Privatization Reform and Inequality of Educational Opportunity - The Case of Chile

Privatization Reform and Inequality ofEducational Opportunity:

The Case of Chile

Florencia TorcheQueens College and Columbia University

Chile has experienced considerable educational expansion over the past few decades, as well

as a privatization reform in 1981 that introduced full parental choice through a voucher sys-

tem, in the context of a market-oriented transformation of the country. Using a cohort analy-

sis of the 2001 Chilean Mobility Survey, this article examines trends in educational stratifica-

tion in Chile over the past 50 years, with a focus on the changes that followed the privatiza-

tion reform. The analysis shows that, in line with international findings, there is “persistent

inequality” of educational opportunity across cohorts in Chile. Persistent inequality is not total,

however. There is a small but significant increase in inequality in the transition to secondary

education, which is cotemporaneous with the market-oriented transformation. Furthermore,

when school sector—a form of “qualitative inequality” expressed in the distinction among

public, private-voucher, and private-paid schools—is considered, the analysis suggests an

increase in the advantages that are associated with private-voucher schools after the privati-

zation reform, as well as in the benefits of attending private-paid schools during and after the

reform. The article concludes by discussing the relationship among economic context, priva-

tization reform, and educational inequality.

Sociology of Education 2005, Vol. 78 (October): 316–343 316

Inequality of educational opportunity(IEO)—the effect of parental resources andconditions when growing up on individual

educational attainment—is a key componentof the intergenerational reproduction ofinequality in contemporary societies (Shavitand Muller 1998; Treiman and Yip 1989). Todate, trends in IEO have been studied inabout two dozen countries, including almostall Western and Eastern European nations, theUnited States, Japan, Hong Kong, Malaysia,the Philippines, Israel, Korea, and Brazil(Garnier and Raffalovic 1984; Mare 1980,1981; Park 2004; Pong 1993; Post 1994;Raftery and Hout 1993; Shavit and Blossfeld1993; Shavit and Westerbeek 1998; Silva2004; Simkus and Andorka 1982; Szelenyi

1998). Most of these national studies haveshown that the effect of social background oneducational attainment has remained con-stant over the past few decades, in spite ofmassive educational expansion and a variedset of policy interventions to reduce inequali-ty. This finding has been summarized as “per-sistent inequality.”

Researchers have used four theoreticalapproaches to explain trends in educationalstratification: the industrialization theory, thereproduction theories, the “maximally main-tained inequality” (MMI) hypothesis, and the“effectively maintained inequality” (EMI)hypothesis. These theoretical approacheshave contributed immensely to the explo-ration of processes that drive temporal

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change in educational stratification. However,with the exception of EMI, they share a rela-tive disregard for the specific institutionalarrangements and mechanisms—organiza-tion of educational systems and policy inter-ventions—that lead to their predicted out-comes.

The finding of persistent inequality cuttinghomogeneously across countries as differentas France and Israel, England and Korea, andthe United States and Poland seems to sup-port the disregard for nationally specific edu-cational policies and reforms. After all, if thereis no variation in the outcome, why wouldone need to introduce institutional arrange-ments and policies as explanatory factors?Before one gives up on the exploration of theinstitutional and economic context of educa-tional stratification, however, it is importantto consider two factors. First, persistentinequality is not universal. There are at leastthree countries—Sweden, the Netherlands,and Germany—in which educational inequal-ity has been found to have declined over time(De Graaf and Ganzeboom 1993; Erikson andJonsson 1996; Jonsson, Mills, and Muller1996), and a recent analysis suggested that itmight have also declined in Britain, France,and Poland (Breen et al. 2005). There is alsoat least one case, Russia, in which inequalityhas been found to have increased at highereducational levels (Gerber 2000, 2003;Gerber and Hout 1995). Second, the pool ofcountries in which trends in educational strat-ification have been studied is still small andconfined almost entirely to the industrializedworld. The question of processes of educa-tional stratification in countries with differentlevels of development and institutionalarrangements is still open.

This article presents an analysis of trends inIEO in Chile and attempts to accomplish twoobjectives. The first is to introduce Chile to thecomparative template of research on educa-tional stratification, thereby adding variationto an enterprise that is focused mostly onindustrialized nations. Chile provides an inter-esting case because it is both a late-industrial-izing country and one that experienced a rad-ical privatization reform of its educational sys-tem in the early 1980s as part of a market-ori-ented transformation by the authoritarian

regime of General Augusto Pinochet. Perhapsthe most salient component of the privatiza-tion reform was the introduction of fullparental choice through a nationwide vouch-er system at the primary and secondary edu-cational levels. Thus, the second objective ofthis article is to explore the educational strati-fication processes that followed the privatiza-tion reform of the early 1980s. To formulatethis question, I used the notion of qualitativeinequality (Ayalon and Shavit 2004; Breen andJonsson 2000; Lucas 2001). While traditionalstudies of educational stratification havefocused on quantitative inequality (“howmuch” education different socioeconomicgroups obtain), qualitative inequality high-lights the fact that educational systems are notone dimensional, but that at any given educa-tional level, there may exist different subsec-tors (e.g., tracks and school sectors) that pro-vide unequal opportunities for further attain-ment. In this article, I explore different kinds ofschools that were formed after the privatiza-tion reform in Chile—public, private-voucher,and private-paid schools—as a potential vehi-cle of educational stratification.

This article is organized in six sections.Following this introduction, the second sec-tion reviews the hypotheses about mecha-nisms that drive educational stratification.The third section describes the Chilean edu-cational system and its change over time,with a focus on the privatization reform of the1980s. The fourth section introduces thedata, variables, and methods. The fifth sec-tion presents the analysis, and the sixth sec-tion presents the discussion and conclusions.

THEORETICAL APPROACHES

Analysts have used four theoretical approach-es to explain trends in educational inequality:the theory of industrialization; reproductiontheories; MMI; and, more recently, EMI.Flourishing in the self-confident post–WorldWar II period, the theory of industrializationclaimed that educational inequality woulddecline as countries industrialized (Parsons1970; Treiman 1970). As a result of economic,institutional, and cultural modernization, larg-er segments of the population would gain

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access to education, and their educationalattainment would be increasingly less depen-dent on background and more dependent onmerit (Bell 1972). Empirical findings in thefields of social and educational mobility havecast doubts on these optimistic predictionsand have highlighted the intergenerationalresilience of inequality. In an attempt toexplain the role of the educational system inthe persistence of inequality, reproductiontheories claim that educational systems areorganized so as to reproduce the unequalsocial structure. Thus, even if educationexpands, stratification will persist becausethose who are in advantaged positions willsuccessfully implement strategies to maintainprivilege. The strategies highlighted by repro-duction theories vary, but they tend toemphasize the cultural dimension of inequali-ty in the form of socialization by the schoolinto hierarchical social roles that are function-al to capitalism (Bowles and Gintis 1976), theuse of language to learn and express class dif-ferences (Bernstein 1971), or the rewarding ofthe cultural capital that upper-class studentsbuild naturally at home and less-privilegedstudents lack (Bourdieu and Passeron 1973).

Even if industrialization and reproductiontheories are opposed in their predictions, theyshare a claim of universal validity and relativelittle attention to the particularities of nationalinstitutional contexts. More recently, an alter-native approach has emerged in the context ofempirical research. MMI (Raftery and Hout1993) was formulated as an explicit attempt toexplain a question that was posed by findingsin several industrialized countries: Why is it thateducational expansion and egalitarian reformsdo not reduce educational inequality amongsocioeconomic strata? MMI asserts that anexpansion in the educational system that doesnot specifically focus on the less-advantagedclasses provides new opportunities for all chil-dren. On average, children of advantaged class-es have more economic and cultural resources,perform better in school, have higher aspira-tions, and are more acquainted with the edu-cational system (Entwisle, Alexander, and Olson1997; Lareau 1987, 2000, 2003; Sewell andHauser 1975); in short, they are “better pre-pared than are others to take advantage of neweducational opportunities” (Ayalon and Shavit

2004:106). Therefore, only when the advan-taged classes have reached saturation at a par-ticular level of education—transition rates at orclose to 100 percent—will other sectors of thesociety benefit from educational expansion.Only in these cases will educational expansioncontribute to the reduction of socioeconomicinequality of educational opportunity (Rafteryand Hout 1993).

According to MMI, a decline in inequalitycan be reversed. If, for example, an educa-tional reform pushes expansion at the sec-ondary level, but this expansion is not cou-pled with a growth of similar magnitude atthe college level, the increasing number ofhigh school graduates face a bottleneck, lead-ing to competition for scarce college places.The advantaged classes have an upper handin that competition, which could lead togrowing inequality at the college level.Evidence supporting this kind of process wasfound for the Russian case during the late-Soviet and post-Soviet periods (Gerber 2003;Gerber and Hout 1995). As Hout (2003) indi-cated, MMI has found empirical support in avariety of settings, but it has been discon-firmed in others, thus transforming it from anempirical generalization into a useful conceptto guide research.

EMI is the most recent approach to educa-tional stratification (see Lucas 2001 for theoriginal formulation, see also Ayalon andShavit 2004; Breen and Jonsson 2000). EMIcriticizes MMI for ignoring the simple factthat educational systems are not one dimen-sional, but include several branches at eachparticular level—for instance, academic andvocational education or college preparatoryand non-college preparatory tracks. EMIargues that when saturation is reached at aparticular level and inequality in attainmentdeclines, “quantitative inequality” may bereplaced by “qualitative inequality,” that is,the advantaged classes will be able to obtaineducational credentials that provide themwith enhanced opportunities for furtherattainment. By focusing on tracking, EMIexplicitly considers the institutional organiza-tion of different educational systems, therebyemphasizing the relevance of including theinstitutional dimension in the study of trendsin educational stratification.

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Qualitative Inequality andPrivatization

EMI highlights an increasingly importantdimension of inequality. However, it presentssome limitations when it is used for interna-tional comparisons. First, EMI treats qualita-tive inequality as an outcome whose determi-nants are to be analyzed. But qualitativeinequality can also be thought of as a predic-tor, a variable that adds to or mediates theeffect of social background and contributes toinequality of attainment. Second, to date,EMI has focused on tracking as an instance ofqualitative inequality—for instance, the dis-tinction among no-math, non-collegepreparatory, and college preparatory tracks inU.S. high schools (Lucas 2001) or the distinc-tion between vocational and academic tracksin Sweden (Breen and Jonsson 2000).However, tracking is not the only form ofqualitative differentiation or even the mostimportant in some educational systems. Asthe Chilean case highlights, the distinctionamong school sectors—public and differentkinds of private schools—may be anotherimportant instance of qualitative or horizontaleducational differentiation. Similar to theorganization of tracking, the kinds of schoolsthat are available to students at different edu-cational levels vary widely across countries. Insome nations, such as most of Western andEastern Europe, Canada, and Israel, the dis-tinction across school sector is of little rele-vance because the large majority of primaryand secondary schools are public. This is notalways the case, however. Because of histori-cal reasons, other advanced industrial nationshave a large proportion of private schools. Forexample, in Belgium and the Netherlands,the enrollment in government-sponsored reli-gious private schools is more than 60 percent.In nations like Australia and Spain, govern-ment-sponsored, mostly secular, privateschools serve about one third of pupils, and inthe United States, independent privateschools represent about 11 percent of thetotal enrollment (OECD 2001).

The impact of attending a particular kindof school on educational attainment andachievement is not a new topic in the studyof educational inequality. The relative efficien-

cy of private, particularly Catholic, schoolshas been a widely researched issue in theUnited States over the past few decades (see,e.g., Alexander and Pallas 1985; Coleman,Hoffer, and Kilgore 1982a, 1982b; Hoffer,Greeley, and Coleman 1985; Jencks 1985).With the recent push for educational privati-zation, the role of school sector in education-al achievement and attainment has regainedrelevance and has included new modalities of“school choice,” such as magnet, charter,and voucher schools1 (Altonji, Elder, andTaber 2002; Bryk, Lee, and Holland 1997;Gamoran 1996; Greene, Peterson, and Du1998; Howell and Peterson 2002; Kruegerand Zhu 2002; McEwan 2000; Rouse 1998;Witte 2000). In the past few years, mostempirical research has focused on voucherprograms, partly because of ideological rea-sons and partly because of the design of someof these programs, which randomly assignsvouchers to families. This design provides aconvenient experimental framework thatallows for the control of omitted family andindividual characteristics (Howell andPeterson 2002; Krueger and Zhou 2002).Research on vouchers and other forms ofschool choice has focused almost entirely onindividual outcomes: How does Student A,who moved to a voucher school, fare in com-parison with an “equivalent” Student B whoremained in the public system? There hasbeen little research on macrolevel conse-quences of school-choice programs on theinequality of the educational system as awhole.2 The lack of attention to aggregateoutcomes of “school-choice” initiatives isunderstandable. Owing to the small scale ofthese initiatives, it is simply impossible toevaluate their consequences at a systemiclevel. As McEwan (2000, 2004) argued, wehave to be extremely careful when extrapo-lating findings about short-term changesfrom small-scale voucher (or other school-choice) programs to long-term outcomes oflarge-scale programs.

An additional difficulty in studying theeffect of changes in educational policy oninequality at the aggregate level is the factthat policy interventions are usually endoge-nous, in the sense that they are a response topopular demands for more or better educa-

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tion. For instance, a policy that is oriented toexpanding secondary education is as much acause of expansion as it is a consequence of apopular demand for it. Therefore attributingany observed change in educational stratifica-tion to the policy change, as if it was anexogenous force, disregards the fact that thevery processes that lead to increased demandaffect the outcomes that are being analyzed.3

In sum, the important question about theconsequences of large-scale school-choiceprograms on educational stratification is stillopen, and its study faces important chal-lenges. The Chilean case provides an oppor-tunity to explore this issue. First, the Chileanvoucher system is nationwide, and it has beenin place almost unaltered for more than twodecades. This fact permits researchers to eval-uate the potential impacts of a national-levelreform. Second, the characteristics of theChilean privatization render it closer to an“exogenous shock” than other instances ofpolicy intervention. On the one hand, theChilean educational reform was part of acomprehensive neoliberal transformation ofthe welfare system that was based on theidea that the market should replace the gov-ernment as the main allocation mechanism.The neoliberal transformation included notonly the privatization of education, but therestructuring of the labor market and the cre-ation of quasi-markets in housing, health, andpensions. On the other hand, the education-al reform took place in the context of anauthoritarian regime that was unbound bydemocratic rule and was backed up byrepression and violence. The transformationwas carried out by a group of ideologicallyhomogeneous and highly motivated youngtechnocrats, who were known as the“Chicago Boys” because they had obtainedtheir graduate education in the University ofChicago’s Department of Economics(Martinez and Diaz 1999). This group wascompletely isolated from the social demandsof citizens, including the until-then-powerfulChilean Teacher’s Association (Gauri 1998).As a result of these factors, the privatization ofeducation took place in record time. As Gauri(1998:22, quoting Infante and Schiefelbein1992) put it, “The most profound transfor-mation ever experienced in Chilean public

education was an idea conceived, designedand implemented in 18 months.” Even if noinstance of a change in social policy is everfully exogenous, the Chilean educationalreform is as close as one may get to an exter-nal shock. Therefore, the Chilean case pro-vides a useful setting not only for the analysisof trends in educational inequality in a devel-oping country, but for the assessment ofchanges following the privatization reform,including the potential role of the vouchersystem.

The analysis of the Chilean case is not freeof limitations, however. Because the data thatare presented in this article came from a sin-gle cross-sectional study, I assess temporalchange by using cohort analysis, as is stan-dard in studies of educational stratification(Garnier and Raffalovic 1984; Gerber andHout 1995; Mare 1980, 1981; Park 2004;Pong 1993; Raftery and Hout 1993; Shavitand Blossfeld 1993; Shavit and Westerbeek1998; Silva 2004; Simkus and Andorka 1982;Smith and Cheung 1986; Szelenyi 1998).Cohort analysis is useful for inferring trends inthe effect of family background on schoolattainment, but it is less able to capture thespecific causal effects of policy (Post 1994).Therefore, it is important to state at the out-set that this article does not claim to offer adefinitive account of the mechanisms that ledto the observed outcomes or conclusivecausal interpretations of the effects of thevoucher system on educational stratification.The results of this study are valuable, howev-er, in that they shed light on the institutionaldimension of educational stratification and onthe potential role of school choice in inequal-ity.

THE CHILEAN EDUCATIONALSYSTEM

The Chilean educational system is comprisedof eight years of compulsory primary educa-tion; four years of secondary schooling; andthree types of tertiary education: colleges,professional institutes, and technical insti-tutes. There is no academic-ability groupingat any level, and tracking begins at the sec-

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ondary level, where students have to choosebetween vocational and academic highschools. Following a universal trend, Chileexperienced significant educational expan-sion in the second half of the 20th century.According to the Chilean census, from 1952to 1992, the proportion of the populationaged 25 and older with no educationdropped from 23.5 percent to 5.8 percent,while the proportion with a secondary educa-tion grew from 19.1 percent to 29.6 percentand the proportion with a postsecondaryeducation increased from 2.4 percent to 7.2percent.

Expansion has unequally benefited differ-ent socioeconomic strata. Historical informa-tion on educational attainment by socialbackground is scattered in Chile, with onlythree large studies available. A study con-ducted in 1955 in the city of Santiago foundthat the survival rate at the sixth grade was 80for the upper class, 48 for the middle class,and only 28 for the lower class (Hamuy1961:104). According to a study that wasconducted in the mid-1960s (Soto 2000:55),access to tertiary education was extremelystratified, with only 3 percent of the collegestudents coming from working-class families.A pioneer longitudinal study conducted dur-ing the 1970s found pervasive inequality ineducational attainment and achievement. Forinstance, the high school graduation rate ofchildren who were starting the eighth gradein 1970 was 100 percent for children of uni-versity-educated parents, but 32 percent forchildren of parents with a secondary educa-tion, 12 percent for children of parents with aprimary education, and only 3 percent forchildren of parents with no education(Schiefelbein and Farrell 1982:89).

Educational inequality is still substantial inChile. Differences in attainment by incomelevel are noticeable even at the primary com-pletion level in Chilean society. Whereas 99.1percent of children in the wealthiest incomequintile completed the primary level in 2000,only 71.9 percent of children in the poorestquintile did so. Socioeconomic differences arewider at the secondary level, with 30 percentof the children in the poorest quintile com-pleting secondary school, compared to 95percent of the children in the wealthiest quin-

tile. Disparities magnify at the tertiary level,with only 3.1 of the poorest youngsters, but48.2 percent of the wealthiest ones, complet-ing tertiary education (Spilerman and Torche2004:Table 8.3).

Institutional Change in theChilean Educational System

The Chilean government slowly expandedprimary and secondary enrollment during thefirst half of the 20th century and started toprovide free public education in the 1920s. Inthe mid-1960s, the expansion of the systemwas boosted by a set of policies that were ori-ented to increasing access to primary andsecondary education, when a progressiveadministration (1964–70) established a man-date to guarantee universal access to primaryand secondary schooling, regardless of socialbackground (Aylwin et al. 1983; Cox andLamaitre 1999). The government built 3,000new public primary and secondary schools inpoorer and rural areas, implemented a dou-ble-shift school day, rapidly trained newteachers to meet the increased educationaldemand, and extended compulsory primaryeducation from six to eight years (Gazmuri2000; Soto 2000). The state’s effort toexpand education was successful: Enrollmentreached more than 93 percent at the primarylevel in 1970, and secondary enrollment rosefrom 18 percent in the late 1950s to 49 per-cent in 1970.

In 1973, a military regime took power aftera violent coup and retained it until 1990.During these 17 years, the military govern-ment conducted a sweeping market-orientedtransformation of the economy and socialwelfare system. A major reform of the Chileaneducational system was launched in 1981 aspart of this transformation (Cox and Lemaitre1999; Graham 1998). Perhaps the most revo-lutionary component of the reform was theintroduction of a universal educational vouch-er system, in which a subsidy was paid topublic and private schools on the basis of stu-dents’ enrollment, and families were free tochoose among schools. Private schools couldreceive the subsidy in exchange for notcharging fees to students. It is important tonote that the Chilean voucher system differs

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from the U.S. voucher experiments in that thegovernment does not give a tuition certificateto the family but, rather, pays the subsidydirectly to the school that the student choos-es. Thus, the Chilean voucher model is knownas a “funds follow the student” system(Mizala and Romaguera 2000; West 1996).However, the basic principles that guidevoucher systems, as paradigmatically definedby Friedman (1962) and Coons andSugarman (1978)—competition amongschools and freedom of the family to chooseamong schools—are the bases of the Chileansystem. Hence, analysts of the Chilean choicemodel have described it as a voucher system(see, e.g., Carnoy 1998; Carnoy and McEwan2001; Contreras 2001; Hsieh and Urquiola2003; McEwan 2000; McEwan and Carnoy2000; Mizala and Romaguera 2000; Parry1997).4

Another important component of the pri-vatization reform was the decentralization ofpublic schools (Cox and Lemaitre 1999).Before the reform, the Ministry of Educationcentrally controlled public schools and wasresponsible for all aspects of their operation.It hired and paid teachers, maintained facili-ties, and designed the curriculum. With thereform, schools were transferred to about 300local (municipal) governments (Gauri 1998).In addition, in the context of welfare stateretrenchment, public spending on educationdropped from 4.9 percent of the grossdomestic product in 1982 to 2.5 percent in1989, and the educational budget reallocatedfunds from the tertiary level to lower educa-tional levels. Because of the budget reduc-tion, insufficient resources to maintain expen-ditures plagued the new voucher system, andthe value of the monthly subsidy per primaryand secondary student dropped by 20 per-cent between 1982 and 1987 and did notregain its 1982 value until 1994 (Cox andLemaitre 1999). This decline in the educa-tional budget was especially consequentialbecause the expansion had drawn in relative-ly poorer children, who were more depen-dent on the educational system’s inputs(Birdsall, Ross, and Sabot 1997).

The privatization reform rapidly created aneducational market at the primary and sec-ondary levels. To understand the depth of

these changes, a before-and-after comparisonis useful. Prior to the privatization reform,almost 80 percent of Chilean students attend-ed public schools. Private-paid schoolscharged relatively high tuition and catered tohigh-income families. These private-paidschools did not opt to take the governmentvoucher, which was low in comparison totheir fees. The voucher system thus enabled anew private sector to enter the market asproviders of publicly financed education: theso-called private-voucher schools.5 Althoughprivate schools that received governmentalsubsidies existed in Chile before the privatiza-tion reform, they received only about half thebudget allocated to public schools, and thesubsidies were usually delayed and eroded byinflation (Espinola 1992; Hsieh and Urquiola2003). Therefore, they functioned as a formof charity, rather than a component of theeducational market. Even if they will be calledvoucher schools as will the government-spon-sored private schools that emerged after theprivatization reform, the reader should keepin mind that they are a different institutionalform.

Some of the voucher schools that emergedafter the privatization reform were managedby religious and nonprofit organizations, butthe majority of them were run by privateagents that capitalized on education as aprofitable business (Hsieh and Urquiola2003). All these schools competed for stu-dents with public schools. Voucher schoolsprospered in urban, highly populated, areas,where they became an attractive alternativefor middle-income families who were unableto afford the expensive private-paid schools.Voucher schools were not profitable, howev-er, in poor and rural areas (Mizala andRomaguera 2000; Parry 1996). As Figure 1indicates, following the introduction of thevoucher system, the voucher sector dramati-cally expanded from an enrollment of 15 per-cent in 1981 to 37 percent in 1999. Thisexpansion was at the expense of publicschools, whose market share dropped from78 percent to 54 percent of the total enroll-ment during that period.

The implementation of a voucher systemin Chile gave rise to creaming, since publicschool students of a higher socioeconomic

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status were more likely to migrate to the pri-vate-voucher system (Hsieh and Urquiola2003). Figure 2 illustrates the point. It pre-sents the distribution of the school sectorattended by income decile in 1990, aftermost of the selective migration from the pub-lic to the private-voucher system had beencompleted. The figure indicates that after theprivatization reform, public schools servedmostly low-income groups, private-voucherschools concentrated on the lower-middleand middle-income sectors, and private-paidschools catered to the top income deciles.

Two characteristics of the Chilean vouch-er system favored creaming. First, voucherschools were established in more-affluentareas of the country, where business wasmore profitable. Second, they could selectstudents according to their own criteria, incontrast to public schools, which wereforced by law to accept all students whoregistered (Cox and Lemaitre 1999; Parry1996).

The Chilean voucher system has been inplace for more than 20 years. Since democra-tic rule was reestablished in 1990, the Center-

Figure 1. Primary and Secondary Enrollment, by School Sector: Chile 1981–99Source: Ministry of Education Chile (2000).

Figure 2. School Sector Attended, by Income Decile: Chile 1990 Source: Author's calculations based on 1990 CASEN survey (Chilean Ministry of Planning)

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Left coalition in power has focused on chan-neling additional resources to “vulnerable”schools, increasing real educational spendingand teachers’ salaries, and financially reward-ing schools with the highest test scores (Hsiehand Urquiola 2003; Mena and Bellei 2000).Nevertheless, the core of the privatization sys-tem—the per-student voucher payment andthe freedom to attend any school—has beenleft intact.

The privatization reform also affected thetertiary level. Since 1980, the governmenthas promoted the expansion of the tertiarylevel via private, fully paid institutions(Brunner 1994; Nuñez 1997). Many of theseinstitutions do not require scores on thenational university admissions test (analogousto the SAT), which is obligatory in public uni-versities. Expansion based on private institu-tions was considerable. Gross tertiary enroll-ment grew from 8 percent of the relevant agepopulation in 1982 to 20 percent in 1997.The number of institutions increased dramat-ically from 8 to almost 300, and the propor-tion of students who attended private tertiaryeducation expanded from 30 percent to 55percent (Ministry of Education Chile, severalyears). In addition, the privatization reformintroduced fees to the previously free publicuniversities, increasing the cost of tertiaryeducation (in 2001, the average annual feewas approximately two thirds of the medianChilean household income). This combina-tion of fees in public institutions, plus theexpansion of the system based on expensiveprivate institutions, may have reduced thechances of lower-class individuals gainingaccess to tertiary education.

Finally, it is important to consider the con-text in which the privatization reform tookplace. This context was marked by a deepeconomic crisis—the deepest in the countrysince the Great Depression—in the late 1970sand early 1980s. The recession further weak-ened the social safety net, producing a signif-icant increase in poverty and inequalitythroughout most of the 1980s (Edwards andCox-Edwards 1991; Larranaga 1999; Marceland Solimano 1994; Meller 1991). This diffi-cult economic context may have intensifiededucational inequality by forcing less-advan-taged families to withdraw children from

school to supplement the family income—aphenomenon that is well known in the devel-oping world (Behrman, Birdsall, and Szekely2000; Moser 1998). The effect of the eco-nomic crisis on the poor should be morenoticeable at the secondary and tertiary edu-cational levels because primary education wascompulsory throughout the period understudy. On the basis of international findings,the null hypothesis for this research is thatthere has been persistent inequality over timein spite of the expansion and reform of theChilean educational system. However, if theeconomic crisis of the 1970s and 1980sdepressed the educational opportunities ofthe lower classes, an increase in inequalitymay be found. Furthermore, if the privatiza-tion reform provided relative benefits to thosewho migrated to voucher schools, an increasein qualitative inequality associated withschool sector may be found. These hypothe-ses are addressed in the analysis. Before Imove to the analytical section, I present thedata and methods.

DATA AND METHODS

Data

The data that were used in this analysis camefrom the 2001 Chilean Social Mobility Survey(CMS). The CMS is a nationally representa-tive, multistage, stratified sample of 3,544male heads of households aged 24–69. Themain objective of the survey was to studyoccupational and educational mobility incontemporary Chilean society.6 The samplingstrategy included three stages. First, 87 pri-mary sampling units (PSUs), called comunas(counties), were selected. Blocks within PSUswere then selected, and finally householdswithin blocks were chosen. Counties werestratified by size (less than 20,000,20,000–100,000, 100,000–200,000, andmore then 200,000 inhabitants) and geo-graphic zone (North, Center, South). Optimalallocation was used to increase efficiency byincluding all PSUs in the large stratum (morethan 200,000 inhabitants) in the sample. Thefieldwork was conducted between April and

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June 2001 and consisted of face-to-face inter-views in the respondents’ households bytrained personnel. The CMS includes infor-mation about family structure; detailed infor-mation about the occupation, education,income, and living standards of the head ofthe household and his partner; and retro-spective information about the parents ofboth members of the couple.

The sample was weighted to bring theproportions of various strata into agreementwith their representation in the population.The weighting scheme used population pro-jections that were based on the 1992 Chileancensus. Excluding the households that werenot eligible for the survey, the response ratewas 63 percent.7 Nonresponse can yield biasif those who were unreachable or refused toparticipate are significantly different fromthose who were included in the sample.Nonresponse bias was not corrected owing tothe lack of information on the cases that werenot obtained. To estimate the magnitude ofthe bias, I compared descriptive statisticsbetween the CMS and the CASEN 2000Survey. CASEN is a large survey (N = 252,595)conducted by the Chilean Ministry ofPlanning, similar to the Current PopulationSurvey in the United States, and has a refusalrate that is lower than 10 percent. The com-parison (available from me on request) sug-gests that the CMS slightly underrepresentsagricultural workers and individuals in theupper end of the status hierarchy. Overall,however, there is no indication of major non-response bias. Missing cases represent 4 per-cent to 12 percent for different variables. Iimputed the missing cases using a multipleimputation algorithm developed by King etal. (2001). This method uses an estimation-maximization procedure to create five com-plete data sets that are analyzed using stan-dard statistical procedures, and parametersand standard errors are then combined. Thistechnique assumes that data are missing atrandom. If the assumption is met, the proce-dure results in valid statistical inferences,which reflect the uncertainty that is due tomissing values, and provide consistent andasymptotically efficient estimates (Allison2002).

Methods

The main objective of this article is to evalu-ate the change in the effect of social back-ground on educational attainment over timein Chile, with a focus on the changes that fol-lowed the privatization reform of the early1980s. One way to do so is to use standardlinear regression models. However, as Mare(1980, 1981) stated, the ordinary least-squares (OLS) coefficients reflect not only thelevel of association, but the variance in edu-cational attainment. Because the variancechanges over time, given the expansion ofthe educational system, comparison of OLScoefficients over time will not reveal whetherthe structural parameters that regulate theprocess of educational attainment havechanged (Lucas 2001:1645). An alternative isto formulate educational attainment as a setof subsequent transitions and to measuresocial background effects using logit models.In contrast to OLS, logit coefficients reflectthe net association between background andeducational continuation decisions, unconta-minated by the variance of education.8

I formulated educational attainment as aseries of transitions. The data enabled me tomodel four transitions: T1 (completion of pri-mary education), T2 (entry to secondary edu-cation), T3 (graduation from secondaryschool), and T4 (entry to tertiary education).To analyze change in social backgroundeffects over time, I distinguished seven birthcohorts: Cohort 1 (C1): 1936–44, Cohort 2(C2): 1945–49, Cohort 3 (C3): 1950–54,Cohort 4 (C4): 1955–59, Cohort 5 (C5):1960–64, Cohort 6 (C6): 1965–69, andCohort 7 (C7): 1970–76. Reducing the analy-sis to the cohorts who were born between1936 and 1976 yielded a weighted sample of3,244. The selection of cohorts was driven bysubstantive interest in assessing the impact ofthe changes in the Chilean educational sys-tem. Figure 3 shows the educational trajecto-ry of each cohort. The seven horizontal blocksidentify the seven cohorts, and the diagonalblock represents their educational careers.Figure 3 should be read horizontally. Forinstance, starting from the bottom (the oldestcohort), the figure indicates that the oldestmembers of the oldest cohort were born in

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326 Torche

1936, entered primary education in 1942,and graduated from college (if he attendedcollege) in 1957. Note that there is a changein the length of primary schooling in 1965,reflecting the extension of compulsory prima-ry education from six to eight years.

As Figure 3 indicates, C1 attended schoolin the 1940s and 1950s. The educationalexperience of C2 and C3 took place mostly inthe 1960s. C4 and C5 attended primaryschool largely in the 1960s and secondaryschool in the 1970s and thus experienced anew compulsory primary education of eightyears and may have benefited from the edu-cational expansion of the 1960s. C5 were thefirst to experience part of their educationaltrajectory in the 1980s, after the privatizationreform was launched, but only partially, at thecollege level. Members of C6 were moreaffected by the privatization reform, fully intheir college education and partly in their sec-ondary schooling. Only C7, the youngestcohort, experienced their entire educationaltrajectory under the new, privatized system ofeducation.

Following the protocol for the comparativeanalysis of educational stratification intro-duced by Shavit and Blossfeld (1993), I usedfather’s education and father’s occupationalstatus when the respondent was aged 14 asmeasures of parental resources. In addition, Iincluded mother’s education, shown to havea significant impact on educational attain-

ment in the developing world (Filmer 1999;Montgomery and Lloyd 1998; Thomas,Schoeni, and Strauss 1996). Father’s andmother’s education were measured as thenumber of years of schooling completed.Father’s status was measured by the interna-tional socioeconomic index (ISEI)(Ganzeboom, de Graaf, and Treiman 1992).Because one of the objectives of this studywas to explore the qualitative dimension ofinequality, I included school sector attendedby the student at the primary and secondarylevels (depending on the transition beinganalyzed) as an explanatory variable. I distin-guished private-paid school, voucher school,and public school. Arguably, other variablesthat are not included in the models affecteducational attainment—rural/urban resi-dence, number of siblings, and family struc-ture, among others. However, given that themain objective of this research was not toestimate the net effect of each individualbackground factor, but to evaluate the overalldynamics of intergenerational inequality ineducational attainment, the use of thesethree standard indicators of socioeconomicbackground is granted. Table 1 presents thedescriptive statistics of the variables that wereincluded in the analysis by birth cohort.

As is shown in Table 1, there was a signifi-cant upgrade in educational attainment andsocial background across cohorts. Thisupgrade supports the use of logit models of

Figure 3. Educational Career, by Birth Cohort

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educational transitions, insensitive to the vari-ance of dependent and independent vari-ables.

I present the analysis in two steps. In thefirst step, I report the effect of social back-ground on the probability of making eachtransition using logit models. To measurechanges over time, I enter cohorts as dummyvariables and an exhaustive set of interactionsbetween the set of cohort dummy variablesand each background variable—father’s edu-cation, mother’s education, and father’s occu-pational status. These interactions identifycohort-specific effects of each social back-ground variable and produce a set of (C-1)interactions for each social background vari-able (where C is the total number of cohorts).To simplify matters, I follow Gerber’s (2000)strategy of estimating separate models foreach transition, rather than pooling the dataacross transitions.

The model selection strategy follows theapproach described by Gerber and Hout(1995). I choose the highest or lowest coeffi-cient in each set of the (cohort * social back-ground variable) interactions as the referencecategory to evaluate the statistical signifi-cance of the remaining coefficients. If none of

the dummy interaction terms capturing thechange in the effect of social backgroundacross cohorts is significantly different fromthe reference category, there is no significantchange in the effect being tested acrosscohorts. For example, the potential change inmother’s education on the probability ofmaking T1 is evaluated by creating a set ofseven interactions: ME*C1 through ME*C7.Then, the interaction term with the lowestcoefficient is excluded and used as the refer-ence category. If, as is the case, none of theremaining six interaction terms is significantlydifferent from zero, it indicates that the effectof mother’s education does not significantlychange across cohorts, so I can express itusing the main effect of mother’s educationonly. After I remove nonsignificant interac-tions, I reformulate each significant set ofinteraction terms as a single ordinal multiplierfor the relevant social background effect, toobtain a more parsimonious model. Forexample, as will be seen shortly, the effect offather’s education on T1 significantly changesacross cohorts. Using the same seven-dummymethod as with mother’s education, I foundthat the coefficients associated with the inter-action terms FE*C5 and FE*C6 are the small-

Table 1. Descriptive Statistics: Means and Standard Deviations of Variables AcrossCohorts, Chilean Men Born 1936–76

Variable C1 C2 C3 C4 C5 C6 C7(1936–44) (1945–49) (1950–54) (1955–59) (1960–64) (1965–69) (1970–76)

Years of schooling 7.6 8.9 10.1 10.8 11.0 11.1 11.6(SD) (4.5) (4.6) (4.4) (3.9) (3.9) (3.7) (3.5)

Father’s education 5.4 5.9 5.9 6.8 7.1 7.0 7.5(SD) (4.6) (4.5) (4.6) (4.7) (4.7) (4.6) (4.5)

Mother’s education 4.7 5.1 5.4 6.4 6.8 6.5 7.2(SD) (4.1) (4.1) (4.1) (4.4) (4.3) (4.3) (4.4)

Father’s occupational status 29.7 31.1 31.9 32.6 33.1 32.3 31.9

(SD) (12.0) (12.8) (13.5) (13.6) (12.3) (12.6) (13.9)

Public schoola 76.1 77.2 77.4 77.1 71.6 65.4 63.6Private-voucher school 11.2 10.7 10.8 11.3 18.2 23.6 24.2Private-paid school 12.7 12.1 11.8 11.6 10.2 11.0 11.9

Number of cases 584 464 453 481 474 430 358

aSchool sector percentages refer to the secondary education level.

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328 Torche

est and not significantly different from eachother, the coefficients associated with FE*C1,FE*C2 and FE*C3 are larger and not signifi-cantly different from each other, and thecoefficients associated with FE*C4 and FE*C7are the largest and not significantly differentfrom each other. The best-fitting specificationof these differences is an ordinal one thatinteracts father’s education with an ordinalvariable coded 0 if cohort = C5 or C6; 1 ifcohort = C1, C2, or C3; and 3 if cohort = C4or C7. These ordinal respecifications are com-pared with the original, less parsimonious,specification using the BIC statistic (Raftery1995). If the fit of the more-parsimoniousmodel is not significantly worse, I choose themore parsimonious ordinal specification.9 AsWong (1994) demonstrated on the basis of aMontecarlo study, differences in BIC of lessthan 5 points should be seen as indetermi-nate. Therefore, to be selected, the less-parsi-monious model has to have a BIC value atleast 5 points lower (lower values indicate abetter fit in the BIC metric) than the moreparsimonious model. The preferred modelfrom this procedure is the one that capturesonly substantively significant changes insocial background effects over time, and it ispresented for each educational transition inAppendix Table A as Model 1.10

In the second step, I include the kind ofschool attended by the respondent, distin-guishing private-paid, voucher, and publicschools. School sector is not a backgroundvariable, but an institutional factor that mayoperate as a mediator of family resources oras an additional vehicle of educational stratifi-cation. Therefore, including school sector in aseparate step allows me to evaluate whetherthis variable adds to or mediates the effect ofsocial background on educational attain-ment. To evaluate changes that are associat-ed with school sectors across cohorts, I usethe same technique described for Step 1. Thepreferred model of background and school-sector effects is presented in Appendix TableA as Model 2 for each educational transition.

A note on the use of cohort analysis tostudy trends over time is in order. As is wellknown, cohort analysis conflates life-cycle,period, and cohort effects (Ryder 1965). Theconfounding impact of life-cycle differences

can be removed by tracing members of eachcohort back to the time when they entered orcompleted each level of schooling (Szelenyi1998:29). However, cohort analysis does notallow me to distinguish period from cohorteffects.11 This is a standard limitation inresearch on trends in educational stratifica-tion, which recommends caution in the inter-pretation of results, especially in the evalua-tion of policy effects. Therefore, as I previous-ly stated, the focus of this article is not onconclusively asserting causal mechanisms thatlead to observed outcomes, but on present-ing a descriptive analysis of trends in inequal-ity and of the role played by school sector ineducational stratification and formulatingempirically grounded, historically informedhypotheses about causal processes.

ANALYSIS

Changing Transition Rates

The expansion of the Chilean educational sys-tem in the past few decades can be assessedin the CMS by tracing the educational attain-ment across cohorts. Figure 4 displays theeducational attainment of each cohort andsuggests a significant increase over time. Thefastest improvement took place from C1 toC4; then there was a plateau for C5 and C6,whose educational experience took placemostly in the 1970s and 1980s; and a newgrowth for the youngest cohort (C7), whoseschooling career took place in the 1980s and1990s.

The cohort-specific transition rates displayeducational expansion in a new light. Figure5 presents the rates for each transition, con-ditional on having made the previous one,and shows increasing educational attainmentacross cohorts at the primary and secondarylevels (T1, T2, and T3). The picture is differentat the tertiary level (T4), where there is noexpansion across cohorts in college entryconditional on secondary graduation, with arelatively flat transition rate of about 48. Thistrend has also been found in the UnitedStates (Hout, Raftery, and Bell 1993) and doesnot indicate that the absolute rate of entry

03. Torche 10/3/05 11:31 AM Page 328


into tertiary education remained constantacross cohorts. Rather, tertiary education sig-nificantly expands over time, pushed byexpansions at lower levels in the system.What this pattern suggests is that havingcompleted secondary education in greaternumbers than before, the increasingly largerpool of high school graduates faces a con-stant hurdle at the college level. In sum,Figure 5 suggests that the expansion of theChilean educational system has been largelydriven by growth at lower educational levels.

Change In EducationalStratification Over Time

With this background information, I move tothe core of the analysis. As a first step, I eval-uate the change across cohorts in the effect ofsocial background on the probability of mak-ing each of the subsequent transitions.Models 1 in Table 2 display this change,obtained from the preferred logit model foreach educational transition (presented inModels 1 in Appendix Table A).

Figure 4. Educational Attainment, by Birth Cohort: Chilean Men Born 1936–76

Figure 5. Educational Transition Rates, by Birth Cohort: Chilean Men Born 1936–76

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330 TorcheTa

ble

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03. Torche 10/3/05 11:31 AM Page 330


Before I move to the interpretation, aword is necessary on how the coefficients inTable 2 were obtained. For example, withregard to the change in the effect of father’seducation on the first educational transition(completion of primary school), this effect isnot significantly different from zero in C5and C6 (-.013), as indicated by the maineffect of the variable in Model 1 for T1 inAppendix Table A. Appendix Table A alsoincludes the ordinal multiplier FE*CohortTrend T1 , which captures a linear increase inthe effect of father’s education from its base-line value in C5 and C6; to .082 [-.013 +(1*.095)] for C1, C2, and C3; and to .117 [-.013 + (2*.095)] for C4 and C7. All coeffi-cients in Table 2 were obtained by combin-ing the baseline effect of the social back-ground variable with the interaction termscapturing changes over time.

The first thing to notice in Models 1 inTable 2 is the minor change in social back-ground effects across cohorts. Social back-ground effects change only in the two earliertransitions, primary completion and sec-ondary entry. In T1, there is a change overtime in the influence of father’s education andfather’s occupational status. The influence offather’s education is the largest in C4 and C7;smaller but still significant in C1, C2, and C3;and insignificant for C5 and C6. The effect offather’s occupational status follows thereverse trend: It is the smallest in C4 and C7;larger for C1, C2, and C3; and the largest forC5 and C6.

This finding suggests that the two effectsmay counteract each other to yield an overalloutcome of no change across cohorts. Themagnitude of these effects cannot be immedi-ately compared because the variables have dif-ferent measurement units, but I obtained arough equivalence by standardizing the coeffi-cients. The standardized effects are .442 forfather’s education (SD FE = 4.65) and -.415 forfather’s occupational status (SD FS = 12.96).Therefore, the magnitude of the standardizedeffects is similar and opposite in sign, whichsuggests no change across cohorts in educa-tional stratification at the primary completionlevel.

The analysis of trends in social back-ground effects on T2 (entry to secondary

education) indicates that the only effect thatvaries is that of father’s education. The effectis the lowest for C2, C3, C4, and C5; largerfor C1; and the largest for C6 and C7, sug-gesting an increase in educational stratifica-tion for the two youngest cohorts. Nochange in social background effects is foundin the two higher transitions—completion ofsecondary education and entry to tertiaryeducation.

In sum, the results of the educational transi-tion model indicate little variation in the effectof social background across cohorts in Chile, inspite of the major educational expansion andreform of the educational system, with oneexception. The only significant change acrosscohorts is that of the effect of father’s educationon the probability of entering secondary school(T2). To show the magnitude of this increase ininequality, Figure 6 presents the predictedprobability of entering secondary school forthree hypothetical cases: children whosefathers have 1 year of schooling, 6 years ofschooling, and 12 years of schooling, with allother social background variables held at theirmeans.12 The figure indicates a decline in thesocioeconomic gap from C1 to C2, then a con-stant gap across educational levels through C5,followed by a significant increase in inequalityfor C6 and C7.

Even if it is not major, the growth in theeffect of father’s education is relevant becauseit suggests increasing inequality in the proba-bility of entering secondary school—a findingthat departs from the results of persistent ordecreasing inequality in international com-parative research. This finding speaks to theMMI hypothesis. If the advantaged classes aredefined as parents with 12 years of education(which represent approximately the top 10percent of the parental educational distribu-tion), the Chilean trends indicate that ratherthan declining, inequality increased after theadvantaged classes reached saturation (fromC6 to C7).13 Therefore, the Chilean case doesnot support the MMI hypothesis and suggeststhat inequality may be driven by factors otherthan saturation of the advantaged classes.

What can these factors be? C6 and C7transitioned to secondary education in themidst of the market-oriented reform in a con-text of a deep economic crisis (see Figure 3).

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332 Torche

The observed trend suggests that dire eco-nomic conditions, coupled with the retrench-ment of the social safety net, may havecaused growing educational stratificationeven as the educational system was expand-ing. Note also that according to Figure 6, thegrowth in inequality was driven by losses bythe least-advantaged classes, not by gains bythe most-advantaged ones. This finding isconsistent with the hypothesis that the grow-ing cost of education, in the form of foregoneearnings, may have induced some children inthe poorest families to drop out of school atan early stage of their educational careers toenter the labor market and supplement theirhouseholds’ incomes.

If the analysis of the Chilean case consid-ered only quantitative inequality, the conclu-sion would be that the Chilean results are inline with the finding of persistent inequality inmost countries of the world, with the excep-tion of a noteworthy increase in inequality inT2, evidenced in losses of the most disadvan-taged classes, probably driven by growingpoverty and inequality in the context of aretrenchment in the safety net.

However, as EMI suggests, there may havebeen changes in qualitative inequality in theperiod under study. Specifically, the shockthat was introduced by the privatization

reform may have induced inequalities thatwere associated with different kinds ofschools. For instance, the creaming thatresulted from the voucher system in the1980s may have resulted in growing benefitsassociated with switching from public tovoucher schools or, alternatively, with lossesfor those who remained in the public system.Also, the reduction of the educational budgetby the military regime may have led to awidening of the gap in attainment betweenpublic and voucher schools that werefinanced by the government and private-paidschools that were funded by private tuition.To explore these hypotheses, I add schoolsector to the educational transition models asa predictor of educational attainment. Severalstudies of the Chilean educational systemafter the privatization reform have attemptedto evaluate the relative efficiency of differentschool sectors at an individual level, usuallymeasured in terms of students’ test scores(e.g., Carnoy and McEwan 2001; Contreras2001; McEwan and Carnoy 2000; Mizala andRomaguera 2000; Sapelli 2003). This is notthe objective of this article. My objective ismore basic: to explore if there were changesacross cohorts in the benefits of attending dif-ferent school sectors.

To explore this question, I add school sec-

Figure 6. Predicted Probability of Entering Secondary Education (T2) for Children withFathers with 1, 6, and 12 Years of Schooling Across Cohorts: Chilean Men Born 1936–76Note: Obtained from Model 1, Transition 2, in Appendix Table A. All social background vari-ables with the exception of father’s education were held at their means.

03. Torche 10/3/05 11:31 AM Page 332


tor in Models 2 in Table 2 to the social back-ground variables presented in Models 1 andevaluate the changes over time in the advan-tages of attending public, private-voucher,and private-paid schools. I enter school sec-tors as a set of dummy variables, with publicschool as the reference category. Coefficientsare obtained from the preferred logit modelof social background and school-sectoreffects presented in Models 2 in AppendixTable A. This formulation permits the assess-ment of the attainment gap across differentschool sectors and of any change in this gapacross cohorts. In addition, by comparing thecoefficients of social background variableswith the coefficients presented in the compa-rable Models 1, I am able to evaluate theextent to which the school sector attendedmediates the effect of social background vari-ables.

Models 2 in Table 2 indicate that the ben-efits that are associated with different types ofschools are similar for the first two transitions(completing primary education and enteringsecondary school). In both transitions, stu-dents in private-voucher and private-paidschools do significantly better than do publicschool students, and in both cases the gainsthat are associated with private-paid schoolare larger, although the difference is not sta-tistically significant (χ2 tests for the difference:p = .22 and p = .26, respectively). Moving tothe focus of this analysis, the evaluation oftrends, in both cases the effects of school sec-tors do not vary across cohorts.

The pattern is different for T3. When theprobability of graduating secondary educa-tion is analyzed, the advantages that are asso-ciated with private-paid school and voucherschool relative to public school change acrosscohorts. The benefit of attending private-paidschool is the smallest in C2 and C3; greater inC1 and C4; and the greatest in C5, C6, andC7—the cohorts who were at risk of complet-ing secondary education in the late1970s,1980s, and early 1990s. This findingsuggests that Chileans who were able to payfor private education got the most for theirmoney in the cohorts who completed sec-ondary schooling during and after the mar-ket-oriented transformation. Because the pri-vatization reform did not directly alter pri-

vate-paid schools, this increase in stratifica-tion is likely to be associated with the grow-ing poverty and inequality and the reductionof the educational budget in the 1980s,rather than with the institutional reorganiza-tion of the educational system brought aboutby the privatization reform. In other words,private school students experienced relativegains because they were not dependent onthe underfunded public system.

The most impressive trend is, however, thechange across cohorts in the effect of attend-ing private-voucher schools on T3, secondaryschool graduation. The effect of voucherschool is slightly negative in C1 and is not dif-ferent from public school for C2–C6. Thisfinding is not surprising, given the differentnature of private-voucher schools as charityinstitutions before the privatization reform.The positive effect of attending voucherschools surged for the youngest cohort (C7),who were the most affected by the privatiza-tion reform. In other words, attending a pri-vate-voucher school, rather than a publicschool, paid off significantly more in terms ofeducational attainment after the Chilean edu-cational reform that introduced a vouchersystem of financing.

To provide a more graphical picture of thedifferential attainment across school sectorsbefore and after the privatization reform, I fol-low the same strategy as presented in Figure6. Figure 7 presents the predicted probabilityof graduating secondary school acrosscohorts for children attending private-paidschools, voucher schools, and public schools,holding all social background variables con-stant at their means.

Figure 7 depicts the probability of graduat-ing secondary school for an “average student”who attended public, private-voucher, andprivate-paid schools across cohorts. In the ear-liest cohort (C1), public school students per-formed better than did those in private-voucher schools. For C2–C6, the statisticallyinsignificant advantage that is associated withprivate-voucher over public school remainedconstant. A new development affected theyoungest cohort: Students who attended thenewly implemented voucher schools caughtup to and drastically surpassed those attend-ing public schools. According to Figure 7,

03. Torche 10/3/05 11:31 AM Page 333

334 Torche

members of C7 who attended a voucherschool had a 90 percent chance of graduatingfrom high school, compared with only 73 per-cent for those who attended a public school.This jump in the attainment of voucher-schoolstudents occurred precisely for the cohortwho was the most affected by the privatiza-tion reform (see Figure 3). Even if no causalinferences can be made from a cohort analysisof a cross-sectional study, the sharp increase inthe advantages that are associated withvoucher schools suggests that the segmenta-tion of students across school sector that fol-lowed the privatization reform became a vehi-cle for the reproduction of educationalinequality. Last, there was no change acrosscohorts in the benefits associated with private-paid and voucher schools for T4 (entry to ter-tiary education).

The analysis also allows me to explore towhat extent the beneficial effect of attendingvoucher schools mediates or adds to theeffect of social background. As Figure 2 indi-cates, there is high segmentation of schoolsector by income in Chile: The lower- andmiddle-income sectors attend public schools,the middle- and upper middle-income sectorsattend private-voucher schools, and themost-advantaged sector pays for privateschools. Therefore, it may be that school sec-tor mediates only the effect of social back-

ground on educational attainment. A com-parison of the social background coefficientsbetween Models 1 and 2 of Table 2 (beforeand after school sector was controlled) revealsthat the coefficients diminished only margin-ally in value after school-sector variables wereentered in the models—a decline of approxi-mately 15 percent. This finding suggests thatschool sector adds to more than mediates theeffects of social background in Chile.

DISCUSSION AND CONCLUSIONS

I return now to the themes raised in the intro-duction. Has inequality of educational oppor-tunity changed during the past few decadesin Chile? If so, are these trends related tochanges in the structure of the Chilean edu-cational system, specifically to the privatiza-tion of education by the authoritarian regimein the 1980s? What are the implications ofthis case study for the comparative analysis ofeducational stratification?

To address these questions, I examined theprobability of making four subsequent educa-tional transitions for different socioeconomicgroups across cohorts. The analysis revealedthat the Chilean case is in line with findings inmost countries of the world: There was littlechange in educational stratification across

Figure 7. Predicted Probability of Graduating Secondary School Across Cohorts, bySchool Sector Attended Across Cohorts: Chilean Men Born 1936–76Note: Obtained from Model 2, Transition 3, in Appendix Table A. All social background vari-ables held at their means.

03. Torche 10/3/05 11:31 AM Page 334


cohorts, in spite of significant educationalexpansion and radical educational reform.Persistent inequality does not fully apply tothe Chilean case, however. Two departuresare particularly important. First, the analysisdetected a rise in the effect of father’s educa-tion on the probability of entering secondaryschooling for the two youngest cohorts, sig-naling an increase in inequality. The increasein inequality questions MMI because it tookplace precisely as the advantaged classeswere reaching saturation for this particulareducational transition. Furthermore, thegrowth in inequality was driven by losses bythe least-advantaged classes, rather than bygains by the most privileged. What canexplain this increase in inequality? It affectedthe cohorts who experienced the transition tosecondary education during the late 1970sand 1980s, a period in which the retrench-ment of the safety net, coupled with an eco-nomic crisis, resulted in growing unemploy-ment, poverty, and inequality. A plausibleexplanation is therefore the increasing cost ofnoncompulsory education for the least-advantaged families, which may have pushedchildren out of the educational system andinto the labor market.

Growing inequality is a noteworthy findingbecause it departs from trends of persistent ordeclining inequality that have been found ininternational comparative research and raisesan important question: Is persistent inequali-ty as universal as researchers currentlybelieve? Or is it partly an artifact of the biasedpool of countries—mostly industrialized—where studies of IEO trends have been con-ducted? Given the economic decline andmarket reform experienced by most LatinAmerican and other developing countriesduring the 1980s and 1990s, it is reasonableto hypothesize that these trends may have ledto a growth in educational inequality similarto or greater than that reported for Chile.Only research using fresh data from countriesbeyond the industrialized core will addressthis question and shed light on potentiallyimportant mechanisms that drive educationalstratification.

Second, this article has also exploredschool sector as a source of qualitativeinequality, specifically the advantages that are

associated with private-voucher and private-paid schools after the privatization reform ofthe 1980s. The analysis found that attainmentwas significantly different across school sec-tors. In general, students of private-paidschools fared better than did those whoattended private-voucher schools, who, inturn, had higher attainment than those whoattended public schools. More important, theanalysis detected a significant change acrosscohorts, with an increase in inequality for theyounger cohorts. On the one hand, the ben-eficial effect of attending private-paid schoolsseems to have increased for those cohortswhose educational careers occurred duringand after the market transformation. Thisfinding indicates that the payoff of a family’sfinancial investments in education in the formof private-school tuition has grown in recentdecades in Chile. On the other hand, theanalysis shows a large improvement in thechances of graduating from secondary schoolfor voucher-school students relative to publicschool students for C7, the cohort who werethe most affected by the privatization of edu-cation. Naturally, this does not mean that thevoucher sector that emerged after the privati-zation reform created educational inequality,but it does mean that this sector became arelevant arena in which inequality was actual-ized and reproduced.

The analysis also shows that school sectoradds to, rather than mediates, the effect ofsocioeconomic status on educational attain-ment. This finding raises important questions.One of the most pressing inquiries thatemerges from the growing gap between pri-vate-voucher and public school students inChile is about the mechanisms that drive thisbreach. On the basis of the current literature,several nonexhaustive mechanisms may besuggested. One of them is a selection effect:unmeasured characteristics related to educa-tional outcomes, such as motivation, ability, orsocial networks, that may be higher amongthose who migrate to the voucher system thanamong those who stay in public schools.Another possible mechanism is peer effectsresulting from school sorting (Cullen, Jacob,and Levitt 2005; Fiske and Ladd 2000; Hsiehand Urquiola 2003; Martinez, Godwin, andKemerer 1996). Yet another is any type of orga-

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336 Torche

nizational feature of voucher schools thatmakes them function better, such as a more-challenging academic environment (Witte1992, 1996), “communal organization” (Bryket al. 1997), or more-autonomous manage-ment (Chubb and Moe 1998). Exploring thepotential impact of these mechanisms—or anyother force that drives the growing inequalityacross school sectors—is beyond the scope ofthis article. The evidence presented here, how-ever, forcefully suggests that the institutionalorganization of the educational system is a rel-evant, distinct source of qualitative inequalityand that much would be gained by its carefulexamination in other national contexts.

This study of trends in educational stratifi-cation in Chile has uncovered some similari-ties and some departures from the industrial-ized world—similarities, because in most tran-sitions, persistent inequality fits the Chileancase well, and departures, because growinginequality, which is likely to be related to theeconomic crisis and privatization of educa-tion, was found. Only more time and freshdata will allow for the confirmation of thesefindings. I hope that this analysis has servedas a baseline to which future studies of Chileand other developing countries can refer.

NOTES

1. Despite the significant attention givento charter schools, educational vouchers, andother forms of educational privatization, theycurrently enroll a small number of students inthe United States. In 2000, charter schoolsrepresented 0.09 percent of total primary andsecondary enrollment. With regard to vouch-er programs, only four states have operationalvoucher programs, and they serve a total ofapproximately 27,000 students (NationalCenter for the Study of Privatization inEducation 2005a, 2005b).

2. But see the studies that have exploredthe links between increasing competitionfrom private schools and public school quali-ty using school districts or other geographi-cally bounded areas as units of analysis (e.g.,Arum 1996; Dee 1998; Hoxby 1994).

3. I thank one anonymous reviewer forhighlighting this point.

4. Some analysts have described theChilean system as a “charter school” model ofeducational provision (see, e.g., Welsh andMcGinn 1999). However, the Chilean privateschools that are supported by public funds donot fulfill the essential characteristic of charterschools, namely, that they negotiate a con-tract (charter) with an authorized public bodythat is designed to be unique in its focus orstudent clientele.

5. In Chile these schools are called privatesubsidized schools because of the per-studentsubsidy they receive from the government.

6. The survey includes only men under theassumption that the dynamics of mobilityvary significantly across genders, and becauseof the moderate sample size, it would not bepossible to conduct a separate analysis ofwomen. The survey excludes men who arenot heads of households, who represent 17percent of the male population of the rele-vant age (Mideplan 2000), 86.5 percent ofwhom are the sons of heads of the house-holds, 12.4 percent of whom are other rela-tives of the heads, and 1.1% of whom areother nonrelated men. Their occupational dis-tribution, once age is controlled, is almostidentical to that of heads of households. Thesmall proportion represented by this groupand their similar occupational distributionsuggest that their inclusion would not signifi-cantly alter the findings presented here.

7. Nonresponse rates are usually notreported in Chilean surveys. Correspondencewith Chilean experts indicated that nonre-sponse is usually about 20–25 percent forface-to-face household surveys of individualsaged 18 or older. The higher nonresponserate of the CMS is due to the difficulty in con-tacting male heads of households.

8. See Cameron and Heckman (1998) for acritical evaluation of the “educational transi-tion” approach and Lucas (2001) for aresponse to that critique.

9. Note that these ordinal specificationsassume a linear change across cohorts in theeffect of the social background variable. Eventhough I could not ascertain if the change isstrictly linear, the fact that the specificationyields the best-fit model supports their selec-tion.

10. It should be emphasized that the term

03. Torche 10/3/05 11:31 AM Page 336


effects is used here as shorthand for partialassociation and does not imply causal attribu-tion.

11. Alternative ways to distinguish amongcohort, period, and life-cycle interpretationsof change require the use of panel data orrepeated cross sections, which are unavailablefor the Chilean case.

12. The predicted probability wasobtained from the logit regression model.The logit transformation can be interpreted asthe natural logarithm of the odds of successand can be expressed as follows: yik = ln{pik/1-pik}Σβjxij, where pik represents the conditionalprobability than individual i will completetransition k, given completion of the previoustransition k-1; xij are the variables that linear-ly influence the log-odds; and βj are parame-ters to be estimated from the data. A featureof the logit model is that the rate of change

in pik with respect to a change in xij is givenby: δpik/δxij = βj pik(1-pik) (Mare 1981). Thisimplies that the partial effect of a change in xon the transition probability is maximal at p =.05, where it equals .25*β. As the baselineprobability moves further from .05 in eitherdirection, the effect of a one-unit change in xdecreases (Gerber 2000).

13. The MMI hypothesis relies heavily onthe notion of advantaged classes, but it doesnot clearly define who belongs to theseadvantaged groups. The lack of a strict defin-ition introduces arbitrariness to the analysisand makes international comparison difficult.To address this limitation, alternate definitionsof advantaged classes—as children whosefathers have 14 and 16 years of education, aswell children of parents with top-decile edu-cation and occupational scores—were used inthis analysis. The findings are insensitive tothe definition that was used.

03. Torche 10/3/05 11:31 AM Page 337

338 TorcheA

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03. Torche 10/3/05 11:31 AM Page 338


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Florencia Torche is an Assistant Professor of Sociology at Queens College, City University of New York,and a Research Associate at the Center for the Study of Wealth and Inequality, Columbia University. Herresearch focuses on the processes of the reproduction of inequality in the occupational, educational, andwealth spheres in different national contexts. She is currently completing a book manuscript entitled“Inconsequential Mobility: The Chilean Case in Comparative Perspective.”

This research was supported by Grant 1040-1239 from the Ford Foundation to the Center for the Studyof Wealth and Inequality, Columbia University, and by Grant 1010474 from the Chilean NationalCenter for Science and Technology FONDECYT. I would like to thank Peter Bearman, Theodore Gerber,Nicole Marwell, Carolina Milesi, Seymour Spilerman, Donald Treiman, Christopher Weiss, and partici-pants in a variety of settings in which this work has been presented for their helpful comments and sug-gestions. Direct correspondence to Florencia Torche, CWI-ISERP, Columbia University 420 West 118thStreet, 805B, New York, NY 10027; e-mail: [email protected].

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