenditure – states find it hard to
lessen the financing for one district in for the benefit of another, thus they
end up bringing the low spending districts up to the level of high spending
districts. Therefore the reactions of states to challenges to their school
financing are to raise the amount of economic inefficiency in the system.
The last policy area that is almost but not precisely
discussed by the research is the: public versus private school debate. A likely
response to the notion that public schools need improving would be a set of
measures that has been suggested to promote further private school competition.
The concept of school vouchers, originally recommended by Milton Friedman
(1962) has always had some appeal to economist since it would encourage more
individual choice and competition.
A study by Coleman, Thomas, Hoffer, and Kilgore (1982)
basically contradicted the public and private school student performance and
concluded that private school consistently performed better than public
schools. There are two basic questions:
1. Are
the results just an indication of selectivity bias occurring from parent’s
choice of school type?
2. Does
the school determine the most significant differences among the schools in the
sample?
The research attempts to measure and to manage a series of
student background measures, however for some critics it was done inaccurately.
In addition, the research makes no effort to explain certain school and teacher
attributes in either the public or private setting. The policy conclusion
depends on having a random school sample and being able to duplicate the
private school success through a policy of expanding the private sector.
V. Some Research
Implications
Another set of questions are raised: what do these results have to say
about other lines of research by economists? Probably the most significant is
the learning on the evaluation of activities where the idiosyncratic natures of
those involve can be the key to the result. In numerous areas, for instance
those related to public policy matters, it is important to assess production
effectiveness and this sequentially calls for the analysis of individual skill
differences. However outside such areas, the relation of the results of the
educational analysis to studies of the effects of education must also be
considered.
Lastly, the signaling opposed to school production models
reflects an area where the preceding analysis is most fitting. Empirical
studies of screening have commonly sought for labor market tests of the
competing hypothesis. Both models suggest higher earnings for the part of the
educated people: (1) screening model through the information provided on
differential skills, (2) production model through altering the skills of
individuals.
The signaling version presumes that individuals are mainly
impassive by school experience – they merely wait and bear with education until
the information on skills draws near to their actual skills. In polar cases,
the weight of available evidence on schools implies that the production model
is more adequate since student achievement is strongly affected by the school
they attended.
Source:
Eric A. Hanushek, “The
Economics of Schooling: Production and Efficiency in Public Schools”, Journal of Economic Literature, Vol. 24,
No.3, (September, 1986), pp. 1141–1177
[1] Not only economists, but
researchers in other disciplines such as psychology, sociology and political
science have made education their subject matter. Although their works center
on matters beyond the interests of economists, there are significant points of
convergence in estimating scholastic performance, in analyzing the educational
production process and in developing educational policy.
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