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Youth transition from school to work in Spain
Ge´rard Lassibille
a,*, Lucı´a Navarro Go´mez
b, Isabel Aguilar Ramos
b, Carolina
de la O Sa´nchez
baInstitut de Recherche sur l’Economie de l’Education, 9 Avenue Alain Savary, BP 47870, 21078 Dijon Cedex, France bDepartamento de Estadı´stica y Econometrı´a, Universidad de Malaga, El Ejido s/n, 29013 Ma´laga, Spain
Received 16 April 1999; accepted 1 September 1999
Abstract
Using a data set drawn from the Encuesta Socio-Demogra´fica conducted by the Instituto Nacional de Estadı´stica in 1991, we analyze the labor market entrance of Spanish school leavers and the match between education and work at the early stages of working life. The empirical evidence shows that human capital exerts a strong influence on the duration of unemployment. With regard to the job match between education and work we find that young workers are more likely to be underutilized compared to their adult co-workers. Regression results indicate that people with higher education have, all else being equal, a lower probability of being overeducated and a shorter length of unemployment. They also show the poor performance of upper secondary education; a key problem in the Spanish educational system.
2001 Elsevier Science Ltd. All rights reserved.
JEL classification: I21; J41; J64
Keywords: Human capital; Youth labor market; Over- and underschooling; Spain
1. Introduction
Labor markets in many European countries have been in continual decline over the last two decades. Of these countries, Spain has probably experienced the most dra-matic change. The unemployment rate of the adult popu-lation rose by over 15 percentage points over the period 1976–1996; today the unemployment rate for the whole population is on average about twice that in other Euro-pean countries (OECD, 1998). Moreover, the deterio-ration of the youth labor market has been still more sev-ere and more pronounced than in other countries (see, for example, Korenman & Neumark, 1997). In the afore-mentioned period, the youth unemployment rate increased by more than 35 percentage points. In 1996,
* Corresponding author. Tel.: +33-380-395457; fax: + 33-380-395479.
E-mail address: [email protected] (G. Lassibille).
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42 percent of the 16–24-year-old population were unem-ployed; this percentage was, for example, about 4 times higher than in Germany, 3 times higher than in the Netherlands, 2 times higher than in Belgium and 1.5 times higher than in France.
Although youth unemployment is particularly high in Spain, there is no study which analyzes the transition process from school to work. This article attempts to fill this gap using the data of the Encuesta
Socio-Demog-ra´fica conducted by the Instituto Nacional de Estadı´stica
in 1991. From this rich dataset we extract two cohorts of school leavers; for each one it is possible to observe an individual transition from school to work over an 18-month period. Based on this unique sample, we analyze the labor market entrance of young people focusing, on one hand, on the duration of unemployment after com-pletion of formal schooling, and, on the other, on the mismatch between education and work during this early stage of the working life.
We follow tradition in presenting empirical evidence on these two topics. We explain the labor market status
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of school leavers at different times by personal endow-ments, family attributes and the overall characteristics of the labor market at a regional level. With regard to the match between education and work we define overeduc-ation and undereducovereduc-ation in the first job, considering the minimum qualifications required for entering a job. We explain the match in the youth labor market by both per-sonal and work characteristics.
The paper proceeds in the following manner. Section 2 briefly describes the data. Section 3 focuses on the duration of youth unemployment. Section 4 presents empirical evidence on the job match in the youth labor market.
2. The data
Empirical results are based on data from the Encuesta
Socio-Demogra´fica conducted in 1991 by the Instituto Nacional de Estadı´stica.1 Although this tracer survey was not specifically designed to study the transition phenomena of school leavers into the labor market, it contains valuable information for the analysis attempted here. The survey details the main activity and the job of each individual at the time the data were collected; it also describes their level of education, marital status, age and gender, as well as their parents’ socio-economic background. Furthermore, the survey contains useful bio-graphical information on the date of school-leaving, labor market entry, job mobility, marriage2 and immi-grant status.
The survey was administered to more than 150,000 individuals. From this large dataset we extract two cohorts of individuals: those who left the formal school-ing system in 1989 and those who left in 1990.3 The selected sample includes young men and women in the 16–30 age bracket. Obviously, this is an extensive defi-nition of youth. We do this because in Spain formal schooling frequently continues into the late twenties. According to the Encuesta Socio Demogra´fica about 52 percent of students aged 16–30 in 1989 and 1990 leave the schooling system; depending on the level of edu-cation this proportion is between 28 percent and 90 per-cent (Table 1). Among these school leavers the perper-cent- percent-age who drop out without a diploma varies between 52 and 82 percent.
For each cohort of school leavers, the survey makes it possible to observe the individual’s transition from
1 See Instituto Nacional de Estadı´stica (1991) for a detailed description of the survey.
2 More than 95 percent of school leavers live with their par-ents; for this reason we do not explore the effect of marital status on the transition process from school to work.
3 We do this to obtain more observations.
school to work over an 18-month period. Inside this win-dow, the data allow us to describe the labor market status of young people 6 and 18 months after they left school, as well as the main characteristics of their first job. The labor market status of school leavers is identified from two crucial survey questions: “When did you look for a first job?” and “When did you find your first job?” (see Instituto Nacional de Estadı´stica, 1991). We exclude individuals who found their first job the same year they were doing military service because the survey does not make it possible to identify their labor market status without ambiguity. Individuals who were working while in school are obviously excluded because they did not find their first job inside the 18-month period in question. Finally, we exclude people who were looking for a job before leaving school as their period of unemployment is outside this frame. After deleting missing values, these exclusions left us with 1,683 observations. These obser-vations account for about 75 percent of school leavers aged 16–30 in 1989 and 1990. Although information is available on the duration of unemployment as expressed in months, it could not be used because of an ambiguity regarding the questionnaire on this point. The survey does not report any information on wages; for this rea-son, the dataset precludes the possibility of any con-clusion on the impact of overeducation and undereduc-ation in the wage-generating process.
Table 2 describes the main characteristics of the selec-ted sample. The results show that individuals are equally distributed by gender and by cohort. On average, individ-uals left the school at the age of 21. When considering the highest level of education completed, 33 percent of young people have left the educational system with a primary education diploma. The secondary general edu-cation category includes individuals who have obtained the bachillerato unificado polivalente;4 they have com-pleted at least 12 years of schooling. According to our results, 16 percent of both cohorts of young men and women have left the educational system with such a dip-loma. The vocational category of education groups together people who have either a lower (10 years of schooling) or an upper (13 years of schooling) vocational diploma; of the 22 percent of young people who left the educational system with a vocational diploma, more than 45 percent have a lower level. Higher education includes, on the one hand, individuals who have an escuela
univer-sitaria diploma (three years of post-secondary education)
and, on the other hand, those who have graduated from a facultad or an escuela tecnica superior—ETS5—(five years of post-secondary education); these two categories
4 This level includes also young people who have reached the curso de orientacion universitaria, which is necessary to register at the university.
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Table 1
School situation of each cohort of students aged 16–30a(percent)
Compulsory Upper Vocational Higher education Total
education secondary education education
Escuela Facultad or Universitaria ETS 1989 cohort
Staying on at school 37.6 72.2 39.3 19.8 24.8 51.9
Leaving school 62.4 27.8 60.7 80.2 75.2 48.1
Total 100.0 100.0 100.0 100.0 100.0 100.0
Leaving school
With diploma 74.8 52.1 62.5 81.6 79.3 79.0
Without diploma 25.2 47.9 37.5 8.4 20.7 21.0
Total 100.0 100.0 100.0 100.0 100.0 100.0
1990 cohort
Staying on at school 35.0 72.1 43.2 21.7 29.5 50.4
Leaving school 65.0 27.9 56.8 78.3 70.5 49.6
Total 100.0 100.0 100.0 100.0 100.0 100.0
Leaving school
With diploma 68.8 49.6 57.8 89.2 83.6 78.5
Without diploma 31.2 50.4 42.2 10.8 16.4 21.5
Total 100.0 100.0 100.0 100.0 100.0 100.0
a The levels of education are defined in the text.
Table 2
Sample characteristics
Mean Standard
deviation
Age (in years) 21.188 3.283
Male 0.499 0.500
Highest educational diploma
Compulsory education 0.323 0.468 Upper secondary education 0.163 0.370 Vocational education 0.222 0.416 Higher education
Escuela Universitaria 0.102 0.303 Facultad or ETS 0.166 0.373 Non-certified years of schooling 0.316 0.465 Participation in non-formal 0.142 0.441 educational program
Father’s occupation
Self-employed 0.262 0.440
Managers and professionals 0.266 0.442
Skilled workers 0.226 0.418
Unskilled workers 0.246 0.409
Living in town of population
Under 5,000 0.137 0.344
Between 5,000 and 20,000 0.166 0.373 Between 20,000 and 100,000 0.223 0.416
Over 100,000 0.470 0.499
Cohort (89/90) 0.532 0.499
Number of observations 1,683 –
represent 10 percent and 16 percent respectively of the total of both cohorts of school leavers.
The award of a diploma is a flawed measure of the investment in education, particularly in Spain where the educational system is characterized by low completion rates compared to other developed countries (OECD, 1998). As shown in Table 2, 32 percent of young Span-ish people have started a level of studies and have dropped out without any diploma. Results not reported to save space indicate that this percentage is particularly high among those individuals who have only a compul-sory level diploma; more than 70 percent of them have enrolled into upper secondary education or vocational education and have not completed one of these two lev-els of studies. To what extent non-certified years of schooling affect the transition process from school to work is one of the issues addressed in this paper.
Apart from the formal level of education attended the survey permits one to observe individual participation in non-formal programs. As shown in Table 2, 14 percent of school leavers have attended a non-formal educational program. These programs are very heterogeneous. They are organized mainly by private educational institutions. Generally, individuals enroll in such institutions to pre-pare selective entry qualifications for particular occu-pations, or to complete their formal training in some very specific field.
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3. The length of youth unemployment
As noted previously, the survey permits measurement of the length of unemployment of both cohorts of school leavers on a discrete scale only, due to data collection observations on both cohorts being right-censored at 18 months.
Table 3 reports the distribution of young people according to the length of unemployment prior to the first job. Results show that 39 percent of school leavers obtain a first job 6 months after completion of formal schooling, 22 percent are unemployed for 6 to 18 months, and about 40 percent are still unemployed 18 months after leaving the education system. Analysis by gender indicates that among young men and women dif-ferences in length of unemployment are quite large: women are considerably less likely than men to find a job 6 months after completing formal schooling (33 per-cent vs. 44 perper-cent), and they are much more likely to be still unemployed 18 months after leaving the education system (45 percent vs. 34 percent).
While it would be useful to compare the situation in Spain with those of other European countries, we are only able to emphasize differences in the length of youth unemployment between France and Spain6. By relating our results with the data from the French Enqueˆte
Emploi, conducted approximately at the same period, we
find that Spanish school leavers are on average in a worst situation compared to their French counterparts. In fact, 50 percent of French school leavers obtain a first job 6 months after leaving the school; this percentage is 12 points higher than in Spain. Furthermore, while less than 20 percent of French school leavers are still unemployed 12 months or more after completion of formal schooling, 40 percent of Spanish school leavers are still
unem-Table 3
Length of youth unemployment (percent)
Females Males Total Less than 6 months 33.41 43.74 38.56 Between 6 and 18 21.92 22.05 21.98 months
More than 18 44.67 34.21 39.45
months
Total 100.00 100.00 100.00
6 The paper by Andrews and Bradley (1997) gives interest-ing insights into transition from school in the United Kinterest-ingdom. However, their results are not comparable because the labor market outcomes considered by these authors differ from the labor market situation we analyze in this paper. Furthermore, Andrew and Bradley’s article focuses only on the situation of school leavers at the end of compulsory education.
ployed 18 months after leaving the education system. Differences between the two countries may arise for at least three reasons: (1) overall conditions of the labor market are different in both countries, (2) the French educational system is organized in a way which makes the transition from school to work easier (see Lassib-ille & Navarro Go´mez, 2000); (3) the relative size of youth cohorts differ in both countries (see Korenman & Neumark, 1997).
Several studies have shown that the burden of unem-ployment is not shared equally among young people (see, for example, Blau & Kahn, 1997; Edin, Forslund & Hol-mund, 1996; Franz, Inkmann, Pohlmeier & Zimmerm-ann, 1997). In the following, we contribute to the exist-ing literature on the topic by explainexist-ing the probability of young Spanish people finding a first job in 6 months or between 6 and 18 months, compared with that of find-ing a job in more than 18 months. Table 4 reports the results of these estimations using a multinomial logit specification;7we follow tradition by computing the mar-ginal effects of the explanatory variables (see, for example, Greene, 1997). The length of unemployment is explained by the following individual attributes: age, gender, highest level of education completed, partici-pation in non-formal programs, father’s occupartici-pation, place of residence and cohort. Apart from these personal characteristics, we control the transition process from school to work for local labor market conditions, includ-ing explicitly in the regression model the unemployment rate of the entire population in the home region. We take also into account the structure of employment at the regional level, using the ratio between the number of workers employed in the service sector and the number of workers employed in the industrial sector.
The results show that, with all else being the same, females are less likely to find their first job in less than 18 months compared with males; an observation which clearly indicates a discrimination against women at a very early stage of their working life.8As formulated by Rees and Gray (1982), youth unemployment may depend on the contacts or the influence parents bear on the labor market. In this case, the greater the parents’ influence the lower the probability of being unemployed. In our analysis, father’s occupation is viewed as a proxy for influence. However, regression results show that, with everything else constant, social class background is not statistically significant. In other words, at the beginning
7 We do not model the decision to stay on at school prior to the labor market status of individuals because the Encuesta Socio Demografica contains no information on the academic performance of pupils, which is a major determinant of the decision to stay on at school.
8 For an analysis of gender differences in the Spanish labor market, see Lassibille (1998).
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Table 4
Multilogit estimates of the probability of employmenta(marginal effects)
In less than 6 months Between 6 and 18 months Coefficient t-statistics Coefficient t-statistics
Intercept 0.1246 0.93 20.0062 20.05
Age 0.0019 0.26 20.0040 20.66
Sex 0.0843 3.33 0.0163 0.76
Highest educational degree
Vocational education 20.0375 20.90 0.0800 2.20
Upper secondary education 20.1959 24.10 0.0246 0.59
Higher education
Escuela Universitaria 20.0259 20.38 0.1114 1.91
Facultad or ETS 20.1403 21.93 0.1348 2.17
Non-certified years of schooling 0.0334 0.97 0.0392 1.29
Participation in non-formal 20.0676 22.15 0.0302 1.32
education program Father’s occupation
Self-employed 20.0243 20.70 20.0352 21.18
Managers and professionals 20.0262 20.73 20.0281 20.93
Skilled workers 20.0179 20.50 0.0052 0.17
Living in town of population
Between 20,000 and 100,000 0.0775 2.02 20.0070 20.22
Over 100,000 0.0645 1.88 20.0178 20.63
Characteristics of the labor market in the home region
Rate of unemployment 20.0026 20.98 20.0054 22.31
Size of the service sector 20.0258 22.42 20.0014 20.16
Cohort (89/90) 20.0629 21.44 0.0602 1.74
Number of observations 1638
Chi2(32) 134.42
Log-likelihood 21675.29
a Individuals unemployed for more than 18 months is the comparison group.
of their professional career young people from lower socio-economic cohorts are not faced with more restric-ted access to networks for job recruitment compared with their counterparts from a higher socio-economic group. To appreciate better the effect of education on the length of employment we use regression results in Table 4 to simulate the employment status of school leavers at the three points in time in question. Table 5 displays the results of these simulations. The results show that, with all else equal, the level of education has a strong effect on the duration of unemployment. Compared with other individuals, young people who have left school with an upper secondary education diploma are in a worse situ-ation. Their probability of being unemployed for more than 18 months is respectively 42 percent and 34 percent higher than those who have a vocational or a compulsory education diploma. It is noteworthy that those people having a higher education diploma have less difficulties in finding a first job in less than 18 months, compared with young people with compulsory or upper secondary education; among individuals who leave the schooling system with a higher education diploma, those who have
Table 5
Simulated probability of employmenta
In less than Between 6 In more than 6 months and 18 18 months
months
Compulsory 0.39 0.15 0.46
education
Vocational 0.39 0.23 0.38
education
Upper secondary 0.12 0.08 0.80 education
Higher education
Escuela 0.42 0.28 0.30
universitaria
Facultad or ETS 0.39 0.15 0.46 a Based on regression results in Table 4. Simulations for the following individuals: 24-year-old male, father unskilled worker, living in a town between 20,000 and 100,000, regional rate of unemployment=16.47, relative size of the tertiary sec-tor=2.55.
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an escuela universitaria diploma are in a better situation compared with those who have a facultad or an ETS dip-loma. Another feature to emphasize is that people who leave the schooling system with a vocational diploma have a higher probability of getting an acceptable job offer in 18 months or less, compared with individuals who have just a compulsory level or an upper secondary school diploma.
The most remarkable findings so far are: (1) after trolling for personal characteristics and overall con-ditions of the regional labor market, individuals with an upper secondary school diploma have problems in find-ing acceptable job offers; (2) young people with a vocational or a higher education diploma have the short-est duration of unemployment; and (3) individuals who have just a compulsory level diploma are in a better situ-ation compared with those who have an upper secondary school diploma; however, they have more difficulties entering the labor market compared with those who have a vocational or an escuela universitaria diploma.
The regressions results in Table 4 show that non-certi-fied years of schooling have no significant impact on the length of unemployment; a result which might confirm the predominance of signaling in the labor market. As this effect probably differs according to the level of edu-cation, we include in a second specification an interac-tion term between the highest diploma obtained and the non-certified years of schooling an individual may have.9 The results indicate that the labor market rewards sig-nificantly non-certified years of schooling for those indi-viduals who have started higher education after either a vocational education diploma or upper secondary edu-cation. Simulations not displayed here show that non-certified years of higher education reduce by respectively 13 percent and 18 percent the probability of these indi-viduals finding a job in more than 18 months.
According to Table 4, participation in non-formal edu-cation programs has no negative impact on the length of unemployment. To what extent does this effect depend on the level of formal education of each individual? To answer this question we re-estimate the probability of employment adding an interaction term between formal and non-formal education.10 The results indicate that non-formal education programs reduce significantly the length of unemployment of young people with upper sec-ondary or vocational education.
Finally, regression results in Table 4 indicate that the higher the unemployment rate in the home region, the greater the length of youth unemployment—a common result in studies on youth unemployment. We observe also that the larger the size of the services sector in a region, the higher the length of youth unemployment;
9 Results available from the authors on request. 10 Results available from the authors on request.
otherwise stated, regions where employment is concen-trated in services industries generate less jobs.
4. Mismatch in the youth labor market
Although the literature on overeducation or mismatch in the labor market is quite extensive (for an updated review see Groot & Massen van den Brink, 2000), stud-ies focusing alone on young people are rather scarce (see, for example, Battu, Belfield & Sloane, 1997; Colle-taz, Sofer & Sollogoub, 1995; Dolton & Vignoles, 2000).11In the following we contribute to this literature by estimating overeducation and undereducation for the sample of about 1,000 Spanish individuals who find a first job 18 months or less after leaving the formal edu-cational system. Self-employed and unpaid family work-ers are excluded from the analysis, as well as young people who found casual employment.
Measuring overeducation raises many discussions in the literature. While some authors use a subjective defi-nition of overeducation based on self-reports by workers on the rate of skill utilization (see, for example, Alba, 1993; Cohn & Khan, 1995; Dolton & Vignoles, 2000; Hartog & Osterbeek, 1988; Sicherman, 1991), others use the distribution of qualifications to construct an overed-ucation index (see, for example, Cohn & Khan, 1995; Groot, 1993; Verdugo & Verdugo, 1989). In the follow-ing we measure the mismatch between education and work by considering the minimum qualifications required for entering a job;12 the same approach was used by Colletaz et al. (1995), Kiker, Santos & Mendes de Oliveira (1997) and Rumberger (1987). The definition of overeducation is based on a comparison of the edu-cation levels of workers and the eduedu-cational require-ments of the jobs, taking as a reference a broad classi-fication of workers in eight qualiclassi-fication levels. These categories are defined from the 3-digit occupational classification of the Instituto Nacional de Estadı´stica on the basis of the training required for adequate job per-formance. The educational requirements of each skill category are shown in Appendix A; they refer to an exogenous definition of schooling requirements based on an objective analysis of job contents. We define a worker as being overeducated if his/her educational attainment is above the educational requirement of his/her job.
11 Battu et al. (1997), like Dolton and Vignoles (2000), focus on university graduates only. Conversely, the study by Colletaz et al. (1995) has a more general scope as it refers to school leavers from primary, secondary and higher education.
12 We do this because the Encuesta Socio Demografica con-tains no information on skill utilization. Furthermore the meas-ure used in this paper enables us to compare the situation in Spain and France.
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Adequately educated workers are those whose edu-cational level just match the eduedu-cational requirement of their jobs. A worker is undereducated if his/her edu-cational attainment is below the eduedu-cational requirement of his/her job. Like the other methods developed to mea-sure overeducation, the objective approach used in this paper has its own advantages and limitations. As pointed out by Rumberger (1987), one of the advantages of the objective measure is that it is independent of the job incumbent since it is based on average educational requirements associated with homogeneous categories of jobs. However, the main problem with the objective measure of required schooling is that educational requirements can change over time due to new techno-logies and work-place organization; in this case some jobs that become more complex over time continue to be associated with lower educational requirements.
The incidence of overeducation and undereducation for the full sample of new entrants in the labor market is reported in Table 6. According to these results, the majority of workers (i.e. 55 percent) have the education required to perform their job adequately, 42 percent are overeducated, and only 3 percent are undereducated. Analysis by gender indicates that mismatches in the labor market are more frequent among women: 18 months after leaving the educational system, about 50 percent of women and 59 percent of men have the required level of education for the job. According to our estimations, 47 percent of the female workers have more education than required compared to only 38 percent for their male counterparts.
Comparing these results with available estimates for the whole Spanish population, mismatches between work and education appear to be more frequent among new entrants in the labor market than among more experi-enced workers. Using different surveys conducted in 1985 or 1991, Alba (1993), Beneito, Ferri, Molto and Uriel (1996) and Garcia Serrano and Malo (1996) report that between 17 and 30 percent of Spanish workers are overeducated, and between 17 and 23 percent are undere-ducated.13Although, our results in Table 6 are based on Table 6
Extent of the mismatch in the youth labor market (percent) Females Males Total
Overeducated 47.45 37.64 42.15
Adequately 49.64 59.41 54.91
educated
Undereducated 2.91 2.95 2.94
Total 100.00 100.00 100.00
13 In each study, the definition of overeducation is based on the individual’s self-evaluation of skill requirements.
a different measure of overeducation, they clearly sug-gest that young people are more underutilized compared to older co-workers. The differences we observe across the life cycle are in line with many other previous find-ings in the literature. They support the evidence that younger cohorts have higher educational attainment in all occupations compared to groups of older workers. As Sicherman (1991) made clear, they also suggest that young people may temporarily accept jobs requiring less education than they have in reality in order to acquire the necessary experience for job mobility. In this context overeducation of new entrants in the labor market may be viewed as being part of a phase of adaptation in the early stages of the working life.
To what extent does the situation of youth in Spain differ from that of other European countries? Owing to the lack of comparable empirical evidence, we are only able to relate our results with those obtained by Colletaz et al. (1995) for France. Using a similar measure to esti-mate the match between work and education in the French labor market, these authors found that 49 percent of young people were overeducated in their first job, 51 percent were adequately educated and about 7 percent were undereducated.14Comparatively, the incidence of overeducation is lower by about 7 percent in Spain; the proportion of adequately educated workers is about 5 percent higher among Spanish workers, and the number of undereducated workers is around 4 percent lower in Spain. These results tend to show that young Spanish workers are thus in a better situation compared to their French counterparts. Differences between the two coun-tries can probably be explained by the length of the job-search process in both countries. As shown in the pre-vious section, the length of unemployment is longer for young Spanish people; this gap may explain the better match of Spanish workers.
In order to identify the determinants of the match between education and work we adjust an ordered multi-nomial logit model from the sample of both groups of students.15Table 7 displays the results of the estimation, and gives the summary statistics of the explanatory vari-ables used in the regression. In this table, P0denotes the probability of being overeducated, P1is the probability that a worker is adequately educated and P2denotes the probability of being undereducated; the marginal effects
14 These results refer to the year 1992; so their findings are quite comparable with our results.
15 We use an ordered logit model rather than a multinomial logit model since we suppose that an individual who is undere-ducated (adequately eundere-ducated) would necessarily prefer to be adequately (overeducated) as second-best alternative. Such a unique a priori ordering of the alternatives does not apply when considering the labor market status of school leavers because, in this case, preferences depend on the reservation wage of each individual.
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Table 7
Multinomial ordered logit estimate of job match
Sample means Coefficient t-statistics Marginal effects
P0 P1 P2
Constant – 1.8404 1.538 20.401 0.391 0.010
Age 21.063 20.0169 20.335 0.004 20.004 0.000
Sex 0.542 0.3905 1.924 20.0854 0.0833 0.0021
Highest educational diploma
Vocational education 0.244 23.6904 26.022 0.7249 20.7112 20.0137
Upper secondary education 0.119 24.6612 27.214 0.7521 20.7426 20.0095
Higher education
Escuela Universitaria 0.106 22.5130 23.506 0.5518 20.5451 20.0067
Facultad or ETS 0.153 22.6321 23.434 0.5749 20.5671 20.0078
Non-certified years of schooling 0.346 0.6693 2.409 20.1399 0.1358 0.0041
Participation in non-formal 0.105 20.1192 20.453 0.0264 20.0258 20.0006
education program
Migrant 0.023 21.0186 21.513 0.2454 20.2418 20.0036
Father’s occupation
Self-employed 0.252 0.1327 0.504 20.0286 0.0278 0.0008
Managers and professionals 0.250 0.3038 1.181 20.0642 0.0624 0.0018
Skilled workers 0.236 0.1539 0.571 20.0330 0.0321 0.0018
Sector of activity
Public sectora 0.184 1.4518 3.031
20.2536 0.2397 0.0139
Industry 0.220 0.3262 0.692 20.0686 0.0666 0.0020
Service 0.484 0.2609 0.576 20.0567 0.0553 0.0015
Working full-time 0.868 20.1463 20.566 0.0312 20.0304 20.0009
Permanent contract 0.724 0.3093 1.435 20.0689 0.0673 0.0016
Previously unemployed for at least 6 0.633 0.2084 1.134 20.045 0.044 0.001
months
Living in town of population
Between 20,000 and 100,000 0.220 0.1739 0.604 20.0372 0.0362 0.0010
Over 100,000 0.469 0.0276 0.117 20.0060 0.0059 0.0001
Characteristics of the labor market in the home region
Rate of unemployment 16.121 20.0150 20.703 0.0033 20.0032 20.0001
Size of the service sector 2.395 0.0733 0.813 20.0160 0.0156 0.0004
Cohort (89/90) 0.532 0.3918 1.026 20.0856 0.0834 0.0022
µ – 5.9363 21.214
Number of observations 979 –
Log likelihood – 2504.854
Restricted likelihood – 2785.9059
Chi-square – 509.6411
a Including public administration, education and health services.
of the explanatory variables are computed in a standard way (see, for example, Greene, 1997). The personal characteristics included in the model are: age, sex, level of education, participation in a non-formal educational program, migrant/non-migrant status, length of unem-ployment and family background. The job characteristics include the sector of current firm and the worker’s employment conditions; we also control for the unem-ployment rate of the whole population in the region, as well as for the percentage of workers employed in the service sector.
According to Table 7, the multinomial logit model fits
relatively well the match between education and work; the chi-squared test is significant at the 1 percent level, indicating that the slope coefficients are significantly dif-ferent from zero.
The results show that with everything else constant, male workers are less likely to be overeducated in their first job compared to their female counterparts. A similar result was found for France (Colletaz et al., 1995); lower matching for females workers may be explained either by discrimination in the labor market or by job search inefficiency. Among the other explanatory variables included in the regression model, family background
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(i.e., father’s occupation, mother’s employment status, family size) has no influence on the job match; however, these variables may have an indirect impact on the inci-dence of overeducation through the educational attain-ment of young people.
So far as the level of education is concerned, a first noteworthy feature in the results is that the probability of being overeducated rather than adequately educated when in employment is higher for young people with upper secondary education or vocational education. A second feature to emphasize is that workers with higher education are less likely to be over- or undereducated compared to individuals with secondary education. Regression results show that the difference between young people who possess a facultad diploma or an
escuela universitaria diploma is small; all else remaining
the same, the probability of a facultad graduate being overeducated is only 2 percent higher compared to his or her escuela universitaria counterpart. Hence, after controlling for other observed characteristics, these pieces of evidence support the arguments that at the beginning of the working life (i) a strong relationship does exist between job match and formal education, and (ii) educated workers are less likely to occupy jobs for which they are overeducated. These results are in line with more general findings on the mismatches in the Spanish adult labor market (Alba, 1993; Garcia Ser-rano & Malo, 1996).
Furthermore, regression results in Table 7 show that non-certified years of schooling increase significantly the probability of being adequately educated or overedu-cated. Additional econometric tests, including an interac-tion term between the highest diploma and the non-certi-fied years of schooling, indicate that this effect differs widely across educational levels.16 In particular, we observe that those individuals who have a secondary education diploma are more likely, if they have started higher education studies, to be adequately educated com-pared with those from the other group.
Participation in non-formal education programs has no significant impact on the job match. However, regression results, not shown here to save space, indicate that a sig-nificant interaction effect between formal and non-formal education does exist. In particular, those who possess a low level of education (i.e., a vocational diploma or a diploma of general secondary education) and who enrolled in a non-formal education program, are less likely to be overeducated compared with those who have a higher education diploma.17This finding supports the idea that non-formal education can substitute for insuf-ficient formal schooling.
All else remaining the same, the length of
unemploy-16 Results available from the authors on request. 17 Results available from the authors on request.
ment after completion of formal education is not a good predictor of job matching. In other words the length of the job search affects neither the probability of being overeducated nor that of being adequately educated. So far as the sector of activity is concerned, the results show that young people employed in the public sector are more likely to be adequately educated compared to their priv-ate sector counterparts. According to regression results in Table 7, holding everything else constant, a public sector employee has a 24 percent points higher prob-ability of being adequately educated than a private sec-tor worker.
All else being equal, workers with a permanent con-tract are less likely to be overeducated. Since the average return to years of overeducation in the labor market is generally smaller than the return to required years of education (see, for example, Groot & Massen van den Brink, 2000), those who receive a permanent contract in their first job are very likely to make a trade-off between job security and pay.
Furthermore, young people who moved from their home region to find a first job have a higher probability of being in a job which requires less qualifications than they have in reality. According to our data, migrant workers are more likely to hold a permanent contract than non-migrant workers (56 percent vs. 48 percent). Thus one interpretation is that the career strategy of migrant workers is more to find job security in a first job rather than to find access to a better paid job.
Finally, the results indicate that local labor market conditions, measured by the rate of unemployment of the entire population in the region, have no significant impact on the job match between education and work. In other words, the competition between job applicants increases the length of unemployment of young workers but leaves unchanged their probability of being overedu-cated or adequately eduoveredu-cated. This is in accordance with meta-analysis of studies on mismatch in the adult labor market (Groot & Massen van den Brink, 2000).
5. Conclusion
Using a unique dataset of school leavers, we focused on both the length of unemployment and the job match in the youth labor market.
So far as the length of unemployment is concerned, the results indicate that family background has no sig-nificant impact on the length of unemployment and that young women are far more likely to be unemployed compared to their male counterparts. We also found that the level of education exerts a strong influence on the length of unemployment. In particular, individuals who leave the school system with upper secondary education have more difficulty than other individuals in finding a job at the beginning of the working life. However,
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par-ticipation in non-formal programs reduces significantly the length of unemployment of the category of individ-uals in question.
Turning to job matching the results reported above suggest that a majority of young Spanish workers have the education required to perform their job adequately. However, there are some important differences in the mismatching across gender, the level of education and the sector of activity. In particular, we found that work-ers with higher education are better matched in their first job than workers with vocational and upper secondary education. Clearly, this observation questions the efficiency of these two levels of education; a key prob-lem in the Spanish education system. As stated, the analysis reported in this paper refers only to job matches at the very early stage of the working life of young work-ers. Because overeducation may be a temporary phenom-enon, additional analysis should be performed to (1) measure the extent of mismatch over a longer period after leaving the educational system and (2) trace its implications on earnings. Owing to the lack of appropri-ate data these two points are left for further investigation. In the light of the results reported above, what are the implications for policy development for the improvement of the transition process from school to work?
Taken together, both the analyses performed in this paper indicate that on average individuals with an upper secondary education diploma experience major problems at the beginning of their working life. These problems are partly due to the organization of the educational sys-tem. As shown by Lassibille and Navarro Go´mez (2000), the Spanish educational system is less differentiated than other European systems. Compulsory education is organized on the basis of a common-core syllabus from the time of entry into primary education to the end of compulsory education. The absence of a selection criteria at the level of the upper secondary education implies that pupils have few incentives to enroll in vocational and technical education, which have lower rates of return in the labor market (see Lassibille & Navarro Go´mez, 1998). As a consequence, a large proportion of pupils leave the schooling system without any professional qualifications. Moreover, public programs designed to put low-skilled youth to work are relatively scarce and a large proportion of disadvantaged school leavers have to take non-formal educational to increase their chances in the labor market. Given the empirical evidence docu-mented in the earlier sections of this paper, a major strat-egy for improving the transition from school to work may well consist in a greater differentiation of the edu-cational system at the compulsory level, based on explicitly sorting pupils into professional and non-pro-fessional streams.
Acknowledgements
This research is part of the EC/TSER program on Schooling, Training and Transition (STT). We are grate-ful to the participants at the Amsterdam STT Meeting, September 1998, and to two anonymous reviewers for their comments on an early draft.
Appendix A. Qualification levels and educational requirements
Table 8
Qualification levels Educational requirements Managers and highly Facultad or ETS diploma skilled technicians
Skilled technicians EEUU diploma
Technicians at Upper secondary education intermediate level diploma
Middle manager Upper secondary education diploma or upper vocational diploma
Skilled clerk Upper secondary education diploma or vocational diploma Unskilled clerk Compulsory education diploma Skilled worker Lower vocational diploma or
compulsory education diploma Unskilled worker Compulsory education diploma
or incomplete compulsory educational level
References
Alba, R. (1993). Mismatch in the Spanish labor market: overed-ucation? The Journal of Human Resources, 28, 259–278. Andrews, M., & Bradley, S. (1997). Modelling the transition
from school and the demand for training in the United King-dom. Economica, 64, 387–413.
Battu, H., Belfield, C. R., & Sloane, P. J. (1997). Overeducation among graduates: A cohort view. Mimeo. Aberdeen: Uni-versity of Aberdeen.
Beneito, P., Ferri, J., Molto, M. L., & Uriel E. (1996). Desajuste educativo y formacion laboral especializada: efectos sobre los rendimientos salariales. Working Paper 9611. Valencia: Instituto Valenciano de Investigaciones Economicas. Blau, F., & Kahn, L. (1997). Gender and youth employment
outcomes: The US and West Germany, 1984–91. Working Paper 6078. Cambridge: National Bureau of Economic Research.
Cohn, E., & Khan, S. (1995). The wage effects of overschooling revisited. Labour Economics, 2, 67–76.
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e´cono-me´trique du marche´ du travail des jeunes a` partir d’enqueˆtes d’insertion. Mimeo. Orle´ans: Leo-CRESEP.
Dolton, P., & Vignoles, A. (2000). The incidence and effects of overeducation in the U.K. graduate labour market. Eco-nomics of Education Review, 19 (2), 000.
Edin, P. A., Forslund, A., & Holmlund, B. (1996). The Swedish youth labor market in boom and depression. Paper presented at the NBER Conference on Youth Unemployment and Employment in Advanced Countries, Winston-Salem. Franz, W., Inkmann, J., Pohlmeier, W., & Zimmermann V.
(1997). Young and out in Germany: On the youth’s chances of labor market entrance in Germany. Working Paper 6212. Cambridge: National Bureau of Economic Research. Garcia Serrano, C., & Malo, M. A. (1996). Desajuste educativo
y movilidad laboral en Espan˜a. Revista de Economia Aplicada, 11, 105–131.
Greene, W. H. (1997). Econometric analysis. (3rd ed.). London: Prentice-Hall International.
Groot, W. (1993). Overeducation and the returns to enterprise-related schooling. Economics of Education Review, 1, 299–309.
Groot, W., & Massen van den Brink, H. (2000). Overeducation in the labor market: a meta-analysis. Economics of Edu-cation Review, 19 (2), 000.
Hartog, J., & Osterbeek, H. (1988). Education, allocation and earnings in the Netherlands: overschooling. Economics of Education Review, 7, 185–194.
Instituto Nacional de Estadı´stica. (1991). Encuesta Sociodemo-gra´fica, Metodologia. Madrid: Instituto Nacional de Estadı´-stica.
Kiker, B. F., Santos, M. C., & Mendes De Oliveira, M. (1997). Overeducation and undereducation: evidence for Portugal. Economics of Education Review, 16, 111–125.
Korenman, S., & Neumark, D. (1997). Cohort crowding and youth labor markets: a cross-national analysis. Working Paper 6031. Cambridge: National Bureau of Economic Research.
Lassibille, G. (1998). Wage gaps between public and private sectors in Spain. Economics of Education Review, 17, 83– 92.
Lassibille, G., & Navarro Go´mez, L. (1998). The evolution of returns to education in Spain. Education Economics, 6, 3–9. Lassibille, G., & Navarro Go´mez, L. (2000). Organization and efficiency of schooling systems: some empirical findings. Comparative Education, 36 (1), 000.
OECD. (1998). Organization for Economic Co-operation and Development. Education at a glance: OECD indicators 1998. Paris: OECD.
Rees, A., & Gray, W. (1982). Family effects in youth employ-ment. In R. B. Freeman, & D. A. Wise, The youth labor market problem: Its nature, causes and consequences. Chicago: Universtiy of Chicago Press.
Rumberger, R. W. (1987). The impact of surplus schooling on productivity and earnings. Journal of Human Resources, 22, 24–50.
Sicherman, N. (1991). Overeducation in the labor market. Jour-nal of Labor Economics, 9, 101–122.
Verdugo, R., & Verdugo, N. (1989). The impact of surplus schooling on earnings: some additional findings. Journal of Human Resources, 24, 629–643.
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an escuela universitaria diploma are in a better situation compared with those who have a facultad or an ETS dip-loma. Another feature to emphasize is that people who leave the schooling system with a vocational diploma have a higher probability of getting an acceptable job offer in 18 months or less, compared with individuals who have just a compulsory level or an upper secondary school diploma.
The most remarkable findings so far are: (1) after trolling for personal characteristics and overall con-ditions of the regional labor market, individuals with an upper secondary school diploma have problems in find-ing acceptable job offers; (2) young people with a vocational or a higher education diploma have the short-est duration of unemployment; and (3) individuals who have just a compulsory level diploma are in a better situ-ation compared with those who have an upper secondary school diploma; however, they have more difficulties entering the labor market compared with those who have a vocational or an escuela universitaria diploma.
The regressions results in Table 4 show that non-certi-fied years of schooling have no significant impact on the length of unemployment; a result which might confirm the predominance of signaling in the labor market. As this effect probably differs according to the level of edu-cation, we include in a second specification an interac-tion term between the highest diploma obtained and the non-certified years of schooling an individual may have.9
The results indicate that the labor market rewards sig-nificantly non-certified years of schooling for those indi-viduals who have started higher education after either a vocational education diploma or upper secondary edu-cation. Simulations not displayed here show that non-certified years of higher education reduce by respectively 13 percent and 18 percent the probability of these indi-viduals finding a job in more than 18 months.
According to Table 4, participation in non-formal edu-cation programs has no negative impact on the length of unemployment. To what extent does this effect depend on the level of formal education of each individual? To answer this question we re-estimate the probability of employment adding an interaction term between formal and non-formal education.10 The results indicate that
non-formal education programs reduce significantly the length of unemployment of young people with upper sec-ondary or vocational education.
Finally, regression results in Table 4 indicate that the higher the unemployment rate in the home region, the greater the length of youth unemployment—a common result in studies on youth unemployment. We observe also that the larger the size of the services sector in a region, the higher the length of youth unemployment;
9 Results available from the authors on request. 10 Results available from the authors on request.
otherwise stated, regions where employment is concen-trated in services industries generate less jobs.
4. Mismatch in the youth labor market
Although the literature on overeducation or mismatch in the labor market is quite extensive (for an updated review see Groot & Massen van den Brink, 2000), stud-ies focusing alone on young people are rather scarce (see, for example, Battu, Belfield & Sloane, 1997; Colle-taz, Sofer & Sollogoub, 1995; Dolton & Vignoles, 2000).11In the following we contribute to this literature
by estimating overeducation and undereducation for the sample of about 1,000 Spanish individuals who find a first job 18 months or less after leaving the formal edu-cational system. Self-employed and unpaid family work-ers are excluded from the analysis, as well as young people who found casual employment.
Measuring overeducation raises many discussions in the literature. While some authors use a subjective defi-nition of overeducation based on self-reports by workers on the rate of skill utilization (see, for example, Alba, 1993; Cohn & Khan, 1995; Dolton & Vignoles, 2000; Hartog & Osterbeek, 1988; Sicherman, 1991), others use the distribution of qualifications to construct an overed-ucation index (see, for example, Cohn & Khan, 1995; Groot, 1993; Verdugo & Verdugo, 1989). In the follow-ing we measure the mismatch between education and work by considering the minimum qualifications required for entering a job;12 the same approach was
used by Colletaz et al. (1995), Kiker, Santos & Mendes de Oliveira (1997) and Rumberger (1987). The definition of overeducation is based on a comparison of the edu-cation levels of workers and the eduedu-cational require-ments of the jobs, taking as a reference a broad classi-fication of workers in eight qualiclassi-fication levels. These categories are defined from the 3-digit occupational classification of the Instituto Nacional de Estadı´stica on the basis of the training required for adequate job per-formance. The educational requirements of each skill category are shown in Appendix A; they refer to an exogenous definition of schooling requirements based on an objective analysis of job contents. We define a worker as being overeducated if his/her educational attainment is above the educational requirement of his/her job.
11 Battu et al. (1997), like Dolton and Vignoles (2000), focus on university graduates only. Conversely, the study by Colletaz et al. (1995) has a more general scope as it refers to school leavers from primary, secondary and higher education.
12 We do this because the Encuesta Socio Demografica con-tains no information on skill utilization. Furthermore the meas-ure used in this paper enables us to compare the situation in Spain and France.
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Adequately educated workers are those whose edu-cational level just match the eduedu-cational requirement of their jobs. A worker is undereducated if his/her edu-cational attainment is below the eduedu-cational requirement of his/her job. Like the other methods developed to mea-sure overeducation, the objective approach used in this paper has its own advantages and limitations. As pointed out by Rumberger (1987), one of the advantages of the objective measure is that it is independent of the job incumbent since it is based on average educational requirements associated with homogeneous categories of jobs. However, the main problem with the objective measure of required schooling is that educational requirements can change over time due to new techno-logies and work-place organization; in this case some jobs that become more complex over time continue to be associated with lower educational requirements.
The incidence of overeducation and undereducation for the full sample of new entrants in the labor market is reported in Table 6. According to these results, the majority of workers (i.e. 55 percent) have the education required to perform their job adequately, 42 percent are overeducated, and only 3 percent are undereducated. Analysis by gender indicates that mismatches in the labor market are more frequent among women: 18 months after leaving the educational system, about 50 percent of women and 59 percent of men have the required level of education for the job. According to our estimations, 47 percent of the female workers have more education than required compared to only 38 percent for their male counterparts.
Comparing these results with available estimates for the whole Spanish population, mismatches between work and education appear to be more frequent among new entrants in the labor market than among more experi-enced workers. Using different surveys conducted in 1985 or 1991, Alba (1993), Beneito, Ferri, Molto and Uriel (1996) and Garcia Serrano and Malo (1996) report that between 17 and 30 percent of Spanish workers are overeducated, and between 17 and 23 percent are undere-ducated.13Although, our results in Table 6 are based on Table 6
Extent of the mismatch in the youth labor market (percent) Females Males Total Overeducated 47.45 37.64 42.15 Adequately 49.64 59.41 54.91 educated
Undereducated 2.91 2.95 2.94 Total 100.00 100.00 100.00
13 In each study, the definition of overeducation is based on the individual’s self-evaluation of skill requirements.
a different measure of overeducation, they clearly sug-gest that young people are more underutilized compared to older co-workers. The differences we observe across the life cycle are in line with many other previous find-ings in the literature. They support the evidence that younger cohorts have higher educational attainment in all occupations compared to groups of older workers. As Sicherman (1991) made clear, they also suggest that young people may temporarily accept jobs requiring less education than they have in reality in order to acquire the necessary experience for job mobility. In this context overeducation of new entrants in the labor market may be viewed as being part of a phase of adaptation in the early stages of the working life.
To what extent does the situation of youth in Spain differ from that of other European countries? Owing to the lack of comparable empirical evidence, we are only able to relate our results with those obtained by Colletaz et al. (1995) for France. Using a similar measure to esti-mate the match between work and education in the French labor market, these authors found that 49 percent of young people were overeducated in their first job, 51 percent were adequately educated and about 7 percent were undereducated.14Comparatively, the incidence of
overeducation is lower by about 7 percent in Spain; the proportion of adequately educated workers is about 5 percent higher among Spanish workers, and the number of undereducated workers is around 4 percent lower in Spain. These results tend to show that young Spanish workers are thus in a better situation compared to their French counterparts. Differences between the two coun-tries can probably be explained by the length of the job-search process in both countries. As shown in the pre-vious section, the length of unemployment is longer for young Spanish people; this gap may explain the better match of Spanish workers.
In order to identify the determinants of the match between education and work we adjust an ordered multi-nomial logit model from the sample of both groups of students.15Table 7 displays the results of the estimation,
and gives the summary statistics of the explanatory vari-ables used in the regression. In this table, P0denotes the
probability of being overeducated, P1is the probability
that a worker is adequately educated and P2denotes the
probability of being undereducated; the marginal effects
14 These results refer to the year 1992; so their findings are quite comparable with our results.
15 We use an ordered logit model rather than a multinomial logit model since we suppose that an individual who is undere-ducated (adequately eundere-ducated) would necessarily prefer to be adequately (overeducated) as second-best alternative. Such a unique a priori ordering of the alternatives does not apply when considering the labor market status of school leavers because, in this case, preferences depend on the reservation wage of each individual.
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Table 7
Multinomial ordered logit estimate of job match
Sample means Coefficient t-statistics Marginal effects
P0 P1 P2
Constant – 1.8404 1.538 20.401 0.391 0.010 Age 21.063 20.0169 20.335 0.004 20.004 0.000 Sex 0.542 0.3905 1.924 20.0854 0.0833 0.0021 Highest educational diploma
Vocational education 0.244 23.6904 26.022 0.7249 20.7112 20.0137 Upper secondary education 0.119 24.6612 27.214 0.7521 20.7426 20.0095 Higher education
Escuela Universitaria 0.106 22.5130 23.506 0.5518 20.5451 20.0067
Facultad or ETS 0.153 22.6321 23.434 0.5749 20.5671 20.0078
Non-certified years of schooling 0.346 0.6693 2.409 20.1399 0.1358 0.0041 Participation in non-formal 0.105 20.1192 20.453 0.0264 20.0258 20.0006 education program
Migrant 0.023 21.0186 21.513 0.2454 20.2418 20.0036 Father’s occupation
Self-employed 0.252 0.1327 0.504 20.0286 0.0278 0.0008 Managers and professionals 0.250 0.3038 1.181 20.0642 0.0624 0.0018 Skilled workers 0.236 0.1539 0.571 20.0330 0.0321 0.0018 Sector of activity
Public sectora 0.184 1.4518 3.031
20.2536 0.2397 0.0139 Industry 0.220 0.3262 0.692 20.0686 0.0666 0.0020 Service 0.484 0.2609 0.576 20.0567 0.0553 0.0015 Working full-time 0.868 20.1463 20.566 0.0312 20.0304 20.0009 Permanent contract 0.724 0.3093 1.435 20.0689 0.0673 0.0016 Previously unemployed for at least 6 0.633 0.2084 1.134 20.045 0.044 0.001 months
Living in town of population
Between 20,000 and 100,000 0.220 0.1739 0.604 20.0372 0.0362 0.0010 Over 100,000 0.469 0.0276 0.117 20.0060 0.0059 0.0001 Characteristics of the labor market
in the home region
Rate of unemployment 16.121 20.0150 20.703 0.0033 20.0032 20.0001 Size of the service sector 2.395 0.0733 0.813 20.0160 0.0156 0.0004 Cohort (89/90) 0.532 0.3918 1.026 20.0856 0.0834 0.0022
µ – 5.9363 21.214
Number of observations 979 – Log likelihood – 2504.854 Restricted likelihood – 2785.9059
Chi-square – 509.6411
a Including public administration, education and health services.
of the explanatory variables are computed in a standard way (see, for example, Greene, 1997). The personal characteristics included in the model are: age, sex, level of education, participation in a non-formal educational program, migrant/non-migrant status, length of unem-ployment and family background. The job characteristics include the sector of current firm and the worker’s employment conditions; we also control for the unem-ployment rate of the whole population in the region, as well as for the percentage of workers employed in the service sector.
According to Table 7, the multinomial logit model fits
relatively well the match between education and work; the chi-squared test is significant at the 1 percent level, indicating that the slope coefficients are significantly dif-ferent from zero.
The results show that with everything else constant, male workers are less likely to be overeducated in their first job compared to their female counterparts. A similar result was found for France (Colletaz et al., 1995); lower matching for females workers may be explained either by discrimination in the labor market or by job search inefficiency. Among the other explanatory variables included in the regression model, family background
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(i.e., father’s occupation, mother’s employment status, family size) has no influence on the job match; however, these variables may have an indirect impact on the inci-dence of overeducation through the educational attain-ment of young people.
So far as the level of education is concerned, a first noteworthy feature in the results is that the probability of being overeducated rather than adequately educated when in employment is higher for young people with upper secondary education or vocational education. A second feature to emphasize is that workers with higher education are less likely to be over- or undereducated compared to individuals with secondary education. Regression results show that the difference between young people who possess a facultad diploma or an escuela universitaria diploma is small; all else remaining the same, the probability of a facultad graduate being overeducated is only 2 percent higher compared to his or her escuela universitaria counterpart. Hence, after controlling for other observed characteristics, these pieces of evidence support the arguments that at the beginning of the working life (i) a strong relationship does exist between job match and formal education, and (ii) educated workers are less likely to occupy jobs for which they are overeducated. These results are in line with more general findings on the mismatches in the Spanish adult labor market (Alba, 1993; Garcia Ser-rano & Malo, 1996).
Furthermore, regression results in Table 7 show that non-certified years of schooling increase significantly the probability of being adequately educated or overedu-cated. Additional econometric tests, including an interac-tion term between the highest diploma and the non-certi-fied years of schooling, indicate that this effect differs widely across educational levels.16 In particular, we
observe that those individuals who have a secondary education diploma are more likely, if they have started higher education studies, to be adequately educated com-pared with those from the other group.
Participation in non-formal education programs has no significant impact on the job match. However, regression results, not shown here to save space, indicate that a sig-nificant interaction effect between formal and non-formal education does exist. In particular, those who possess a low level of education (i.e., a vocational diploma or a diploma of general secondary education) and who enrolled in a non-formal education program, are less likely to be overeducated compared with those who have a higher education diploma.17This finding supports the
idea that non-formal education can substitute for insuf-ficient formal schooling.
All else remaining the same, the length of
unemploy-16 Results available from the authors on request. 17 Results available from the authors on request.
ment after completion of formal education is not a good predictor of job matching. In other words the length of the job search affects neither the probability of being overeducated nor that of being adequately educated. So far as the sector of activity is concerned, the results show that young people employed in the public sector are more likely to be adequately educated compared to their priv-ate sector counterparts. According to regression results in Table 7, holding everything else constant, a public sector employee has a 24 percent points higher prob-ability of being adequately educated than a private sec-tor worker.
All else being equal, workers with a permanent con-tract are less likely to be overeducated. Since the average return to years of overeducation in the labor market is generally smaller than the return to required years of education (see, for example, Groot & Massen van den Brink, 2000), those who receive a permanent contract in their first job are very likely to make a trade-off between job security and pay.
Furthermore, young people who moved from their home region to find a first job have a higher probability of being in a job which requires less qualifications than they have in reality. According to our data, migrant workers are more likely to hold a permanent contract than non-migrant workers (56 percent vs. 48 percent). Thus one interpretation is that the career strategy of migrant workers is more to find job security in a first job rather than to find access to a better paid job.
Finally, the results indicate that local labor market conditions, measured by the rate of unemployment of the entire population in the region, have no significant impact on the job match between education and work. In other words, the competition between job applicants increases the length of unemployment of young workers but leaves unchanged their probability of being overedu-cated or adequately eduoveredu-cated. This is in accordance with meta-analysis of studies on mismatch in the adult labor market (Groot & Massen van den Brink, 2000).
5. Conclusion
Using a unique dataset of school leavers, we focused on both the length of unemployment and the job match in the youth labor market.
So far as the length of unemployment is concerned, the results indicate that family background has no sig-nificant impact on the length of unemployment and that young women are far more likely to be unemployed compared to their male counterparts. We also found that the level of education exerts a strong influence on the length of unemployment. In particular, individuals who leave the school system with upper secondary education have more difficulty than other individuals in finding a job at the beginning of the working life. However,
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par-ticipation in non-formal programs reduces significantly the length of unemployment of the category of individ-uals in question.
Turning to job matching the results reported above suggest that a majority of young Spanish workers have the education required to perform their job adequately. However, there are some important differences in the mismatching across gender, the level of education and the sector of activity. In particular, we found that work-ers with higher education are better matched in their first job than workers with vocational and upper secondary education. Clearly, this observation questions the efficiency of these two levels of education; a key prob-lem in the Spanish education system. As stated, the analysis reported in this paper refers only to job matches at the very early stage of the working life of young work-ers. Because overeducation may be a temporary phenom-enon, additional analysis should be performed to (1) measure the extent of mismatch over a longer period after leaving the educational system and (2) trace its implications on earnings. Owing to the lack of appropri-ate data these two points are left for further investigation. In the light of the results reported above, what are the implications for policy development for the improvement of the transition process from school to work?
Taken together, both the analyses performed in this paper indicate that on average individuals with an upper secondary education diploma experience major problems at the beginning of their working life. These problems are partly due to the organization of the educational sys-tem. As shown by Lassibille and Navarro Go´mez (2000), the Spanish educational system is less differentiated than other European systems. Compulsory education is organized on the basis of a common-core syllabus from the time of entry into primary education to the end of compulsory education. The absence of a selection criteria at the level of the upper secondary education implies that pupils have few incentives to enroll in vocational and technical education, which have lower rates of return in the labor market (see Lassibille & Navarro Go´mez, 1998). As a consequence, a large proportion of pupils leave the schooling system without any professional qualifications. Moreover, public programs designed to put low-skilled youth to work are relatively scarce and a large proportion of disadvantaged school leavers have to take non-formal educational to increase their chances in the labor market. Given the empirical evidence docu-mented in the earlier sections of this paper, a major strat-egy for improving the transition from school to work may well consist in a greater differentiation of the edu-cational system at the compulsory level, based on explicitly sorting pupils into professional and non-pro-fessional streams.
Acknowledgements
This research is part of the EC/TSER program on Schooling, Training and Transition (STT). We are grate-ful to the participants at the Amsterdam STT Meeting, September 1998, and to two anonymous reviewers for their comments on an early draft.
Appendix A. Qualification levels and educational requirements
Table 8
Qualification levels Educational requirements Managers and highly Facultad or ETS diploma
skilled technicians
Skilled technicians EEUU diploma
Technicians at Upper secondary education intermediate level diploma
Middle manager Upper secondary education diploma or upper vocational diploma
Skilled clerk Upper secondary education diploma or vocational diploma Unskilled clerk Compulsory education diploma Skilled worker Lower vocational diploma or
compulsory education diploma Unskilled worker Compulsory education diploma
or incomplete compulsory educational level
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