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Apples and Oranges:Educational Enrollment and

Attainment across Countries in Latin America and the Caribbean

Miguel Urquiola Valentina Calderón Authors

INTER-AMERICAN DEVELOPMENT BANK • REGIONAL POLICY DIALOGUE

Integration and Regional Programs DepartmentSustainable Development Department

Inter-American Development BankRegional Policy Dialogue

1300 New York Avenue, N.W. • Washington, D.C. 20577Phone 202-623-2271 • Fax 202-312-4034

E-mail: [email protected] • www.iadb.org/int/drp

Education NetworkApples and Oranges:

Educational Enrollment and Attainment acrossCountries in Latin America and the Caribbean

Authors

Miguel UrquiolaColumbia University

Valentina CalderónInter-American Development Bank

January 2005

Integration and Regional Programs Department

Sustainable Development Department

INTER-AMERICAN DEVELOPMENT BANK

REGIONAL POLICY DIALOGUE STUDY SERIES

Technical and editorial comments on the document were provided by: Sergio Ardila, Niels Holm-Nielsen, Michele Lemay, Ricardo Quiroga, Diego Rodriguez, Michael Toman, and David Wilk.

The opinions expressed in this paper are the responsibility of the authors and do not necessarilyreflect the official position of the Inter-American Development Bank.

Cover: Shell-shaped pendant belonging to the Quimbaya prehispanic Society.Gold Museum Collection – Bank of the Republic, Colombia

January 2005

Additional copies of this publication can be obtained from:

Secretariat of the Regional Policy DialogueMail Stop W-0610Inter-American Development Bank1300 New York Avenue, N.W.Washington, D.C. 20577

E-mail: [email protected]: 202-623-2271Fax: 202-312-4034Web Site: http://www.iadb.org/int/drp

For useful feedback we thank Viola Espínola, Patrick McEwan, Juan Carlos Navarro, EmilianaVegas, and Aimee Verdisco. All remaining errors are ours only. Further, the views and interpreta-tions in this document are ours, and should not be attributed to the Inter-American DevelopmentBank, or to any individual acting on its behalf. Comments welcome: [email protected]@contractual.iadb.org

Inter-American Development Bank

Regional Policy Dialogue

The Regional Policy Dialogue was established in December 1999 by the initiative of the Board ofExecutive Directors. The objective was to create a forum of communication within the Bank toexpand and enhance dialogue among the countries in the region by sharing experiences, preparingthem to face the great challenges of globalization, and generating processes for regional coopera-tion. The Bank identified seven areas to be included on the Dialogue and created seven specializednetworks in which government officials at the Vice-Minister level from Latin America and the Car-ibbean, who are responsible for decision making and public policy design, participate.

1) Trade and Integration;2) Poverty and Social Protection Networks;3) Education and Human Resources Training;4) Macroeconomic and Financial Policy;5) Public Policy and Transparency;6) Natural Disasters Management; and7) Environment.

General CoordinationIntegration and Regional Programs DepartmentManager: Nohra Rey de Marulanda

Regional Technical Cooperation DivisionChief: Laura Bocalandro

Coordinator: María Carmenza McLean,Senior Specialist INT/RTC

SecretariatPabla Ayala and Rodrigo Salas, INT/RTC

Trade and Integration NetworkTechnical Coordinator: Robert Devlin, Deputy Manager INT/INT

Natural Disasters NetworkJanine Ferretti, Division Chief SDS/ENVTechnical Coordinator: Kari Juhani Keipi, Natural Resources Senior Specialist SDS/ENVTechnical Support: Victoria Imperiale

Education and Human Resources Training NetworkJuan Carlos Navarro, Division Chief SDS/EDUTechnical Coordinator: Viola Espínola, Senior Education Specialist SDS/EDUTechnical Support: Soledad Urrutia

Public Policy Management and Transparency NetworkTechnical Coordinator: Koldo Echebarría, Principal Public Sector Management Specialist SDS/SGCTechnical Support: Ingrid Carlson

Technical CoordinationSustainable Development DepartmentManager: Carlos M. Jarque

Legal DepartmentGeneral Counsel: J. James Spinner

Research DepartmentChief Economist: Guillermo Calvo

Environment NetworkJanine Ferretti, Division Chief SDS/ENVTechnical Coordinator: David Wilk, Senior Urban Environment Specialist SDS/ENVTechnical Support: Priscilla Stephan

Poverty and Social Protection NetworkCarlos Eduardo Velez-Echavarria, Division Chief SDS/POVTechnical Coordinator: Wanda Engel Aduan, Poverty Alleviation Specialist SDS/POVTechnical Support: Elba Luna

Macroeconomic and Financial Policy NetworkTechnical Coordinator: Eduardo Lora, Research Economist RESNorelis Betancourt, General Coordinator RES

STRUCTURE OF THE DIALOGUE

○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○

Apples and Oranges: Educational Enrollment and At-tainment Rates Across Countries in Latin America andthe Caribbean reflects the long-standing interest ofpolicymakers and practitioners, and of the RegionalPolicy Dialogue’s Education Network members inparticular, to have consistent and comparable mea-sures of educational outcomes for a series ofcountries. Utilizing micro-level data from house-hold surveys, the paper provides a means forcomparing four indicators—age-specific net enroll-ment ratios, average years children spend in school,average number of grades they complete, and thegap between the preceding two measures—acrossthe majority of countries in the Region. The paperis pioneering in that the use of micro-data has en-abled the age-specific calculation of each of the fourindicators examined, thus addressing issues of com-parability and broadening the range of analysisbeyond the more standard or traditional indicatorsderived from administrative data or other sourcesof secondary data.

Based on the indicators and cross-national analy-sis it presents, the paper also provides multiplerankings of each country’s performance in getting

children in school and keeping them there, and ofturning year of contact with the education systeminto completed years of schooling. These rankingspoint to a number of policy issues. Insofar as chil-dren tend to spend a substantial number of years inschool, enrollment rates throughout Latin Americaand the Caribbean tend to be quite high. Notably,however, significant variation exists in how well sys-tems have done in reducing delayed entry into schooland in turning time spent in school into actual gradescompleted. Additional concerns are noted in termsof the progress countries have made in raising en-rollments at the secondary and tertiary levels.

It is in this regard that Apples and Oranges: Edu-cational Enrollment and Attainment Rates AcrossCountries in Latin America and the Caribbean contrib-utes to ongoing dialogue, within the framework ofthe Education Network of the Regional Policy Dia-logue, on issues of data comparability and theimportance of such data in informing policy deci-sions. We hope this document will contribute to theimprovement of the education sector in the region,as well as an opportunity for a more fruitful exchangeand a more informed decision-making.

Foreword

Nohra Rey de Marulanda Carlos M. JarqueManager ManagerDepartment of Integration and Department ofRegional Programs Sustainable Development

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

WHY USE HOUSEHOLD SURVEYS? COMPARABILITY ISSUES . . . . . . . . . . . . . 3

EDUCATIONAL “QUANTITY”:BASIC RESULTS ON NET ENROLLMENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

INCORPORATING EDUCATIONAL QUALITY:YEARS IN SCHOOL AND YEARS OF SCHOOLING . . . . . . . . . . . . . . . . . . . . . . . . 13

BRINGING SOME RESULTS TOGETHER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

SOME FURTHER RESULTS ON INEQUALITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

ENROLLMENTS IN HIGHER EDUCATIONAL LEVELS . . . . . . . . . . . . . . . . . . . . . 25

CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

APPENDIXES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Table of Contents

Which countries are closer to achieving the goals ofuniversal enrollment in primary and/or secondaryschool? Which have done best at maintaining edu-cational quality, even as they increase enrollments?Such questions are of particular relevance when coun-tries set themselves common objectives in these ar-eas, such as they have with the “MillenniumDevelopment Goals.”1

Making the cross-country comparisons requiredto answer such questions, however, is not a simpletask. This paper attempts to do so for the majority ofcountries in Latin America and the Caribbean (hence-forth, LAC). First, it presents some simple indicatorsof access and quality that are comparable across coun-tries, in the sense of having been generated using simi-lar information—household survey micro data. As afirst section illustrates, this turns out to be crucialbecause international rankings that rely on second-ary information–mainly aggregate official statistics–encounter significant obstacles. Of course, the use ofhousehold survey data is not without its own set ofdrawbacks, which we discuss in detail.

We use this information to generate four simpleand/or generally well known indicators: i) age-spe-cific net enrollment ratios, ii) a measure of the aver-age number of years children spend in school, iii) ameasure of the average number of grades they actu-ally complete, and iv) the gap between the last two.Because we use micro-data, all these are calculatedin an age-specific manner that enables us to makesome comparisons that, to our knowledge, have notbeen feasible before.2

We then use these measures to produce severalrankings as well as a “bottom line” classification ofcountries. These seek to capture their performancein two areas: i) getting children into school on timeand keeping them there, and ii) turning their contactwith the educational system into years of schooling.

The results suggest that LAC countries’ overallenrollment rates are relatively high, and that there-fore children on average spend a substantial numberof years in school. There is nevertheless wide varia-tion in how well different systems have done in termsof reducing delayed entry and raising secondary en-rollments; and there are also substantial differencesin how effectively their educational systems turnchildren’s time in school into actual grades completed.

Further, the multiple rankings we present turnout to be useful because specific countries’ perfor-mance along these dimensions is not uniform. Forinstance, the Dominican Republic performs almostas well as the richest cou ntries when it comes toenrollment, but as badly as the poorest few in termsof turning attendance into years of schooling. Simi-larly, there are countries, such as Chile, which havebeen relatively successful at increasing secondary en-rollment, and yet are relative under-performers whenit comes to reducing delayed entry.

In two final exercises, we present some simpleinformation on the heterogeneity of attainment withincountries, and we briefly review the situation of ac-cess to post-secondary education.

Introduction

1 Under this initiative, developing countries aim to achieveuniversal primary enrollment by the year 2015. Developedcountries, in turn, agree to facilitate financing for efforts to-wards this goal. Similar objectives have been agreed uponearlier. Clemens (2004) provides a comprehensive review.2 An exception is the cross-country survey-based infor-mation described in Filmer and Pritchett (1999) and avail-able at www.worldbank.org/research/projects/edattain/edattain.htm. Some comparisons we make here are similar tothose made by Filmer and Pritchett, but our coverage of LACcountries is more comprehensive.

outcomes to dominate those of the countries citedalong almost all dimensions (for instance, Chile isessentially the first LAC country making a seriouspush towards universal secondary enrollment).

One might conjecture that such puzzling resultsreflect over-reporting by Ministries of Education in-tent on casting their respective governments in a posi-tive light. More likely, however, such unexpectedorderings have their origin in the fact that differentcountries use different definitions and tools to mea-sure enrollment. Two examples are useful to illus-trate this.

First, countries’ definitions of primary educationvary (e.g. grades 1–5 vs. grades 1–8; ages 7–11 vs.ages 6–13). As we show below, this alone can causeotherwise identical performers to place rather differ-ently in aggregate comparisons. Adding to the com-plications this can create, such definitions sometimeschange over time even within countries.5

A key task in this paper is to use household surveymicro data to generate comparable enrollment andeducational attainment information for as many LACcountries as possible. This might seem redundant, tothe extent that a large quantity of administrative, ag-gregate information on such variables is already pub-licly available.

COMPARABILITY PROBLEMS

Nonetheless, a first reason to use micro data is thatcomparisons using aggregate information from sec-ondary sources can be fairly problematic. Table 1 il-lustrates this using data for the 23 countries coveredin this study.3 Columns 1 and 2 contain the net pri-mary enrollment rates that the World Bank (WorldDevelopment Indicators, 2004) and the UNDP (Hu-man Development Index, 2004), two of the most citedsources of such information, report for this set ofcountries.

Two examples illustrate the type of difficultiesone encounters, and which are crucial particularly ifone wishes to generate country rankings, as we dobelow. First, in the UNDP’s classification, a few coun-tries have net enrollment ratios above 100 percent(e.g. Argentina and Ecuador with 108 and 102 per-cent, respectively), something which by definitionshould not happen.4

Second, there are some results that are surprisingto the point of leading one to question the validity ofcross-country comparisons using these data. For in-stance, the UNDP lists Chile as having a primary netenrollment rate significantly below that of countriessuch as Bolivia, Ecuador, and Paraguay. Although thenumbers are slightly different, the World Bank dataagree with this ordering. This is surprising given thatmost researchers would expect Chile’s educational

Why use household surveys?Comparability issues

3 This sample accounts for the vast majority of LAC coun-tries. It accounts, for instance, for all LAC members of theInter-American Development Bank except for: Bahamas, Bar-bados, and Suriname. We return to issues of coverage below.4 The UNDP data come from the Human Development Reportfor 2004, which, as is standard, defines the net enrollmentratio as “the number of students enrolled in a level of educa-tion who are of official school age for that level, as a percent-age of the population of official school age for that level.”This should not produce ratios in excess of 100 percent.Clemens (2004) points out that this problem exists in manydata sets used to make international comparisons, and that itis not confined to the LAC region.5 For instance, up to its 1994 educational reform, Bolivia wouldhave defined primary as the “Ciclo Básico,” which spannedgrades 1 through 5 and ages 6–10. After the reform, it under-stands it as grades 1–8 and ages 6–13. Argentina also madesignificant reforms in 1994, and to our knowledge these havenot been implemented uniformly across the country (givenits federalized educational system), introducing further com-plications.

4 APPLES AND ORANGES: EDUCATIONAL ENROLLMENT AND ATTAINMENT ACROSS COUNTRIES IN LATIN AMERICA AND THE CARIBBEAN

TABLE 1

PRIMARY NET ENROLLMENT RATES IN SELECTED LAC COUNTRIES, CIRCA 2000

Primary net enrollment rate (%)

This report

Country World Bank UNDP Ages: 7–13 Ages: 6–13(1) (2) (3) (4)

1 Argentina1 99.7 108 98.9 99.0

2 Belize 96.2 96 96.9 97.7

3 Bolivia 95.0 94 93.2 95.2

4 Brazil 94.6 97 94.5 96.3

5 Chile 88.8 89 97.5 98.9

6 Colombia 88.5 87 90.8 91.5

7 Costa Rica 92.1 91 94.4 95.1

8 Dominican Republic 92.7 97 96.3 97.1

9 Ecuador 99.5 102 90.9 91.0

10 El Salvador 88.9 89 86.2 88.9

11 Guatemala 84.2 85 N/A 81.3

12 Guyana1 98.4 98 96.2 96.5

13 Haiti1 N/A N/A 65.0 69.3

14 Honduras 87.5 87 81.5 85.1

15 Jamaica 95.0 95 99.6 99.5

16 Mexico 99.4 101 95.1 95.3

17 Nicaragua 80.7 82 84.5 87.6

18 Panama 97.8 99 96.8 97.5

19 Paraguay 92.2 92 93.5 94.5

20 Peru 99.9 100 96.4 96.8

21 Trinidad and Tobago1 92.6 94 96.2 96.2

22 Uruguay1 90.4 90 97.9 98.1

23 Venezuela 88.2 92 95.9 96.3

Average 93.4 94.0 92.6 93.2

Std. Dev. 5.4 6.4 7.7 7.0

Minimum 80.7 82 65.0 69.3

Maximum 99.9 108 99.6 99.5

Sources: For the World Bank, the figures come from the online version of World Development Indicators, for 2004. Seehttp://www.worldbank.org/data/onlinedatabases/onlinedatabases.html. For the UNDP, the data are as listed in the HumanDevelopment Report, 2004.Notes: (1) The figures correspond to those the World Bank lists for 2000.

(2) The figures correspond to those the UNDP lists for 2000/2001.

(3), (4) We use surveys mainly for the year 2000, see section II.B for a description of the data.

1 The figures for Argentina, Guyana, Haiti, Trinidad and Tobago, and Uruguay are for their respective urban areas only.

WHY USE HOUSEHOLD SURVEYS? COMPARABILITY ISSUES 5

Second, enrollment ratios are often measured usingdifferent sources of data within each country. For in-stance, the numerator may come from administra-tive information, while the denominators may becalculated using population estimates generated fromcensus data.6 This can easily result in enrollment ra-tios in excess of 100 percent, even if there is nomisreporting. For instance, if children transfer be-tween schools during the academic year, they mightbe counted twice in administrative data, but only oncein the population estimate.7

HOUSEHOLD SURVEY DATA

In order to address such issues, we rely instead oninformation collected directly from households,namely an extensive set of household surveys as-sembled by the Inter-American Development Bank(henceforth, IDB).8 The questions we use are quitesimilar across countries, and are roughly variants ofthe following:

1) Are you currently enrolled in an educationalinstitution?

2) What type of studies are you pursuing?(With possible answers including primaryschooling, and different types of secondaryand post-secondary education).

3) If you are done with your studies, what typeof studies did you last pursue?

4) Which is the last grade you passed withinthat type of study?

Such questions enable us to construct enrollment andattainment measures that are age specific, consistentacross countries, and obviously based on a singlesource of data within each country.

Nonetheless, these data are not without their owndisadvantages. First, all results are based on house-holds’ self-declared reports. One might think that theseestimates provide an upper bound on most measures,to the extent, for instance, that households might erron the side of declaring their children are in schoolrather than not. Unfortunately, there is no way to besure of this, although the average enrollment rateswe calculate, for instance, are often lower than thosewhich emerge from official statistics.

In order to maximize the number of countrieswith chronologically proximate surveys available, wefocus the analysis roughly on the year 2000. Table 2

lists the countries considered, along with the yearclosest to 2000 for which a survey is available at theIDB. The analysis covers 23 countries with data for1999, 2000, or 2001.9 The sample contains informa-tion on close to the totality of the LAC population,since the countries excluded are few and have com-paratively very small populations.

We note some further drawbacks to these data.First, for five countries (Argentina, Guyana, Haiti,Trinidad and Tobago, and Uruguay), the surveys arerepresentative of urban areas only, and we have toaccount for this in the comparisons below. Morebroadly, while the remaining surveys are nationallyrepresentative, the sampling schemes used might dif-fer across countries, and it is next to impossible tocontrol for that.10

For a preview of the results these data yield, Table1 (columns 3 and 4) presents net enrollment ratesfor the 6–13 and 7–13 age ranges, respectively.11 Theoverall averages of these rates are close to those cal-culated by the World Bank and UNDP, but the two“anomalies” we arbitrarily focused on above are re-solved: i) there are no net enrollment ratios in excessof 100 percent, and ii) Chile now has a primary en-rollment rate significantly higher than those of Bo-livia, Ecuador, and Paraguay.

6 In many countries, further, administrative data does notclassify the age break-down of children enrolled in a givengrade.7 It is particularly easy to observe net enrollment in excess of100 percent in jurisdictions within countries, again, even inthe absence of misreporting. This can happen, for instance,because migration patterns (some of which are seasonal) cancause children to enter administrative and not populationcounts (and vice versa). See Urquiola (2000) for a discussionand illustrations using Bolivian data.8 Specifically, these are part of the Program for the Improve-ment of Surveys and the Measurement of Living Conditions(MECOVI for its Spanish acronym), sponsored jointly by theInter-American Development Bank, the U.N. Economic Com-mission for Latin America and the Caribbean, and the WorldBank.9 As stated, among the IDB members, only Bahamas, Barba-dos, and Suriname are excluded (we used only surveys avail-able at the IDB—so their absence does not indicate the datamight not exist at all). Further, for Trinidad and Tobago, weuse a survey from 1992, the only one we could get access to.10 In all calculations below, we use the weights providedwithin each survey.11 We include both of these for two reasons. First, countriesdiffer as to the age at which children are officially expected tostart school (6 or 7). Second, one of our surveys (Guatemala)starts recording attendance only at age 7, an issue we returnto below.


TABLE 2COUNTRIES AND HOUSEHOLD SURVEYS USED

Level at which the surveyCountry Survey date is representative

1 Argentina Oct 2000 Urban area only

2 Belize Apr 1999 National

3 Bolivia Nov-Dec 2000 National

4 Brazil Sept 1999 National

5 Chile IV Q-2000 National

6 Colombia III Q-2000 National

7 Costa Rica Jul 2000 National

8 Dominican Republic 2000 National

9 Ecuador Nov 2000 National

10 El Salvador 2000 National

11 Guatemala Jul-Nov 2000 National

12 Guyana 1999 Urban area only

13 Haiti 2001 Urban area only

14 Honduras Sept 1999 National

15 Jamaica 2000 National

16 Mexico 2000 National

17 Nicaragua 2001 National

18 Panama Aug 2000 National

19 Paraguay Sept 2000 Aug 2001 National

20 Peru IV Q-2000 National

21 Trinidad and Tobago May-Jun 1992 Urban area only

22 Uruguay 2000 Urban area only

23 Venezuela II Q-2000 National

While Table 1 presents results for age ranges, thehousehold survey data yield more detailed age-spe-cific enrollment ratios. For illustration, Figure 1graphs these for Chile and Honduras, two fairly ex-treme cases in the LAC region. The complete set ofsuch figures is in Appendix A, and the actual datathey rely on are in Appendix B. The figures and tablespresent the national enrollment rates as well as thoseobserved for: males, females, the rural area, and theurban area.

An important note here is that for reasons wewill return to below, we only considered individualsenrolled when they were attending grades 1–12. Thisis only relevant in the upper age ranges (17 and 18)where some high school graduates will be enrolledin postsecondary education. Because our focus here

Educational “quantity”:Basic results on net enrollment

is on the “1–12” system, we netted out such indi-viduals.12

There are several observations regarding this firstset of results:

1) As is well known, in most LAC countriesand for most age ranges, there are few dif-ferences between males and females’ aggre-gate enrollment outcomes—so much so thatin many cases it is hard to visually tell the

12 We did this by not counting the attendance of individu-als who report they are enrolled in an educational institu-tion, and who also report they have completed 12 years ofschooling.

FIGURE 1

AGE-ENROLLMENT PROFILES FOR CHILE AND HONDURAS

Age

Maximum Males Urban Total Females Rural

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Chile Honduras

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

.2.4

.5.6

.81


three series (male, female, and total) apart.As for Honduras in Figure 1, when differ-ences emerge, they frequently are in favorof females, although they are often prob-ably not statistically significant.13

2) In contrast, the differences between the ur-ban and rural areas are much more substan-tial, even in a country like Chile. Animportant caveat in making comparisonsalong this dimension is that we have madeno attempt to define the rural area consistentlyacross countries—we simply take the defi-nition that comes with each household sur-vey. Thus, some countries may have a“worse” performance here simply becausetheir urban/rural classification system iden-tifies a more “extreme” population.

3) A look at the lower age ranges reflects a gen-erally under-appreciated phenomenon inLAC countries: delayed entry into primaryschool. Even in Chile, where primaryschooling is close to universal, the net en-rollment rate for children of age 6 is below90 percent overall, and below 80 percent inrural areas. In Honduras, roughly 40 per-cent and 20 percent of 6 and 7 year-olds,respectively, are not attending school, witheven lower enrollments rates observed inrural areas. Across all the countries consid-ered, the average net enrollment rates forrural 6 and 7 year-olds are 79 and 89 per-cent, respectively.

4) In the 8–13 age range, enrollments are in-deed quite high—in urban areas they ex-ceed 90 percent in all countries but Haiti.Nevertheless, in some countries like Hon-duras and Guatemala, the national ratenever quite approaches 100, which leavesopen the possibility that a small but non-negligible percentage of children never ac-tually enter school.

5) As is well known, enrollment rates begin todrop at about 13, 14, or 15 years of age,depending on the country.

6) Delayed entry and dropping out lead to an“inverted-U” age enrollment profile, whichis evident for the rural populations in al-most all countries considered. It is also vis-ible even for the aggregate population inBolivia, Brazil, Colombia, El Salvador, Gua-temala, Haiti, Honduras, and Nicaragua.

7) This pattern is of particular concern if thereis reason to believe that children who enter

late are also more likely to exit early (some-thing our data cannot reveal directly). Itmight be the case, for instance, that boysfrom low income households enter late be-cause their parents wish to postpone incur-ring some of the direct costs of schooling(e.g. school materials, bus fare, or uniforms).Once such boys turn 13 or 14 and theiropportunity costs climb, their parents mightallow them to leave school and start work-ing. In such a scenario, even a system witha relatively high average primary net enroll-ment rate, like Honduras’, will be produc-ing many “graduates” with 5 or fewer yearsof schooling, even assuming no repetition.

8) Even among countries that do not have par-ticularly high enrollment rates overall, thereare some interesting exceptions to the “in-verted-U” pattern. Jamaica, for instance,displays the usual drop-out problems in theteenage years, but nevertheless manages toenroll almost every 6 and 7 year old.Guyana, Mexico, and Venezuela also standout as “good performers” in this regard. Itis beyond the scope of this paper to analyzewhat policies may be leading to these out-comes (e.g. attendance subsidies inMexico), but they still highlight a differenceacross countries that may result in educa-tional attainment differences down the line.

In terms of ranking countries, these observationssuggest we should consider how thoroughly differ-ent educational systems serve three populations: i)children aged 6–7, those in the range in which de-layed entry can be a problem, ii) ages 8–13, the rangein which most children are actually in school in vir-tually every LAC country, and iii) ages 14–18, therange generally associated with secondary schooling,in which net enrollment rates fall in every country.The next section provides some initial rankings basedon these criteria.

Before proceeding to those results, it is impor-tant to note two characteristics that vary across coun-tries: normative starting ages, and the number ofgrades in the formal primary and secondary educa-tional system. In most countries in the region, thenormative start age is 6 and the whole primary and

13 Because these results are based on samples of households,they should be viewed as point estimates with associated es-timation errors.

EDUCATIONAL “QUANTITY”: BASIC RESULTS ON NET ENROLLMENT 9

secondary sequence consists of 12 grades. In a few,however, the start age is 7 (e.g. Guatemala), or thesystem has only 11 grades (e.g. Colombia). Evenamong countries with the same normative startingage, the anecdotal evidence suggests there is widevariance in how “seriously” it is enforced.

In the results below, we make no explicit allow-ance for these differences. If a given country is pro-ducing fewer years of schooling at a given age becauseit explicitly aims to do so (e.g. a country with an of-ficial entry age of 7), we simply let the data reflectthat and in some sense count it against this country.Nonetheless, one of the final indicators we use torank countries—a measure of the gap between theaverage number of years children spend in school

and the number of grades they actually complete—does in partially adjust for cross-country differencesin target attainment.

URBAN ENROLLMENT

We begin with a ranking based solely on enrollmentsin urban areas. This is our benchmark because, asshown in Table 2, five of the 23 countries we con-sider have surveys representative of only their ur-ban populations. As a first exercise, Table 3 presentsrankings according to aggregate net enrollment ra-

TABLE 3COUNTRY RANKINGS BY URBAN ENROLLMENT RATES IN SPECIFIC AGE RANGES

Ranking 1 Ranking 2 Ranking 3 Ranking 4Ages 6–18 Ages 6–7 Ages 8–13 Ages 14–18

Country Rate Country Rate Country Rate Country Rate(1) (2) (3) (4) (5) (6) (7) (8)

Chile 94.3 Jamaica 100.0 Chile 99.0 Chile 88.7Argentina 93.2 Belize 99.0 Jamaica 99.4 Bolivia 87.0Dom. Rep. 92.5 Argentina 98.8 Argentina 99.0 Dom. Rep. 84.6Bolivia 92.0 Uruguay 97.6 Panama 98.5 Argentina 84.0Panama 92.4 Mexico 97.5 Dom. Rep 98.3 Panama 82.0Brazil 92.0 Peru 97.3 Belize 98.3 Brazil 79.7Peru 89.0 Panama 97.2 Paraguay 98.1 Jamaica 78.9Paraguay 88.6 Venezuela 97.2 Peru 98.1 Paraguay 75.2Jamaica 88.0 Costa Rica 96.6 Uruguay 97.9 Peru 74.7Belize 88.0 Trin. & Tob. 96.2 Venezuela 97.6 Ecuador 73.5Uruguay 87.8 Guyana 95.4 Brazil 97.2 Haiti 72.9Venezuela 87.8 Dom. Rep. 94.6 Bolivia 97.0 El Salvador 72.8Costa Rica 86.9 Ecuador 94.4 Costa Rica 96.8 Colombia 72.4Mexico 86.1 Paraguay 94.0 Guyana 96.5 Venezuela 72.2Ecuador 85.7 Chile 94.0 Trin. & Tob. 96.2 Uruguay 71.6Colombia 85.7 Colombia 93.5 Mexico 96.0 Belize 71.3Trin. & Tob. 84.6 Bolivia 92.1 El Salvador 94.4 Costa Rica 71.2El Salvador 84.4 Brazil 90.2 Colombia 94.2 Nicaragua 70.2Nicaragua 82.9 El Salvador 83.5 Nicaragua 93.9 Mexico 69.7Guyana 80.7 Guatemala1 82.7 Ecuador 93.0 Trin. & Tob. 66.1Guatemala1 77.2 Nicaragua 81.5 Honduras 91.4 Guatemala 60.9Honduras 75.8 Honduras 76.3 Guatemala 90.0 Honduras 56.8Haiti 68.0 Haiti 42.6 Haiti 72.6 Guyana 55.9

Notes: In making these calculations, we used each country’s definitions of urban and rural. In the case of Mexico, we defined as ruralthose locations with fewer than 15,000 people. For Venezuela, we consider only metropolitan Caracas as urban.1 The figures for Guatemala begin only at age 7. Footnote 14 discusses how this affects its relative performance in Rankings 1 and 2,which include age 6.


tios as well as according to those observed in each ofthe three age ranges cited.14

Columns 1 and 2 present what we will labelRanking 1, which is based on the entire 6-18 agerange. Chile and Argentina place at the top, as onemight expect given their per-capita income. None-theless, perhaps more surprisingly, countries like theDominican Republic, Bolivia, and Panama placenext, although one must bear in mind that Table 3covers urban areas only. El Salvador, Nicaragua,Guyana, Guatemala, Honduras, and Haiti place atthe bottom of this sample, as will be the case in manyof the comparisons below. Thus, columns 1 and 2present perhaps the simplest ranking of LAC coun-tries that our data can produce. We also note thatthis is exactly the ordering that would come out of a“Human Development Index (HDI)”-type calcula-tion based on enrollment, i.e., this is essentially theeducation part of the ranking that the UNDP wouldgenerate if it used our data.15

The following columns break down the resultsinto more specific age ranges, and show that Rank-ing 1 conceals interesting variation. For instance,Chile ranks highest in both the 8–13 and 14–18 ageranges (rankings 3 and 4). The latter in particular isexpected given this country’s pioneering (in the re-gion) efforts to make secondary schooling universal.In contrast, it ranks much lower, 15th, in the 6-7 agerange (Ranking 2). Jamaica illustrates the oppositepattern—it is close to the median in the highest ageranges, but is at the top of Ranking 2 because it man-ages to get almost all young children into school.

Rankings 1–4 may well reflect policy choices.As already stated, different countries have differentnormative entry ages (6 or 7), and enforce them todifferent extents. Further, some countries,likeNicaragua, have enrollment subsidies targeted atchildren of young ages.16

One possibility this raises is that countries thatdo manage to incorporate children on time mayend up with higher average years of schooling. Onemust be careful about such inferences, however.To see this, suppose households have a target setof skills or grades that they want their children toachieve. For instance, assume they want them tolearn basic reading and writing skills, but not muchbeyond that (say because they consider those skillssufficient in the type of labor market they envisiontheir children will enter). Assume also that this setof skills is mastered upon completion of the 3rd or4th grade.

If this is the case, then the age at entry mightindeed affect the age at which children leave, but

perhaps not the years of schooling they eventuallycomplete. In one country, a child might enter at 6and leave at age 12, after repeating two grades. Inanother, she might enter at 7 and leave at 13, alsoafter repeating two years. In the extreme, in such ascenario, implementing policies to lower the age atentry might have no effect on years of schooling out-comes.17

This type of reasoning also suggests that theremight be a tradeoff in how well countries do in thethree age ranges in Table 3. For a final illustration,consider Bolivia and Uruguay. Bolivia is ranked 17th

in the earliest range, 12th in the second, and 2nd inthe last. As the above implies, this might reflect chil-dren “hanging around” in school trying to achievethe skills they have not mastered, either because theyentered late or repeated a lot (or because standardsare very low, an issue we turn to below). In con-trast, Uruguay does well (4th) in the earliest range,but its relative performance goes down thereafter(15th in the final range), which might reflect achieve-ment of a target set of skills or grades at a youngerage.

The bottom line is that Table 3 yields interestingcomparisons, but these must be made with care andrealizing that implicit in many of them is a model ofhow people decide on the number of years of school-ing they desire; i.e., these numbers always reflect theinteraction of supply and demand, and hence draw-ing policy implications from them is complicated.

14 A final caveat here concerns Guatemala–the one countrywith a survey that does not collect attendance data for 6-yearolds. This is relevant for rankings 1 and 2, which thereforeconsider this country’s performance beginning only at age 7.This does not alter Ranking 1, but it has the effect of movingGuatemala ahead of Honduras and Nicaragua in Ranking 2.15 This reflects the fact that the HDI methodology takes anygiven education indicator and then calculates what it labelsthe Dimension index = (Actual–Max)/(Max–Min), where Maxand Min stand for the maximum and minimum values theindicator can feasibly take, and Actual is the country’s value.Because the maximum and minimum enrollment rates are100 and 0, respectively, for enrollment the dimension indexis simply equal to the enrollment rate.16 Maluccio and Flores (2004) analyze the impact of such aprogram in Nicaragua, one of the countries that at least judg-ing by Figure 1, needs it the most. Brazil and Mexico havesimilar and much more widely studied programs.17 Glewwe and Jacoby (1995) refer to this issue using evi-dence from Ghana. They suggest that delayed entry mightindeed be optimal if children’s readiness for school is cumu-lative due to nutritional reasons. From this point of view,reducing it might even be counterproductive.

EDUCATIONAL “QUANTITY”: BASIC RESULTS ON NET ENROLLMENT 11

NATIONAL AND RURAL ENROLLMENT

Next we present rankings of countries according totheir enrollment in the same age ranges, but consid-ering countries in their entirety and in their rural areas(again, as defined by each country). As already noted,this forces us to drop five countries (Argentina,Guyana, Haiti, Uruguay, and Trinidad and Tobago).Table 4 presents the results for the nationwidesamples, and Table 5 those for the rural areas. Be-cause the rankings are very similar to those in Table3, we simply append an “a” (Table 4) or a “b” (Table5) to them for purposes of labeling.

Table 4 begins with the nationwide figures. Notsurprisingly, the net enrollment rates here are lowerthan those observed in Table 3, and in general theyalso become more variable. In the 14–18 age rangein rural areas, only six countries have enrollment ratesabove 70 percent (as opposed to 18 in the urbansample above). In the 6–7 range, a number of enroll-ment ratios now fall below 90 percent. Such figuresraise the possibility that some of the enrollment short-falls in rural areas are due to a lack of supply.

In the rural area-based rankings (Table 5), coun-tries with relatively low overall population densities(such as Bolivia and Colombia) generally fare worse,although others, such as Brazil, seem to hold up their

TABLE 4

COUNTRY RANKINGS BY NATIONWIDE ENROLLMENT RATES IN SPECIFIC AGE RANGES

Ranking 1 Ranking 2 Ranking 3 Ranking 4Ages 6–18 Ages 6–7 Ages 8–13 Ages 14–18

Country Rate Country Rate Country Rate Country Rate(1) (2) (3) (4) (5) (6) (7) (8)

Chile 93.1 Jamaica 100.0 Jamaica 99.4 Chile 86.1

Dom. Rep. 91.1 Peru 95.5 Chile 98.9 Dom. Rep. 82.7

Jamaica 89.9 Mexico 95.1 Belize 97.8 Brazil 77.1

Panama 88.1 Panama 94.9 Dom. Rep. 97.8 Bolivia 74.7

Brazil 87.8 Belize 94.4 Panama 97.4 Jamaica 75.6

Bolivia 86.5 Venezuela 94.2 Brazil 96.7 Panama 74.2

Peru 85.8 Costa Rica 93.7 Peru 96.6 Peru 68.8

Venezuela 84.7 Chile 93.3 Venezuela 96.4 Venezuela 66.7

Paraguay 82.3 Dom. Rep. 92.3 Bolivia 95.1 Paraguay 64.4

Mexico 81.5 Ecuador 92.2 Mexico 95.1 Colombia 64.3

Belize 81.4 Paraguay 89.1 Paraguay 95.0 Ecuador 62.0

Colombia 80.6 Colombia 88.7 Costa Rica 94.6 El Salvador 61.3

Costa Rica 80.5 Brazil 87.9 Colombia 91.5 Mexico 59.8

Ecuador 79.8 Bolivia 87.5 Ecuador 90.5 Costa Rica 58.3

El Salvador 76.6 El Salvador 75.7 El Salvador 89.7 Nicaragua 58.1

Nicaragua 74.3 Nicaragua 73.2 Nicaragua 88.2 Belize 56.5

Honduras 65.9 Guatemala 71.3 Honduras 85.4 Guatemala 41.9

Guatemala 64.9 Honduras 69.8 Guatemala 82.9 Honduras 40.8


previous performance. It is also interesting to notethat the countries that do well in the rural sampleare not necessarily those that did so in the urban

samples. One of the salient and perhaps surprisingperformers is the Dominican Republic, which doesquite well in almost all age ranges and areas.

TABLE 5COUNTRY RANKINGS BY RURAL ENROLLMENT RATES IN SPECIFIC AGE RANGES

Ranking 1b Ranking 2b Ranking 3b Ranking 4bAges 6–18 Ages 6–7 Ages 8–13 Ages 14–18

Country Rate Country Rate Country Rate Country Rate

Dom. Rep. 88.7 Jamaica 100.0 Jamaica 100.0 Dom. Rep. 79.1

Jamaica 88.2 Venezuela 93.9 Chile 97.8 Chile 70.2

Chile 85.9 Peru 93.6 Belize 97.4 Jamaica 70.0

Venezuela 84.2 Panama 92.5 Dom. Rep. 96.7 Brazil 67.8

Panama 82.4 Mexico 92.2 Venezuela 96.3 Venezuela 66.0

Brazil 82.4 Belize 91.8 Panama 96.2 Panama 61.9

Peru 80.9 Costa Rica 91.4 Brazil 95.0 Peru 59.1

Belize 75.8 Chile 89.1 Peru 94.9 Colombia 52.4

Paraguay 75.3 Ecuador 88.8 Mexico 94.0 Bolivia 52.3

Bolivia 75.1 Dom. Rep. 88.8 Costa Rica 92.9 Paraguay 51.3

Mexico 75.0 Paraguay 83.9 Paraguay 92.3 El Salvador 47.8

Costa Rica 75.0 Colombia 82.5 Bolivia 92.0 Costa Rica 47.1

Colombia 73.5 Bolivia 81.3 Colombia 88.0 Mexico 45.5

Ecuador 69.9 Brazil 80.9 Ecuador 86.8 Belize 43.6

El Salvador 67.9 El Salvador 67.3 El Salvador 84.8 Ecuador 42.1

Nicaragua 63.1 Guatemala 65.6 Nicaragua 81.5 Nicaragua 40.9

Honduras 58.0 Honduras 65.5 Honduras 81.4 Guatemala 30.6

Guatemala 57.7 Nicaragua 63.5 Guatemala 79.0 Honduras 27.0

Note: In making these calculations, we used each country’s definitions of urban and rural. In the case of Mexico, we counted as rural lo-cations with fewer than 15,000 people. In the case of Venezuela, we consider only metropolitan Caracas as urban.

The rankings presented thus far contain no informa-tion on the quality of education different countries’systems are delivering. Incorporating data on this isvery difficult. One direct way of doing it is by con-sidering the results of international testing rounds,but unfortunately these are only available for a lim-ited set of countries. This section attempts to getaround this issue by using two additional measuresof educational outcomes: average years in school andaverage years of schooling. Under significant assump-tions, these measures can allow us to extract a qual-ity-based comparison from the household surveys,but even setting aside the quality issue, they are in-formative of the performance of different nationaleducational systems.

AVERAGE YEARS IN SCHOOL

Net enrollment rates display the interaction of de-mand and supply: the State and the private sectormake slots in school available (at given direct andindirect costs), and households decide to use themor not. Thinking of the situation this way suggestsanother intuitive and still purely “quantity oriented”measure: average years in school (not to be confusedwith average years of schooling, to which we turnbelow), obtained by cumulatively adding age-specificnet enrollment rates like those in Table 3.

This summation yields the expected or averagenumber of years that an individual will spend inschool by a given age, given the enrollment patternscurrently observed in his or her country. In some sensethis measure contains no new information relative tothat already conveyed by the age-specific net enroll-ment rates (after all, it is only their cumulative sum).Nonetheless, we introduce it both because it providesa convenient summary of the resources (if only in

time) expended by States and households to keep kidsin school, and because it will providea useful bench-mark against which to compare countries’ perfor-mance in terms of producing years of schooling—i.e.,actual grades completed.

To illustrate, columns 2 and 5 in Table 6 presentthis measure for Chile and Honduras. For age 6, it issimply equal to the net enrollment rate expressed asa proportion (0.88 in Chile, and 0.57 in Honduras).This entry indicates that, on average, by the time theyare six years old, children will have spent 0.88 yearsin school in Chile, and 0.57 in Honduras. Columns2 and 5 then cumulate the entries in columns 1 and4, showing, for instance, that by age 15 Chilean chil-dren will have spent an average of 9.7 years in school,while Honduran children will have spent 7.5; by age18, these figures are 12.1 and 8.6, respectively.

Figure 2 illustrates why we find this measureuseful. For each country, the top segment graphs themaximum feasible attainment (measured in years ofschooling) that an individual of a given age couldhave, if she started at age six and had a “normal”progression through the educational system. For ex-ample, this person could have completed a maximumof one year of schooling by age six, two by age seven,and so on, up to 12 by age 17.

The middle line is the average years in schoolmeasure, drawn from columns 2 and 5 in Table 6.Focusing first on Honduras, note that at age 6, thegap between these two segments is relatively small.A gap is clearly visible, nonetheless, because of thenon-trivial delayed entry observed in this country.The two series then run roughly parallel up to aboutage 10, reflecting the high net enrollment rates inthis age range. After that, the two lines diverge mark-edly, as dropout rates increase.

In the case of Chile, the average years in schoolsegment begins very slightly below the maximum,which reflects the non-zero delayed entry observedeven in this country. The gap then essentially does

Incorporating educational quality:years in school and years of schooling


TABLE 6

NET ENROLLMENT RATE, YEARS OF SCHOOL,AND YEARS OF SCHOOLING – CHILE AND HONDURAS

Age Chile Honduras

Net Average Average Net Average Averageenrollment years years enrollment years years

rate in school of schooling rate in school of schooling (1) (2) (3) (4) (5) (6)

6 87.7 0.88 0.2 56.8 0.57 0.0

7 98.9 1.87 0.8 82.8 1.40 0.2

8 98.9 2.86 1.8 90.1 2.3 0.9

9 99.2 3.85 2.7 91.3 3.2 1.7

10 99.0 4.84 3.7 91.9 4.1 2.4

11 99.2 5.83 4.7 89.3 5.0 3.2

12 98.5 6.81 5.5 82.0 5.8 3.9

13 98.3 7.80 6.4 68.0 6.5 4.6

14 96.6 8.76 7.3 54.7 7.1 5.0

15 94.4 9.71 8.2 47.2 7.5 5.5

16 89.3 10.6 9.0 38.7 7.9 5.9

17 84.0 11.4 9.8 36.6 8.3 6.2

18 66.3 12.1 10.4 26.7 8.6 6.2

FIGURE 2MAXIMUM SCHOOLING, AVERAGE YEARS IN SCHOOL,

AND AVERAGE YEARS OF SCHOOLING IN CHILE AND HONDURAS

Age

Max. feasible attainment Avg. years of schooling Avg. years in school

0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Chile Honduras

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

INCORPORATING EDUCATIONAL QUALITY: YEARS IN SCHOOL AND YEARS OF SCHOOLING 15

not grow until about age 14; after that, some diver-gence is again observed as enrollment rates drop forsecondary schooling (Appendix C presents analo-gous figures for all the countries considered, and Ap-pendix D contains the precise data behind thesefigures).

In short, the middle segment captures the ex-pected number of years a child in each country willspend in school. It bears repeating that this expecta-tion is taken from a single survey, which imposes sev-eral limitations. For one example, suppose thatHonduras’ educational system suddenly improved interms of the quality of skills it provides in the earlygrades. One might then reasonably expect that a childwho begins school today might eventually display adifferent trajectory than that experienced by his oldersiblings. Our calculation, however, is based only ona snapshot of data, and will therefore incorporate thebehavior of just such older children.

AVERAGE YEARS OF SCHOOLING

Finally, columns 3 and 6 in Table 6, as well as thethird segment in Figure 2, present the average yearsof schooling reported by individuals in each of thesecountries—that is, the grades they claim they haveactually passed. An important note is that as explainedabove, we “truncate” the possible years of schoolingat 12 years, so that these results are not comparablewith those that emerge from many other studies orthe usual aggregate statistics. We do this for two rea-sons. First, our focus in this paper is on the “1–12”educational system, so we are less interested inschooling people obtain outside of it (e.g. in a uni-versity or other post-secondary institution). Second,for schooling levels beyond secondary, it is very dif-ficult to generate comparable years of schooling mea-sures across countries.18

With these caveats, comparing the second andthird segments in Figure 2 gives an indication as tohow effectively an educational system turns averageyears in school (contact with the system) into aver-age years of schooling (under significant assumptions,skills). Put otherwise, considering the three segmentsin Figure 2 provides one answer to the question “whydoesn’t every 18 year old in Honduras achieve 12years of schooling?” The figure makes clear that thisis due to two distinct problems: the lack of universalattendance (the gap between the first and the sec-ond segment), and the failure to turn years in school

into years of schooling (the gap between the secondand the third), largely but not exclusively due to rep-etition.

Some further caveats deserve mention. First, theyears of schooling series (the lower segment) gener-ally does not begin at one. In other words, even atage six the gaps between the second and third seg-ment can be large. Not too much should be made ofthis because six year old children would typically notall have completed one year of schooling. This willbe particularly the case in countries in which thesurvey is collected during the school year, since inalmost every case we construct the years of school-ing measure based on the number of grades peopledeclare they have completed.

More important (and a measure we use below)is the growth in the gap between these segments asone moves to the right in these graphs, which re-flects the increasing failure of the system to turn yearsin school into years of schooling. The figure for Chileindicates, for instance, that this gap has grown toabout one year by the time children reach age 18. Inthe case of Honduras, the gap at this age exceeds twoyears.

It is tempting to treat this gap as a measure ofa system’s ineffectiveness, as it is to treat average yearsof schooling as a quality measure, and we indeeduse them both to generate rankings in the nextsection. In both of these cases, however, there areissues to consider before presenting results, and

18 For instance, in different countries the number of yearsstudents spend in college or teaching school will be quitedifferent. Further, the coding of questions that apply to theselevels tends to be blunter and therefore much harder to makeconsistent. In many countries, for instance, people in highereducation will only respond that they are an “alumno,”“egresado,” or “titulado” of a given higher educational level.This means that they are either in post-secondary education,have finished all the requirements but some form of thesis,or have finished the degree. Particularly in the first category,assigning a given number of years of schooling is a roughexercise. In fact, it is difficult enough to generate comparablemeasures even for primary and secondary. First, knowing howto code the responses to the relevant questions requires some-what detailed knowledge of each country’s educational sys-tem (we benefited from the help of colleagues at the IDB andWorld Bank in this regard). Second, even with expert knowl-edge, complicated issues remain. One important one is thatevery so often countries alter the organization of their educa-tional systems (the examples of Argentina and Bolivia werecited above). This introduces significant uncertainty as to howboth the survey administrators and the respondents inter-pret the questionnaire.


they suggest that these two measures (years inschool and years of schooling) should be viewed ascomplementary.

A salient one arises because the measure onemight prefer is to some extent a function of whetherthere are differences in how countries organize theireducational system. To see this, consider two identi-cal countries, each of which has 30 children and oneteacher. Both countries have two years to teach theirchildren the same set of skills. Country 1 splits the“curriculum” into two years, and all kids pass year 1and successfully complete year 2 as well. Country 2puts the entire (identical) “curriculum” into firstgrade. Its children have not mastered it at the end ofthe first year. They all fail but by the end of the sec-ond year have mastered the same set of material. Theoutcomes in terms of skills and cost—one teacherfor two years—are identical, these countries are sim-ply organizing their systems differently.

Age-specific enrollment rates (or the averageyears in school measure, which essentially sum-marizes them) would correctly suggest that theiroutcomes are similar, while the usual average yearsof schooling measure would erroneously suggestone does better than the other. Put otherwise, itis hard to interpret differences in repetition ratesacross countries unless one has some prior on dif-ferences in the structure of their respective schoolsystems.

Thus, the key assumption if one wants to useaverage years of schooling as a quality measure, isthat the body of knowledge children are expected tohave at the end of a given year does not differ toomuch across countries. If this is the case, the gapbetween average years in school and average years ofschooling might also be viewed as an “effectiveness”measure—countries with a small gap would be thosethat successfully address the problem of excessiverepetition, for instance.

With these caveats, Table 7 begins to presentrankings according to these two measures. Ranking5 orders countries according to the average years inschool observed at age 18 (we include only a “final”indicator in this case since this measure essentiallysummarizes the enrollment rates we described indetail above). What is clear from this is that LACcountries devote a lot of resources to education, atleast as measured by the time households declare chil-dren are in contact with the schooling system—in allbut four countries, the average time spent in schoolexceeds 10 years by age 18. Note that an individualwho entered school at age 6 and repeated at least onegrade would have spent 13 years in school by the

time she is 18, so that 13 rather than 12 is the upperbound on this measure.

Rankings 6, 7, and 8 are based on the averageyears of schooling children have accumulated at threeages: 18, 8, and 13, respectively.19 The full data forevery age are in Appendix D. We exclude Guyanaand Trinidad and Tobago from these rankings, be-cause their questionnaire does not allow one to cal-culate years of schooling in the detail that is possiblefor the rest of the sample.

Ranking 6 (columns 3 and 4) refers to age 18.The country with the best performance in this “fi-nal” outcome is Chile, which achieved an averageof more than 10 years of schooling among 18 yearsolds in 2000. Argentina and Panama place close be-hind. There is then a large number of countries(more than half the sample) with between 8 and 9years of schooling, and a smaller number produc-ing less than 8. The latter group contains some ofthe usual suspects but also, perhaps more surpris-ingly, Brazil and Costa Rica. At the extreme, Guate-malan 18-year olds in 2000 had only 5.5 years ofschooling on average.

As above, the rankings that result at earlier agesare substantially different. For instance, Chile is muchcloser to the median in terms of attainment at age 8,partially reflecting its underperformance in the de-layed entry-related rankings above. In contrast, Ec-uador and Belize start out very strongly, but thenfactors like repetition or high drop out rates drivethem down substantially.

The fact that the variance in Ranking 6 is greaterthan that in 5 suggests considerable variation on howeffective different systems are at turning attendanceinto years of schooling—countries that do well inrankings 1–5 but not in rankings 6–8 areunderperformers in this regard. Brazil and the Do-minican Republic are notable examples, albeit in dif-ferent age ranges.

Because this “failure” is an interesting outcomeper se, we present another set of rankings based onthe following measure:

19 One issue here is that we stop making the distinction be-tween urban and rural areas despite the fact that the latter arenot represented in the surveys of Argentina, Guyana, Haiti,Uruguay, and Trinidad and Tobago. This will introduce somebias in the results, but we omit any correction for two rea-sons. First, we do not have data on years of schooling forGuyana and Trinidad and Tobago anyway. Second, Argentinaand Uruguay are the most urban countries our sample (eachwith an urbanization rate exceeding 90 percent), so that inthese two cases the bias is hopefully not large.


TABLE 7

RANKING BY AVERAGE YEARS OF SCHOOLING ACCUMULATEDIN THE FORMAL “1–12” SYSTEM

Ranking 5 Ranking 6 Ranking 7 Ranking 8Avg. yrs. Avg. yrs. of Avg. yrs. of Avg. yrs. ofin school at age 18 schooling at age 18 schooling at age 8 schooling at age 13

Country Years Country Years Country Years Country Years(1) (2) (3) (4) (5) (6) (5) (6)

Argentina 12.1 Chile 10.4 Jamaica 2.6 Jamaica 7.2Chile 12.1 Argentina 9.8 Ecuador 2.5 Argentina 6.5Dom. Rep. 11.8 Panama 9.5 Belize 2.1 Chile 6.4Jamaica 11.7 Peru 9.0 Uruguay 2.0 Uruguay 6.3Panama 11.5 Bolivia 8.9 Venezuela 1.9 Ecuador 6.3Brazil 11.4 Jamaica 8.8 Dom. Rep. 1.9 Mexico 6.2Uruguay 11.4 Uruguay 8.7 Mexico 1.8 Venezuela 6.1Bolivia 11.2 Ecuador 8.7 Chile 1.8 Bolivia 6.0Peru 11.1 Mexico 8.7 El Salvador 1.8 Panama 6.0Venezuela 11.0 Venezuela 8.6 Brazil 1.7 Belize 5.6Trin. & Tob. 11.0 Colombia 8.4 Bolivia 1.7 El Salvador 5.6Paraguay 10.7 Paraguay 8.4 Argentina 1.7 Peru 5.6Mexico 10.6 Dom. Rep. 8.3 Panama 1.5 Costa Rica 5.4Belize 10.6 El Salvador 8.0 Peru 1.5 Colombia 5.3Guyana 10.5 Costa Rica 7.8 Paraguay 1.5 Dom. Rep. 5.3Colombia 10.5 Brazil 7.3 Colombia 1.3 Brazil 5.3Costa Rica 10.5 Belize 6.6 Haiti 1.2 Paraguay 5.0Ecuador 10.4 Honduras 6.2 Nicaragua 1.2 Honduras 4.6El Salvador 10.0 Nicaragua 5.9 Costa Rica 1.1 Nicaragua 4.4Nicaragua 9.7 Haiti 5.9 Honduras 0.9 Guatemala 3.8Haiti 8.8 Guatemala 5.5 Guatemala 0.7 Haiti 3.4Honduras 8.6Guatemala 8.2

20 In other words, this is a blunt way to control for the factthat the interaction between factors such as the school cal-endar, school-starting cutoff months of birth, and the monthin which the survey is taken, will introduce constant differ-ences between these two measures across all age ranges.21 In general, that concept is measured using a “cohort analy-sis method,” which relies on administrative data that indi-cates the precise number of students who are promoted,repeat, and drop out of a given educational system (from dif-ferent cohorts entering the educational system). Naturally,our single cross section of household surveys does not allowus to implement such a measure. We could have also calcu-lated an age-grade distortion indicator, but our measure al-lows us to abstract from the fact that different countries havedifferent entry ages, as noted below.

Effectiveness gap = (avg. years in school – avg.years of schooling) –(avg. years in school at age6 – avg. years of schoolingat age 6)

where the last term is meant to capture that a con-stant difference might exist between these two mea-sures, as mentioned above, perhaps due to the monthat which the survey was collected (and how it inter-acts with the school calendar).20 Note also that thismeasure captures a concept similar to the one labeled“internal efficiency” in the educational literature.21

Finally, note that this measure is also attractive be-


TABLE 8RANKING BY EFFECTIVENESS GAP

Ranking 9 Ranking 10 Ranking 11Age 8 Age 13 Age 18

Country Gap Country Rate Country Rate(1) (2) (3) (4) (5) (6)

Uruguay 0.2 Argentina 0.5 Chile 0.9

Mexico 0.2 Mexico 0.6 Panama 1.1

El Salvador 0.5 Chile 0.7 Mexico 1.1

Venezuela 0.3 Uruguay 0.7 Colombia 1.3

Chile 0.3 Jamaica 0.9 Peru 1.3

Ecuador 0.3 Panama 0.9 Argentina 1.4

Argentina 0.4 Venezuela 0.9 Paraguay 1.5

Haiti 0.4 El Salvador 1.0 El Salvador 1.7

Guatemala 0.4 Ecuador 1.0 Ecuador 1.7

Belize 0.4 Bolivia 1.1 Guatemala 1.8

DominicanRepublic 0.5 Colombia 1.2 Venezuela 1.8

Panama 0.5 Costa Rica 1.3 Costa Rica 1.8

Paraguay 0.5 Peru 1.3 Honduras 1.8

Jamaica 0.5 Honduras 1.4 Bolivia 1.9

Peru 0.6 Guatemala 1.4 Uruguay 1.9

Bolivia 0.6 Paraguay 1.6 Jamaica 3.0

Brazil 0.6 Belize 1.8 Dom. Rep. 3.0

Nicaragua 0.6 Nicaragua 1.8 Haiti 3.1

Colombia 0.6 Brazil 1.9 Nicaragua 3.2

Costa Rica 0.8 Haiti 1.9 Belize 3.7

Honduras 0.8 Dom. Rep. 2.0 Brazil 3.7

cause it at least partially controls for differences incountries’ normative starting ages.22

Table 8 presents rankings based on the valuesthis measure takes at ages 8, 13, and 18 (using thedata provided in Appendix D, interested readers cangenerate it at any particular age). As expected, theaverage level of this gap grows with age, althoughmore so in some countries. Because these rankingstake countries’ enrollment performances as given, its

results are somewhat different from those seen above.For instance, Guatemala and Honduras no longerplace at the bottom, but closer to the median of the

22 For instance, if a country’s starting age is 7 rather than the moreusual 6, this will be captured in both the average years in schooland average years of schooling measures, and hence should notaffect countries’ relative position in terms of the effectiveness gap.


distribution. In other words, abstracting from theirrelative poor performance in getting kids in school,these two countries do “OK” in terms of turning at-tendance into years of schooling. Chile is at the topof the ranking, showing that its first place in “final”outcomes comes not only from high enrollment. Incontrast, Brazil, with well-known repetition prob-lems, ranks at the bottom of the table by age 18.

As in all cases above, the results also illustratethat countries’ performance is not static along theage range. Colombia is a good example of rapid im-provement, i.e., it seems to start with substantial rep-etition problems, which seem to get mitigated aschildren move on in school. Venezuela is an exampleof the opposite pattern.

From a policy point of view, the results we have pre-sented essentially highlight countries’ performancealong two dimensions: i) getting children into schoolin time and keeping them there, and ii) turning theircontact with the school system into years of school-ing. The different rankings we generated show thatperformance along these dimensions is not uniform—we cited many examples in which a given country’sranking in the same measure varies across age ranges.This implies that readers interested in understand-ing a specific country’s performance will be bestserved by looking at all these rankings together, andin fact by looking at the information in the appendi-ces, which is even more detailed and age-specific.

Bringing some results together

Nonetheless, many readers will also be interestedin some “bottom line” classification of countries. Weattempted to arrive at one by summarizing countriesoutcomes along the above two dimensions: enroll-ment and our measure of “effectiveness.” More spe-cifically, we first created four groups of countriesaccording to their enrollment performance. These arepresented in the four rows of Table 9. As one movesdown these rows one finds countries which have gen-erally made less progress in terms of getting childreninto school. Within each row, countries are simplypresented in alphabetical order.

We generated these groups simply by averagingrankings 2, 3, 4, 2b, 3b, and 4b. That is, by taking a

TABLE 9A “BOTTOM LINE” ORDERING OF COUNTRIES

BY ATTENDANCE AND EFFECTIVENESS

Enrollment group Effectiveness group

1 2 3 4(Best (Worst

performance) performance)

1 (Best performance) Argentina Jamaica Dom. Rep.

Chile

Panama

Uruguay

2 Bolivia Paraguay Belize

Peru Peru Brazil

Venezuela

3 Mexico Colombia Costa Rica

Ecuador Paraguay

4 (Worst performance) El Salvador Guatemala Haiti NicaraguaHonduras


simple average of countries’ urban and rural enroll-ment performance in the three age ranges we focusedon: 6–7, 8–13, and 14–18.23 We then took this aver-age and used it to separate all cases into four roughlyequally sized groups.

The four columns in turn order countries bytheir relative performance in the effectiveness mea-sure we introduced above—the gap between aver-age years in school and average years ofschooling—where those in the left-most column arethe best performers. In this case we simply averagedrankings 9, 10, and 11 (all at the national level–ex-cept again in countries with urban area-only sur-veys), which capture countries’ performance at ages8, 13, and 18. We then again used the average todivide the countries into four roughly equally sizedgroups.

The rows indicate that the best performers interms of enrollment are Argentina, Chile, the Domini-can Republic, Jamaica, Panama, and Uruguay. Thecolumns suggest, however, that within this group,Jamaica and particularly the Dominican Republicperform much worse in turning children’s contactwith the school system into years of schooling.

At the opposite extreme, El Salvador, Guatemala,Haiti, Honduras, and Nicaragua do worst in enroll-ment. But again there is variance in their “effective-ness”: El Salvador does as well as Argentina, Chile,Panama, or Uruguay in this regard, given the atten-dance patterns it starts with. Nicaragua, in contrast,does as poorly as the Dominican Republic.

The countries in the two middle rows are some-what more similar in that minor changes in theweighting schemes can result in countries crossingfrom the 2nd to the 3rd group, and vice versa, i.e., thecountries in these two rows are not as clearly differ-entiated—although they are rather more clearly dif-ferentiated from the best and worst and bestperformers (rows 1 and 4).

As far as “effectiveness,” Mexico is the best per-former in this middle group, and Belize and Brazilare the worst. The last two are probably the clearestexamples (along with the Dominican Republic ingroup 1) of countries that enroll children with sub-stantial success, but whose systems are then verymuch afflicted by repetition or other problems (ourdata cannot reveal which specifically).

In short, Table 9 provides a summary of coun-tries’ performance along the dimensions we have fo-cused on using comparable household survey data.We experimented with alternate ways of ordering thecountries, and as we stated, found that it is possibleto get the countries in the middle two rows to movearound a bit (e.g. Bolivia and Costa Rica might switchplaces). Nonetheless, the overall distribution remainssimilar, and the bottom line is that readers interestedin a particular country should focus on the range ofboxes close to the one this country occupies—thisyields an idea of the type of challenges this country’seducational system faces in a comparative perspec-tive. Further, as emphasized above, such readers willwant to focus on the more detailed data available inthe appendices.

23 This again raises the issue of the countries with urban-only samples: Argentina, Guyana, Haiti, Trinidad and To-bago, and Uruguay. We do not introduce any correction forthis (that is, we use only their urban enrollment rates in thecalculation) for several reasons. First, Guyana and Trinidadand Tobago are excluded from Table 9 anyway because wedo not have information on years of schooling and henceeffectiveness for them. Based on attendance data only, theywould be in the middle groups (2 and 3). Second, Haiti is inthe last group by enrollment anyway, and considering itsrural area as well would in all likelihood make its perfor-mance look even worse, and hence have no effect on thisaggregate ranking. Finally, Argentina and Uruguay are themost urban countries in the region, so that excluding theirrural populations hopefully does not produce a large bias.

A final measure we consider arises because one mightlike to know how unequally a given attainment levelis distributed within a country. To get a sense of thisin a simple way, we look at the years of schoolingobserved at the 25th and 75th percentiles of the yearsof schooling distribution.24 For an illustration, Fig-ure 3 again plots the maximum feasible attainmentand the mean years of schooling for Chile and Hon-duras, but additionally presents the 25th and 75th per-centile of the years of schooling distribution (figuresand data for all countries are in appendices E and F,respectively).

By this measure inequality increases in both ofthese countries at very early ages. One can see thisbecause while the mean and the 75th percentile startincreasing immediately with age, the attainment atthe 25th percentile is essentially zero until ages 7 and8 in Chile and Honduras, respectively. The 25th and

75th percentiles then move in lockstep in Chile up toage 15, and up to age 10 in Honduras. In other words,in these age ranges children at these two places ofthe distribution accumulate years of schooling essen-tially at the same pace. In Honduras, the two seg-ments then diverge significantly—by age 18, there isa difference of about 4 years of attainment between

Some further results on inequality

FIGURE 3MAXIMUM SCHOOLING, AVERAGE YEARS IN SCHOOL,

AND AVERAGE YEARS OF SCHOOLING IN CHILE AND HONDURAS

24 In other words, suppose that a country has 100 fifteenyear olds, and that one orders them from the individual withthe least years of schooling to the one with the most. Thesemeasures would pick up the number of years of schoolingthat the 25th and the 75th individuals have. In a country withno inequality of attainment (say one in which every childenters school at the same age and no one ever repeats), thesetwo would be equal, and the gap between them (which weconsider below) would be zero.

Age

Max. feasible attainment Avg. years of schooling 75th percentile 25th percentile

0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Chile Honduras

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s


children at the 25th and 75th percentile of the years ofschooling distribution.

Using these measures, Table 10 presents a rank-ing of countries according to the difference in theyears of schooling at the 25th and 75th percentile ofthe distribution. Rankings 12 and 13 are based onthe absolute difference, taken at ages 13 and 18,respectively. As this shows, at age 13, the most equalcountry by this measure is Belize, with no differ-ence in the attainment of children at the 25th and75th percentile. At the other extreme is Guatemala,in which the difference even at this relatively youngage is already equal to 4 years. This reflects that anon-negligible portion of 13 year olds in this coun-try have only one or even zero years of schooling.

By age 18 (Ranking 13), the best performeris still Belize, joined by Chile in displaying aninter-quartile range of only two. Differences aregenerally much greater by this point, however,and at the other extreme, Nicaragua, Haiti, Bra-zil, El Salvador, and Guatemala display a differ-ence of at least six years.

We also experimented by normalizing thesegaps by countries’ mean attainment. There is somemovement in the observed rankings, but we omitthem because the changes this produces are notsubstantial. In part, this reflects that countries withsmall absolute differences also tend to have rela-tively high attainment.

TABLE 10RANKINGS BASED ON INTER-QUARTILE

RANGES OF YEARS OF SCHOOLING

Ranking 12 Ranking 13

Absolute differenceat Absolute difference at age 13 at age 18

Country Diff. Country Rate(1) (2) (3) (4)

Belize 0 Belize 2Argentina ChileChile Jamaica 3Costa Rica PeruEcuador ArgentinaJamaica 1 BoliviaMexico Costa RicaPanama Dominican Republic 4Uruguay Costa RicaVenezuela HondurasBolivia MexicoParaguay 2 PanamaPeru UruguayBrazil ColombiaColombia Paraguay 5Dominican Republic VenezuelaEl Salvador 3 NicaraguaHaiti Haiti 6Honduras El SalvadorNicaragua BrazilGuatemala 4 Guatemala 7

While we have focused exclusively on the “1–12”educational system, we close the paper with some

Enrollments in higher educational levels

data on the enrollment rates in post-secondary edu-cation among 18–25 year olds (these rates exclude

TABLE 11ENROLLMENT RATE IN POST-SECONDARY SCHOOLING

AMONG 18-25 YEAR OLDS

Total enrollment For countries in which a distinctionrate in post-secondary between university and other types

institutions of post-secondary studies is possible:

Other postUniversity secondary studies

Country (1) (2) (3)

Argentina 28.3 23.3 5.0Uruguay 20.6 15.0 5.6Chile 17.7 12.8 4.9Venezuela1 16.3 10.9 5.4Panama 15.9 15.7 0.2Colombia 15.2 – –Bolivia 14.9 12.3 2.6Mexico 14.5 11.5 3.0Dominican Republic 13.5 13.3 0.2Peru 13.1 8.4 4.7El Salvador 13.0 12.1 0.9Ecuador 11.8 – –Costa Rica 11.5 11.0 0.5Paraguay 9.1 6.7 2.4Nicaragua 8.3 7.9 0.4Brazil 7.2 – –Jamaica 6.4 1.7 4.7Honduras 6.0 5.5 0.5Guatemala 4.7 – –Trinidad & Tobago 4.4 2.3 2.2Haiti 3.1 1.1 2.1Belize 2.6 – –Guyana 0.7 0.5 0.2

Note: 1For Venezuela, the enrollment rates are for 18-21 year olds only.


they are in university or some other type of post-sec-ondary education. This includes, for instance, tech-nical training. We do not attempt finer distinctionsbecause it is very difficult to achieve consistent defi-nitions across countries.

Interestingly, the variability in the non-univer-sity enrollment rates is much larger. It turns out, forinstance, that Chile, Jamaica and Peru have the larg-est proportionate enrollments of this type (while incontrast the former two countries have relatively lowoverall post-secondary enrollment rates). These re-sults must be viewed with caution, however, becausethey could be partially driven by the way in whichcountries organize post-secondary training. In some,for instance, teachers will be trained within univer-sities (and hence counted in Column 2), while inothers they study in independent, stand-alone teachertraining institutes.

people still attending the “1–12” system). Of course,here it is less obviously the case that higher enroll-ments are more desirable, all else equal, if only be-cause few governments declare a specific intent toraise, let alone universalize, enrollments at the highereducational level. Additionally, there is often a con-cern that expenditure at this level is less “progres-sive” than at lower educational levels.

Nonetheless, we present this information in theform of a ranking in Table 11. The data show thatArgentina, Uruguay and Chile have the highest post-secondary enrollment rates, followed by Venezuela,Panama, and Colombia. Interestingly countries’ rankat this level is not tightly related to their performancein primary and secondary. For instance, Jamaica,which was in the first attendance group in Table 9,ranks rather close to the bottom here. Trinidad andTobago, Belize, and Guyana also display this behav-ior, so in part this is a Caribbean phenomenon.25 Incontrast, there are countries that gain here relative totheir previous overall position, such as El Salvador.

For the countries for which it is possible, col-umns 2 and 3 distinguish enrollments by whether

25 We thank Juan Carlos Navarro for this observation.

Comparing educational enrollment and attainmentacross countries in the LAC region is a challenge. Atsome level, one begins the exercise comparing applesand oranges because data in different countries arecollected using different definitions and instruments.Even setting this problem aside, policy makers some-times believe that in comparing countries like Chileand Honduras, one is also comparing apples and or-anges—i.e., the educational situations and problemsof such countries are so diverse that they should betreated separately.

In this paper, we have sought to deal with thefirst issue by using household surveys to generatewhat is hopefully more comparable cross-countryinformation. Specifically, we calculated four simpleindicators: i) age-specific net enrollment ratios, ii) ameasure of the average number of years childrenspend in school, iii) a measure of the average num-ber of years of schooling they actually complete, andiv) the gap between the last two, which we term “ef-fectiveness.”

We then used these measures to produce a num-ber of rankings and a “bottom line” classification thathighlight countries’ performance in terms of twogoals: i) getting children into school on time and

keeping them there, and ii) turning their contact withthe educational system into years of schooling.

The results suggest that in LAC countries, over-all enrollment rates are relatively high and that there-fore on average children spend a substantial numberof years in school. At least by this measure, these so-cieties spend a lot of resources on education. Thereis nevertheless wide variation in how well differentsystems have done in terms of reducing delayed en-try and raising secondary enrollments; and there arealso substantial differences in how effectively theireducational systems turn children’s time in schoolinto actual grades completed.

Further, calculating multiple rankings and clas-sifications turns out to be useful because countries’performance along these dimensions is not uniform.For instance, the Dominican Republic performs al-most as well as the richest countries in the region interms of enrollment, but as badly as the poorest groupin terms of “effectiveness” (turning attendance intoyears of schooling). Similarly, there are countrieswhich have been relatively successful at increasingsecondary enrollment, and yet are relative under-per-formers in terms of reducing delayed entry (e.g.,Chile, one of the richest in the region).

Conclusion

References

Clemens, M. (2004) The long walk to school: Interna-tional education goals in historical perspective.Mimeo, Center for Global Development.

Filmer, D. and L. Pritchett (1999) The Effect of House-hold Wealth on Educational Attainment: Evidencefrom 35 Countries, Population and Develop-ment Review 25(1).

Maluccio, J. and Flores, R. (1994) An evaluation of aconditional cash transfer program: The Nicara-guan “Red de Proteccion Social”. Mimeo, Inter-national Food Policy Research Institute.

Glewwe, P. and H. Jacoby (1995) An Economic Analy-sis of Delayed Primary School Enrollment in a LowIncome Country: The Role of Early ChildhoodNutrition, The Review of Economics and Sta-tistics, Vol. 77, No. 1. (Feb., 1995), pp. 156-169.

Urquiola, M. (2000) Universal education, in Defeat-ing poverty: Eight goals at a time. La Paz:EDOBOL. 2000.

APPENDIX A

AGE SPECIFIC NET ENROLLMENT RATIOS — FIGURES


0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Argentina

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Bolivia

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Chile

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Belize

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

eBrazil

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Colombia

.2.4

.5.6

.81

Age


APPENDIX A



0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Costa Rica

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Ecuador

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Guatemala

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Dominican Republic

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

eEl Salvador

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Guyana

.2.4

.5.6

.81

Age

APPENDIX A 33

APPENDIX A



0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Haiti

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Jamaica

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Nicaragua

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Honduras

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

eMexico

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Panama

.2.4

.5.6

.81

Age


APPENDIX A



0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Paraguay

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Trinidad and Tobago

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Venezuela

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Peru

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

eUruguay

.2.4

.5.6

.81

Age

APPENDIX BAGE SPECIFIC NET ENROLLMENT RATIOS – DATA

Urban

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Argentina 0.984 0.992 0.997 0.992 0.993 0.991 0.989 0.976 0.967 0.937 0.847 0.772 0.680

Belize 0.992 0.989 1.000 1.000 0.985 0.982 0.984 0.945 0.892 0.810 0.755 0.611 0.496

Bolivia 0.869 0.972 0.983 0.982 0.978 0.974 0.936 0.969 0.947 0.909 0.882 0.851 0.759

Brazil 0.851 0.954 0.974 0.979 0.975 0.981 0.972 0.952 0.931 0.880 0.821 0.741 0.611

Chile 0.891 0.989 0.991 0.993 0.992 0.993 0.988 0.985 0.976 0.958 0.920 0.877 0.703

Colombia 0.920 0.950 0.941 0.965 0.949 0.953 0.947 0.895 0.897 0.836 0.773 0.629 0.485

C. Rica 0.945 0.987 0.986 0.983 0.990 0.984 0.961 0.904 0.884 0.785 0.694 0.661 0.536

Dom.Rep. 0.939 0.953 0.971 0.981 0.990 0.972 0.992 0.993 0.961 0.920 0.863 0.798 0.689

Ecuador 0.938 0.949 0.962 0.972 0.956 0.881 0.930 0.881 0.832 0.798 0.789 0.700 0.558

El Salv. 0.753 0.917 0.956 0.960 0.959 0.940 0.937 0.912 0.865 0.852 0.757 0.638 0.529

Guatemala 0.827 0.883 0.928 0.903 0.927 0.880 0.876 0.742 0.668 0.597 0.577 0.459

Guyana 0.940 0.969 0.965 0.983 0.974 0.971 0.973 0.923 0.820 0.792 0.610 0.335 0.237

Haiti 0.349 0.503 0.611 0.662 0.740 0.765 0.804 0.766 0.793 0.775 0.756 0.707 0.614

Honduras 0.645 0.881 0.942 0.943 0.959 0.948 0.909 0.781 0.692 0.626 0.545 0.540 0.436

Jamaica 1.000 1.000 1.000 0.984 1.000 1.000 0.981 1.000 1.000 0.946 0.833 0.691 0.474

Mexico 0.970 0.980 0.975 0.976 0.970 0.984 0.957 0.899 0.916 0.743 0.753 0.545 0.529

Nicaragua 0.721 0.909 0.890 0.956 0.942 0.948 0.949 0.949 0.834 0.828 0.690 0.630 0.527

Panama 0.956 0.988 0.994 0.992 0.997 0.999 0.975 0.954 0.966 0.895 0.837 0.780 0.623

Paraguay 0.945 0.934 0.991 0.988 0.982 0.992 0.985 0.947 0.904 0.843 0.783 0.678 0.553

Peru 0.974 0.972 0.984 0.972 0.986 0.992 0.967 0.983 0.897 0.888 0.838 0.616 0.496

T & T 0.960 0.963 1.000 0.993 1.000 0.981 0.956 0.842 0.896 0.861 0.672 0.535 0.339

Uruguay 0.960 0.992 0.994 0.974 0.982 0.996 0.981 0.949 0.883 0.819 0.725 0.669 0.486

Venezuela 0.959 0.984 0.971 0.978 0.985 0.984 0.985 0.953 0.955 0.850 0.789 0.576 0.440



Nationwide

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Belize 0.915 0.972 0.991 0.996 0.988 0.985 0.976 0.930 0.770 0.649 0.570 0.484 0.353

Bolivia 0.791 0.959 0.976 0.981 0.972 0.955 0.913 0.911 0.853 0.803 0.774 0.710 0.648

Brazil 0.818 0.941 0.969 0.976 0.974 0.977 0.966 0.940 0.914 0.862 0.786 0.709 0.585

Chile 0.877 0.989 0.989 0.992 0.990 0.992 0.985 0.983 0.966 0.944 0.893 0.840 0.663

Colombia 0.855 0.919 0.931 0.950 0.934 0.937 0.899 0.837 0.810 0.737 0.692 0.553 0.423

C. Rica 0.893 0.980 0.974 0.980 0.972 0.975 0.922 0.852 0.736 0.649 0.573 0.519 0.437

Dom.Rep. 0.911 0.935 0.963 0.972 0.988 0.971 0.982 0.985 0.949 0.908 0.848 0.777 0.653

Ecuador 0.905 0.939 0.952 0.963 0.946 0.889 0.880 0.797 0.729 0.672 0.658 0.588 0.451

El Salv. 0.673 0.841 0.893 0.933 0.909 0.909 0.892 0.848 0.773 0.724 0.627 0.523 0.418

Guatemala 0.713 0.825 0.863 0.862 0.854 0.833 0.740 0.599 0.469 0.386 0.360 0.281

Honduras 0.568 0.828 0.901 0.913 0.919 0.893 0.820 0.680 0.547 0.472 0.387 0.366 0.267

Jamaica 1.000 1.000 1.000 0.993 1.000 1.000 0.992 0.979 0.991 0.931 0.827 0.615 0.360

Mexico 0.938 0.965 0.975 0.977 0.967 0.967 0.939 0.880 0.841 0.652 0.626 0.465 0.405

Nicaragua 0.628 0.836 0.864 0.920 0.895 0.893 0.875 0.847 0.756 0.724 0.548 0.486 0.392

Panama 0.922 0.976 0.993 0.992 0.991 0.991 0.957 0.922 0.907 0.823 0.748 0.685 0.546

Paraguay 0.868 0.913 0.975 0.965 0.970 0.976 0.934 0.878 0.807 0.712 0.643 0.579 0.480

Peru 0.934 0.977 0.968 0.973 0.986 0.979 0.955 0.938 0.854 0.807 0.747 0.562 0.468

Venezuela 0.926 0.959 0.978 0.974 0.974 0.971 0.961 0.927 0.876 0.785 0.684 0.541 0.450

APPENDIX B 37


Rural

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Belize 0.875 0.961 0.985 0.993 0.990 0.988 0.969 0.916 0.683 0.519 0.381 0.359 0.240

Bolivia 0.686 0.941 0.966 0.979 0.963 0.923 0.882 0.807 0.698 0.605 0.522 0.402 0.388

Brazil 0.718 0.901 0.954 0.965 0.969 0.962 0.949 0.903 0.861 0.799 0.664 0.585 0.483

Chile 0.795 0.987 0.978 0.988 0.982 0.986 0.970 0.968 0.905 0.859 0.727 0.613 0.407

Colombia 0.768 0.883 0.920 0.932 0.914 0.910 0.841 0.763 0.692 0.606 0.569 0.436 0.319

C. Rica 0.852 0.976 0.965 0.979 0.958 0.966 0.892 0.811 0.627 0.532 0.476 0.391 0.329

Dom.Rep. 0.863 0.913 0.950 0.958 0.984 0.969 0.970 0.971 0.933 0.886 0.822 0.735 0.578

Ecuador 0.851 0.925 0.937 0.948 0.933 0.901 0.817 0.675 0.561 0.483 0.439 0.368 0.253

El Salv. 0.582 0.764 0.831 0.900 0.860 0.875 0.844 0.778 0.670 0.575 0.483 0.384 0.277

Guatemala 0.656 0.794 0.826 0.841 0.818 0.807 0.654 0.510 0.357 0.267 0.234 0.161

Honduras 0.510 0.800 0.873 0.890 0.894 0.852 0.768 0.609 0.451 0.353 0.237 0.211 0.098

Jamaica 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.962 0.986 0.915 0.823 0.537 0.241

Mexico 0.899 0.945 0.975 0.980 0.964 0.947 0.917 0.854 0.742 0.533 0.447 0.345 0.206

Nicaragua 0.517 0.752 0.832 0.877 0.845 0.825 0.778 0.730 0.649 0.570 0.356 0.272 0.200

Panama 0.888 0.962 0.992 0.991 0.985 0.981 0.939 0.881 0.812 0.720 0.613 0.536 0.413

Paraguay 0.788 0.891 0.961 0.945 0.960 0.964 0.892 0.817 0.718 0.556 0.478 0.454 0.361

Peru 0.887 0.984 0.950 0.975 0.985 0.963 0.936 0.882 0.788 0.691 0.603 0.456 0.415

Venezuela 0.921 0.956 0.979 0.974 0.973 0.970 0.957 0.924 0.864 0.776 0.671 0.535 0.452


APPENDIX C

AVERAGE YEARS IN SCHOOL AND AVERAGE YEARS OF SCHOOLING

0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Argentina

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Bolivia

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Chile

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

00

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

Belize

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Brazil

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Colombia

Age


APPENDIX C 39

APPENDIX C


0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

00

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age


Costa Rica

Ecuador

Guatemala

Dominican Republic

El Salvador

Guyana


APPENDIX C


0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

00

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age


Haiti

Jamaica

Nicaragua

Honduras

Mexico

Panama

APPENDIX C 41

APPENDIX C



0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Paraguay

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Trinidad and Tobago

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Venezuela

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

e

Peru

.2.4

.5.6

.81

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Net e

nrol

lmen

t rat

eUruguay

.2.4

.5.6

.81

Age


APPENDIX DAVERAGE YEARS IN SCHOOL AND AVERAGE YEARS OF SCHOOLING

Average years in school

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Argentina 0.98 1.98 2.97 3.97 4.96 5.95 6.94 7.91 8.88 9.82 10.67 11.44 12.12

Belize 0.92 1.89 2.88 3.87 4.86 5.85 6.82 7.75 8.52 9.17 9.74 10.23 10.58

Bolivia 0.79 1.75 2.73 3.71 4.68 5.63 6.55 7.46 8.31 9.11 9.89 10.60 11.25

Brazil 0.82 1.76 2.73 3.70 4.68 5.65 6.62 7.56 8.48 9.34 10.12 10.83 11.42

Chile 0.88 1.87 2.86 3.85 4.84 5.83 6.81 7.80 8.76 9.71 10.60 11.44 12.10

Colombia 0.86 1.77 2.71 3.66 4.59 5.53 6.43 7.26 8.07 8.81 9.50 10.06 10.48

C. Rica 0.89 1.87 2.85 3.83 4.80 5.77 6.70 7.55 8.28 8.93 9.51 10.03 10.46

Dom.Rep. 0.91 1.85 2.81 3.78 4.77 5.74 6.72 7.71 8.66 9.56 10.41 11.19 11.84

Ecuador 0.91 1.84 2.80 3.76 4.71 5.59 6.47 7.27 8.00 8.67 9.33 9.92 10.37

El Salv. 0.67 1.51 2.41 3.34 4.25 5.16 6.05 6.90 7.67 8.39 9.02 9.54 9.96

Guatemala 1.13 1.96 2.82 3.68 4.53 5.37 6.11 6.70 7.17 7.56 7.92 8.20

Guyana 0.94 1.91 2.87 3.86 4.83 5.80 6.77 7.70 8.52 9.31 9.92 10.25 10.49

Haiti 0.35 0.85 1.46 2.13 2.87 3.63 4.43 5.20 5.99 6.77 7.53 8.23 8.85

Honduras 0.57 1.40 2.30 3.21 4.13 5.02 5.84 6.52 7.07 7.54 7.93 8.29 8.56

Jamaica 1.00 2.00 3.00 3.99 4.99 5.99 6.99 7.96 8.96 9.89 10.71 11.33 11.69

Mexico 0.94 1.90 2.88 3.85 4.82 5.79 6.73 7.61 8.45 9.10 9.73 10.19 10.60

Nicaragua 0.63 1.46 2.33 3.25 4.14 5.04 5.91 6.76 7.51 8.24 8.79 9.27 9.66

Panama 0.92 1.90 2.89 3.88 4.87 5.86 6.82 7.74 8.65 9.47 10.22 10.91 11.45

Paraguay 0.87 1.78 2.76 3.72 4.69 5.67 6.60 7.48 8.29 9.00 9.64 10.22 10.70

Peru 0.93 1.91 2.88 3.85 4.84 5.82 6.77 7.71 8.56 9.37 10.12 10.68 11.15

T & T 0.96 1.92 2.92 3.92 4.92 5.90 6.85 7.69 8.59 9.45 10.12 10.66 11.00

Uruguay 0.96 1.95 2.95 3.92 4.90 5.90 6.88 7.83 8.71 9.53 10.26 10.92 11.41

Venezuela 0.93 1.88 2.86 3.84 4.81 5.78 6.74 7.67 8.54 9.33 10.01 10.55 11.00

APPENDIX D 43

APPENDIX DAVERAGE YEARS IN SCHOOL AND AVERAGE YEARS OF SCHOOLING

Average years of schooling

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Argentina 0.06 0.78 1.69 2.61 3.49 4.50 5.50 6.50 7.37 8.05 8.56 9.23 9.77

Belize 0.58 1.28 2.13 3.01 3.82 4.69 5.26 5.62 5.97 6.26 6.59 6.91 6.56

Bolivia 0.34 0.92 1.72 2.61 3.38 4.44 4.69 5.96 6.56 7.28 8.18 8.98 8.90

Brazil 0.40 1.03 1.74 2.44 3.21 3.94 4.62 5.25 5.89 6.47 6.95 7.28 7.27

Chile 0.15 0.84 1.81 2.73 3.65 4.65 5.51 6.42 7.30 8.22 9.02 9.77 10.43

Colombia 0.12 0.61 1.33 2.18 2.95 3.87 4.51 5.32 6.08 6.78 7.49 7.95 8.43

C. Rica 0.02 0.31 1.15 1.89 2.78 3.66 4.51 5.37 6.01 6.51 6.97 7.42 7.76

Dom.Rep. 0.45 1.05 1.88 2.52 3.22 3.78 4.63 5.29 6.02 6.73 7.42 8.20 8.34

Ecuador 0.92 1.66 2.47 3.37 4.06 4.74 5.64 6.28 6.95 7.47 8.14 8.54 8.68

El Salv. 0.33 1.03 1.78 2.61 3.24 4.11 4.82 5.58 6.15 6.91 7.39 7.62 7.95

Guatemala 0.22 0.67 1.19 1.83 2.42 3.07 3.76 4.01 4.52 4.90 5.11 5.49

Haiti 0.47 0.76 1.22 1.65 2.12 2.49 3.03 3.40 4.06 4.60 5.02 5.68 5.87

Honduras 0.01 0.24 0.91 1.67 2.45 3.24 3.93 4.59 5.00 5.53 5.94 6.16 6.16

Jamaica 1.11 1.72 2.63 3.45 4.54 5.31 6.26 7.21 8.08 9.01 9.35 9.71 8.76

Mexico 0.11 0.93 1.82 2.75 3.57 4.53 5.47 6.20 7.09 7.77 8.31 8.26 8.65

Nicaragua 0.09 0.58 1.18 1.85 2.42 3.00 3.74 4.38 5.12 5.71 5.88 6.20 5.95

Panama 0.03 0.67 1.53 2.49 3.49 4.43 5.29 5.96 6.98 7.77 8.39 9.13 9.46

Paraguay 0.08 0.67 1.48 2.30 3.06 3.79 4.61 5.05 5.38 6.27 7.05 7.62 8.37

Peru 0.12 0.84 1.52 2.41 3.28 4.20 4.96 5.56 6.36 7.13 7.94 8.62 9.02

Uruguay 0.18 1.04 1.96 2.79 3.68 4.62 5.59 6.33 6.96 7.84 8.33 8.64 8.72

Venezuela 0.29 1.11 1.92 2.83 3.64 4.52 5.37 6.09 6.70 7.28 7.87 8.28 8.57


APPENDIX D:AVERAGE YEARS IN SCHOOL AND AVERAGE YEARS OF SCHOOLING

Effectiveness gap at each age

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Argentina 0.000 0.273 0.355 0.429 0.541 0.519 0.507 0.487 0.588 0.842 1.178 1.284 1.417

Belize 0.000 0.271 0.412 0.528 0.704 0.817 1.224 1.798 2.216 2.577 2.814 2.983 3.682

Bolivia 0.000 0.379 0.558 0.648 0.853 0.740 1.403 1.049 1.305 1.382 1.254 1.170 1.894

Brazil 0.000 0.307 0.570 0.840 1.043 1.296 1.581 1.888 2.159 2.444 2.749 3.131 3.724

Chile 0.000 0.302 0.324 0.398 0.464 0.451 0.578 0.658 0.741 0.762 0.859 0.948 0.949

Colombia 0.000 0.424 0.638 0.736 0.901 0.926 1.178 1.203 1.261 1.294 1.277 1.365 1.312

C. Rica 0.000 0.691 0.829 1.064 1.149 1.246 1.312 1.303 1.404 1.554 1.660 1.734 1.828

Dom.Rep. 0.000 0.341 0.477 0.803 1.092 1.502 1.633 1.960 2.175 2.377 2.538 2.528 3.042

Ecuador 0.000 0.200 0.339 0.407 0.662 0.871 0.850 1.002 1.064 1.220 1.207 1.394 1.705

El Salv. 0.000 0.137 0.285 0.380 0.662 0.700 0.884 0.970 1.178 1.143 1.288 1.583 1.665

Guatemala 0.000 0.381 0.722 0.938 1.200 1.385 1.437 1.786 1.743 1.755 1.896 1.804

Haiti 0.000 0.212 0.366 0.599 0.866 1.260 1.526 1.923 2.062 2.289 2.629 2.677 3.102

Honduras 0.000 0.603 0.829 0.987 1.125 1.223 1.354 1.375 1.518 1.453 1.434 1.576 1.844

Jamaica 0.000 0.391 0.484 0.650 0.565 0.789 0.835 0.862 0.982 0.982 1.476 1.730 3.040

Mexico 0.000 0.136 0.224 0.274 0.425 0.431 0.430 0.574 0.532 0.503 0.584 1.095 1.113

Nicaragua 0.000 0.345 0.607 0.856 1.181 1.491 1.635 1.836 1.858 1.985 2.369 2.532 3.177

Panama 0.000 0.339 0.478 0.502 0.498 0.541 0.640 0.896 0.780 0.815 0.947 0.883 1.104

Paraguay 0.000 0.321 0.484 0.630 0.842 1.086 1.201 1.643 2.113 1.943 1.799 1.814 1.544

Peru 0.000 0.264 0.549 0.631 0.747 0.805 1.001 1.340 1.390 1.435 1.373 1.251 1.316

Uruguay 0.000 0.140 0.213 0.358 0.445 0.505 0.517 0.727 0.973 0.917 1.152 1.513 1.915

Venezuela 0.000 0.141 0.312 0.379 0.538 0.632 0.738 0.943 1.211 1.416 1.513 1.642 1.805

APPENDIX E

YEARS OF SCHOOLING AT THE 25TH AND 75TH PERCENTILE

0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Argentina

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Bolivia

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Chile

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

00

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

Belize

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Brazil

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Colombia

Age



APPENDIX E


0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

00

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

Costa Rica

Ecuador

Guatemala

Dominican Republic

El Salvador

Guyana


APPENDIX E 47

APPENDIX E


0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

00

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

Haiti

Jamaica

Nicaragua

Honduras

Mexico

Panama



APPENDIX E


0

2

4

6

8

10

12

0

2

4

6

8

10

12

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

Age

0

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Year

s

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Year

s

Year

s

0

2

4

6

8

10

12

Year

s

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

Paraguay

Trinidad and Tobago

Venezuela

Peru

Uruguay


APPENDIX FYEARS OF SCHOOLING AT THE 25TH AND 75TH PERCENTILE

Years of schooling at the 25th percentile

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Argentina 0 0 1 2 3 4 5 6 7 7 8 8 8

Belize 0 1 2 3 3 4 5 6 6 6 6 6 6

Bolivia 0 0 1 2 3 4 4 5 5 6 7 8 7

Brazil 0 1 1 2 3 3 4 4 5 5 5 5 5

Chile 0 0 1 2 3 4 5 6 7 8 8 9 10

Colombia 0 0 1 1 2 3 4 4 5 5 6 6 6

C. Rica 0 0 1 1 2 3 4 5 6 6 6 6 6

Dom.Rep. 0 0 1 2 2 3 3 4 5 5 6 7 7

Ecuador 0 1 2 3 3 4 5 6 6 6 6 6 6

El Salv. 0 1 1 2 2 3 4 4 5 5 6 5 5

Guatemala 0 0 0 1 1 2 2 2 2 3 2 2

Haiti 0 0 0 0 1 1 1 2 2 3 3 3 3

Honduras 0 0 0 1 2 2 3 3 4 4 5 5 4

Jamaica 1 1 2 3 4 5 6 7 8 9 9 9 8

Mexico 0 1 1 2 3 4 5 6 6 6 7 6 6

Nicaragua 0 0 0 1 1 2 2 3 4 4 4 4 3

Panama 0 0 1 2 3 4 5 6 6 7 7 8 8

Paraguay 0 0 1 2 2 3 4 4 5 6 6 6 6

Peru 0 0 1 2 3 4 5 5 5 6 7 7 8

Uruguay 0 1 2 2 3 4 5 6 6 7 7 7 7

Venezuela 0 1 1 2 3 4 5 6 6 6 6 6 6



Years of schooling at the 75th percentile

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Argentina 0 1 2 3 4 5 6 7 8 9 10 11 12

Belize 1 2 3 4 4 6 6 6 6 7 7 8 8

Bolivia 1 1 2 3 4 5 6 7 8 9 10 11 11

Brazil 0 1 2 3 4 5 6 7 8 8 9 10 11

Chile 0 1 2 3 4 5 6 7 8 9 10 11 12

Colombia 0 1 2 3 4 5 6 7 8 8 9 10 11

C. Rica 0 1 2 2 3 4 5 6 7 8 9 10 10

Dom.Rep. 1 2 3 3 4 5 6 7 8 9 9 11 11

Ecuador 1 2 3 4 5 6 6 7 8 9 10 11 12

El Salv. 1 1 2 3 4 5 6 7 8 9 10 10 11

Guatemala 0 1 2 3 4 4 6 6 6 7 8 9

Haiti 1 1 2 3 3 4 5 5 6 6 7 8 9

Honduras 0 0 1 2 3 4 5 6 6 7 8 8 8

Jamaica 1 2 3 4 5 6 7 8 9 10 11 11 11

Mexico 0 1 2 3 4 5 6 7 8 9 10.5 10.5 10.5

Nicaragua 0 1 2 3 4 5 5 6 7 8 8 9 9

Panama 0 1 2 3 4 5 6 7 8 9 10 11 12

Paraguay 0 1 2 3 4 5 6 6 6 8 9 10 11

Peru 0 1 2 3 4 5 6 7 8 8 10 11 11

Uruguay 0 1 2 3 4 5 6 7 8 9 10 11 11

Venezuela 1 2 2 3 4 5 6 7 8 9 10 10 11

APPENDIX F 51


Absolute gap between 75th and 25th percentile (years of schooling)

Ages

Country 6 7 8 9 10 11 12 13 14 15 16 17 18

Argentina 0 1 1 1 1 1 1 1 1 2 2 3 4

Belize 1 1 1 1 1 2 1 0 0 1 1 2 2

Bolivia 1 1 1 1 1 1 2 2 3 3 3 3 4

Brazil 0 0 1 1 1 2 2 3 3 3 4 5 6

Chile 0 1 1 1 1 1 1 1 1 1 2 2 2

Colombia 0 1 1 2 2 2 2 3 3 3 3 4 5

C. Rica 0 1 1 1 1 1 1 1 1 2 3 4 4

Dom.Rep. 1 2 2 1 2 2 3 3 3 4 3 4 4

Ecuador 1 1 1 1 2 2 1 1 2 3 4 5 6

El Salv. 1 0 1 1 2 2 2 3 3 4 4 5 6

Guatemala 0 1 2 2 3 2 4 4 4 4 6 7

Haiti 1 1 2 3 2 3 4 3 4 3 4 5 6

Honduras 0 0 1 1 1 2 2 3 2 3 3 3 4

Jamaica 0 1 1 1 1 1 1 1 1 1 2 2 3

Mexico 0 0 1 1 1 1 1 1 2 3 3.5 4.5 4.5

Nicaragua 0 1 2 2 3 3 3 3 3 4 4 5 6

Panama 0 1 1 1 1 1 1 1 2 2 3 3 4

Paraguay 0 1 1 1 2 2 2 2 1 2 3 4 5

Peru 0 1 1 1 1 1 1 2 3 2 3 4 3

Uruguay 0 0 0 1 1 1 1 1 2 2 3 4 4

Venezuela 1 1 1 1 1 1 1 1 2 3 4 4 5

Apples and Oranges: Educational Enrollment and Attainment … · 2010. 1. 8. · Apples and...

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