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Please cite this article in press as: Wu, X. Economic transition, school expansion andeducational inequality in China, 19902000. Research in Social Stratication and Mobility (2010), doi: 10.1016/j.rssm.2009.12.003

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Research in Social Stratication and Mobility xxx (2010) xxxxxx

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Economic transition, school expansion and educationalinequality in China, 19902000

Xiaogang Wu

Social Science Division, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China

Received 16 January 2008; accepted 23 December 2009

Abstract

This paper examines the trends in educational stratication during Chinas economic reforms in the 1990s. Based on the sampledata of population censuses in 1990 and 2000, school-age children were matched to their parents background information, and theeffects of familybackground on their school enrollment and continuationwere investigated. Results show that despite the substantialexpansion of educational opportunities in the decade, family background continues to play an important role in determining schoolenrollment status and school transitions. During the decade, children of rural- hukou status became more disadvantaged compared totheir urban counterparts, and the effect of their fathers socioeconomic status on school enrollment was enhanced. Despite the factthat children of rural- hukou statusgainedrelativelymore opportunitiesat juniorhigh school level, as a resultof nationwide saturationat the 9-year compulsory education, the ruralurban gap in the likelihood of transition to senior high school level enlarged, and theeffect of their fathers socioeconomic status increasedeven after controlling for regional variations in economic development. 2010 International Sociological Association Research Committee 28 on Social Stratication and Mobility. Published by ElsevierLtd. All rights reserved.

Keywords: China; Educational inequality; Market transition; Social stratication

This paper was presented at the ISA Research Committee onSocial Stratication and Mobility (RC28) Spring Meeting in Brno,the Czech Republic, May 2427th, 2007. The author would like tothank Sam Lucas of University of California, Berkeley, and otherconference participants for comments and suggestions, and YuxiaoWu and Zhigang Nie for their assistance in data analysis. Specialthanks are due to the National Bureau of Statistics of the PeopleRepublic of China and John Z. Ma for his assistance in data access.This project is funded by a grant from Research Grants Council of Hong Kong (HKUST6424/05H) and a post-doctoral fellowship fromNational Academy of Education/Spencer Foundation. Please directall correspondence to Dr. Xiaogang Wu, Social Science Division, theHong Kong University of Science and Technology, Clear Water Bay,Kowloon, Hong Kong (email: [email protected] ). Fax: +852 23350014.

E-mail address: [email protected] .

Education plays an important role in modern soci-eties, both as an avenue of social mobility and as atool for social reproduction. On the one hand, formalschooling can help children from disadvantaged back-grounds to change their fate; on the other hand, theschooling that individuals have received also dependson the advantages/disadvantages that theirparents conferon them throughout childhood ( Ishida, Muller, & Ridge,1995 ). In other words, access to educational opportuni-ties is unequallydistributed among different social strata.The increasing importance of education, together withlong-term growth of enrollment in a school system of a country in the process of economic development, hasled some scholars to claim that educational achievementhas become more and more independent of family back-ground ( Boudon, 1974; Treiman, 1970 ). However, linearregression analyses of educational attainment reveal that

0276-5624/$ see front matter 2010 International Sociological Association Research Committee 28 on Social Stratication and Mobility. Published by Elsevier Ltd. All rights reserved.

doi:10.1016/j.rssm.2009.12.003
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Please cite this article in press as: Wu, X. Economic transition, school expansion andeducational inequality in China,19902000. Research in Social Stratication and Mobility (2010), doi: 10.1016/j.rssm.2009.12.003


2 X. Wu / Research in Social Stratication and Mobility xxx (2010) xxxxxx

the effect of family background has stabilized over timein many industrialized countries (e.g. Featherman &Hauser, 1978 ). This is because the expansion of edu-cation and the distribution of educational opportunitiesare twoseparate processes ( Mare,1980 ): the former maynot necessarily lead to more equal access to educationamong different social strata.

The expansion of theschool systemin many countriesin the 20th century, reinforced by educational reforms,seems to have had little impact on the role played byfamily background on an individuals educational attain-ment (Shavit & Blossfeld, 1993 ). Just as income growthdoes not necessarily lead to a more equal distribution of income, educational expansion has no intrinsic implica-tions on the change in educational inequality. Instead,the distribution of educational opportunities may resem-ble the distribution of other scarce resources that affect

educational outcomes, which are both embedded in thefundamental social structure of a particular nation at aparticular time.

Since education plays an increasingly importantrole in attaining a better job and receiving more eco-nomic benets in a modern society, the question of who gets educated assumes a central place in strat-ication research ( Deng & Treiman, 1997; Shavit &Blossfeld, 1993 ). To understand the change of strati-cation outcomes in a society that is undergoing dramatictransformation in the mechanism of resource distribu-

tion, it is necessary to investigate how the transformationhas altered the allocation of educational opportunitiesamong different social strata, which may have a long-term impact on the change in social structure.

The dramatic institutional changes in former statesocialist countriesstimulateda lively debate among soci-ologists in the 1990s on how the social straticationorder is reshaped by the shift from state socialism tomarket capitalism as the main mechanism of resourcedistribution ( Bian & Logan, 1996; Cao & Nee, 2000;Gerber & Hout, 1998; Nee, 1989; Parish & Michelson,1996; Rna-Tas, 1994; Szelnyi & Kostello, 1996; Xie& Hannum, 1996; Zhou, 2000 ). Much of the existingliterature in this area, nonetheless, is largely focused onincome outcomes (e.g. Bian & Logan, 1996; Gerber &Hout, 1998; Nee, 1989; Xie & Hannum, 1996; Zhou,2000 ). Despite the growing importance of education(human capital) in determining income (e.g. Bian &Logan, 1996; Zhou, 2000 ) and controversial interpre-tations of the evidence ( Xie & Hannum, 1996; Wu &Xie, 2003 ), few scholars have explicitly examined theimpact of economic reforms on educational inequalityper sean important issue to examine if one would like

to understand the changes in the patterns of job shifts,

career mobility, and intergenerational transfers in the eraof market transition ( Gerber & Hout, 2004; Walder, Li,& Treiman, 2000; Zhou, Tuma, & Moen, 1997 ).

This study investigates the change in educationalstratication in Chinas late reform period, during whichsubstantial socioeconomic transformations were under-taken. Based on the samples of population census datain 1990 and 2000, I match school-age children agedfrom 6 to 18 to their parents background information,and investigate the impact family backgrounds on theirschool enrollment and transitions over the decade. Inparticular, I focus on the effects of the household regis-tration (hukou ) status and fathers socioeconomic statuson a childs educational outcomes.

In the remaining part of this paper, I will rst pro-vide the historical background on economic reforms andschool expansion in China since the 1980s, and explain

how the census data can be employed to address the tem-poral trend in educational inequality. I then demonstratehow family socioeconomic backgrounds have affectedchildrens educational outcomes in the context of eco-nomic marketization and school expansion. Finally, Idiscuss theimplicationsof thechange in inequality struc-ture in reform-era China.

1. Economic reforms and school expansion

Few nations have undergone changes as dramatic

as China has since the 1970s. Chinas GDP per capitahas consistently grown from 379 RMB yuan in 1978 to14,040 RMB yuan in 2005 (see Column A of Table 1 ).At a xed price in 1978, the per capita GDP increasedby 5.8 times in 2000 and 8.8 times in 2005, with anannual growth of about 9 percent (Nation Bureau of Statistics 2006). The economic growth has been espe-cially phenomenal since 1992 when Deng Xiaopingcalled for further market reform in his famous tour tosouthern China. The market economy had been fullylegitimized by the Chinese Communist Partys ideol-ogy and started playing an increasingly important role inChinas economicgrowth.Thegovernment hadretreatedto a large extent from the provisions of housing, edu-cation, health care, and other social services in the1990s.

Accompanied with Chinas economic miracle was arapid growth of inequality. As Column C of Table 1shows, the Gini coefcient, a common measure of incomeinequality, increasedfrom 0.317 in 1978 to 0.449in 2005 for the nation as a whole. Income inequalitybetween urban and rural population, institutionalizedby the household registration ( hukou ) system (Wu &

Treiman, 2004, 2007 ), was particularly prominent: the
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X. Wu / Research in Social Stratication and Mobility xxx (2010) xxxxxx 3

Table 1Selected indicators of economic growth and income inequality in China, 19802005.

Year A. GDP per capita(RMB yuan)

B: GDP per capita comparedto 1978 price as 100

C: Gini index D: urbanrural ratio of income ratio per capita

1978 379 100.0 0.317 2.351980 460 113.0 0.295 2.751985 853 175.5 0.331 2.141990 1643 237.3 0.357 2.511995 4854 398.6 0.290 2.792000 6392 575.5 0.390 3.102005 14,040 878.9 0.449 3.22

Data sources : A, B, D: Comprehensive statistical data and materials on 50 years of new China, China Statistics Publishing House, also available athttp://www.stats.gov.cn/tjsj/ndsj/ . C: World Income Inequality Database http://www.wider.unu.edu/wiid/wiid.htm .

urbanrural ratio of income per capita declined slightlyin the early 1980s, but has increased dramatically sincethen, from 2.5 in 1990 to 3.1 in 2000 and 3.2 in 2005(Table 1 : Column D). Urbanrural income inequality hascontributed 43 percent to overall income inequality inChina (Cai & Wan, 2006 , p. 3).

Sociologists have always been interested in inves-tigating who wins and who loses in the institutionaltransition( Nee, 1989; Szelnyi & Kostello, 1996 ). Whilea large body of literature has been devoted to the discus-sion of changing returns to human capital (education) asa result of the market transition ( Bian & Logan, 1996;Gerber & Hout, 1998; Wu & Xie, 2003; Xie & Hannum,1996; Zhou, 2000 ), few scholars have explicitly exam-ined the impact of economic reforms on unequal accessto educational opportunities.

Despite the fact that the pattern of educational strat-ication was relatively stable compared to the changein the distribution of economic resources, it was byno means immune to the economic reform in China,especially since the 1990s. Economic reform affectededucational stratication in three respects. First, sus-tainable economic growth demanded skilled labor. Thecommencement of the reform era was marked by thecompletedismantling of theeducational policies adoptedduring the Cultural Revolution, which severely con-

demnedthesystemof evaluating student performancebyexaminations ( Tsui, 1997; Wang, 2002 ). Despite the factthat the pattern of educational attainment in China wasfound to vary across different historical periods associ-ated with major shifts in government policies ( Hannum& Xie, 1994; Zhou, Moen, & Tuma, 1998 ), educationalinequality observed in the 1980s after the Cultural Rev-olution was largely seen as reecting a return to thegeneric practice under socialism ( Gerber & Hout, 1995;Simkus & Andorka, 1982; Wong, 1998 ), rather than theeffect of market transition ( Deng & Treiman, 1997;Tsui,1997; Zhou et al., 1997 ).

Second, economic growth afforded more resourcesfor educational development and school expansion. Thegovernment budgetary expenditure on education hasbeen increasing dramatically since 1978 (see Table 2 ). In1980, theChinese government set the targetof universal-izing primary education by the end of the 1980s; and theimplementation of 9-year compulsory education in the1990s (Tsui, 1997 ). These goals were largely attainedby 1998. As indicated in Fig. 1, the enrollment rate hadreached over 98% in the 1990s. The progression rateto junior high school, given the completion of primaryschool education, was almost 100% by the mid-1990s;theprogressionratio to seniorhigh schoolgiven thecom-pletion of junior high school increased from 30% in the1980s to 60% in 2005. Higher education has also beenopening up since 1998 ( Min, 2007 ). Within the nextfew years, the progression ratio to tertiary education,given the completion of senior high school, increaseddramatically from 40% to 80%.

Although there is no doubt that the central govern-ment intended to promote educational opportunities forall its citizens, economic reforms in rural areas slowed

Fig. 1. Educational expansion in China, 19782005.
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Table 2Government educational spending and educational expansion in China, 19782005.

Year Government budgetary educationexpenditure (100 million yuan)

Enrollment rate of school-age children %

Transition rate to junior high school %

Transition rate tosenior high school %

Transition rate totertiary school %

1978 76.23 95.5 87.7 40.9 -1979 93.16 93.0 82.8 40.0 -1980 113.19 93.9 75.9 45.9 -1981 122.22 93.0 68.3 31.5 -1982 137.20 93.2 66.2 32.3 -1983 154.72 94.0 67.3 35.5 -1984 180.14 95.3 66.2 38.4 -1985 224.89 96.0 68.4 41.7 -1986 267.30 96.4 69.5 40.6 -1987 276.57 97.2 69.1 39.1 -1988 330.91 97.2 70.4 38.0 -1989 397.72 97.4 71.5 38.3 -1990 563.99 97.8 74.6 40.6 27.31991 617.83 97.8 75.7 42.6 28.71992 728.76 97.2 79.7 43.4 34.9

1993 867.76 97.7 81.8 44.1 43.31994 1174.74 98.4 86.6 46.4 46.71995 1411.52 98.5 90.8 48.3 49.91996 1671.70 98.8 92.6 48.8 51.01997 1862.55 98.9 93.7 44.3 48.61998 2032.45 98.9 94.3 50.7 46.11999 2287.18 99.1 94.4 50.0 63.82000 2562.61 99.1 94.9 51.1 73.22001 3057.01 98.3 95.5 52.9 78.82002 3491.40 98.6 97.0 58.3 83.52003 3850.62 98.7 97.9 60.2 83.42004 4465.86 98.9 98.1 62.9 82.52005 a 99.2 98.4 69.7 76.3

Sources : Comprehensive statistical data and materials on 50 years of new China, Beijing: China Statistics Publishing House. The data after 1998from http://www.stats.gov.cn/tjsj/ndsj/ .a Data unavailable for this year.

down progress to a certain extent and yielded a nega-tive impact on school enrollments. On the one hand, thehousehold responsibility system implemented in ruralChina since 1978 drove rural children out of school foragriculture labor and employment in the rural indus-try (as shown in the decline in the school enrollmentrate in the mid-1980s in Fig. 1, even though the aggre-gate government statistics would not allow a breakdownby rural and urban areas). Moreover, the scal reformin education in the early 1990s exacerbated the situ-ation. In the context of the decentralization of publicnances in China since the early 1980s, the responsi-bility of funding primary and secondary education wasshifted to local governments who had a strong incen-tive to invest in projects that could quickly reap protsand generate tax revenues, resulting in a low prior-ity for investment in education. The uneven regionaleconomic development further differentiated local gov-ernments capacity in funding education. In many poor

andruralareas, local governments could hardlyraise suf-

cient revenue to cover teachers salaries, not to mentionother non-instructive costs. In contrast, local govern-ments in developed areas could mobilize signicantlymore resources, both government and non-government,for education ( Tsang & Ding, 2005 ). This has resultedin the substantial disparities in per-student educationalexpenditure across areas and regions. 1

Hence, to accommodate the increasing number of enrollments and increasing educational costs, schoolshave been allowed to charge tuition and other fees,even for 9-year compulsory education. For example, in1999, the surcharges and miscellaneous fees togetheraccounted for 62% of all out-of-budgeted revenue for

1 Amongthe 2070 Chinese countiesand county-levelcities (contain-ing rural population) in 2000, the educational expenditure per capita in2000ranges from 3.4 RMB Yuan to 1,474 RMB Yuan, with an averageof 164 RMB Yuan and standard deviation of 94 RMB Yuan (1 RMByuan 0.128 USD) ( Ministry of Education and National Bureau of

Statistics, 2002 ).
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primary schools and 57% of that for lower secondaryschools ( Tsang & Ding, 2005 : Table 5 ). Recent surveysconductedbysomesociologists in selectedrural countiesrevealed that Chinese farmers with an annual per capitanet income of 3200 yuan in 2005 had to pay about 800yuan a year for a childs education in primary and lowersecondary education. Excessive charges by schools havebecome a major reason behind the increasing ruralschool dropouts in recent years. In 2004, the rural aver-age dropout ratios for primary and junior high schoolswere 2.45% and 3.91%, respectively. Schools chargedeven higher for schooling beyond the compulsory lev-els, thereby economic considerations signicantly affectthe decision to continue schooling ( Min, 2007 ).

Such policy reforms have had important implicationson howfamily socioeconomicresourcesaffect childrenseducational opportunities in Chinas expanding school

system. Educational affordability has become one of thegreatest public concerns ( Kahn & Yardley, 2004 ). Thereis also a reported decline in the number of student enroll-ments fromdisadvantagedfamily backgroundsat severalelite universities ( Liu, 2004; Min, 2007; Yang, 2006 ).

In the era of rapid educational expansion and eco-nomic marketization in the 1990s, how are increasingeducational opportunities distributed among differentsocial groups? Based on the analyses of school enroll-ment and transitions in the population census data of China in 1990 and 2000, this paper will examine the

recent trend in the impact of family background on edu-cational opportunities in reform-era China.

2. Social differentiations in access to educationalopportunities: research hypotheses

Regarding the consequences of educational expan-sion on educational inequalities, early scholars arguedthat if school attendance rates increased over time, theinequalities in educational opportunity would declinesteadily, because children from disadvantaged back-grounds could increase the attendance rates by a largerpercentage than those from the upperclasses whose rateswere already high ( Boudon, 1974 ). Thisprediction, how-ever, has received little empirical support. Instead, linearregression analyses of educational attainment reveal thatthe effect of family backgrounds has been stable overtime in many industrialized countries ( Featherman &Hauser, 1978 ).

Mare (1980) distinguished the processes of selectionandallocation of students from the expansion of the edu-cational system per se, and proposed a logit model of change in inequality of educational opportunity whose

parameters are not affected by the degree of educational

expansion. Comparative studies of educational attain-ment in 13 industrialized societies have conrmed thatthe logit effects of social origins on educational transi-tions remain largely stable across cohorts, even in thecontext of long-term educational expansion (except forSwedenandtheNetherlands where the effects of fathersoccupation and education on the low and intermediatetransition decline). 2

Most relevant to Chinese educational inequality arethe cases in former state socialist countries. Simkus andAndorka (1982) analyzed educational stratication inHungary for the period from 1923 to 1973 and reportedan actual decrease of the effect of social origins on ear-lier transitions, accompanied by stableeffects in the latertransition. Mateju found similar results in Czechoslo-vakia (op. cit. Shavit & Blossfeld, 1993 ). These resultssuggest that the institutional shift to state socialism

immediately after the revolution, along with the edu-cational expansion, does bring more equality in schooltransitions at lower levels (also see Russia in Gerber &Hout, 1995 ) for a certain period of time, but educationalstratication would subsequently resume to the normalorder, in which family background would exert a stableinuence, as found in many other modern societies.

The above analysis of educational stratication undersocialism did not cover the market transition era, whenthe institutional mechanism of distributing educationalresources was undergoing a dramatic shift. Using the

data collected in 1998, Gerber (2000) extended an ear-lier study of educational stratication in Russia ( Gerber& Hout, 1995 ) and reported that the political chaos andeconomic crisis in transitionalRussia increased themag-nitude of origin-based inequalities in access to academicsecondary schools for the cohorts who completed theireducation in the tumultuous late-Soviet and post-Sovietyears when school enrollment contracted.

Evidence from all countries other than post-SovietRussia demonstrated either a stable effect or decliningeffect (for some welfare states and state socialistcountries) of family origins on educational attainment.Together with the post-Soviet Russia case, it suggeststhat the distribution of educational opportunity is morerelated to the rules that govern the educational selectionrather than the expansion of the education system perse. The former, to a large extent, is reected in thebroader inequality structure of a society. Hence, evenwithout post-Soviet Russias experience of enrollment

2 These countries include USA, West Germany, England, Wales,Italy, Switzerland, the Netherlands, Sweden, Japan, Taiwan, Poland,

Hungary and Czechoslovakia.


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contraction, the educational expansion in China in the1990s may not necessarily lead to more educationalequality. Instead, the rapid marketization of educationand withdrawal of the state in provision of education asa public good may lead to more unequal access to theenlarged educational pie. Hence, it is expected that theeffect of family background on educational opportunitywill increase over time in China. Educational expansion,if it has an effect, only increases equality at low level of transitions.

Given thechange of theinequalitystructurein reform-era China described above, in the following analysis, Iwill focus on the trend in the effects of household reg-istration status and fathers socioeconomic backgroundon school enrollment/continuation and transitions from1990 to 2000 for young cohorts between 6 and 18 yearsold in respective years.

3. Data, variables and methods

3.1. Data

As far as we know, no national survey data are avail-able on young cohorts who completed their primary andsecondary educationin theperiod whenChina proceededdeeply into marketization, including the marketizationof the educational system. This paper analyzes a sampleof micro-data from the China population censuses in

1990 and 2000. The decennial census is a unique toolstudying social changes, because it provides a rich setof data for the detail analysis of social and demographicgroups. For the most part, the census employs a constantset of measures for each decade, thereby avoiding theproblem of confusing changes in the population in theway that the population is measured ( Mare, 1995 ).

The 1990 Chinese census data includes two variableson education: educational level and enrollment status,which can be combined, together with age/cohort infor-mation, to dene whether a person of a certain age group(618) is enrolled in school or not. While the questionson education in the 2000 census are slightly modied,the variables are basically comparable to those in 1990. 3

3 Educational questions differed slightly in 1990 and 2000 censuses.For example, illiteracy/semi-illiteracy was a category of the educa-tional attainment variable, while illiteracy was asked as a separatequestion in 2000. This discrepancy suggests that results for educa-tional attainment for the same cohort in 1990 and 2000 may not bedirectly comparable. This paper deals with school enrollment ratherthan educational attainment for the relatively young cohorts, who arealmost impossible to fall in the group of illiteracy/semi-illiteracy (see

Hannum, 2005 , p. 290).

From the variable relationship to the householdhead, a childs father and mother can be identied;the childs individual records can be matched to his/herparents occupational and educational backgrounds andused as the main measures of family background. Otherindividual characteristics (gender and nationality) andhousehold characteristics ( hukou type) are available forthe multivariate analyses in both census data sets.

The data analyzed here is a sub-sample (0.1%) of the micro-data of population censuses in China in 1990and 2000. I rst extract those individuals aged between6 and 18, and then match them with their parents orcaretakers, based on the variable indicating the rela-tionship of the respondent to the household. 4 As aresult, childrenparent (or caretaker) records, as well ashousehold records encompassing geographical location,household registration ( hukou ) status, fathers education

and occupation, gender, and ethnicity were all obtained.

3.2. Variables

The dependent variable is the enrollment status andtransition of the young cohorts at certain ages, which iscoded as a dummy variable. Given the fact that primaryschool education is almost saturated in both rural andurban China, I focus on the determinations of enrollmentstatus at secondary school level (junior high school andsenior high school). While tertiary enrollment is of great

interest, family background information for most tertiarystudents arenot available in thecensus,because most col-lege students moved out of their parents homes to live instudent dormitories where their universities are located.

In addition to school enrollment, I also examine thetransition rate at two specic levels, from primary to junior high school, and from junior high school to seniorhigh school. From 1990 to 2000, the Chinese school sys-temremainedlargelythe same.As Fig.2 shows, a studenttypically starts school at age 7, proceeds to junior highschool at 13 after 6 years of primary school, and thenproceeds to senior high school/vocational school at age16. Because there is no information about the particulargrade/level that a student is attending, I approximate thetransition rate at specic levels by referring to respon-

4 Tabulation of the 2000 population census data shows that 90%of Chinese children aged between 6 and 18 years old are living withtheir parents. About another 7.8% of children live with grandparentsashousehold head, 2.1% with others as household head. In cases wherethe parents information is not identiable, the household head andspouse are used to replace fathers and mothers characteristics. Chil-dren who arehousehold heads themselves (1.2%) were excluded in the

analysis.


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Fig. 2. Age-specic full-time school enrollment rates in China, 1990and 2000.

dents age. For the transition to junior high school, it isdened as those aged between 13 and 15 still enrolled inschool divided by those of the same age group who have

completed primary school education (i.e. those in juniorhigh school and those who completed primary schoolbut were not enrolled in school). For the transition tosenior high school (i.e. continuing school after compul-sory education), it is dened as those aged between 16and 18 still enrolled in senior high school divided bythose of the same age group who have completed juniorhigh school education, namely, those who are currentlyin senior high school plus those who have completed junior high school but are currently not in school.

The main independent variable in the following

analysis is family background, measured by fathersoccupation, education, and mothers education. Thefathers occupation is converted into a socioeconomicstatus scale, which is a continuous variable. To makethe measurement consistent, I rst convert the Chinesestandard classication of occupation to internationalstandard classication of occupations (1968 version),and then map them to international socioeconomic index(Ganzeboom, de Graaf, & Treiman, 1992 ). Fatherseducation and mothers education are measured inthree levels (1 = primary school; 2 = junior high school;3 = senior high school or above). They are treated as aset of dummy variables in the multivariate analysis.

The effects of household registration ( hukou ) sta-tus were also taken into account. Hukou type capturesnot only the effect of family background, but also theregional inequality that reects the fundamental divide inthecountry ( Wu & Treiman, 2007 ). Hukou type indicateswhether oneholds agricultural (rural) or non-agricultural(urban) hukou . It is also coded as a dummy variable(rural = 1 and urban = 0).

The available resources need to be distributed amongall children in a family. While scholars have demon-

strated that the number of siblings has a negative impact

on educational attainment in western society (e.g. Mare& Chen, 1986 ), the census data allows us to identify achilds relationship only with the household head. Andbecause of the Chinese one-child policy which has beenstrictly implemented since the early 1980s, the effect of sibling size was notconsidered in the following analysis.

To capture regional variations in socioeconomicdevelopment ( Wu & Ma, 2004 ), all 31 province-level jurisdictions in China have been grouped into threeregions based on their levels of economic development:1 = East; 2 = Middle; and 3 = West. The eastern regionincludes Liaoning, Beijing, Tianjin, Hebei, Shandong,Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, andHainan. The middle region covers Heilongjiang, Jilin,Inner Mongolia, Shanxi, Henan, Anhui, Hubei, Hunan,Jiangxi, and Guangxi; and the rest of the provincesbelong to the western region. There exist great dispari-

ties in the level of economic and social development aswell as education among the three geographical regions.County-level statistics on GDP per capita in both 1990and2000,andeducational expenditure in 2000 were alsocompiled. The educational expenditure statistical datafor 1990 was not available.

In addition to geographical region, residential typehas been coded as a dummy variable (rural = 1 andurban = 0). Residential locale need not be identical tohousehold registration status (see footnote 3 in Wu &Treiman, 2007 ). People with rural- hukou status can

live in cities, as exemplied by the increasingly largenumbers of migrant workers since the early 1980s.Similarly, people with urban- hukou status can live inrural areas, as exemplied by agricultural techniciansand school teachers. 5

Becauseprevious studies have shown thatbothgenderand ethnicity are important predictors of school enroll-ment (Bauer, Wang, Riley, & Zhao, 1992; Hannum,2002, 2005; Hannum & Xie, 1994 ), they are includedin the models as the control variables. Gender is codedas a dummy variable (boy= 1), so is ethnicity (Han Chi-nese = 1 and non-Han minority= 0).

3.3. Methods

To model the probability of enrollment, omitting sub-scripts denoting the ith person of jth birth cohort in t

5 According to the authors own tabulation on the 2000 census data,about 20% of rural hukou holders resided in cities and townships,constituting 33% of the population in cities and 54% of the populationin townships. On the other hand, 12% of urban hukou holders actually

resided in villages, constituting only 4.7% of the rural population.


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period (census year), a general model is specied as

lnp

1 p= + X,

where p is the probability of being enrolled in school of certain level/age range, X is the vector of independentvariables measuring family backgrounds (more controlvariables are to be added when necessary), and is thevector of estimated coefcients. Note that in this speci-cation is estimated separately for each cohort in eachof the two periods. To examine the temporal trend, themodel can be expressed equivalently as

lnp

1 p= + X + S

where S = tX , t is s scalar dummy variable (2000 = 1), and is a vector of parameters representing the interactioneffects between family background variables and time(t ) (Wooldridge, 2003 , Chapter 13).

Because the sample was clustered within city dis-tricts/counties, an adjustment of standard errors isneeded in regression analyses. All the models reportedwere estimated using Stata 9.2, with robust standarderrors corrected for clustering on sampling units (dis-tricts/counties).

4. Descriptive statistics

Fig. 2 plots age-specic enrollment rates in Chinafrom 6 to 18 years old in 1990 and 2000, respectively.Except for age 67, the enrollment rate atage 12orbelowwas quite high in 1990 and was almost at saturationlevel in 2000, which is consistent with the governmentstatistics from the Ministry of Education presented inTable 1 (although the latter may be over-reported). Thisevidence suggests that enrollment in primary school hasbeen near saturation in China since 1990. From age13 to 15 (typically junior high school years), the ratedropped from 81.7% to 54.4% in 1990 and from 94.4%to 75.4%, suggesting the successful expansion of com-pulsory education at lower secondary level. From age16 to 18 (typically upper secondary school years), therate dropped further from 38.9% to 16.9% in 1990,and 58.9% to 24.1% in 2000. By comparing the statis-tics across the 2 years, we can observe a signicantincrease in enrollment rates within the decade, thanks tothe successful implementation of the 9-year compulsory

education law in the 1990s.

Table 3 presents descriptive statistics for those agedbetween 6 and 18. 6 The rate of full-time school atten-dance increased from 64.9% in 1990 to 82.5% in 2000.Gender and age structure, ethnic composition, and resi-dence remain largely the same between the two samples.However, whilethefathers occupational status index haschanged little, both fathers and mothers education haveimproved signicantly. For example, fathers who have junior school education or above increased from 40%in 1990 to 65% in 2000; mothers who have junior highschool education increased from 20% to 44% within thedecade.

At the bottom of Table 3 , the rate of transition to junior high school given the completion of elementaryschool for those aged between 13 and 15 and the rateof transition to senior high school given the completionof junior high school for those aged between 16 and

18 in both 1990 and 2000 have been calculated. Therate of transition to junior high school in both yearsmatch government statistics quite closely, as shown inTable 2 (75.9% vs. 74.6% in 1990 and 93.2% vs. 94.9%in 2000);whereas therate ofschooladvancement beyondthe compulsory level is much lower than that reported ingovernment statistics (31% vs. 41% in 1990 and 41%vs. 51% in 2000). The discrepancy conrms previousclaims that the ofcial net enrollment rate may haveoverestimated the number of students actually attend-ing classes, because it only recorded enrollment status

at the beginning of the school year ( Tsui, 1997 ).As of 2000 in China, there still exists a huge variationin school attendance rate. Among 2,870 counties andurban districts, the enrollment rate ranges from 69.5%(Nimu county, Tibet) to 100% among those childrenaged between 6 and 15 years old (the national average is94.6%), as plotted in Fig. 3a. Beyond compulsory educa-tion, the spatial differentials in school attendance amongchildren aged between 16 and 18 years old are even moreprominent ( Fig. 3b). On average, only 45% of Chineseaged between 16and 18years were still staying in schoolin 2000. 7

In the following analysis I rst examine the effectof family background on the enrollment status for chil-dren aged 618, who mostly live with their parents. Ithen analyze school transition for those aged between 13and 15 (from primary to junior high school) and thosebetween 16 and 18, separated by urban and rural resi-

6 Children of age 67 who have not started school were excluded incalculating the rate of full-time school attendance.

7 City/county-level enrollment rates are computed by the author

based on 0.9% of the 2000 census micro-data.


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Fig. 3. (a)County-level school enrollment rate in China (age 615) 2000. Notes : prefecture boundary shown in themap. Each dot represents a countyor a city. (b) County-level school enrollment rate in China (age 1618), 2000. Notes : prefecture boundary shown in the map. Each dot represents acounty or a city.


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Table 3Descriptive statistics of school-age children (618) in China, 1990 and 2000.

Variables 1990 2000

Full-time enrolled in school (yes = 1) 0.649 0.825Sex (female = 1) 0.485 0.472Age 12.20 (S.D. = 3.80) 11.92 (S.D. = 3.45)

RegionEast 0.335 0.364Middle 0.438 0.403West 0.227 0.232

Ethnicity (Han = 1) 0.905 0.897 Hukou (rural = 1) 0.842 0.818Residential (county = 1) 0.689 0.709Fathers ISEI 24.18 (S.D. = 15.32) 24.12 (S.D. = 14.01)

Fathers schoolingLess than Elementary school 0.147 0.041Elementary school 0.451 0.302Junior high school 0.288 0.472Senior high school or above 0.115 0.184

Mothers schoolingLess than elementary school 0.380 0.128Elementary school 0.414 0.420Junior high school 0.150 0.343Senior high school or above 0.057 0.109

Number of cases 290,860 289,769Advance to junior high school given

completion of elementary school (aged1315)

0.759 ( N = 37,406) 0.932 ( N = 58,611)

Advance to senior high school givencompletion of junior high school (aged1618)

0.305 ( N = 27,686) 0.410 ( N = 33,977)

Sources : 0.1% micro-data of 1990 and 2000 censuses.

dence. Special attention is given to the changing role of hukou status and fathers socioeconomic status in affect-ing the status of enrollment and the likelihood of schooltransition within the decade. Finally, I specically inves-tigate school transition in rural areas in the local contextof economic development and educational nancing in2000.

5. Empirical ndings from a multivariateanalysis

Table 4 presents the results from binary logisticregression predicting the likelihood of enrollment inschool for all children aged 618 in 1990 and 2000.Model 1 includes a dummy variable for year 2000to cap-turetheincrease in enrollment rate,gender, region, hukoustatus and residential place. The variables of fathersoccupation and education, and mothers education areadded to Model 2. Finally, Model 3 includes an interac-

tion between the hukou status and fathers occupational

status with the dummy variable for year 2000 to testwhether these effects have changed over time.

Not surprisingly, year, sex, ethnicity, hukou status,residential place and region, are all signicant predic-tors of enrollment status, and so are family backgroundvariables. Children whose father holds a high-statusoccupation and whose parents have higher education aremore likely to be enrolled in school.

The interaction terms in Model 3 indicate that, despitethe signicant improvement in school enrollment in thepast decade, the effect of fathers socioeconomic statuson the likelihood of school enrollment was stronger in2000 than in 1990, and the change is statistically signif-icant ( p < .05). Moreover, children of rural- hukou statuswere even more disadvantaged in 2000 than in 1990,as indicated by the negative coefcient of the interactionterm.Other things beingequal, theoddsofbeingenrolledin school for rural- hukou holders are 86% (= e 0.155 )of those for urban- hukou holders in 1990; such gures

decreased to 73% (= e 0.1550.160

) in 2000.


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Table 4Logistic model predicting full-time school enrollment for those aged 618, 1990 and 2000.

Variables Model 1 Model 2 Model 3

Year of 2000 0.945 ** 0.626 ** 0.735 **

(0.007) (0.008) (0.042)Female 0.256 ** 0.276 ** 0.276 **

(0.007) (0.008) (0.008) Hukou (rural= 1) 0.678 ** 0.212 ** 0.155 **

(0.014) (0.018) (0.024)

Region a

Middle 0.159 ** 0.122 ** 0.120 **

(0.008) (0.009) (0.009)West 0.344 ** 0.154 ** 0.151 **

(0.009) (0.010) (0.010)

Ethnicity (Han = 1) 0.395 ** 0.272 ** 0.270 **

(0.011) (0.012) (0.012)Residence (rural area= 1) 0.138 ** 0.065 ** 0.063 **

(0.010) (0.011) (0.011)

Fathers schooling bElementary school 0.413 ** 0.415 **

(0.014) (0.014)Junior high school 0.724 ** 0.729 **

(0.015) (0.016)Senior high school or above 0.767 ** 0.765 **

(0.020) (0.020)

Mothers schooling c

Elementary school 0.370 ** 0.374 **

(0.010) (0.010)Junior high school 0.662 ** 0.667 **

(0.014) (0.014)Senior high school or above 0.663 ** 0.651 **

(0.023) (0.023)Fathers socioeconomic index (ISEI) 0.007 ** 0.007 **

(0.000) (0.000)Fathers ISEI * year of 2000 0.002 *

(0.001)Rural hukou * year 2000 0.160 **

(0.033)Constant 1.216 ** 0.053 0.101 **

(0.017) (0.028) (0.033)

Pseudo- R2 0.057 0.078 0.078Observations 579546 477605 477605

Notes :a East region as the reference.b Less than elementary school as the reference Robust standard errors in parentheses.c Less than elementary school as the reference Robust standard errors in parentheses.* Signicant at 5%.

** Signicant at 1%.

Because descriptive statistics in Table 2 and Fig. 1suggest thatenrollment in primaryschool almost reachedsaturation in the 1990s as a result of successful imple-mentation of the compulsory education in China, tospecically investigate the social differentials in schoolattendance, school transition models for those aged

between 13 and 15 have been formulated (see Table 5 )

with the same independent variables and modelingstrategies as in Table 4 , but separately according to urbanand rural residence.

The results show that the patterns are quite sim-ilar to those previously observed in Table 4 , exceptfor the changing effects of fathers socioeconomic

status and hukou status. In both rural and urban


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Table 5Logit models predicting transition to junior high school given the completion of elementary school (for those aged 1315), 1990 and 2000.

Urban Rural

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Year of 2000 1.711 ** 1.270 ** 0.692 * 1.654 ** 1.331 ** 0.578

(0.061) (0.075) (0.297) (0.025) (0.030) (0.366)Female 0.435** 0.491** 0.492** 0.667** 0.762** 0.762**

(0.056) (0.065) (0.065) (0.024) (0.028) (0.028) Hukou (rural= 1) 1.987** 1.178** 1.310** 2.141** 1.242** 1.537**

(0.076) (0.107) (0.128) (0.135) (0.178) (0.246)

Region a

Middle 0.361** 0.279** 0.279** 0.451** 0.396** 0.396**

(0.066) (0.075) (0.075) (0.030) (0.034) (0.034)West 0.656** 0.508** 0.512** 0.826** 0.645** 0.644**

(0.073) (0.085) (0.085) (0.032) (0.037) (0.037)

Ethnicity (Han =1) 0.426 ** 0.297 ** 0.298 ** 0.650 ** 0.577 ** 0.578 **

(0.102) (0.112) (0.113) (0.039) (0.044) (0.044)

Fathers schoolingb

Elementary school 0.227 0.228 0.304 ** 0.304 **

(0.118) (0.119) (0.048) (0.048)Junior high school 0.739 ** 0.741 ** 0.805 ** 0.806 **

(0.129) (0.130) (0.053) (0.053)Senior high school or above 0.967 ** 0.987 ** 1.137 ** 1.137 **

(0.177) (0.180) (0.080) (0.080)

Mothers schooling c

Elementary school 0.343 ** 0.337 ** 0.297 ** 0.297 **

(0.086) (0.086) (0.033) (0.033)Junior high school 0.964 ** 0.953 ** 1.052 ** 1.051 **

(0.119) (0.120) (0.053) (0.053)Senior high school or above 0.859 ** 0.896 ** 1.398 ** 1.396 **

(0.192) (0.195) (0.138) (0.138)Fathers ISEI 0.020 ** 0.019 ** 0.032 ** 0.031 **

(0.003) (0.003) (0.002) (0.002)Fathers ISEI * year 2000 0.005 0.004

(0.006) (0.004)Rural hukou * year 2000 0.543 ** 0.690 *

(0.209) (0.348)Constant 3.404 ** 1.531 ** 1.679 ** 3.013 ** 0.838 ** 1.148 **

(0.130) (0.205) (0.223) (0.140) (0.197) (0.264)

Pseudo- R2 0.185 0.229 0.230 0.131 0.192 0.192Observations 32856 25404 25404 63123 52637 52637

Notes :a East region as the reference.b Less than elementary school as the reference; Robust standard errors in parentheses.c Less than elementary school as the reference; Robust standard errors in parentheses.* Signicant at 5%.

** Signicant at 1%.

areas, fathers socioeconomic status has a signicantimpact on the likelihood of transition to junior highschool given one has completed primary school edu-cation, but there seems to be no signicant changebetween 1990 and 2000. Children of rural- hukoustatus, however, have indeed gained relatively more

advantages, given their low starting point. This pat-

tern implies that the expansion of education, andin particular of compulsory education, has benetedrural children and overcome their disadvantages com-pared to urban children. Educational expansion hasreduced urbanrural inequality at lower levels, but notthe inequality associated with family socioeconomic

backgrounds.


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Table 6Logit models predicting transition to senior high school given the completion of junior high school (for those aged 1618), 1990 and 2000.

Variables Urban Rural


Year of 2000 1.010 ** 0.817** 0.805 ** 0.478 ** 0.379** 0.863 **

(0.034) (0.045) (0.136) (0.029) (0.037) (0.179)Female 0.014 0.047 0.045 0.322** 0.378 ** 0.375 **

(0.033) (0.041) (0.041) (0.028) (0.032) (0.032) Hukou (rural= 1) 2.077** 1.411 ** 1.183 ** 1.614** 1.075 ** 0.672 **

(0.034) (0.048) (0.072) (0.056) (0.075) (0.132)

Region a

Middle 0.433** 0.414 ** 0.402 ** 0.151** 0.155 ** 0.147 **

(0.037) (0.046) (0.046) (0.031) (0.035) (0.035)West 0.138** 0.048 0.042 0.011 0.084 0.091 *

(0.046) (0.059) (0.059) (0.039) (0.044) (0.044)

Ethnicity (Han= 1) 0.020 0.047 0.062 0.212 ** 0.184** 0.171 **

(0.076) (0.098) (0.099) (0.055) (0.063) (0.063)

Fathers schoolingb

Elementary school 0.343 * 0.356 ** 0.250** 0.266 **

(0.138) (0.136) (0.083) (0.083)Junior high school 0.494 ** 0.512 ** 0.405** 0.435 **

(0.140) (0.138) (0.085) (0.085)Senior high or above 0.960 ** 0.986 ** 0.802** 0.829 **

(0.145) (0.144) (0.093) (0.093)

Mothers schooling c

Elementary school 0.066 0.106 0.056 0.072(0.077) (0.076) (0.046) (0.045)

Junior high school 0.323 ** 0.356 ** 0.245** 0.257 **

(0.081) (0.081) (0.054) (0.054)Senior high or above 1.045 ** 1.052 ** 0.883** 0.880 **

(0.093) (0.093) (0.081) (0.081)Fathers ISEI 0.021 ** 0.019 ** 0.020** 0.017 **

(0.001) (0.002) (0.001) (0.002)Fathers ISEI * year 2000 0.005 0.008 **

(0.003) (0.002)Rural hukou * year 2000 0.420 ** 0.718 **

(0.094) (0.161)Constant 0.777 ** 1.004 ** 1.053 ** 0.084 1.511 ** 1.821 **

(0.083) (0.172) (0.180) (0.079) (0.127) (0.172)


Notes :a East region as the reference.b Less than elementary school as the reference; Robust standard errors in parentheses.c Less than elementary school as the reference; Robust standard errors in parentheses.* Signicant at 5%.

** Signicant at 1%.

Table6 presents theschool transition models forthoseaged between 16 and 18, who have completed juniorhigh school education. The patterns are quite differentfrom the early transition. For children of urban- hukoustatus, fathers socioeconomicstatus still plays an impor-tant role, but the effect remained the same from 1990 to

2000. For children of rural- hukou status, however, mak-

ing the transition to senior high school becomes evenmore difcult. In other words, in Chinese cities, peoplewith rural- hukou status (namely, rural migrants deniedurban citizens rights) face signicant disadvantages inentering senior highschool aftercompleting compulsory junior high school education, compared to those with

urban permanent hukou status (Liang & Chen, 2007 ).


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Table 7Logit model predicting school transitions for those living in rural areas (counties), 1990 and 2000.

Variables Transition to junior high Transition to senior high


Year of 2000 0.761 ** 0.589 ** 0.087 0.266 ** 0.173 ** 0.650 **

(0.037) (0.042) (0.404) (0.043) (0.051) (0.198)Female 0.673** 0.759 ** 0.758 ** 0.330 ** 0.383 ** 0.381**

(0.026) (0.030) (0.030) (0.031) (0.036) (0.036) Hukou (rural= 1) 2.101** 1.254 ** 1.483 ** 1.577 ** 1.049 ** 0.707**

(0.143) (0.193) (0.250) (0.063) (0.085) (0.137)Ethnicity (Han Chinese=1) 0.530 ** 0.467 ** 0.468** 0.109 0.053 0.043

(0.042) (0.046) (0.046) (0.057) (0.066) (0.066)County per capital GDP 0.750 ** 0.637 ** 0.636** 0.144** 0.128 ** 0.128 **

(0.025) (0.028) (0.028) (0.028) (0.032) (0.032)

Fathers schooling a

Elementary school 0.299 ** 0.299** 0.271 ** 0.284 **

(0.050) (0.050) (0.090) (0.090)Junior high school 0.808 ** 0.809** 0.433 ** 0.457 **

(0.056) (0.056) (0.093) (0.093)Senior high or above 1.190 ** 1.190** 0.836 ** 0.855 **

(0.086) (0.086) (0.103) (0.103)

Mothers schooling b

Elementary school 0.241 ** 0.241** 0.048 0.062(0.035) (0.035) (0.051) (0.051)

Junior high school 0.941 ** 0.940** 0.252 ** 0.265 **

(0.058) (0.058) (0.060) (0.060)Senior high or above 1.389 ** 1.388** 0.862 ** 0.859 **

(0.158) (0.158) (0.093) (0.094)

Fathers ISEI 0.029 ** 0.028** 0.018 ** 0.016 **

(0.002) (0.002) (0.001) (0.002)Fathers ISEI * year 2000 0.003 0.007 **

(0.005) (0.003)Rural hukou * year 2000 0.623 0.693**

(0.384) (0.177)Constant 2.736** 3.886 ** 3.643 ** 1.157 ** 2.394 ** 2.664**

(0.225) (0.280) (0.325) (0.214) (0.263) (0.286)


Notes :a Less than elementary school as the reference; Robust standard errors in parentheses.b Less than elementary school as the reference; Robust standard errors in parentheses.* Signicant at 5%.

** Signicant at 1%.

Compared to 1990, the situation in 2000 deteriorated,given the surging wave of migration from rural to urbanareas (Liang & Ma, 2004 ).

In rural areas, the scenario was quite different from1990 to 2000. Fathers socioeconomic status was stilla signicant predictor of the likelihood of transition tosenior high school and the effect was even stronger in2000 than in 1990.For rural- hukou holders in rural areas,their situation was worse in 2000 than in 1990. There-fore, thanks to the successful implementation of the

9-year compulsory education in China in the1990s, fam-

ily background and registration status still play an evengreater role in determining whether school-age childrenreceive further education beyond the compulsory level,despite the fact that the educational expansion benetedchildren of rural hukou in lower secondary education.

Does this reect the uneven regional economic devel-opment in rural China? In Table 7 , local economicdevelopment level, measured by (logged) GDP percapita of the county in 2 years, was controlled for.The results show that local economic development does

play an important role in determining school atten-


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dance rate: children in more developed counties/areashave more educational opportunities (also see Fig. 3aand b). The effect of fathers socioeconomic status andfamilys hukou status on school transition continue toaffect school transition rates, and these effects, whileunchanged on the transition to junior high school, werestronger in 2000 than in 1990 in favor of those who areat advantaged status, namely, those who have fathers of high occupational status and who hold urban- hukou sta-tus. Educational inequality at senior high school levelincreased within that decade.

Local per capita GDP may not capture the exactamount of resources spent on education. Two county-level indicators educational expenditure per capita and

the percentage of educational surcharge on per capitaincome are available only for the year 2000. They areincluded in the models of Table 8 , which predict schooltransitions in rural China in 2000. As shown in the mod-els, both are signicant predictors of school transitionrates, but again, the effects of family backgrounds andhukou status remain substantial.

What might explain the above-mentioned difcultyfacedby children of rural hukou are the exclusionarybar-riers they encounter for not holding local urban hukou(Liang & Chen, 2007 ). Societal norms and values mightalso have a role in making them less interested in contin-uing education beyond the compulsory levels. The latterfactor could also explain why rural- hukou children have

Table 8Logit model predicting school transitions for those living in rural areas, controlling for county educational expenditure, 2000.

Variables Transition to junior high school Transition to senior high school

Model 1 Model 2 Model 3 Model 4

Female 0.597 ** 0.593** 0.326** 0.324 **

(0.051) (0.053) (0.043) (0.044) Hukou (rural= 1) 0.762 ** 0.779** 1.428** 1.387 **

(0.278) (0.302) (0.115) (0.118)Ethnicity (Han = 1) 0.837 ** 0.797 ** 0.211 * 0.176*

(0.074) (0.078) (0.082) (0.087)

Fathers schooling a

Elementary school 0.177 0.145 0.122 0.036(0.099) (0.109) (0.157) (0.168)

Junior high school 0.669 ** 0.648 ** 0.272 0.249(0.105) (0.116) (0.158) (0.168)

Senior high or above 1.088 ** 1.110 ** 0.677 ** 0.682**

(0.143) (0.157) (0.162) (0.174)

Mothers schooling b

Elementary school 0.503 ** 0.467 ** 0.004 0.036(0.066) (0.070) (0.077) (0.080)

Junior high school 1.356 ** 1.264 ** 0.258 ** 0.249**

(0.095) (0.100) (0.085) (0.088)Senior high or above 1.894 ** 1.826 ** 0.767 ** 0.707**

(0.225) (0.235) (0.112) (0.117)

Fathers ISEI 0.040 ** 0.035 ** 0.026 ** 0.023**

(0.005) (0.005) (0.002) (0.002)Education spending per capita (logged) 0.502 ** 0.584**

(0.126) (0.096)% Surcharge in per capita income (logged) 0.073 * 0.065*

(0.034) (0.032)Constant 0.770 * 1.431* 0.887** 3.637 **

(0.317) (0.704) (0.201) (0.544)

Pseudo- R2 0.108 0.108 0.069 0.069Observations 24627 22837 13457 12569

Notes :a Less than elementary school as the reference; Robust standard errors in parentheses.b Less than elementary school as the reference; Robust standard errors in parentheses.* Signicant at 5%.

**Signicant at 1%


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lower attendance rates at senior high school level com-pared to urban- hukou children in rural areas. As yet, nodata are available to directly address this issue.

6. Summary and conclusions

To summarize, this studyexaminedthe trendineduca-tional stratication during Chinas economic reforms inthe 1990s. Based on the samples of the population cen-sus data for 1990 and 2000, school-age children werematched to their parents background information andthe effects of family background on their school enroll-ment and transitions were investigated. Results showthat, despite the substantial expansion of educationalopportunities from 1990 to 2000, family backgroundshave continued to play an important role in determiningschool enrollment status and school transitions. During

the decade, children of rural- hukou status became moredisadvantaged compared to their urban counterparts andthe effect of fathers socioeconomic status on schoolenrollment was enhanced.While children of rural- hukoustatus gained more opportunities at junior high schoollevel as a result of saturation in the 9-year compulsoryeducation at the national level, the ruralurban gap in thelikelihood of transition to senior high school level wasenlarged and the effect of fathers socioeconomic statuson the transition rate increased, even after controlling forregional variations in economic development.

Hence, educational expansion in China, accompaniedby the rapid marketization in the 1990s, did not bringmore equal access to educational opportunities amongdifferent social strata. Instead, uneven distribution of educational opportunities seems to have exacerbated inthe context of market reforms in the educational sphereand rising inequality in the distribution of economicresources. Thechange in educational inequality to a largeextent mimicked the change in the overall structure of inequality in reform-era China in the 1990s.

Chinas case is consistent with the thesis of maxi-mally maintained inequality ( Raftery & Hout, 1993 ),which argues that inequality in educational opportunityis maximally maintained, namely in modern societies,where the effect of social origin at all levels of edu-cation does not change. Only when the enrollment of advantaged groups is already high at a given level, couldfurther expansion be feasible by increasing the opportu-nity of disadvantaged groups to make the transitions.The implications of the ndings in this paper, how-ever, may go further beyond the thesis of maximallymaintained inequality. While the thesis predicts that edu-cational expansion does not lead to better chances for

disadvantaged groups to transition to a higher school

level, and that it will not change the association betweenfamily background and the given level of school tran-sitions, the analysis of this paper has demonstrated thatthe effect of family background has indeed increased (rather than remained constant and decreased condition-ally), and educational opportunities of the disadvantagedgroups were less in 2000 than a decade prior.

What are the implications of these ndings for thechange in social stratication order and the evolutionof social structure in China in the future? While theavailable data do not allow us to examine the trend in ter-tiary school attendance rates of children from differentsocial backgrounds, one can reasonably speculate thatthe expansion of higher education in the late 1990s willlargely benet urban children and children from better-off families, further increasing educational inequalityat higher levels ( Min, 2007; Yang, 2006 ).8 The ris-

ing educational inequality among students of differentsocioeconomic backgrounds in the 1990s could lead toincreasing earnings inequality after they complete edu-cation and enter the labor markets. In the long run,intergenerational transmission is enhanced in the courseof market transition (as observed in post-Soviet Russiaby Gerber & Hout, 2004 ); the role of education as animportant channel for socioeconomic mobility is weak-ened. Future research should be devoted to assessingthe far-reaching social consequences of the rising edu-cational inequality in China in recent years.

The reversed equalization of educational opportuni-ties reported from China has echoed previous ndingsfrom post-Soviet Russia ( Gerber, 2000 ) and Hong Kong(Wu, 2007 ). The political chaos and economic crisis hadharmed the Russian educational system and increasedorigin-based inequality in access to secondary schoolsfor certain cohorts, who completed education duringthe later Soviet and post-Soviet years when enrollmenthad contracted. In Hong Kong, despite a decline in the1980s, family background affected more importantlythe progression to higher levels of education (particu-larly to university) in 2001. The economic prosperityaccompanying dramatic institutional changes seems tohave brought limited equality in access to upper sec-ondary education in China, which is still in short supplyfor the majority of the population. All three societieshave experienced a rapid increase in income inequalityover the past decades. In Russia, the Gini coefcientsamong all employed workers increased from 0.261 in

8 There were 2.04 million full-time students enrolled in colleges in1991; the enrollment increased to 5.56 million in 2000 and 12 million

in 2003. Also see the transition rate to tertiary school in Table 2 .


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1986 to 0.296 in 1991, 0.483 in 1996 and further to0.521 in 2001. In Hong Kong, the Gini coefcient forhousehold income rose from 0.453 in 1986 to 0.476 in1991, 0.518 in 1996, and 0.525 in 2001 ( World IncomeInequality Database, 2004 , for China statistics fromthe same source, see Table 2 ), and, nally, 0.533 in2006 (Census and Statistics Department, 2007 ). Theseobservations suggest that the distribution of educationalopportunities may reect the mechanism of resourcedistribution rather than a direct response to expandingopportunities. Thus, more comparative studies of edu-cational stratication in rapidly changing societies arecalled for in order to establish such a direct linkage.

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Documents

00 WU economic transition