vocational education and productivity.pdf

Economics of Education Review, Vol. 9. No. 4, pp. 351-W. 1990. 0272-7x7/90 $3.00 + 0.00 Printed in Great Britain. 0 1590 Pergamon Press plc

Vocational Education and Productivity: A Case Study of the Beijing General Auto

Industry Company

WEI-FANG MIN* and MUN CHIU TSANGPS

*Institute of Higher Education, Peking University, Beijing 100871, China; and tCoUege of Education, Michigan State University, East Lansing, MI 48824, U.S.A.

Abatraet -This paper examines the economic rationale for the current vocationahxation of secondary education in China by comparing the performance of vocational education graduates and general education graduates in the workplace. It uses a model that recognixes the importance of work effort and group dynamics on production, employs a more direct measure of productivity, and presents an empirical study in the context of the current educational and workplace reforms in China. Based on data from the Beijing Auto Industry Company, China, the study finds that vocational-technical education graduates engaged in factory work relevant to their previous trainidg were more satisfied with their job and were more productive than general education graduates. It also found that a workers education had a lesser impact on productivity when the worker performed in a more co-operative environment.

I. INTRODUCTION

SINCE THE Third Plenary Session of the Eleventh Congress in 1978, the Peoples Republic of China (China) has pursued a national policy of modemiz- ation. This policy has resulted in a major shift in the purpose and function of the education system. Instead of being used for political indoctrination and as an instrument for class struggle, the school is trying to inculcate the young in both the skills and values needed by a changing economy and to be the strategic foundation of the modernization pro- gram. In the late 1970s and the early 198Os, the education system underwent several significant changes; including reinstating national exami- nations, re-establishing key schools and universities, re-focusing on skill training, and sending students and faculty for training overseas. The call for changes in education reached its peak in May, 1985, with an official pronouncement of a large-scale reform of the education system (Peoples Press, 1985).

One of the most important components of the 1985 reform plan was the vocationalization of

education at the upper-secondary level. The plan calls for a rapid development of secondary vocational and technical schools so that enrollments in these schools would constitute about 50% of the total enrollment in upper-secondary education in the near future, a dramatic increase from the 5% level in the early 1980s.

Since modernization policies were formulated in the late 197Os, a large-scale industrialization pro- gram has been implemented. As industrialization accelerated, serious shortages of skilled workers, semi-skilled workers and middle-level technicians have emerged. In many factories, some of the low- and middle-level technical work has to be performed by high-level technicians and engineers. Also, workers recruited from general senior high schools were found to be inadequately prepared for technical work. However, in the late 1970s in China, less than 5% of senior high schools had a vocational track. Most of the senior high schools focused on college preparation, but the transition rate from these schools to colleges was less than 4% (National Bureau of Statistics, 1986). Most of these senior high school graduates had to work in industry as

*To whom correspondence should be addressed.

351

352 Economics of Education Review

skilled or semi-skilled workers. Besides, there is increased emphasis on economic efficiency. In the belief that vocational-technical education can better prepare young people in the skills needed for employment in industry than general education, vocationalizing senior high schools is seen as a strategy that contributes to increased efficiency in educational investment. Thus, industries and government agencies appeal for more upper- secondary vocational-technical schools (Ministry of Education, Ministry of Labor and Personnel, Ministry of Finance, State Planning Commission, 1983).

productivity, presents a model of education and productivity that highlights the role of work effort and group dynamics in production, and constructs several testable hypotheses to be tested in the empirical study.

Economic Relevance of Vocational Education

A key assumption in the economic motive behind this secondary education reform is that vocational- technical school graduates are more productive than general school graduates in factory work. How- ever, there exists no systematic empirical study to test the validity of this assumption in the present day workplace in China.

The linkage between education and productivity has been the subject of numerous studies in both the economics and sociology literatures. Many studies have examined how different levels of education and different types of education influence worker productivity. In particular, a significant number of studies exist which compare the productivity of vocational school graduates with that of general education graduates.

This paper attempts to examine the relationship between the vocationalization of secondary education and economic development in China by studying the impact of vocational education on productivity in the specific institutional context of China. By presenting a case study conducted at the Beijing General Auto Industry Company, it compares the performance of vocational-technical education graduates and general education graduates in the workplace. The object is to examine whether secondary vocational-technical school graduates are more satisfied with their jobs and more productive than senior high general education graduates. The empirical analysis has some origi- nality in applying a model of productivity that recognizes the importance of work effort and group dynamics on production, and in employing a more direct measure of productivity.

Most of these studies use earnings as a measure for productivity. A few use alternative proxies such as a worker efficiency rate (Fuller, 1970, 1976; Godfrey, 1977). Most of the studies are cross- sectional in design. Some have examined the over- time differences in the relative effectiveness of vocational and general education (Hu et al., 1971; Gustman and Steinmeier, 1982; Meyer and Wise, 1982; Bolino and Uri, 1982; Tannen, 1983).

The rest of this paper is divided into three sections. Section II provides the conceptual treat- ment that guides the empirical study presented in Section III. Section IV summarizes the findings of the study and makes recommendations for further research.

II. VOCATIONAL EDUCATION AND PRODUCTIVITY: EMPIRICAL EVIDENCE AND

CONCEPTUAL ISSUES

The findings from these studies are mixed, with some showing higher earnings or productivity for vocational graduates (Hu ef al., 1971; Freeman, 1974; Corazzini, 1968; Fredland and Little, 1980; Li et al., 1981; Bolino and Uri, 1982; Gustman and Steinmeier, 1982) and others showing no significant difference or negative results in comparison with general education graduates (Taussig, 1968; God- frey, 1977; Grass0 and Shea, 1978; Rumberger and Daymont, 1984; Meyer and Wise, 1982; Psacharo- poulos and Loxley, 1985). Some investigators have found that the economic effects of vocational education vary with programs, and the gender and ethnicity of students (Gustman and Steinmeier, 1982; Li et al., 1981; Meyer, 1982); and the effectiveness of vocational training depends upon the nature of the training received and type of insti- tutions providing it (Tannen, 1983). Also, the estimated results can change significantly with the model employed and the time period studied (Gustman and Steinmeier, 1982). In general, there is no consistent and convincing evidence in support of the presumed productivity advantage of vocational education over academic education.

This section provides a brief critical review of the Besides the mixed evidence in the existing litera- existing literature on vocational education and ture, there are some issues to consider in applying

Vocational Education and Productivity 353

the methods of these studies to the Chinese situ- work experience, and other on-the-job training ation: variables.

First, most of the studies do not measure productivity directly but assume that productivity is reflected in individual wages. While the use of wages as a proxy for productivity is questionable for capitalist economies characterized by imperfect competition, it is even more problematic for China. China has a centrally planned economy; wages are tightly controlled and set by the government. In such a case, wages would not be a valid measure of productivity.

Second, most of the studies have not taken account of the impact of work effort on productivity. The degree to which workers exert their effort on their jobs could make a significant difference in productivity; and work effort is an important intermediate variable linking education and productivity (Pencavel, 1977; Levin, 1984; Tsang and Levin, 1985; Tsang, 1987). Without taking account of the work effort variable, the linkage_ between education and productivity would not be properly revealed.

Third, most of the studies have taken the individual worker as the unit of analysis and have ignored the potential interaction among workers that might affect productivity. In modem production, however, a large proportion of work is group work which can influence how an individual worker behaves (Alchian and Demsetz, 1972). In China, especially, many incentives are given at the group level. The impact of group dynamics on individual productivity should be taken into account.

Recent research on the relationship between education and productivity has focused on work effort as an important intermediate variable relating the education of workers and their productivity (Tsang and Levin, 1985; Tsang, 1987). Work effort is seen as a function of worker characteristics, job characteristics, and the degree of match/mismatch between these two sets of characteristics. Worker characteristics include worker skills and abilities, type and level of education, worker needs and expectations, experience, age, and gender. Job characteristics include both physical aspects such as the nature of job and its skill requirements, the reward structure and promotional opportunities, and the physical environment; and social aspects such as peer-group interaction, supervision and worker-supervisor relationship, atmosphere for co- operation, etc. Two types of match/mismatch can be identified: match/mismatch in skill and match/mismatch in occupational expectations. If a worker finds his skills to be underutilized in his job or his occupational expectation unfulfilled, he may be- come dissatisfied with his job, exert lower level of effort, thus resulting in lower productivity (Vroom, 1964; Sheppard and Herrick, 1972; Quinn and Mandilovitch, 1975; Srivastva ef al., 1977).

Fourth, vocational education might have different impacts on productivity in different social, economic and institutional contexts. An empirical study on China is needed to examine the economic rationale for the vocationalization of secondary education within Chinese contexts. This study attempts to resolve these issues.

Education can affect worker characteristics by its influence on an individuals skill, needs, and expectations; it can also affect the job characteristics of a worker by influencing the kind of jobs available to him/her as a result of his/her education. Through its influence on both worker characteristics and job characteristics, education can affect the degree of match/mismatch between these two sets of characteristics, and thus work effort and productivity. Education can have an indirect effect on productivity besides a direct effect.

Education, Work Effort and Productivity Most of the empirical work on the relationship

between education and productivity is based on human capital theory (Schultz, 1961; Becker, 1964; Mincer, 1974). According to this theory, education can raise the productivity of an individual, primarily by increasing the individuals cognitive skills. Thus, there is a direct and positive relationship between education and productivity. This relationship is usually estimated by relating earnings to human- capital variables such as years of formal schooling,

This model of work effort has been applied to the study of the impact of the level of education on productivity (Tsang, 1987; Tsang et al., 1991). It was found that workers with more education than their jobs require (i.e. underutilization of education) tend to exert lower work effort (proxied by job satisfaction) and have lower productivity. It is conceivable that the type of education (vocational or general) that workers receive can be related to differences in productivity among workers. To the degree that vocational education and general education socialize individuals with different skills,

3.54 Economics of Education Review

needs and occupational expectations, the type of education may be correlated with work effort and productivity.

Individual Behavior and Group Dynamics It should be noted that the Tsang-Levin model of

work effort is based on indi~duafs, not groups. Because of the possible interactions among individuals in a group setting (Forsyth, 1983; Shaw, 1981; Schmuck and Schmuck, 1983), an individual may perform differently under different group settings. The impact of the interaction among workers in a group on the relationship between education and productivity has to be taken into account. Consider the situation in the workplace in China.

On the one hand, since most of the work is group work and many incentives (bonuses) are given at the group level, co-operation among group members is likely. For example, in a co-operative work environment those with more knowledge and skills may share that information with those with less knowf- edge and skiffs. This may equalize skiff proficiencies among workers and may obscure the differences in productivity due to differences in the skill background of workers.

On the other hand, since 1979, the promotion of workers to a higher wage level within groups has been partially based on the evaluation of individual performance both in the production process and in the tests of technical knowledge and skiffs. Only a small proportion of workers is promoted each year. In the unified eight-level wage system, the ratio of the Iowest wages to the highest wages is 1:3. This promotion policy is supposed to encourage workers to improve themselves technically, but it may also prevent workers from helping each other, thus maintaining individual differences in skills and productivity. Since both group-based incentives and individual-based incentives exist in the workplace, both group interactions and individual behavior are assumed in this study. Some indicators and hypotheses related to group dynamics will be developed and included in the Tsang-Levin work effort model. This study provides a preliminary analysis of the impact of group dynamics on the relationship between education and productivity in China, a previously unexplored area of research on China.

Hypotheses to be Tested Based on the above discussion the foIlowing

hypotheses, to be tested empirically, have been generated.

Hypothesis (1): Secondary vocational school graduates as factory workers holding jobs more closely related to their training tend to exert higher work effort in their jobs than general senior high school grad~tes who hold the same jobs. This result might arise because vocational education graduates have better matched occupational expectation in China. Since secondary vocational schools prepare students for employment after graduation, students in these schools expect to be factory workers. General senior high school graduates are prepared for college. What they want is to be college students, but college cannot enroll them all. Most of them are forced to work as factory workers. They do not have the psychological preparations for the jobs they are going to do. Thus with respect to occupational expectation, vocational education graduates are better matched and they thus have higher work effort2 Vocational education graduates may also have higher work effort than general education graduates because their skills acquired in school better match those required in the workplace.

Hypothes~ (2): Secondary vocationat school graduates as factory workers hoIding jobs closely related to their training tend to be more productive than general senior high school graduates who hold the same jobs. This result may arise because vocational school graduates exert higher work effort in their jobs than genera1 senior high school graduates, and the skills they have acquired from the vocational programs better meet the skill requirements of their jobs.

Hypothesis (3): A workers educational background has a less significant impact on productivity in a more co-operative work group than that in a less co-operative one. This result may arise because, in a group with a high level of co-operation, individuals with more skills may share their knowledge with individuals with fess skills. This will equalize skill proficiencies among members of the group, thus obscuring differences in productivity due to differences in the educational background of the group. The impact of vocational education on pr~ucti~ty in a workplace with a higher level of co-operation may be fess significant than that with a lower level of w-operation.

III. VOCATIONAL EDUCATION AND and other programs. A larger proportion of these PRODUCTIVITY: A CASE STUDY OF THE training programs are programs for training skilled

BELjING GENERAL AUTO INDUSTRY and semi-skilled workers and middle level tech- COMPANY nicians because of the serious shortages of these

technical personnel. This study will focus on evalu- Methodology ating the programs for training skilled and semi-

This includes the specification of the population skilled factory workers. to be studied, and the discussion on the definition of variables, data needs and collection, and methods of Defining the variables. According to the frame- analysis. work and the hypotheses, the following variables are

included in this study: Specifying rhe population. There are two tracks in Job satisfaction (work effort). Job satisfaction of

upper-secondary education in China at the present workers is measured by a five-item scale with a value time: of one for the lowest level of job satisfaction and a

(1) General senior high schools in which students value of five for the highest level and is taken as a mainly have a college-preparatory curriculum. The proxy for work effort (see Tsang, 1987). Accord- transition rate to college was below 4% before 1980. ingly, job satisfaction is a function of worker Only those students who are from a few key-point characteristics and job structures and the degree of senior high schools have a good chance of entering match/mismatch between these two sets of charac- the college. Most of the senior high schools gradu- teristics. It is also an important intermediate vari- ates go to work as semi-skilled or skilled workers. able relating education and productivity. It is ex- This study considers general senior high school pected that job satisfaction is positively related to graduates who did not go to college but are working productivity. in the factory. Work efficiency. Instead of using wages as a

(2) Secondary vocational schools in which measure of productivity, this study uses an alter- students spend half time studying academic subjects and half time learning specific skills.3 There are two

native measure: work efficiency (Fuller, 1970). Work efficiency reflects the amount of goods and

kinds of secondary vocational schools. services produced by a worker during a period of There are senior high schools with a large propor- time and is defined as:

tion of vocational courses. These are schools that switched recently from a general track to a Work efficiency = vocational track. Their programs are being developed. Some of these schools are still short of actual output of a worker per period

vocational teachers, funding, and equipment (Li et production quota for a worker per period al., 1985).

There are also company-affiliated vocational The production quota in the above ratio is a function schools. These schools have a relative long and of labor, equipment, technology, materials and stable history. Compared with the other kind, they time. It reflects the physical conditions and inputs to are much better funded and managed. Students in production. Thus work efficiency measures the these schools spend half of their time studying performance of the worker based on a given set of academic courses, and half of their time learning inputs and physical conditions of production per specific skills needed by the companies with which period. their schools are affiliated. Generally speaking, they The advantages of using worker efficiency as a will be assigned jobs in the affiliated companies. The measure of productivity are: (1) it is a direct vocational school graduates in this study came from company affiliated vocational schools.

measure of worker productivity, and (2) since quotas are designed to take account of factors that

There are various training programs in secondary might affect worker output other than the workers vocational schools, such as skilled and semi-skilled contribution, work efficiency holds constant factors worker training programs, middle-level technician that might affect worker performance, but are training programs, clerical staff training programs, extraneous to the worker, such as machine capacity, cook training programs, barber training programs, availability of tools and quality of materials. Thus it



enables us to concentrate on the performance of a worker.

Variables related to worker characteristics: (1) Type of education. This is .the major explanatory variable to be considered. The types of education are secondary vocational-technical education and secondary general education. It has a value of one for vocational-technical graduates and a value of zero for general education graduates. The rest are control variables. (2) Levef of education. It is measured by the number of years of schooling. (3) Experience. It reflects abilities acquired on the job and is measured by the number of years of work experience. Because some workers had on-the-job training and others did not, an on-the-job-tra~nf~g variable (measured in months) is also included. (4) ~ocfoeconumic status. It is measured by parents level of education. (5) Gender. It has a value of one for females and a value of zero for males.

Variables related to job characteristics: (6) Salary. Salary is measured by an eight-Ievel wage scale. Other relevant job variables include (7) promotional opportunities, (8) level of autonomy in work, (9) feader-member relationship, (10) peer relatfon~hj~, and (11) co-operution among workers.6 Variables (7) to (11) are measured by a five-item scale with a value of one for the lowest level and a value of five for the highest level.

Data needs and data collection. Data were col- lected in 1986 from the Beijing General Auto Industry Company,7 which currently has 12 factories and 59,369 employees. There are nine vocationai- technical schools affiliated with this company. These schools enroll 600 students each year. Students are admitted to these v~ational-techni~l schools according to their own applications, test scores and their academic performance at junior high schools. Upon finishing 3 years learning at these vocational- technical schools, the graduates are assigned to jobs in the company. Selection bias does not appear to be a problem.

566 workers were selected based upon a clustered sampling strategy from two of the factories within the company. The average level of education is 10.8 years and 41% of the workers are females. Among the 566 workers, 150 are vocational-technical school graduates, and 90% of them consider themselves as holding jobs related to their training.

Of the 566 workers selected from the cumpany, this study focuses on the 413 workers who are under

40 years old. Since this study is concerned with the productivity impact of the current educational reform, the older workers who have undergone a different educational process from the younger workers are excluded from our analysis. Among the 413 younger workers, 114 are vocational-technical school graduates, and 93% of them consider themselves holding jobs related to their training. 288 of the 4I3 workers had 12 years of schooling. Both the 413-worker and the 288-worker samples are analyzed.

The production records were examined and a questionnaire was designed by us in collaboration with the staff members of the company. The questionnaire was administered by the Workers Education and Training Center of Beijing General Auto Industry Company through each of the factories Education and Training Office for Workers. Reliability and validity of these measurements were tested in a pilot study including 137 individual workers. I0

Methods of analysis. Our model of productivity consists of a two-equation recursive system. The first equation is a job satisfaction equation in which job satisfaction is a function of the type of education, and other worker and job characteristics. The second equation relates work efficiency to job satisfaction, type of education, and other worker and job characteristics. The type of education is expected to have a direct effect and an indirect effect (through job satisfaction) on work efficiency.

To examine the impact of the level of co- operation among group members on the reiation- ship between education and productivity, two sub- samples are considered: individuals working in groups with a high level of co-operation (co-operation among workers has a value higher than three), and individuals working in groups with a low level of co-operation (co-operation among workers has a value not higher than three).

Empirical Results Table 1 presents the regression results for the 413

workers. The dependent variable in Equation 1.1 is job satisfaction. The estimated coefficient for the variable type of education is both positive and significant, showing that vocational-technical school graduates tend to be more satisfied with their jobs as factory workers than genera1 education graduates, thus supporting hypothesis (1). The

Table

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under 4

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old

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the jo

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sq

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Job c

hara

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s:

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ry

Peer

rela

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Leader-

mem

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Pro

moti

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opporl

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auto

nom

y

Co-o

pera

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am

ong

work

ers

Equati

on 1

.1

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SA

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0.0

51

(1

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W

OR

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0

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6

Equati

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coefficients for all the other independent variables were statistically insignificant except for the job characteristic variables for salary promotional opportunity, and co-operation among workers which were statistically significant and positive.

The dependent variable in Equation 1.2 is work efficiency. Equations 1.1 and 1.2 constitute the recursive model for the 413-worker sample. From Equation 1.2 we can find that the type of education is positively and significantly related to work efficiency, indicating that vocational-technical graduates as factory workers holding jobs closely related to their training are more productive than general education graduates. Job satisfaction (as a proxy for work effort) is also positively and significantly related to work efficiency. Thus the type of education has a direct and indirect effect on productivity, supporting hypothesis (2). From Equations 1.1 and 1.2, the average total productivity advantage of vocational education relative to general education is 0.078 (= 0.069 + 0.28 x 0.033). The direct effect of the type of education (0.069) is much larger than the indirect effect (0.009 = 0.28 x 0.033). Except for gender and leader-member relationship, the other variables are all significantly related to work efficiency.

Equations 1.3 and 1.4 are the work-efficiency equations for workers in more co-operative groups and less co-operative groups, respectively. From the R-square values of these two equations, we can see that our individual-based model explains productivity significantly better for less co-operative groups than more co-operative groups. It is also interesting to compare the coefficients in these two equations. We find that the human-capital variables reflecting individual differences in skills, such as type of education, level of education, on-the-job training, and experience are less significant and less strong in more co-operative groups. In particular, the coefficient for level of education is 0.012 and is significant in Equation 1.4; but it is only 0.006 and is insignificant in Equation 1.3. Also the coefficient for type of education in Equation 1.4 is 50% larger than the one in Equation 1.3. This result is consistent with hypothesis (3). Thus, the level of co-operation among group members appears to affect the relationship between productivity and the skills of workers.

Table 2 presents the regression results for the 288 workers who are under 40 years old but also with 12 years of schooling. Equations 2.1 and 2.2 are the

estimated equations for the recursive model for these 288 workers. The results indicate that, at the upper-secondary level, vocational-technical graduates are both more satisfied with their jobs and are more productive than general education graduates. Work effort, proxied by job satisfaction, is a significant determinant of work efficiency. The total productivity advantage of upper-secondary vocational-technical education relative to upper- secondary general education is 0.096 (= 0.087 + 0.24 X 0.037). The direct effect of type of education is again much larger than the indirect effect.

Equations 2.3 and 2.4 are respectively the estimated work efficiency equations for more co-operative groups and less co-operative groups in the 28& worker sample. The results are supportive of hypothesis (3). In particular, type-of-education has a much larger coefficient in Equation 2.4 than 2.3. The coefficient for on-the-job training in Equation 2.4 is twice as large as that in Equation 2.3; it is significant in Equation 2.4 and insignificant in Equation 2.3. In general, skill-related variables appear to be more important factors for explaining productivity differences in less co-operative groups than they are for more co-operative groups.

IV. CONCLUSIONS AND RECOMMENDATIONS FOR FURTHER RESEARCH

Our empirical study found that secondary vocational education graduates holding jobs closely related to their training are more satisfied than secondary general education graduates with their jobs as factory workers. A plausible reason is that vocational school graduates have better preparation for their jobs. The expectations and skills they acquire in vocational schools better match the job characteristics of factory work in China.

Vocational education graduates holding jobs closely related to their training are also more productive than general education graduates. This may be explained by the higher level of job satisfaction of vocational education graduates and the specific skills of these graduates.

Moreover, there is significant interaction between education and the level of co-operation among group members. In a work environment which is more co-operative, the education or skill background of workers becomes less important. This may be due to the sharing of knowledge and mutual

Table

2. R

esu

lts o

f re

gre

ssio

n analy

ses fo

r w

ork

ers

under 4

0 years

old

and w

ith 1

2 years

of sc

hoolin

g

Equati

on 2.1

JOB

SA

TIS

FAC

TIO

N

Equati

on 2.2

Equati

on 2.3

D

ependent v

ari

able

W

OR

K E

FFIC

IEN

CY

W

OR

K E

FFJC

IEN

CY

Equati

on 2.4

WOR

K EF

FICIEN

CY

Job

sati

sfac

tion

W

ork

er c

hara

cteri

stic

s:

Lev

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f ed

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Typ

e of

edu

cati

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trai

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assistance among workers that reduce individual differences in skills.

Furthermore, the results show work effort (proxied by job satisfaction) to be a significant factor affecting productivity. It is an important intermediate variable relating education and productivity. Thus, education can affect productivity directly through its human-capital capacity; it can also affect productivity indirectly through the work effort variable. This indirect effect depends on the degree of match/mismatch of worker characteristics and job characteristics. If education socializes students in the skills, expectations and needs that are consistent with the jobs they find in the workplace, then education has a positive and significant indirect effect on productivity. If there is a significant level of mismatch in skills and expectations, the indirect effect can be negative (Tsang, 1987). Since the indirect effect of education depends on a complex set of factors, the relationship between education and productivity is necessarily intricate, and is likely to vary under different conditions. This may partly explain the mixed evidence on the relationship between vocational education and productivity in the literature. From the findings of this study it might be implied that at Chinas current stage of social and economic development, company-affiliated and job-directed secondary vocational education, not general education, would be the appropriate way for preparing factory workers for Chinas industrialization. Such a recommendation, however, is premature, for several reasons.

First, our study relates to only one company of the auto industry. Further research is needed to deter- mine if the findings are generalizable to other companies in the same industry and other industries in China. It would also be revealing to study the productivity of graduates of vocational schools not affiliated with a company. In fact, our study has considered user graduates of well-established company-affiliated vocational schools only, non- user graduates from non-affiliated vocational schools might not perform as well. Our finding may represent the upper bound of the productivity advantage of vocational-technical education relative to general education. Further research should be conducted to examine the cases for non-users and non-affiliated schools.

Second, even if the findings are generalizable to other companies and industries at a point in time,

we need to examine the education-productivity relationship over time. It is conceivable that, in the long run, general education graduates can catch up and even surpass vocational education graduates in productivity. Because of their general training, general education graduates may be more flexible in handling a range of tasks and are more adaptive to technologically induced changes in the workplace than vocational education graduates trained in specific skills. Time and rates of renewal of technol- ogies of production will play a critical role. General education graduates may be more productive than vocational education graduates in a dynamic environment after they have made an initial adjust- ment to their job.

Third, our study compares the relative productivity advantages of two types of education, without considering their respective costs. To in- form decisions on efficient allocation of scarce resources, a cost-benefit approach should be adopted. Further research should thus examine the costs of different types of education.

Finally, our analysis has been confined narrowly to a comparison of economic returns to different types of education; but economic rationality is not the sole basis for national policy-making for education in China in general and the vocationalization of secondary education in particular. Political and social considerations are also relevant. The vocationalization of secondary education in the broader context of the current educational reform in China can be seen as part of an effort to rally popular support for the modernization policy of the new leadership, thus carrying both economic and political legitimation implications. In China as well as in other countries, vocational streaming is a form of social stratification. It is also a commonly used strategy for reducing the social demand for higher education. Thus, the vocationalization of secondary education reflects a reassessment of the social function of education in China. These various considerations should be properly balanced in arriv- ing at an educational policy13 to promote national development.

Acknowledgements - An earlier version of the paper was presented at the Comparative and International Education Society Conference in Washington, D.C., March, 1987. The authors contributed equally to the paper, and they gratefully acknowledge the helpful comments of Henry Levin, Edwin Bridges, Russel Rumberger, and an


anonymous referee. The authors would like to thank the General Auto Industry Company for its cooperation and Workers Education and Training Center of Beijing support for the field work.

NOTES

1. There are various kinds of training programs in vocational schools, such as training programs for semi-skilled and skilled workers and middle-level technical personnel (vocational-technical programs), as well as training programs for cooks, barbers, and other non-technical personnel. The emphasis in the current reform is on vocational-technical programs to prepare young people for factory work.

2. Note that this hypothesis refers to employed vocational and general education graduates. This study does not consider graduates who are seeking employment.

3. There are significant differences in curriculum between the two tracks. For example, general senior high school graduates have a total of 400 h in Chinese language and 465 h in mathematics while vocational education graduates have 114 h in Chinese language and 194 h in mathematics. General education students have more courses in humanities and sciences; vocational education students have more technical subjects.

4. In recent years, more and more vocational schools have affiliated themselves with companies. For some areas, company-affiliated vocational schools represent a large proportion of secondary vocational schools. For example, in Chongqing City, among the 115 secondary vocational-technical schools, 105 are affiliated with companies (Chongqing City Bureau of Labor, 1986). Given the problems of non-affiliated vocational schools, it is likely that more and more of such schools will seek affiliation with companies. Thus this study has focused its attention on company-affiliated vocational schools.

5. Industrial psychologists usually use job satisfaction as a proxy for work effort and assume that higher levels of job satisfaction produce higher levels of work effort (Vroom, 1964; Srivastva et al., 1977). Following a practice often adopted by studies on job satisfaction (Kallenberg and Sorensen, 1973; Quinn and Mandilovitch, 1975) this study has treated the job satisfaction scale as a continuous scale. The job satisfaction variable was based on the response to two questions (How well do you like your job? On the whole are you satisfied with your job?) and a statement (I am bored with my job).

6. For the relevance of these variables, see Porter and Steers (1973) March and Simon (19.58). Slavin (1983) and Chew (1983) Price and Mueller (1986). In this study, these variables were constructed from responses to questions or statements in a survey. Promotionof opportunities was based on the responses to What do you think is the possibility that your wage level will be raised?, Think of the opportunities for promotion that you have now. Which of the following statements best describes your situation? and the promotion responses to How much does your job allow you to take part in decisions that affect you?, How much autonomy do you enjoy as to how you do your work? In the production process, my job allows me to make a lot of decisions on my own. Leader-member relationship was based on the responses to Does your group leader usually give you recognition for work well done? and I like my group leader very much and We are encouraged to speak our mind, even if it means disagreeing with our group leader. Peer relationship was based on responses to Do you like your fellow workers in your work group?, Are there opportunities to develop close friendships among workers in your group?, and A harmonious and friendly atmosphere prevails among the workers in my work group. Co-operation among workers was based on responses to Workers in our group always cooperate with one another and help one another in our work, Workers with knowledge and skills in our group always share their knowledge and skills with those without the knowledge and skills, and When you run into problems in your work, can you get help from your fellow workers in your group?.

7. This company was chosen because it met the conditions for our study: it has semi-skilled and skilled workers engaged in industrial work, it has a good representation of general education graduates and vocational-technical education graduates among these workers, and it has vocational-technical schools with welI established programs. The access to, and co-operation from, the company were also important considerations.

8. The issue of selection bias should be considered seriously. In particular, the general education graduates and vocational education graduates in the company may have different ability so that the impact of type of education on productivity may reflect the influences of both skill training and ability. It is thus desirable to include measures of ability in the analysis to control for selection bias. However ability measures such as IQ or test scores are not available. Nevertheless, interviews with the


administrators of the vocational technical school affiliated with the Beijing General Auto-Industry Company indicate that there should not be significant differences in the ability levels of the two groups of graduates in our sample. The great majority of the workers in our sample graduated from junior high schools before 1980. At that time, there were very few vocational-technical schools at the upper-secondary level, most senior high schools (over 95%) offered a general education curricuhtm. Only 4% of these general education graduates succeeded in getting into college. The vocational- technical school afftiated with the company selected junior high school graduates whose test scores in the graduating examination were comparable to those who enroll in general education senior high schools. The mean of the test scores of the students enrolled in the vocational-technical school affiliated with the company was about the same as that of the students enrolled in the general education senior high schools. Since only a very small percentage of high school graduates (presumably the most able) proceeded onto college, the test scores of the general education graduates in our sample (who did not attend college) should be comparable to those of the vocational-technical education graduates in our sample. Thus it has assumed that the two groups of graduates in our sample are of similar ability. The impact of rype ofeducarion on productivity can then be attributed to the type of skill training. Finally, the lack of data on the background of individuals does not permit a probit analysis of self selection in secondary education (Willis and Rosen, 1979).

9. It is the policy of the company to assign graduates to jobs directly related to their training. In the questionnaire, graduates were asked if they held jobs related to their previous training. Ninety percent of the vocational-technical school graduates responded in the affirmative. A distinction can be made between vocational graduates holding jobs related to their previous training (users) and graduates holding jobs not related to their previous training (non-users). For a given job, it is possible that a user performs better than a non-user. Since graduates from company-affiliated vocational schools are usually assigned to jobs in the company related to their training, a high percentage of such graduates are users. But graduates of non-company affiliated vocational schools may not be able to find jobs related to their training; such schools will have a higher percentage of non-users. While our study has focused on users, non-users can be the subjects of further research.

10. Reliability and validity tests were conducted on the measures for job satisfaction, peer relationship, leader-member relationship, work autonomy, perceived promotional opportunities, and group co- operation. For the pilot study, both the Cronbachs alpha and the inter-item correlation coefficient had values well above 0.7. Also, intra-scale correlations are stronger than inter-scale correlations. Thus the measures in this study are both reliable and valid.

11. In the regressions, the five variables for peer relationship, leader-member relationship, promotional opportunity, work autonomy, and co-operation among workers were measured by a continuous scale from 1 to 5. This measurement procedure is analogous to the one commonly used for job satisfaction. Separate equations were also estimated using categorical variables for these job characteristics. The results were similar to those in Equations 1.1 and 1.2. Also, additional statistical analyses indicated that there was very low (and insignificant) correlation between the error terms of equations 1.1 and 1.2 and the exogeneous variables in these two equations. This justified the use of ordinary-least-squares estimation of the recursive system.

12. According to interviews with the administrators of the vocational-technical school affiliated with the Beijing General Auto Industry Company, the average cost of a vocational-technical school student is about 1000 yuan per year, while that for a general senior high school student is about 210 yuan per year; and the average net profit produced by each worker in the factories (in which our sample was drawn) is 7500 yuan per year. Assuming that vocational-technical school graduates are 8% more productive than general senior high school graduates and this productivity advantage lasts for 8 years, and assuming a discount rate of 5%, one can derive .a benefit-cost ratio of 1.62 to 1, showing that vocational-technical schools affiliated with companies are more cost-effective in economic terms. It should be recognized that this is only a simplified simulation. In subsequent research, the costs of different types of vocational-technical schools should be studied.

13. It should be added that company schools are a policy option that is limited by the number of large companies that have large training needs. Small-medium sized companies may have to use CO- operative training efforts or free-standing schools with closely managed linkages.

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