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Massification of higher education and youthtransition: skills mismatch, informal sector jobs andimplications for China

Ka Ho Mok & Jiwei Qian

To cite this article: Ka Ho Mok & Jiwei Qian (2018) Massification of higher education and youthtransition: skills�mismatch,�informal�sector�jobs�and�implications�for�China, Journal of Education andWork, 31:4, 339-352, DOI: 10.1080/13639080.2018.1479838

To link to this article: https://doi.org/10.1080/13639080.2018.1479838

Published online: 10 Jun 2018.

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ARTICLE

Massification of higher education and youth transition: skillsmismatch, informal sector jobs and implications for ChinaKa Ho Moka and Jiwei Qianb

aWong Administration Building, Lingnan University, Tuen Mun, Hong Kong; bEast Asian Institute, NationalUniversity of Singapore, Singapore

ABSTRACTThis study adopts a nationwide survey data set between 2005 and 2013(Chinese General Social Survey) to explore the influence of the massifica-tion of higher education on the transition of Chinese youth into thelabour market. Data analysis reveals two major findings. First, the eco-nomic returns to college education of recent cohorts of university grad-uates (those who have graduated from universities not more than3 years ago) are lower than the cohorts who graduated in 2005 and2006. Second, recent cohorts of college graduates are likely to work inthe urban informal sector, unlike their senior counterparts. These find-ings could partially be explained by skills mismatch in the labour marketbut a comprehensive understanding of graduate unemployment inChina could be obtained by bringing the broader political economyperspective into the analysis.

ARTICLE HISTORYReceived 5 April 2017Accepted 19 May 2018

KEYWORDSYouth transition; graduateemployment; massificationof higher education (HE);social mobility; skillsmismatch; labour market

Introduction

The Chinese economy has grown rapidly since the late 1990s with an annual GDP growth rate ofapproximately 10% between 1998 and 2010.1 Moreover, wage growth rate in China has been highduring the same period. The annual real wage growth rate in the urban formal sector between1998 and 2010 was 13.8%, which is higher than the GDP growth rate (Li et al. 2012a). Therefore,real wage has increased faster for people with higher education (HE) qualifications than for peoplewithout such qualifications. However, the upward wage increase has slowed due to the massifica-tion of HE. This phenomenon comprises a current annual production of over 7 million universitygraduates (Ding, Yu, and Yu 2017). The steady growth of university graduates along with theconcern for a mismatch between skills offered by university graduates and the labour marketrequirements for skills has become a silent feature of the unemployment and underemployment ofChinese graduates (Mok and Wu 2016). These issues have led to the growing research interest onthe employment destination and satisfaction of graduates (Mok and Jiang 2017; Mok et al., forth-coming; Yue 2017).

A close scrutiny of the employment trends of university graduates in China has indicated twomajor structural changes in the Chinese labour market in recent years. First, the massification of HEhas, arguably, created a skills mismatch in the labour market. Massification has led to an oversupplyof college graduates with general academic degrees but resulted in the shortage of graduates withvocational and technical skills and qualifications relevant to the requirements of the labour market.Second, the importance of the informal sector in the urban labour market has increased in recentyears. Employment outside urban formal sector enterprises reached over 200 million in 2013 or

CONTACT Ka Ho Mok kahomok@Ln.edu.hk Wong Administration Building, Lingnan University, Tuen Mun, Hong Kong

JOURNAL OF EDUCATION AND WORK2018, VOL. 31, NO. 4, 339–352https://doi.org/10.1080/13639080.2018.1479838

© 2018 Informa UK Limited, trading as Taylor & Francis Group

approximately 52.6% of the total urban labour force compared with approximately 55 million or27% in 1997 (National Bureau of Statistics [NBS] various years).

The present study explores the influences of the changing labour conditions in Mainland China onthe transition of Chinese youth from universities to the workplace by using a nationwide survey dataset, namely, the Chinese General Social Survey (CGSS), between 2005 and 2013. This study alsodiscusses major findings on the basis of an analysis of employment patterns and choices of universitygraduates in China. The final part of the study examines the Chinese experience of competition in skillsand changes in labour market perspectives, particularly reflecting upon how a wider political economyperspective can offer complementary explanations for the skills mismatch in the labour market.

Massifying HE in China

To enhance its global competitiveness, the Chinese government expanded and strengthenedpublic universities, engaged non-state actors to establish minban (people-run) colleges and invitedoverseas HE institutions to collaborate with local institutions and thus establish various forms oftransnational HE programmes or campuses (Mok and Han 2017). Such efforts led to a steadyincrease in university graduates in China from about 950 thousand in 2000 to about 6.39 million in2013 (NBS, various years). In addition, the Chinese government either provided scholarships tosend students abroad or allowed Chinese families to send their children to study abroad. Thenumber of Chinese students studying overseas increased from 860 in 1978 to over 523,000 in 2015(National Bureau of Statistics (NBS) 2016). This dramatic increase is also observed in transnationalHE through Sino-foreign cooperation during this period from 2 in 1995 (Huang 2010) to 1176 in2016 (Ministry of Education (MOE) 2016). However, graduate unemployment has become serious;an increase from 7.5% in 2008 to 25.5% in 2013 is observed (Chinese Academy of Social Sciences2015). The number of unemployed with college degrees in China has increased from 58 thousandin the 2000 census (or 5.0% of total unemployed) to over 370 thousand in the 2010 census (or17.7% of total unemployed) (Walder, Li, and Treiman 2000; National Bureau of Statistics (NBS)2010). This figure suggests that university graduates have encountered difficulties in finding jobsthat match their skills and knowledge sets and career expectations. The rapid expansion of HE hasintensified educational inequality (Liu, Green, and Pensiero 2016; Mok, Wen, and Dale 2016).

Massification of HE and youth transition

Conventionally, economic returns to college education are estimated as the proportional increase inthe labour market earnings of university graduates compared with those without university degrees,especially when we adopt orthodox human capital development and skill-biased technologicalchange perspectives as explanations (Goldin and Katz 2007). Previous studies report that economicreturns to college education in China have increased (Cai, Park, and Zhao 2008; Li et al. 2012b).However, a 2010 census indicates that 22.9% of urban unemployed have at least 3 years of collegeeducation,2 while the proportion of employed migrant workers with college education was only 5.7%in 2009 (Meng 2012). Similar findings are reported by Ding et al. in Ding, Yu and Yu (2017). Theseresults imply the difficulties encountered by young university graduates in the labour market. Recentstudies related to job search and career development of overseas Chinese student returnees clearlyshow that the returnees outperform graduates of local universities in terms of salary packages andpromotion opportunities, suggesting that there is a problem with the labour market skills of those thathave studied in China (Mok 2017; Mok, Leng, and Han, forthcoming).

Increasing returns to schooling and the mismatch of skills and qualifications

A mismatch between qualifications and skills offered and needed in the labour market is observedin China (Meng 2012; Li, Whalley, and Xing 2014). College graduates with educational qualifications

340 K. H. MOK AND J. QIAN

but without technical qualifications may not find jobs despite limited technically skilled labour.Consequently, there appears to be a mismatch in the subjects studied at HE. This structuralproblem stems from the call for HE expansion in the late 1990s in terms of quantitative growthwithout the careful mapping of diverse and changing labour market requirements (Mok and Jiang2017; Tam and Jiang 2015). The increasing number of Chinese students returning to MainlandChina after studying overseas intensifies the competition for job opportunities (Mok et al.,forthcoming).

Furthermore, skills mismatch is important in the context of technological changes and economicgrowth. In recent decades, labour productivity has increased dramatically in China with improve-ments in human capital (Li et al. 2017a). The supply–demand gap for high-skilled labour isbecoming extensive with (skill-biased) technological changes in China, and thus, income for anelite of highly skilled workers is rising (Li et al. 2017a). A report by JP Morgan published in 2016presents that highly skilled workers represented only 5% of the entire labour force in China and arein a serious supply shortage.3 Added to this problem is that identified by Loyalka et al. (2016) whofound that students in China have zero or negative improvement on average in terms of cognitiveskills after 2 years of college. By contrast, college students in Russia and the United States havesignificant cognitive skill improvements over the first 2 years of college (Loyalka et al. 2016).

Changing labour demand and structural transformation in China

However, we should treat such an inference with caution because universities are challenged bythe transformation of China’s economic growth model. The success of the Chinese economicreforms since the late 1970s has indeed transformed the country as the second largest economyin the world, particularly when China is well known for being the ‘World’s Factory’, offeringrelatively cheap labour to other global capitalists for production. It is against such a context thatthe demand for unskilled labour had increased rapidly in the 1990s and 2000s (Meng, Shen, andXue 2013).

Realising that depending upon the cheaper labour formula for serving as the productionhouse for the developed economies would no longer be sustainable for the Chinese economy,the Chinese government has begun to direct its economic development towards high-technol-ogy, actively investing in research and development, promoting technological advance andinnovation-centric entrepreneurship (Mok and Kan 2013). Under this new economic growthmodel, demand for skilled labour was expected to increase dramatically (Meng, Shen, andXue 2013). The increase in the demand for high skilled labour depends on the success ofeconomic restructuring from an exported-oriented and labour-intensive economy to a highvalue added and capital-intensive economy. Consequently, the graduate employment situationthat China confronts now may partially be explained by the progress of the transformation ofChina’s economic growth model.

Labour market structures: the informal sector in urban China

In the literature, the formal sector in urban China is characterised by registered enterprises,including state-owned enterprises, collectively owned enterprises, limited liability companies,shareholding corporations, foreign-owned companies and joint ventures (Ghose 2005; Qian andMok 2016; Jiang, Qian, and Wen 2017). The informal sector labour force in urban China can becategorised into two non-exclusive groups. The first group is defined by the ownership ofenterprises. Self-employed individuals and small business owners/workers are therefore consideredpart of the informal sector (Ghose 2005; Kumar and Li 2007; Park and Cai 2011). The second groupis defined by the type of labour contract. Individuals without a written employment contract areidentified as informally employed (Zuo 2013). In addition, informal sector labour force for bothgroups can be employees or (self)employers.

JOURNAL OF EDUCATION AND WORK 341

The segmentation of the labour market in China into formal and informal sectors has beendiscussed in the literature (Meng 2001; Park and Cai 2011). The total urban labour force andnumber of labourers that work in formal sector enterprises in China in 2013 were approximately380 million and 180 million, respectively. By contrast, the informal sector labour force currentlycomprises over 50% of the total labour force (approximately 200 million in 2013) (National Bureauof Statistics (NBS) 2014).

The number of workers in the informal sector increased dramatically after the reform of state-owned enterprises in the late 1990s and after further marketisation in urban China (Brooks and Tao2003). Employees who worked in privately owned businesses increased from approximately 30million in 2004 to over 82 million in 2013. The number of self-employed persons also rose fromapproximately 25 million in 2004 to over 61 million in 2013 (NBS various years). In particular, theliterature suggests that migrant workers will likely find jobs in the informal sector because formalsector employment typically requires a local household registration status (hukou). However,workers in this sector can expect lower wages than in the formal sector.

Workers in the informal sector are also disadvantaged in terms of coverage of social insurance(Jiang, Qian, and Wen 2017). Unlike members of the formal sector labour force, members of theinformal sector labour force are unlikely to enrol in social insurance (Jiang, Qian, and Wen 2017).The institutional discrimination of hukou and the occupation-based welfare regime still persist(Ringen and Ngok 2013).

The urban labour market has experienced structural changes in recent years given the discus-sion in previous sections. First, the economic returns of young college graduates have decreasedfor all except the few who are highly technically skilled. But there are numerous job opportunitiesavailable in the urban informal sector, although the income level and social protection coverageare low. In such a context, youth with university degrees will likely find jobs in the urban informalsector. Thus, the income level and social protection coverage of these individuals will likely belower than their counterparts who graduated prior to the massification of HE.

Research design of the study

Hypotheses

Based on the above discussions, the massification of HE via the structure of the labour market cansignificantly affect university graduates in two aspects. First, the economic returns to collegeeducation may be lower for the recent cohorts of university graduates than older graduateswhen the older cohorts graduated at the beginning period of the massification of HE. Second,young graduates will likely find jobs in the informal sector, where wage level is typically low andsocial protection level is shallow, after the massification of HE. Two hypotheses can be proposedaccordingly.

Hypothesis 1: The economic returns to college education are lower for recent cohorts ofuniversity graduates than those of older graduates, when older cohorts graduated at the beginningperiod of the massification of HE.

Hypothesis 2: recent cohorts of university graduates will likely work in the informal sector thanworkers who graduated at the beginning of the massification of HE.

Data

This study uses the CGSS managed by the People’s University of China. The time span of interest inthe data set is between 2005 and 2013. Multistage cluster sampling was used, and approximately100–125 counties were drawn from over 2800 counties in China (Bian and Li 2012). We use four

342 K. H. MOK AND J. QIAN

waves of data from the CGSS (i.e. 2005, 2006, 2012 and 2013). We only include urban residentsaged between 18 and 65 years from the data set. Urban labour market outcome (e.g. wage) ofcohorts who graduated in 2005 and 2006 was compared with that of 2012 and 2013 cohorts. Thegraduates of 2005 and 2006 cohorts are among the first batch of university graduates who enterthe labour market after the massification of HE. The 2012 and 2013 cohorts graduated 10 yearsafter HE was first massified and are the latest waves with figures available from the CGSS. The effectof the massification of HE on the labour market can be evaluated by comparing waves 2005–2006with waves 2012–2013. The CGSS sampled 125 counties out of the 2800 county-level units nation-wide in 2005 and 2006. For waves 2012–2013, the CGSS sampled from 100 counties and 5 majorcities.

Several advantages of using this data set were identified for the research questions raised in thisstudy. First, data were obtained nationwide, and nearly all provinces were covered in the data set.Second, the time span from the data set used in the study is 9 years, which is sufficient for coveringthe earliest cohorts of graduates after the massification of HE in China. Third, useful informationabout the informal sector is collected in this survey, including the status of employment of workersand the forms of their labour contract. Two threshold values are used to define ‘youth’ in the dataset. We define ‘youth’ as university graduates with less than 3 years of work experience (i.e.younger than 26 years old) or masters graduates with less than 3 years of work experience (i.e.younger than 29 years old).

We include two groups of informal sector workers, that is by ownership and by an employmentcontract, following the definition of the informal sector. In this study, we define ‘informal sector’through answers to questions about employment and labour contract status in the CGSS ques-tionnaire in various waves. Informal sector workers in our data set consist of people who areinformally employed, including workers who are flexibly employed or working part-time, do nothave a fixed employer or are unemployed and do not have a formal labour contract. We alsoinclude workers who are self-employed and own or work in small-businesses (geti jinyin) on thebasis of the ownership of their firms.

Descriptive statistics

Table 1 indicates that the age structure in our data set is relatively stable throughout the fourwaves of our data set. The percentage of youth under 26 years old in the total population in 2005was 11%, and the figure in 2013 was 10%. The descriptive statistics are presented in the Appendix.The percentage of youth under 29 years old in the total labour force in 2005 was 19%, and thefigure in 2013 was 17%. However, the percentages of informal sector workers in the total labourforce are substantially larger in 2012 and 2013 than in 2005 and 2006. Only approximately 36% ofthe labour force worked in the informal sector in the 2005/2006 combined sample, whereas over42% of the labour force worked in the informal sector in the 2012/2013 combined sample.

Table 1. Number and composition of labour force in the formal and informal sector.

Year Formal sector Informal sector Youth (<26) Youth (<29) Total

No. of observations2005 2094 1842 435 753 39362006 3259 1204 596 956 44632012 2798 2074 504 840 48722013 2780 2072 487 823 4852

Composition of the labour force2005 53.2% 46.8% 11.1% 19.1% 100%2006 73.0% 27.0% 13.4% 21.4% 100%2012 57.4% 42.6% 10.3% 17.2% 100%2013 57.3% 42.7% 10.0% 17.0% 100%

JOURNAL OF EDUCATION AND WORK 343

Table 2 displays the composition of the labour force in the data set who received tertiaryeducation. The number of people in the labour force with university degrees has increaseddramatically after 10 years of the massification of HE. Only 838 out of 3936 (21.2%) have obtaineda university degree in 2005, whereas 1413 out of 4852 (29.1%) have obtained a university degree in2013. Therefore, the percentage of youth with HE in the labour force is low considering thesubstantial number of people with university degrees. The percentage of youth under the age of26 with HE has decreased from 19.2% in 2005 to 15.6% in 2013. By contrast, absolution numbers ofyouth with HE increased in 2012 and 2013. The absolution number for youth under the age of 26was 220 in 2013 but was only 161 in 2005.

Table 3 summarises the trend of income changes in the labour market throughout the fourwaves of the data set. The income for all groups divided by age and formal or informal sectordramatically has increased between 2005 and 2013. In all waves, the average income was lower inthe informal sector than in the formal sector, except in 2006. However, the relative wage for theyouth decreased. In 2005 and 2006, the average wage of the youth was higher than the wage ofaverage workers. However, the average wage for the youth in 2012 and 2013 was significantlylower than the wage of average workers.

Table 4 shows the income level for workers with and without college degrees. In general,workers with college degrees earn more than workers without college degrees. The ratio ofincome between the two groups is over 2.02 in 2005 and 1.82 in 2013. However, the ratio ofincome between workers with HE and youth under 26 years old with HE also increased from0.92 in 2005 to 1.69 in 2013. This trend indicates that income for young college graduates hasbeen relatively decreased in recent cohorts compared with those in early cohorts.

Table 2. Number and composition of labour force with higher education in the formal and informal sector.

Year Formal sector Informal sector Youth (<26) Youth (<29) Total

Number of observations2005 694 144 161 282 8382006 742 126 208 325 8682012 989 425 216 389 14142013 995 418 220 377 1413

Composition of the labour force2005 82.8% 17.2% 19.2% 33.7% 100%2006 85.5% 14.5% 24.0% 37.4% 100%2012 69.9% 30.1% 15.3% 27.5% 100%2013 70.4% 29.6% 15.6% 26.7% 100%

Table 3. Average income of labour force in the formal and informal sector (RMB).

Year Formal sector Informal sector Youth (<26) Youth (<29) Overall

2005 17,380 10,611 17,547 17,302 14,3642006 17,735 18,102 19,830 20,371 17,8372012 36,017 33,764 27,164 32,346 34,9802013 41,914 38,061 32,200 37,432 40,065

Table 4. Average income of labour force by education (RMB).

YearWith highereducation

Without highereducation

Youth with higher education(<26)

Youth with higher education(<29)

2005 23,676 11,716 25,646 24,9672006 25,581 15,758 21,361 24,0182012 55,891 25,579 30,979 38,0342013 58,064 31,779 34,336 42,554

Note: The descriptive statistics are shown in Appendix.

344 K. H. MOK AND J. QIAN

Data analysis strategy

Linear and logistic regression models are used to analyse the data. Two major dependent variables,namely logged income and dummy variable, are identified to determine whether an individualworks in the informal or formal sector (zero or one, respectively). The major independent variable isthe dummy variable, which indicates whether a worker is a youth from recent cohorts withuniversity degrees or not (zero or one, respectively).

Several control variables are used in the regressions, including informal, gender, rural hukou,age, age square, party membership and education level. The variable ‘informal’ is equal to one if aworker is working in the informal sector, otherwise zero. As discussed earlier, hukou status is animportant determinant of the labour market. The literature in China contends that education leveland party membership are key variables of social mobility (Walder, Li, and Treiman 2000). Thus,education level and party membership are controlled in the regression model. Whether or notparents are cadre members is also included as a control variable, because the literature states thata network of cadre parents is important in labour market outcomes (Bian 1994).

We also control the dummy variable ‘youth’ which denotes whether a worker is a member of theyouth or not. The variables ‘age’ and ‘age square’ are also controlled as a measurement of workexperience. Consumer price index, which is collected from the China Statistical Yearbook, is alsocontrolled to capture the effect of price changes between 2005 and 2013. Year fixed effect istherefore controlled.

Results

Table 5 summarises the regression results on the effect of HE on income and entry to the informalsector of the youth. The reference group in all models is the group of workers with HE. Thedependent variable in Models (1)–(3) is logged income. Thus, the coefficients of regressors indicatethe percentage changes of the dependent variable with one unit change of a regressor.

Model (1) in Table 5 illustrates that the wage gap between the young graduates and workerswith HE in 2012 and 2013 increased significantly compared to the case of the 2005 and 2006cohorts. In concrete, the income is about 19% lower on average in the young graduates than inworkers who had university degrees (i.e. the coefficient youth with HE). However, the income is60% lower on average in the youth of 2012 and 2013 cohorts with HE than in workers who haduniversity degrees (i.e. the coefficient youth with HE [after 2012]). In other words, the economicreturns of college degree for the recent cohorts in 2012 and 2013 are lower than those of theearlier cohorts when they graduated at the early phase of massification of HE. These results are alsoconsistent with Li et al. (2017b), who use a different data set covering a similar time period (i.e.China Urban Household Survey).4 Hypothesis 1 is supported in this case.

However, economic returns to college education remain high. The income for the labour ofpersons without university degrees is 65% lower than those with university degrees when otherdeterminants (i.e. the coefficient of the variable ‘W/O HE’ in Model (1)) are controlled.

This difference can also be inferred from descriptive statistics reported in Table 4 in whichworkers with university degrees earn much higher than those without HE. This university premiumcan be due to the effect from earlier cohorts of university graduates, who can earn much morethan recent cohorts of university graduates. These results are also consistent with findings in theliterature which suggests that the college premium for experienced workers with college degreesincreases with the current college expansion in China (Li et al. 2017b). For earlier cohorts, thereturns are closely related to the condition when HE expansion was still at the initial stage, unlikewhen the sector is significantly massified.

Also, the informal sector workers in general have a lower income compared to the formal sectorworkers (i.e. the coefficient ‘informal’ is negative). Results of Model (1) in Table 5 are also consistentwith findings in previous studies which suggest that party membership and cadre networks of

JOURNAL OF EDUCATION AND WORK 345

parents positively and significantly influence labour income. Workers with a rural hukou will alsolikely earn more than other workers.

Models (2) and (3) show the regression results of subsamples in the formal and informal sectors,respectively. The pattern of the results in Model (2) and the youth with HE in Model (1) are similar.In the urban formal sector, the wage gap between the young graduates and workers with HE in2012 and 2013 increased significantly compared with that of 2005 and 2006 cohorts. Model (3)displays that the wage gap between the young graduates and the workers with HE is statisti-cally insignificant on average in the informal sector (i.e. the coefficient ‘youth with HE’). In Model(3), recent cohorts of the youth with HE in the urban informal sector also earned significantly lessthan workers with HE on average, as well as the older cohorts when they graduated in 2005 or2006. Hypothesis 1 is supported by the outcomes both in the formal and informal sectors.

Model (4) of Table 5 indicates the logistic regression results of the challenges that individualsexperience in the informal sector. Recent cohorts of the youth with HE exhibit a higher possibility forworking in the informal sector than workers with HE on average. Thus, Hypothesis 2 is supported.

Workers with HE will be much less likely to work in the informal sector than workers withoutHE (i.e. the coefficient for the variable ‘W/O HE’ is positive). This result is statistically significant.The probability that young graduates working in the informal sector is not statistically differentfrom that of workers with HE on average (i.e. the coefficient ‘youth with HE’). However, recentcohort of young graduates in 2012/2013 has a larger probability of working in the informalsector, compared to workers with HE on average (i.e. indicated by the coefficient ‘youth withHE [after 2012]’). Also, party membership negatively and significantly affects the possibility for a

Table 5. Regression result for the young graduate in the labour market (age < 26).

(1) (2) (3) (4)

Log(Income)Log(Income) (formal

sector)Log(Income) (informal

sector)Entry of the informal

sector

Youth with higher education(after 2012)

−0.595***(0.0686)

−0.423***(0.0784)

−0.803***(0.141)

0.488**(0.180)

Youth with higher education −0.186**(0.0595)

−0.269***(0.0684)

−0.0889(0.127)

−0.249(0.163)

W/O higher education −0.652***(0.0192)

−0.655***(0.0225)

−0.630***(0.0359)

0.876***(0.0478)

Gender −0.379***(0.0139)

−0.358***(0.0177)

−0.371***(0.0220)

−0.260***(0.0321)

Rural Hukou −0.133***(0.0176)

−0.277***(0.0244)

−0.0179(0.0254)

0.311***(0.0384)

Youth 0.145***(0.0407)

0.235***(0.0528)

0.00231(0.0629)

−0.00458(0.0925)

Age 0.0595***(0.00615)

0.0757***(0.00780)

0.0234*(0.00978)

0.0690***(0.0141)

Age square −0.000896***(0.0000709)

−0.00107***(0.0000899)

−0.000480***(0.000113)

−0.000934***(0.000161)

Party membership 0.118***(0.0221)

0.0994***(0.0255)

0.106*(0.0423)

−0.393***(0.0573)

Parents (cadre) 0.0915***(0.0156)

0.0804***(0.0196)

0.0665**(0.0252)

−0.215***(0.0367)

CPI 14.67***(1.372)

5.840***(1.687)

24.91***(2.360)

−66.60***(3.262)

Informal −0.0567***(0.0145)

Year dummy Yes Yes Yes YesN 15,062 8752 6310 18,123Adj./Pseudo R2 0.345 0.338 0.374 0.0592

Standard errors in parentheses, reference group is labour force with higher education.*p < 0.05; **p < 0.01; ***p < 0.001.CPI: Consumer price index.

346 K. H. MOK AND J. QIAN

worker to find a job in the informal sector. This is consistent with the literature that partymembership as a measurement of achieved status is relevant for social mobility in China (Linand Bian 1991).

Table 6 displays the regression results when the threshold value for the youth is set to 29 years.Patterns of the regression results presented in Table 6 are similar to those in Table 5. Models (1)–(3)indicate that the wage gap between the young graduates and workers with HE in 2012 and 2013increased significantly compared to the case of the 2005 and 2006 cohorts (i.e. indicated by thecoefficient ‘youth with HE [after 2012]’). The economic returns of college degree for the recentcohorts in 2012 and 2013 are lower than those of the earlier cohorts when they graduated at theearly phase of massification of HE. Hypothesis 1 is supported. Model (4) denotes that recent cohortsof the youth with HE (i.e. 2012 and 2013) have on average a large and significant possibility ofworking in the informal sector, compared to workers with HE (including workers graduated in 2005and 2006). Thus, Hypothesis 2 is supported.

Discussion

Major findings and significance of the study

The present study explored the influence of the massification of HE on the transition of the youthfrom universities to the workforce in China by using a nationwide survey data set between 2005and 2013. Data analysis yields two major findings. First, economic returns to college education willlikely be lower for university graduates who finished school not more than 3 years ago than incohorts who graduated in 2005 and 2006 when the massification of HE began. Second, recent

Table 6. Regression result for the young graduate in the labour market (age < 29).

(1) (2) (3) (4)

Log(Income)Log(Income) (formal

sector)Log(Income) (informal

sector)Entry of the informal

sector

Youth with higher education(after 2012)

−0.404***(0.0522)

−0.230***(0.0588)

−0.672***(0.113)

0.517***(0.143)

Youth with higher education −0.196***(0.0475)

−0.301***(0.0547)

0.0197(0.105)

−0.408**(0.134)

W/O higher education −0.683***(0.0203)

−0.689***(0.0237)

−0.645***(0.0381)

0.842***(0.0506)

Gender −0.379***(0.0139)

−0.360***(0.0177)

−0.370***(0.0221)

−0.260***(0.0322)

Rural Hukou −0.136***(0.0176)

−0.281***(0.0244)

−0.0209(0.0254)

0.313***(0.0384)

Youth 0.237***(0.0382)

0.278***(0.0501)

0.173**(0.0582)

0.00500(0.0871)

Age 0.0764***(0.00689)

0.0855***(0.00883)

0.0515***(0.0108)

0.0649***(0.0155)

Age square −0.00107***(0.0000772)

−0.00117***(0.0000988)

−0.000779***(0.000121)

−0.000887***(0.000173)

Party membership 0.114***(0.0222)

0.0936***(0.0255)

0.108*(0.0425)

−0.401***(0.0574)

Parents (cadre) 0.0877***(0.0156)

0.0782***(0.0196)

0.0627*(0.0253)

−0.212***(0.0368)

CPI 14.51***(1.372)

5.660***(1.688)

24.74***(2.365)

−66.83***(3.268)

Informal −0.0590***(0.0145)

Year dummy Yes Yes Yes YesN 15,062 8752 6310 18,123Adj./Pseudo R2 0.344 0.338 0.372 0.0590

Note: Standard errors in parentheses, reference group is labour force with higher education.*p < 0.05; **p < 0.01; ***p < 0.001.CPI: Consumer price index.

JOURNAL OF EDUCATION AND WORK 347

cohorts of college graduates will likely work in the urban informal sector unlike their oldcounterparts.

Diverse graduate backgrounds and intensified competition for employment

The above analysis of the Chinese experiences suggests that the changing labour market condi-tions, such as the skills mismatch and increase in the size of the informal sector, have significantinfluences on the transition of the youth from universities to the workforce. Access to HE varies forpeople from different social and geographical origins (Liu 2015); moreover, concerns over spatialinequality have intensified, especially when Chinese citizens across various parts of the country aregiven diverse but unequal treagent in university admissions (Mok and Jiang 2017). The wagepremium is substantially higher in graduates from elite universities than in graduates from non-elite universities (Hartog, Sun, and Ding 2010; Li et al. 2012b). Companies in the formal sector willlikely recruit graduates from higher tier universities, whereas graduates from lower tier universitieswill likely be employed in the informal sector given the inequality in HE.

We also observed that funding support is concentrated on elite universities that are beingprepared to compete for global ranking (Jiang 2017). The competition for talent in Chinademonstrates the serious attempts by the Chinese government to mobilise, attract and retainhuman talent. However, the measures adopted by the Chinese government in rewarding whatis seen as global talent further intensify inequality across disciplines and universities, therebyresulting in stratification of universities positional conflict and social inequality among gradu-ates from different tiered universities; this finding is suggested by Brown, Lauder and Ashton(2011) and Kupfer (2011). In particular, rewarding overseas Chinese student returnees orattracting overseas talent to accept high positions with enhanced salary packages in the formalsector is common in Mainland China; such actions have intensified the competition betweenlocals and non-locals, thus driving additional local graduates to venture in the informal sectorfor career development (Mok, Leng, and Han, forthcoming). Chinese returnees have also foundthe labour market increasingly competitive because a steady stream of international studentshas returned and a growing number of students have obtained overseas university qualifica-tions and working experiences. However, a study conducted in 2015 by New Oriental, which isa corporation promoting international education in China, estimated that the expected returnon investment after studying abroad is 49% for those who spend at least 5 years abroad and18% for those who spend 3 years abroad (New Oriental 2017). Similarly, another study reportedwage gaps across disciplines when returnees with overseas academic qualifications were paid3–4 times higher than local graduates, and academics in the fields of engineering and scienceswere offered better compensation packages than those in the fields of humanities and socialsciences. Thus, growing tensions are unsurprisingly observed between locally groomed aca-demics and returnees or overseas-recruited academics (Mok 2017).

The broader political economy perspective for graduate employment

Our findings in the present studies have clearly suggested that China is currently caught in thedilemma of ‘rush-to’ expansion of HE without a careful mapping with its economic structure ingeneral and labour market needs in particular. Despite the calls for innovation and technologyadvancement, investing more in innovation-centric entrepreneurship, and reforming its HE curri-cula with more emphasis on innovation, creativity and entrepreneurship education, universitygraduates in China are confronted with skills mismatch with what the labour market needs becausethe existing economic structure simply fails to offer sufficient jobs to the ‘over-supply’ of theseeducated/skilled labour (Mok and Jiang 2017).

Putting the above findings into perspective, we would argue that the growing concerns ofgraduate employment or underemployment in China may be related to the human capital

348 K. H. MOK AND J. QIAN

development and skill-biased technological changes. As discussed previously, a closer scrutinyof the growing number of graduates venturing into the informal sector in urban China forjobs and career developments could be also related to economic transformation in China.China is now in a transitional period from an export-oriented and labour-intensive economy toa high value added and capital-intensive economy. In this context, it may take some time forthe increases of the demand for the skilled labour to catch up the supply of the collegegraduates.

More significant of all, China is also challenged by the wider political economy context in thattechnology may not be skill biased but skill replacing. What worries us most, as Lauder, Brown andCheung (forthcoming) rightly suggest, is that

Digital Taylorism is not simply creating a polarisation been high and low skilled workers, but the segmentationof knowledge work and of middle class occupations, where the benefits of productive growth are concen-trated in the hands of executives and senior personnel, especially when combined with a shareholderapproach to corporate governance. (Lauder, Brown, and Cheung, forthcoming, 24)

When China opens to more global competition, local university graduates will find the pressure forcompetition being intensified not only within the Chinese labour market but also regionally andglobally. If this argument stands, it accounts for the repeated calls from the Beijing government forencouraging the youth to look for opportunities outside the country like venturing in the ‘Belt andRoad Initiatives’. We should therefore carefully revisit the conventional wisdom drawn from theorthodox human capital development and skill-biased technological changes by taking intoaccount of a broader political economy perspective when analysing the relationship betweeneducation and work.

Conclusion

The present study has clearly shown the effects of the massification of HE on employment ofgraduates in China. The data and analysis presented in this paper clearly show decreasingeconomic returns to college education. The rapid expansion of HE without the careful mappingof graduate employment and changing labour market requirements has resulted in growingconcerns in skills mismatch and the underemployment and unemployment of graduates (Ding,Yu, and Yu 2017). The massification of HE and its influence on graduate employment as discussedin this article suggest the importance of reforms in the curriculum and student learning. The kindsof job opportunities and employment available in the system that has produced more graduatesthan the market requires must be determined. The type of planning that must be designed shouldtake account of generational inequalities in education, work, housing and welfare, as criticallyreviewed by Green in his recent work (Green 2017).

Notes

1. Calculated from the World Bank database. Accessed on 27 March 2017. http://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG.

2. Tabulation on the 2010 Population Census of the People’s Republic of China. Accessed on 27 March 2017.http://www.stats.gov.cn/tjsj/pcsj/rkpc/6rp/indexch.htm.

3. http://europe.chinadaily.com.cn/epaper/2016-11/11/content_27341958.htm, accessed on 28 August 2017.4. Li et al. (2017b) report that while college premium for the age group 20–60 years old was about 60% in the

2000s in China, college premium for young workers (i.e. 20–24 years old) has declined and was equal to about0 between 2007 and 2009.

Disclosure statement

No potential conflict of interest was reported by the authors.

JOURNAL OF EDUCATION AND WORK 349

Notes on contributors

Prof. Ka Ho Mok is the vice president and concurrently Lam Man Tsan Chair Professor of Comparative Policy atLingnan University, Hong Kong, and a co-investigator at the Centre for Global Higher Education, UCL.

Dr. Qian Jiwei is a senior research fellow at East Asian Institute, National University of Singapore. His research interestsinclude health economics, political economy and development economics.

Geolocation information

The policy implication can be applied to HE systems in other Asian countries, although this paper focuses on China.

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Appendix. Descriptive statistics

Variable Obs Mean Std. Dev. Min Max

Youth with HE (below age 26) 18,123 0.0444 0.206 0 1Youth with HE (below age 26, graduated after 2012) 18,123 0.0241 0.153 0 1Youth with HE (below age 29) 18,123 0.0758 0.265 0 1Youth with HE (below age 29, graduated after 2012) 18,123 0.0423 0.201 0 1Informal 18,123 0.397 0.489 0 1Income (logged) 15,062 9.702 1.034 3.871 14.122Gender 18,123 1.495 0.500 1 2Age 18,123 39.567 10.932 17 65Rural Hukou 18,123 0.265 0.441 0 1Party membership 18,123 0.112 0.316 0 1W/O HE 18,123 0.750 0.433 0 1Parents cadres 18,123 0.289 0.453 0 1CPI 18,123 1.146 0.129 1 1.282

CPI: Consumer price index; HE: higher education.

352 K. H. MOK AND J. QIAN