The role of vocational education on unemployment in Indonesia

Abstract

In 2006, the Government of Indonesia began a national program of vocational high school expansion in Indonesia. Since then, the number of vocational high school graduates has been increasing significantly. The purpose of this study is to examine the role of vocational education on the probability of unemployment in developing countries using the case of Indonesia. We include demographic factors of age, squared age, gender, location of residence and marital status as control variables. This study uses cross-section data from the Indonesian National Labor Force Survey of August 2019. We restrict our sample to individuals with secondary high school as their highest education level. With binary dependent variable of unemployment status, we employ logit and probit estimation model in our estimation. The estimation results show that individuals with vocational education have a statistically significant lower probability of being unemployed contrasted to those individuals with non-vocational education. However, further analysis of the unemployment rates of vocational high school graduates by age shows that the case might not be applicable to recent graduates of vocational high school. Meanwhile, the control variables of age, age squared, gender, location of residence and marital status show the expected signs.

Keywords:

• Indonesia
• labor market
• secondary education
• unemployment
• vocational education

REVIEWING EDITOR:

• Arif H. Kabir, Deakin University School of Education, Australia

SUBJECTS:

• Education – Social Sciences
• Development Policy
• Education Policy

Introduction

Economic growth is an important aspect in the development of a country as it indicates the level of economic activity and welfare of the country. Broadly speaking, the three factors that affect a country’s economic growth are gross domestic product, unemployment and inflation. Unemployment is one of the concerns of economists because it relates to social welfare and output per capita which directly affects the economy (Blanchard, 2017). Unemployment in Indonesia fluctuates from time to time with a downward trend. Figure 1 shows that the open unemployment rate in Indonesia has a downward trend in 2012–2019, except for a slight increase in 2015 and significant increase in 2020. The significant increase in 2020 was particularly due to the COVID-19 pandemic where there were rampant layoffs and a lack of absorption of labor due to a disproportionate increase in the labor force compared to the number of jobs available.

Figure 1. Indonesia’s open unemployment rate 2012–2022 (%).

In addition to education, work experience is an added value possessed by an individual or workforce in getting a job or avoiding unemployment status. According to Oswald-Egg and Renold (2021), a workforce with more experience will have a higher demand in the labor market. However, a study in Uganda argues that the higher a person’s education will increase the probability of unemployment because reservation wages are higher as education is completed (Egessa et al., 2021). Debate about the relationship between education and experience with the unemployment rate is still going on along with studies at various times and places.

In Indonesia, the level of completion of education is still relatively low and most of the Indonesian population can only complete education up to secondary education (according to the 12-year compulsory education). Figure 2 shows that the largest proportion of the last education of the workforce aged over 15 years in Indonesia is primary school (24.78%) and general high school (20.11%) while the completion rate of vocational high school is still low at 12.28%. The fact of low schooling is quite worrying because the results a study by Seran (2017) during 2000–2015 in Indonesia show that an individual will only have a higher probability of getting a job when the individual is having a higher education. Another study by Kharisma and Wardhana (2021) using data from 33 provinces in Indonesia in 2011–2019 shows that the average length of schooling has a significant negative effect on unemployment, which means that the lower the average schooling length of an individual will further increase the individual’s probability of being unemployed.

Figure 2. Education completion rate of the workforce aged >15 years in Indonesia, 2022 (%).

In responding to this phenomenon, a type of education is needed that can meet both criteria, namely formal education accompanied by good work experience. Vocational education is one of the government’s efforts to provide formal education. Vocational education is one of the main concerns to the government along with the need for a workforce that has quality human capital and ‘ensures quality education that is inclusive and equitable and promotes lifelong learning opportunities for all’ as written in Goal 4 of the Sustainable Development Goals (UN, 2015). Vocational education does not only teach theoretical information but also important work skills in accordance with the majors they take. Both are a combination that is expected to improve the quality of labor market output (Suharno et al., 2020). Since 2006, the Ministry of National Education has begun to expand to SMK or vocational high school (which is included in vocational education other than diplomas and academies) through the Strategic Plan of the Ministry of National Education 2005–2009. The objective of the policy is to increase the workforce who are ready to work, especially those who do not continue to higher education by increasing the proportion of the number of senior high school (Sekolah Menengah Atas - SMA/ Sekolah Menengah Atas - SMU) students to vocational high school (SMK). Initially, the ratio of general high school students to vocational high school students was 70:30 in 2004 and the target is to achieve the ratio of 50:50 in 2015, and finally to 70:30 in 202530:70 in 2015.

This policy is supported by the increasing interest of junior high school graduates to continue their education to the vocational high school (SMK). Junior high school graduates continue their education to the SMK level for several reasons, such as getting a better job upon graduation so that they can help the economy of their family and also families who want their children to have better knowledge and skills to compete in the labor market (Lestari & Mudzakkir, 2016; Santoso, 2014). The number of SMK students has continued to increase every year in the last few years. Vocational high school students have the expectation of getting a job faster and better than general high school graduates thereby reducing their probability of being unemployed. The fact that vocational education, particularly at high school level, has been one of the main focuses of the Government of Indonesia, it is important to identify the role of vocational high school on the probability of unemployment at the individual level.

Literature review

According to Suharno et al. (2020) vocational education means education that can produce expert interpreters who are capable of doing specific jobs in a professional manner. Vocational education in Indonesia is carried out at the upper secondary education level, namely vocational high schools (SMK). The government through the Ministry of National Education launched the Strategic Plan of the Ministry of National Education for 2005–2009 which targeted the existence of vocational education compared to general education at 70:30 in 2015. The program was carried out considering that many high school students do not continue on to higher education so they do not have work experience upon graduation. In this case, vocational education is a solution to create a skilled and educated work force, considering that 87% of students graduating from vocational high school do not continue on to higher education, such as university or diploma. Vocational education in Indonesia combines formal education and practical work according to expertize, such as automotive, management and engineering.

There have been several studies examining the role of vocational education on unemployment. In comparison to non-vocational education, vocational education has a greater positive effect on the probability of remaining employed so that the probability of unemployment will be lower because vocational education has more job-specific education programs (Brunello & Rocco, 2017; Forster et al., 2016). This statement was also examined by Korber and Oesch (2019) in Switzerland which stated that individuals with the highest education of general high school education would be more prone to unemployment than individuals with the highest education of vocational high school education. Torun and Tumen (2019) in their research in Turkey also compared vocational education and non-vocational education in terms of the probability of getting a job and their result shows that individuals with the vocational education had a 5% higher probability in getting a job than individuals with non-vocational education. Vocational education also has the potential to increase labor productivity which makes it contribute to reducing unemployment at a young age (Lee, 2020) and increases the possibility of being employed in the formal sector (Malamud & Pop-Eleches, 2010). These previous studies show that vocational education, especially vocational high school education, can reduce the probability of being unemployed during the life cycle of the graduates, especially for young workers. In addition, the probability of individuals with the vocational high school education to be employed in the formal sector is also higher than individuals with general high school education.

Several studies have been conducted both in Indonesia and abroad regarding the effect of vocational education on unemployment. Abroad, several authors use PIAAC (Program for the International Assessment of Adult Competencies) data such as Brunello and Rocco (2017) and Choi et al. (2019) which has the result that vocational education is superior to non-vocational in terms of the probability of being employed but there are differences in results between vocational which are more inclined toward formal education and work practices. In the context of research in Indonesia, Newhouse and Suryadarma (2011) conducted research on the relationship between senior secondary education possessed by young Indonesians and their labor output as measured by wages, labor market participation, probability of unemployment and quality of work. The result is that vocational education succeeds in reducing the probability of unemployment for both men and women until the age of thirties. It indicates that individuals with a vocational education background are less vulnerable to unemployment than individuals with a non-vocational education background. Another study by Ohara et al. (2020) explore the proportion of general and vocational secondary high school students, to find out the unemployment rate of both school types and to identify policy alternatives to reduce the unemployment rate of vocational high school graduates. The research find that a new policy is needed to reduce the unemployment rate of vocational high school graduates in the form of a moratorium for vocational secondary school expansion, particularly in Java Island. If for some reason, there is a need to build new vocational secondary schools in a certain area, it must be based on demand-driven guided by labor market signals. The result of the study by Ohara et al. (2020) is different from the previous study by Newhouse and Suryadarma (2011). Thus, our study tries to contribute to examine this contrasting result.

Revitalization of vocational high school in Indonesia

Vocational education in Indonesia originated during the Dutch colonial era, when different types of specialized schools were established for the country’s lower- and middle-class Dutch nationals. Thirteen thousand two hundred thirty students were enrolled in 88 vocational schools in Indonesia at the end of Dutch rule (1942–1945) (Supriadi, 2002). After independence, the Indonesian government quickly expanded the number of vocational schools and higher vocational institutions, realizing the value of vocational education in preparing students for the workforce. However, the demand for vocational education was initially low, despite the Indonesian government’s efforts to expand the number of SMKs and tertiary vocational institutions. Between 1997 and 2007, the proportion of SMK students to all senior secondary students was only 20–27%. Demand for senior secondary education in general high school was higher than that of senior secondary vocational education in SMKs over the course of the decade (Kadir & Bachrul, 2016).

One of the causes of the low take up of vocational high school in Indonesia is the stigma toward vocational schools where SMKs are often perceived as ‘second class’ institutions. Firstly, vocational schools in Indonesia are perceived as mainly targeting poorer students who cannot afford higher general high school fees. SMA and SMK students’ characteristics differ in which SMA students tend to have better results in national examinations and a higher socio-economic status. The higher applicant to entrant ratio of SMAs indicates that there is a general preference for general high school compared to vocational high school (Kadir & Bachrul, 2016). Secondly, vocational education graduates are often perceived negatively by employers as they often see that graduates of vocational education lack the competencies required for industry. Many businesses still discover that the graduates of vocational education require retraining after being hired (OECD/ADB, 2020).

In responding to these issues, in 2016, the President of the Republic of Indonesia issued Presidential Instruction (Inpres) of the Republic of Indonesia Number 9 of 2016 concerning Revitalization of Vocational High Schools in the Context of Improving the Quality and Competitiveness of Indonesian Human Resources. This Presidential Instruction aims to revitalize vocational high schools (SMK) to improve the quality of vocational high school graduates. Prior to 2016, the program on vocational school has been focusing on increasing the quantity of schools and graduates. The flagship programs in the revitalization effort are the link and match program (refining and aligning the vocational high schools curriculum with competencies according to the needs of graduate users), increasing the capacity of vocational high schools to become First Party Professional Certification Institutions (LSP-P1) levels 2–3, increasing the competency of vocational high schools teachers through various training programs, short courses and industrial apprenticeships both at home and abroad, collaboration with industry, as well as dual expertize certification programs, increasing the entrepreneurial spirit of vocational high schools students through the Entrepreneurial Printing Vocational School program, and building new schools and facilities in throughout Indonesia. All of these programs have the goal of revitalizing all resources of vocational high schools, starting from educators, students, learning system units and education units.

Data and methodology

This study uses a quantitative approach using a cross-sectional dataset from the National Labor Force Survey (SAKERNAS) of August 2019. The SAKERNAS data is sampled from 197.91 million individuals of working age in Indonesia, of which 133.56 million individuals are in the labor force (BPS, 2022). The August 2019 SAKERNAS covers 782,789 individuals. For the analysis, we only include individuals with the highest education level of high school (secondary education level). From these individuals, we then identify the type of high school whether it is vocational high school (SMK) or general high school (SMA).

The SAKERNAS data includes employment information, individual characteristics such as type of highest education level and also demographic information such as age, gender, place of residence and marital status. In this case, the dependent variable is whether an individual is unemployed (coded as 1 or employed coded as 0). As the dependent variable is a binary variable, we employ two types of estimation, namely logistic regression (logit) and probability unit (probit) regression estimates. The linear probability model is not included in the study as the results of the regression estimation do not always lie between 0 and 1, so it may not be accurate in estimating the probability of an event occurring.

The empirical model for the estimation is: (1) $$d\mathrm{ }{\mathit{\text{Unemployment}}}_i={\beta }_0+{\beta }_1\mathrm{ }d\mathrm{ }{\mathit{\text{Voc}}}_i+{\beta }_2\mathrm{ }d\mathrm{ }{\mathit{\text{Age}}}_i+{\beta }_3\mathrm{ }{\mathit{\text{AgeSquared}}}_i+{\beta }_4\mathrm{ }{d\mathrm{ }\mathit{\text{Gender}}}_i+{\beta }_5\mathrm{ }d\mathrm{ }{\mathit{\text{ResidentialArea}}}_i+{\beta }_6\mathrm{ }d\mathrm{ }{\mathit{\text{MaritalStatus}}}_i+{\epsilon }_i$$(1) where:

$\mathit{d }\mathit{\text{Unemployment}}$ = unemployment status (1 = unemployed, 0 =employed)

$\beta 0$ = intercept

$\beta 1$-$\beta 6$ = regression coefficients

$\mathit{d }\mathit{\text{Voc}}$ = vocational high school education = 1, general high school = 0

$\mathit{\text{Age}}$ = age (years)

$\mathit{\text{AgeSquared}}$ = age squared (years)

$\mathit{d }\mathit{\text{Gender}}$ = gender (1 = male, 0 = female)

$\mathit{d }\mathit{\text{ResidentialArea}}$ = area of residence (1 = urban, 0 = rural)

$\mathit{d }\mathit{\text{MaritalStatus}}$ = marital status (1 = married, 0 = unmarried)

$\epsilon$ = error term

$i$ = individual units observed

Results and discussion

In this study, we examine the effect of Vocational education at high school level and relevant demographic factors on the probability of being unemployed. After keeping individuals with high school as their highest education level, there are 140,563 individuals in our dataset. The summary of the descriptive statistics is provided in Table 1.

Table 1. Descriptive statistics of main variables (n = 140,563).

Variable	Mean	Std. dev	Min	Max
Unemployed = 1	0.079	0.269	0	1
Vocational = 1	0.345	0.475	0	1
Age	34.834	11.729	17	64
Age squared	1350.952	868.977	289	4096
Male = 1	0.668	0.471	0	1
Urban = 1	0.551	0.497	0	1
Married = 1	0.676	0.468	0	1

The descriptive statistics show that almost 8% of individuals are unemployed. Following the definition of Indonesian Statistics, an individual is said to be unemployed if the individual is not working, a week ago the individual was actively looking for work/preparing for a business, has been accepted for work but has not started work, already has a business but has not started (BPS, 2022). Around 34.5% of individuals have vocational high school education as the highest education or 12 years of education in the Indonesian education system. The average age of the individuals in the dataset is almost 35 years old. Almost 67% of individuals are male, around a little over a half reside in the urban areas, and more than 67% are married.

The empirical model is estimated using the logit and probit estimation method. Table 2 displays the estimation results.

Table 2. Logit and probit regression results.

Independent variable	Dependent variable: probability of being unemployed
	Logit	Odds ratio	Probit
Voc = 1	−0.0472**	0.954	−0.0255**
	(0.0219)	(0.021)	(0.0115)
Age	−0.275***	0.759	−0.140***
	(0.00748)	(0.006)	(0.00361)
Age squared	0.00299***	1.003	0.00154***
	(0.000103)	(0.000)	(4.83e-05)
Male = 1	−0.0614***	0.940	−0.0464***
	(0.0222)	(0.021)	(0.0116)
Urban = 1	0.208***	1.231	0.126***
	(0.0217)	(0.027)	(0.0113)
Married = 1	−1.117***	0.327	−0.553***
	(0.0351)	(0.011)	(0.0165)
Constant	3.140	23.111	1.456
	(0.114)	(2.639)	(0.0566)
Observation	140,563	140,563	140,563

Note: The significance level * = 10%, ** = 5% and *** = 1%.

The regression results in Table 2 show that the vocational high school education variable has a statistically significant negative effect on the probability of an individual being unemployed. The odd ratio of the logit regression show that a vocational high school graduate is approximately 5% less likely to be unemployed contrasted to a general high school graduate, ceteris paribus. Older age, up to certain age, male and married individuals are less likely to be unemployed. Meanwhile, being in urban areas increase the probability of being unemployed in Indonesia. In the logit model, the count R squared is 0.921 meaning that the proportion of subjects who are classified correctly is 92.1%. This result indicates that the model is declared fit for interpretation. The results of probit estimation show the same signs and significant level as the estimation of the logit method.

This estimation results shows the same results as previous studies such as Newhouse and Suryadarma (2011), Hanushek et al. (2017), Torun and Tumen (2019), Ullah et al. (2021) and Oswald-Egg and Renold (2021), namely the level of vocational high school education has a negative effect on the probability of unemployment, which means that the vocational high school education can reduce an individual’s probability of being unemployed compared to individuals with general high school education.

It is necessary to note that the majority of adult individuals in Indonesia are general high school graduates. Data on the number of individuals over 15 years of age who have vocational high school education compared to general high school or equivalent can explain the potential number of the workforce with vocational education. In Figure 3, based on data from the BPS (2022), shows that the number of adult individuals with senior high school education is far greater than those with vocational high school education. This phenomenon occurred because the expansion of vocational high school only occurred starting in 2006 with an initial ratio between the number of general high school students to the vocational high school students of 70:30. Following the vocational school expansionary policy in 2006, the growth of individuals with vocational high school education continue to increase and becoming greater than the general high school, with a total increase from 2015–2019 reaching 5,206,837 individuals (BPS, 2022).

Figure 3. Number of population aged 15 and older with highest education of general (SMA) and vocational (SMK) high school, 2015–2019.

Figure 4 describes the open unemployment rate in Indonesia based on the highest education of vocational and general high school. As shown in Figure 4, the greater number of general high school graduates translates to the greater number of unemployed individuals with the general high school education. However, the number has continued to decline over the last 5 years. On the other hand, while the number of unemployed with the highest vocational high school education has been fluctuated, but recent data shows an increasing trend. The latter case has been due to the rapid increase of vocational high school graduates and at the same time not all SMK graduates can immediately get a job due to the limited number of jobs available.

Figure 4. Open unemployment based on highest education of general (SMA) and vocational (SMK) high school, 2015–2019.

Interestingly, breaking down the individuals by their ages shows that individuals with vocational high school education aged 17–19 years have a higher percentage of unemployment (Figure 5). This might be due to they have just graduated from vocational school. Individuals will experience difficulties in getting their first job because of competition in the labor market with job seekers who are better prepared in terms of work experience, skills and knowledge of the labor market (Wardhana et al., 2019). In addition, according to Vandenberg and Laranjo (2021) it is more difficult for individuals with the highest education of vocational high school education to get a job when they are under 30 years of age because of their selective attitude toward jobs according to their skills learned while at school. However, the proportion decrease over time until at the age of 30 years, the proportion stabilizes at a low number. According to Woessmann (2018), unemployment will decrease (and the probability that someone will be employed will increase) at the ‘prime’ age, which is around 30–45 years for individuals with the high school education. Kratz et al. (2019) also argued that individuals with the vocational high school education aged 30–35 years are more likely to get a job and being a vocational graduate is a deterrent against the risk of unemployment throughout their productive age. This phenomenon indicates that mature individuals are more likely to work than younger individuals indicated by a lower proportion of unemployed people. Apart from having more qualified work experience, skills and knowledge at the age of 30 and over, individuals aged 30 and over see more that work is a necessity related to contributing to economic fulfillment both personally and for the family (Pratomo, 2017).

Figure 5. Proportion of unemployment to total labor force with vocational education by age.

Further analysis on vocational high school graduates aged 40 years old and older, displayed in Figure 6, shows that there are fluctuations in the unemployment rate across different ages. This result is different from those aged 17–39 years who tend to stabilize toward a decrease in the probability of being unemployed. This confirms research that the advantages owned by individuals with vocational high school graduates may only last at younger age, whereas for the older individuals the benefits may decrease indicated by the differences in the unemployment rates (Hanushek et al., 2017). In this regard, Brunello and Rocco (2017) show for vocational graduates when they are above 40 years old, skills acquired through vocational education may become less relevant over time due to rapid technological advancements and changes in industry practices. They also may find that their vocational training lacks alignment with current job requirements, especially if their field has evolved significantly. In addition, older workers, especially those deeply rooted in a specific field, might face challenges in transitioning to new roles or industries. Furthermore, some vocational fields involve physical demands or hazardous conditions. As workers age, these demands might become more challenging (OECD/ADB, 2020).

Figure 6. Proportion of open unemployment to the vocational education graduate workforce by age (40–64 years).

Based on the regression estimation results, using a relatively recent dataset, we can see the significant effect of vocational education in lowering the probability of individual to become unemployed in general. However, when we take a closer look on the unemployment rates of recent graduates of vocational high school in Indonesia, we can see that there are issues in securing employment for these recent graduates. Newhouse and Suryadarma (2011) argue that plausible possibilities include a fall in the educational quality of the vocational school as the expense of rapid increase in quantity, and declining relevance of skills gained in vocational school which mostly more manufacture-oriented with increasingly service-oriented Indonesian economy. In addition, Pritadrajati (2022) assert that current economic conditions are increasingly valuing employers with general cognitive expertize. In this case, Di Gropello et al (2011) show that Indonesia’s vocational education system did not accommodate the needs of industry and employers, and contained weaknesses in supply-side components such as teacher qualifications and industry-relevant training programs. It is not surprising that Choi et al. (2023) find that upper secondary vocational education does lead to more decent work than just primary or lower secondary education, but upper secondary general education is superior, except in terms of workplace pensions and training. This implies that the Indonesian government needs to focus more on the content and quality of vocational education as well as simply expanding it.

Conclusion

Vocational high schools play an important role in reducing the probability of an individual to become unemployed. Vocational high schools can help individuals who need shortcuts to become decent workers with good work skills without having to continue their education to a higher level. They provide students with practical skills and knowledge that are directly applicable to the workforce. This makes them more attractive to employers and increases their chances of finding employment after graduation. Vocational high schools also offer students the opportunity to gain work experience through internships and apprenticeships, which can further enhance their employability. In general, this case is confirmed in our estimation result. The result of the logit model shows that, overall, vocational high school education has a negative and statistically significant effect on the probability of being unemployed. However, further analysis on the unemployment rates of vocational high school graduates by age show that the case might not be applicable to the recent graduates of vocational high school.

One of the policy implications of the results of this study is that the government can continue the SMK revitalization program by focusing on collaboration with companies and industries to reduce the probability of unemployment at recent graduates of vocational high school. However, the industry collaboration needs to be in line with the link and match programs so that the competencies of vocational high school graduates will meet industry needs. In addition, the government also needs to pay attention on the equality of the infrastructure and facilities in vocational high schools, especially in districts/cities that are still lagging behind. The existence of adequate facilities and infrastructure will support the implementation of the link and match program and make vocational high school students better in their skill learning through practice at school.

Future research can add the level of vocational education at the tertiary level such as diploma and academy and its comparison with general undergraduate programs. It is necessary to note that vocational diploma and applied undergraduate programs in Indonesia are increasing both in terms of the number of offering institutions and number of students and graduates. The study will complement the studies which focus on the secondary vocational education.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Yoana

Yoana holds a Bachelor in Economics from the Department of Economics, Faculty of Economics and Business, Universitas Airlangga, Indonesia. Her research interest is development economics, particularly labour market issues in developing countries.

Ilmiawan Auwalin

Ilmiawan Auwalin is a lecturer and researcher at the Faculty of Economics and Business, Universitas Airlangga, Indonesia. He holds a Ph. D in Economics from the School of Economics, the University of Sydney, Australia. His research interests include economic development, labour market studies, and micro and small enterprises development and finance.

Rumayya

Rumayya is a full-time lecturer at Faculty of Economic and Business, Universitas Airlangga, Indonesia. He holds a Ph.D. in Economics from the University of Western Australia. His research interests include Development Economics and Political Economics.