The Economics of Schooling: Production and Efficiency in Public Schools

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

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[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.