metadata: authors: 0: author: Arriagada, Ana-Maria
1: author: Ziderman, Adrian
count: Brazil
docna: 0: docna: Vocational secondary schooling, occupational
            choice, and earnings in Brazil
docty: Policy Research Working Paper
subtopic: Labor Markets,Public Sector Management and Reform,Vocational Education & Technical Training,Educational Sciences,Rural Labor Markets
teratopic: Gender
abstracts: cdata!: Empirical studies on the efficacy of
            vocational education, mainly in developing countries - a
            literature now comprising dozens of evaluation studies -
            have been fairly unanimous in recording a negative verdict
            on the costs and benefits of vocational secondary education,
            particularly compared with traditional academic school. The
            authors, in this study set in Brazil, reach a different
            conclusion. Like a number of recent evaluation studies (for
            Hong Kong, Israel, and the United States), this one
            challenges the established orthodoxy by reporting findings
            far more supportive of vocational schooling. Unlike
            traditional approaches, it focuses on the relationship
            between field of vocational study and subsequent occupation.
            The authors report that students who complete vocational
            school and work in related fields have significant earnings
            advantages over students who do not work in fields related
            to what they studied and over students who complete academic school.
geo_reg_key: 119228,517191
repnme: repnme: Vocational secondary schooling,
            occupational choice, and earnings in Brazil
display_title: Vocational secondary schooling,
            occupational choice, and earnings in Brazil
listing_relative_url: /research/1992/11/437268/vocational-secondary-schooling-occupational-choice-earnings-brazil
topicv3: Human Resources m1326304 1211,Labor Markets m1326488 855,Vocational Education and Training m1326810 483,Education m1327048 470,Jobs m1503931 2670
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Gender
origu: Pop & Human Resources Department
no_of_pages: 22
model_extractions: <!-- Start of picture text --> I ~~PolicyR "aroh|<br>EuaJnand Employment |<br><!-- End of picture text -->

**WPS 1037**

- This paper a product of the Education and Employment Division, Population and Human Resources - Department is part of a larger effort in the department to provide policy guidance for vocational and technical education and training. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Cynthia Cristobal, room S6-214, extension 33640 (November 1992, 16 pages).

Empirical studies on the efficacy of vocational education, mainly in developing countries - a literature now comprising dozens of evaluation studies - have been fairly unanimous in recording a negative verdict on the costs and benefits of vocational secondary education, particularly compared with traditional academic school.

Arriagada and Ziderman, in this study set in Brazil, reach a different conclusion.

Like a number of recent evaluation studies (for Hong Kong, Israel, and the United States), this one challenges the established orthodoxy by reporting fndings far more supportive of vocational schooling. Unlike traditional approaches, it focuses on the relationship between field of vocational study and subsequent occupation.

Arriagada and Ziderman report that students who complete vocational school and work in related fields have significant earnings advantages over students who do not work in fields related to what they studied and over students who complete academic school.

**hePolicy ResrchWorking ParSeriesdissePiinates the fmdings of work atder way** in **theBank. Anobjectiveof the seCnes is to get these findings out quickly.** even **if presentations are less** tha **fully polished.** 'Me **fmdings. interpretations.** and **conclusions** in **these papers do not necessariy represent of ficial Bank policy.**

**Pxoduced by the Policy Research Dissemination Center**
# Vocational Secondary Schooling, Occupational Choice and Earnings in Brazil

## by

Ana-Maria Arriagada and Adrian Ziderman The World Bank
# **TABLE OF CONTENTS**

# Page

|Int|roduction<br>.................................<br>1|
|---|---|
|1.|Trends In Vocational Schooling ..................................<br>1|
|2.|Vocational Schooling In Brazil ................<br>..................<br>4|
|3.|Labor Market Outcomes of Secondary Schooling.<br>6<br>Data.<br>6<br>|
||Methodology.<br>8|
|4.|Vocational Schooling, Occupation and Eamings<br>.9<br>Education-occupation<br>matchings<br>......................................<br>9<br>Eaamings<br>Functions Results for Vocational School Leavers .10<br>|
||Eamings Functions for Academic and Vocational Leavers .11|
|5.|Summary and Conclusions<br>.13|
|Re|ferences<br>..<br>15|
|Ta|bles<br>|
||Table 1 .......<br>4<br>|
||Table 2 .......<br>5<br>|
||Table3........<br>7<br>|
||Table 4.......<br>10<br>|
||Table 5 .......<br>11<br>|
||Table 6.......<br>12|
|Ch|arts<br>|
||Chart I .......<br>2<br>|
||Chart 2 .......<br>3<br>Chart 3 .......<br>3|

Ana-Maria Arriagada Is an Economist in the Human Resources Operation Divislon, Latin American and the Caribbean Country Department Il; Adrian Ziderman, formerly Senior Economist in the Education and Employment Division, Is consultant to the Division and Professor of Economics at Bar Ilan University, Israel.
# Introduction

A major theme In the economics of education literature over the past quarter of a century has been the empirical examination of the efficacy of vocational education. mainly In developing countries. Initiated by Foster's classic study of vocational schooling in Ghana In the years following independence (Foster 1965), this literature, now comprising dozens of empirical studies, has been fairly unanimous in recording a negative verdict on vocational secondary education in cost-benefit terms, particularly in relation to more traditionally academic forms of secondary schooling. Summaries of this literature are given in Zymelman (1976), Metcalf (1985), Psacharopoulos (1987) and Tilak (1988).

More recently, a number of evaluation studies have challenged the established orthodoxy in adducing findings far more supportive of vocational schooling. Set in the US, Israel and Hong Kong these studies have departed from traditonal approaches by focussing on the relation between vocational field of study and subsequent occupaticn. They report significant eamings advantages for vocational school completers working in related fields compared both to those who do not work in related fields and also to academic school completers. Fredland and Little (1980) contrasted the eamings of "users' and "non-users^ of vocational education in the actual job of a sample of males from the National Longitudinal Survey In the US. Rumberger and Daymont (1984) matched vocational education credits in school with current fields of work. Neuman and Ziderman (1991) examined the earnings effects of vocational school completers in "matched" and "non-matched" occupations in a sample of prime age males in Israel. Chung (1990) compared the eamings of vocational school "users" to those of "non-users" and academic school graduates in a subsample of males of the Hong Kong population census.

Thus all these studies report results that are far more favorable to vocational schooling than is the main thrust of the traditional evaluation literature. In this paper, a parallel methodology is applied to Brazilian data. The results reported in this paper are in broad conformity with those of the new wave of studies, in showing eamings advantages to vocational school completers who are employed In *matched" occupations.

# 1. Trends In Vocatlonal Schooling

Based on an analysis of UNESCO enrollment data, Benavot (1983) examined the vocational enrollment ratio (the proportion of secondary school pupils enrolled in vocational schools) over time. He found a general shift away from vocational schooling in relative terms since the mid-1950, a finding consistent with the negative results for vocational schooling from evaluation studies. We report below a reexamination of these trends for the period 1960-1984, based on unweighted vocational enrollment ratios for 65 countries'.

' This discussion is drawn from Middleton, Ziderman and Adams (1992). To compute the average unweighted vocational enrollment ratio for a region or a country group by income level, a simple average of individual vocational enrollment ratios is taken for the countries of interest; thus the experience of each country, regardless of size, is accorded equal weight in the overall enrollment ratio average.
2 Looking at regional trends (Chart 1), decreasing vocational schooling ratios (though not absolute numbers) Is the prevalent pattem, except in Eastem Europe (not shown) and in Latin America, where the ratio is also more than double that in other developing country reglons.

## Chart **1**

# Vocational Enrollment Ratio **by Region**

<!-- Start of picture text --> Ratio<br>0.30 1<br>0220 - '<br>;-U- Lati Amrican Lotin Amrrict WeeEure *nd<br>0.16 Afra Crabbebn theh<br>WesAerin EurioMdleEaten<br>3.06 North Afric<br>19r0 19o e 1970 1971 1980 1984<br>Year<br>Af rica Asia Middle East and<br>-G Latin America and -Western Europe North Africa<br>the Caribbean<br><!-- End of picture text --> Trends over the period 1960-1984 diffler markedly in low and middle Income countries (Chart 2 and 3)2. In low income countries, as total secondary school enrollment (as a proportion of the age population of secondary school age) rose from three to about 20 percent, the vocational schooling **ratio** declined from 19 percent leveling off to 8 percent. Thus the albeit slow growth In secondary schooling in low Income countries has taken place primarily in the academic/general streams.

2 We use World Bank categories: low income countries are those with a GNP per capita below $1,810 in 1986: middle income countries have a GNP per capita in the range $1,810 - $7,410.
3 Chart 2 Low Income Countries <!-- Start of picture text --> Ratlo<br>0..<br>0.5<br>0.4<br>0.3-<br>0,2<br>0.1<br>0- E<br>1960 1965 1970 1975 1980 1984<br>Year<br>1 Proportion of -4- Proportion of<br>Secondary Level Students Age Eligible Population<br>In Vocational Schools Enrolled In Secondary Schools<br>Chart 3<br>Middle Income Countries<br>(Excluding E.Europe)<br>Ratio<br>0.1<br>0.5<br>0.4-<br>0.3 -<br>0.1<br>100 i065 1970 1975 180 194<br>her<br>1 Proportlon of I4+ Proportion of<br>econdary Lel Students Age Elilible PoputlIon<br>In VooatIonal Sohols Enrollud In 8econdory S8hoold<br><!-- End of picture text -->
4 The pattem is dIfferent for the middle Income countries group, to which Brazil belongs. Here, the share of total secondary enrollments in vocational schools has remained fairly constant, hovering at around 20 percent, while overall secondary school enrollments as a proportion of the relevant age group has risen dramatically from 18 to 55 percent. This Indicates that vocational schooling in middle Income countries generally has expanded at about the same rate as the secondary school system as a whole. We shall comment further on this more favorable experience in middle income countries, In the concluding section. But first, we consider the case of Brazil.

# 2. Vocatlonal Schooling In Brazil

The average educational attainment of the Brazilian population lags substantially behind that of other middle income countries. In 1980, the mean years of schooling of the male labor force was about 5.6 years with 67.9 percent of the male workers having less than secondary schooling (Psacharopoulos and Arriagada, 1986). Available data for secondary school enrollment sugges **t** hat there has been a general underinvestment in this level of education in Brazil. In 1987, enrollments at the secondary level represented only 37 percent of the school age population compared to 59 percent for other middle income countries. Table 1 presents secondary school enrollment rates for selected countries.

Table 1 Secondary School Enrollment Rates Selected countries (1965 and 1986) <!-- Start of picture text --> Country 1965 1986<br>Brazil 16 37<br>Korea 35 95<br>Chile 34 70<br>Mexico 17 55<br>Average Upper<br>Middle-income<br>Countries * 29 59<br><!-- End of picture text --> Source: World Bank (1989) <!-- Start of picture text -->
*  Defined as per capita GDP between US$ 1,810 and $ 7,410 in<br>1988.<br><!-- End of picture text -->

Available analyses of secondary schooling In Brazil indicate that the system experienced rapid growth between the 1960s and 1970s, averaging 11 percent a year between 1960 and 1980, and
S stagnation of such growth since 19808; this expansion appears to have been accompanied by increased diversity of curriculum, administration, unit costs by type of school, Inequitable allocatlon of resources across schools, and school quality differences, which are partly the result of a long term lack of public policy with regard to secondary education. There has been an expansion of nonformal programs provided by the major training institutions Serviclo [' ^Ional de Aprendizagem Industrial (SENA) and Serviclo Nacional de Aprendizegem Commerclo (SENAC) over the last two decades.

Brazilian vocatlonal educatlon at the secondary school level Is provided by all three levels of govemment: federa!, state and municipal as well as outside the formal education system by SENAI and SENAC. Over 96 percent of public secondary school enrollment and 75 percent of total secondary school enrollment Is located In state/municipal schools. These schools offer academic and vocational programs leading to a general secondary diploma. Vocational students may specialize In the following major fields: 4 agriculture, Industrial, accounting, pedagogical, and para-medical. Most state schools In Brazil offer vocational and academic curriculum fields in the same schools and the unit costs of the former are likely to be similar to those of academic education, particularly In those vocational education fields that do not require special machinery or equipment.

Table 2 Public Secondary Schooling In Brazil Enrollment and Expenditures by Type of School (1985)

|Type of School|Enrollme<br>1985|nt<br>%|Number<br>of<br>Schools|Per student<br>cost<br>US$|
|---|---|---|---|---|
|Federal Technical<br>|67,657|<br>3.4|137|1,759|
|Agricultural<br>|13,568<br>|0.7<br> <br>|-|2,727<br>|
|industrial|54,089|<br>2.7|-|1,516|
|State/Municipal*|1,912,488|96.2|5,059|249|
|State|1,780,155|89.6|4,421|257|
|Municipal|132,333|6.7|638|136|
|SENAI Secondary|7,543|0.4|-|1,880|

Source: World Bank (1989)

- Not available.

* cost figures relate to both technical and academic schools.

3 World Bank (1989), p.i.

4In detail, the fields offered are: industrial electrical, industrial mechanics, industrial chemical, industrial textile, architectural design, agriculture, accounting, secretarial, administratlon, insurance, and para-medical.
# S

Unfortunately, there is no up to date research on the labor market outcomes of vocational secondary schooling in Brazil. The only research available refers to nonformal training, and covers SENAI graduates In the early 1970s (do Moura Castro, 1979). This study yielded high estimates of social rates of retum: 24 percent for those who received SENAI training .- ter four years of primary schooling, 12 percent for those who received SENAI training after eight years of schooling, and 23 percent for those who received SENAI training after secondary school.

## 3. Labor Market Outcomes of Secondary Schooling

## Data

The data source Is a nationally representative subsample of males drawn from the 1980 Brazilian Population Census. The sample was restricted to males between the ages of 15 and 65, who attended secondary and were working full time (36 hours per week or more In the week prior to the census) in private sector wage employment". The Census questionnaire gathered Information on years and type of terminal schooling. This Information was used to distinguish between academic and vocational secondary school leavers (i.e. those that terminated full time education at secondary level). While the Census questionnaire did not gather explicit information on the type of school attended by secondary school leavers (this is inferred from courses of study), available Information presented In Table 2 enables us to believe that the majority of the Individuals who received vocatlonal schoollng In our sample come from state/municipal schools. In all, 2,743 individuals were included In the final sample: of these, nearly 407 (some 15 percent) received vocational schooling.

Table 3 presents the characteristics of the sample of secondary school leavers as a whole, and by type of schooling attended. It appears that most personal characteristics (age, experience, migrant origin) are similar for vocational and academic leavers. The two groups differ in the amount of schooling attained, where vocational school leavers have over 1.5 more years than their academic counterparts. There are also some differences between the two groups In terms of the distribution by occupation and eamings. Clerical work, followed by professional/technical work, are the main occupatlons for vocational leavers while production and clerical work are the main occupations for those of academic fields. On average, vocational school leavers appear to earn about 6,000 cruzados more per month than their academic counterparts.

> 5 Originally we worked with the full sample of salaried workers employing a dummy variable 1 if employed In the public sector. However, the estimation of F test Indicated that the samples of private and public sector workers come from different populaftons, which conform with available evidence on the operation of labor markets in Brazil.
7 Table 3 Distribution of the Sample by Type of Secondary Schooling (Means and standard deviations)

|Characteristics|Whol<br>|e Sample<br> <br>|Vg<br>|ocational<br>|<br>A<br>|cademic<br> <br>|
|---|---|---|---|---|---|---|
||Mean|<br>sd.|Mean|<br>ed.|Mean|<br>sd.|
|Number obaservations|2,743||407||2,336||
|Age|29.04|<br>9.52|30.18|<br>6.72|28.84|<br>9.64|
|Experience|13.25|<br>9.34|12.87|<br>8.56|13.32|<br>9.47|
|Monthly earnings<br>(Cruzados)|18,495|18,635|23,686*|21,545|17,590*|17,932|
|Schoolina|||||||
|Secondary academic|0.84||||||
|<br>Secondary vocational|0.16||||||
|Years of schooling|9.78|1.43|11.31*|<br>0.55|9.51|<br>1.37|
|<br>Yrs. Industrial|||11.23|<br>0.77|||
|Yrs. accounting|||11.37|<br>0.48|||
|<br>Yrs. other vocational|||11.19|<br>0.43|||
|Occupation|||||||
|Farm worker|0.02||0.01*||0.02||
|Production worker|0.27||0.17*||0.28||
|Sales worker|0.12||0.12||0.13||
|Soevice<br>worker|0.13||0.04*||0.15||
|Clerical worker|0.26||0.35*||0.25||
|Professional/technical|0.13||0.25*||0.12||
|Non-defined occupation|0.07||0.04||0.04||
|Location|||||||
|North|0.01||0.01||0.01||
|North-east|0.13||0.17*||0.12||
|South-east|0.64||0.53||0.66||
|South|0.17||0.19||0.16||
|Central-west|0.05||0.09*||0.04||
|Other variables|||||||
|Social socurity|0.92||0.96*||0.91||
|<br>Migrant|0.55||0.55||0.54||

Signicant at the .001 level or better, Differences between means were tested employing tbtests,
8

# Methodology

The analytical framework for this study Is the traditional Mincerlan earnings function (Mincer 1974). The log of monthly earnings Is run against a set of spline variables (SPLYRSC) descrlbing the number of years of schooling attained In the secondary school field of study (academic, Industrial, accounting, pedagogilc **a** l nd other vocational courses). We chose to use of spline variables for years of educatlon because they provide dirsct estimates of the returns to an additional year of schoollng In each field of study. We control for several explanatory variables relating to personal and background characteimstics and labor market features. Dlrect comparisons of the coefficients on the secondary school splines show whether vocatlonal leavers earn more than their academic counterparts: they also Indlcate any eamings differences between the various fields of vocational schooling.

# The full set of variables employed in the regressions are as follows:

SPLYRSC2 Years of academic secondary schooling SPLYRSC3 Years of Industrial secondary schooling SPLYRSC4 Years of accounting secondary schooling SPLYRSC5 Years of other vocational secondary schooling EXPER Years of experience defined as Age - Schooling years - 6 PRODW 6 Dummy variable = 1 f Production worker, 0 otherwise FARMW Dummy variable = 1 If Farm worker, 0 otherwise SALES Dummy variable = 1 if Sales worker, 0 otherwise CLERICAL Dummy variable = 1 if Clerical worker, 0 otherwise SERVICE Dummy variable = 1 if Other service worker, Ootherwise NONDEF Dummy variable = I If Non-defined occupation, 0 otherwise REGIN Dummy variable = 1 i Uves in the North region, 0 otherwise REG2N Dummy variable = 1 if Uves in the North-east region, 0 otherwise REG3N ' Dummy variable = 1 i Uves In the South-east region, o otherwise REG4N Dummy variable = 1 if Uves in the South region, 0 otherwise REG5N Dummy variable = 1 f Uves in the central-west region, 0 otherwise MIGRANT Dummy variable = 1 If Not born In current state of residence, 0 otherwise SOCSEC Dummy variable = if Job provides social security benefits, 0 otherwise MATCH1 Dummy variable = I i strict matching between vocational schooling field of study and work, 0 otherwise MATCH2 Dummy variable = 1 if wider matching between vocational field of study and work, 0 otherwise OmiKted category in regressions.

" Omitted category in regressions.
9

# 4. Vocatlonal Schooling, Occupation and Earnings

The empirical estimation reported in this paper focuses on three questions: To what extent are vocational schoo **l** eavers employed in occupations related to their field of study in secondary school? Given the amount of matching, are there any earnings differences between those vocational schoo **l** eavers that are employed in subjects related to their field of study and those that are not? How do the earnings of vocationally educated workers (in both matched and non matched occupations) compare with those of workers who studied In academic schools?

# Education-Occupation Matchings

To examineth **e** xtentto which vocational schooling is related to occupation, we compare field of study with current job held, using 3-digit occupational codes. Two alternative matching criteria were employed, Istrict" matching and "wider matching. For strict matchings, a worker was defined as matched If he works In an occupation directly related to the vocational field of study; for example, the subject Industrial electronics and the occupation electrical technician constiute a strict match. To account for career development, wider matchings add closely related occupations, for example an Individual who 6 received electronics at school might go on to become a technical salesman In an electrical business. Table 4 shows the proportion of matched workers by field of study, according to the strict and wider matching criteria. Overall, 25.3 percent of vocational leavers were employed In occupation **s** trictly related to the field of study. 40 percent were in matched occupations according to the wider criteria. Examining strictly matched workers, the average eamings difference amounts to 11 percent; however the situation varies by field of study. With regard to wider matching, the average eamings difference Increases to 37.2 percent, also varying by field of study. However, these figures represent gross differences which do not take Into account other determinants of earnings and therefore must be Interpreted with caution.

° Details of the educational-occupational equivalences used in the matching procedure are available on request.
10 Table 4 Matched and Non-matched Vocational School Leavers in Private Sector Wage Employment (Numbers, Mean monthly eamings and sds.)

||All V<br>Scho<br>|ocational<br>ol Leavers<br>|Strict|<br>Match<br>|ina<br>|Wide|r<br>Matc<br>|hina<br>|
|---|---|---|---|---|---|---|---|---|
|Field of<br>study|No.|Mean<br>Eamings|%<br>Matc|Mean E<br>Match<br>h|arninas<br>Non-<br>match|%<br>Matc|Mean Ea<br>Match<br>h|minas<br>Non-<br>Match|
|Industrial|82|28,469<br>(20,115)|57.3|27,907<br>(18,111)|29,223<br>(22,784)|69.5|28,567<br>(19,130)|28,268<br>(22,618)|
|Accounting|257|23,673<br>(23,482)|16.3|25,507<br>(18,759)|23,315<br>(24,319)|32.7|35,395*<br>(30,537)|17,981<br>(16,463)|
|Other Vocational|68|17,967<br>(12,471)|20.6|20,074<br>(13,323)|17,420<br>(12,313)|30.9|16,290<br>(10,139)|18,716<br>(13,417)|
|All Vocational|407|23,686<br>(21,5M)|25.3|25,864*<br>(17,849)|22,948<br>(22,640)|40.0|30,512*<br>(39,512)|19,172<br>(16,877)|

> * Significant at the .001 level. Differences between means were tested employing t-tests.

# Eaminis Functions Results for Vocational School Leavers

Earnings functions were estimated for the sample of vocational school leavers with the purpose of examining whether work in a study related field makes a significant contribution to their eamings. Table 5 presents the results. Column 1 shows the model with the strict match between field of study and work, and Column 2 shows the same model using the wider matching criteria.

The table shows clear labor market eamings advantages accruing to vocationally educated workers that are employed in occupations related to courses of study followed. For the strictmatch model, the earnings differential Is some 16 percent, while for the wider-match model the dffferential exceeds 27 percent. The stronger effect for the wider-match definition reflects subsequent career development, in a broader range of (better-payed) jobs.
11 Table 5

# Eamings Functions. Brazilian Vocational Leavers Full Time Private Sector Males (dependent variable Ln monthly earnings)

|Independent<br>variables|Matchl<br>coeff.|Model<br>t|Match<br>coeff.|2 Model<br> <br>t|
|---|---|---|---|---|
||(1)||(|2)|
|Intercept|6.055*|8.56|6.007*|8.61|
|EXPER|0.078*|6.25|0.080*|6.47|
|EXPERSQ|-0.001*|3.69|-0.001|*4.01|
|YRSCHL|0.223*|3.67|0.220*|3.67|
|MATCH1|0.164*|2.02|||
|MATCH2|||0.272*|3.67|
|SERVICE|40.676*|3.94|-0.631*|3.71|
|FARMW|-0.339*|1.62|-0.291 *|1.41|
|SALES|-0.103|0.94|-0.029|0.26|
|CLERICAL|-0.306*|3.86|-0.226*|2.74|
|NONDEF|0.290*|1.62|0.352*|1.98|
|REGIN|-0.281*|1.07|-0.288*|1.10|
|REG2N|-0.251*|2.80|-0.253*|2.86|
|REG4N|-0.035|0.40|-0.046|0.54|
|REG5N|-0.285*|2.42|-0.307*|2.65|
|SOCSEC|0.570*|3.22|0.545*|3.12|
|MIGRANT|0.130*|1.98|0.123*|1.90|
|R2|0.393||0.407||
|Number observations|406||406||

* Significant at the .001 level or better.

The results presented in Table 5 support the findings of other studies with regard to expected eamings outcomes of vocational school leavers when matched in relevant fields of employment. The coefficients of both the strict and the wider match indicate that vocational leavers who work in fields related to their studies do have higher eamings than those who do not.

# EamInas Functions Results for Academic and Vocational Leavers

Eamings functions are estimated for the overall sample of secondary school leavers. The purpose of the analysis is to examine the comparative returns to vocational and academic study, and to examine whether work in a study related field makes a significant contribution to the eamings of the
12 vocational school leavers. Table 6 presents the results of the estimations. Column I shows a simple Mlncerian model. Column 2 shows the full model with the strict match between field of study and work, while column 3 shows the same model, with the wider match dummy variable.

Table 6 Earningc Functions. Brazilian Full Time Males Private Sector Workers (dependent variable Lin monthly eamings)

|Independent<br>variables|Simple<br>coeff.<br>(1)|Model<br>t<br>|Match<br>coeff.<br>(2)|1 Mode<br>t<br>|l Match<br>coeff.<br>(3)|2 Model<br>t|
|---|---|---|---|---|---|---|
|Intercept|6.694*|73.64|<br>6.606*|68.97|6.603*|69.12|
|EXPER|0.104*|24.43|<br>0.098*|23.35|0.098*|23.40|
|EXPERSQ|-0.001*|16.30|-0.001*|15.81|.0.001*|15.90|
|SPLYRSC2|0.190*|21.12|<br>0.172*|19.52|0.172*|19.60|
|SPLYRSC3|0.214*|21.70|<br>0.183*|17.70|0.175*|16.88|
|SPLYRSC4|0.179*|21.49|<br>0.161*|19.28|0.155*|18.35|
|SPLYRSC5|0.175*|17.90|<br>0.159*|16.44|0.155*|15.94|
|MATCHI|||0.166*|<br>2.20|||
|MATCH2|||||0.284*|<br>4.34|
|SERVICE|||-0.290*|7.93|-0.283*|<br>7.74|
|FARMW|||-0.279*|3.91|-0.276*|<br>3.16|
|SALES|||0.008|0.22|0.002|0.06|
|CLERICAL|||-0.082|2.78|-0.068*|<br>2.29|
|NONDEF|||-0.032|0.57|-0.024|0.42|
|REGiN|||-0.107|0.73|-0.112|0.76|
|REG2N|||-0.238*|6.78|40.238*|6.79|
|REG4N|||-0.118*|3.73|-0.119*|<br>3.75|
|REGSN|||-0.143*|2.63|.0.150*|2.77|
|SOCSEC|||0.426*|9.09|0.422*|9.03|
|MIGRANT|||0.100*|4.20|0.100*|4.21|
|R<sup>2</sup>|0.391||0.443||0.445||
|Number obs.|2,742||2,742||2,742||

* Significant at the .001 level or better.

The results presented in Column 1 are closely in line with those from other countries and prior research in Brazil. Psacharopoulos (1986) estimates a return to schooling in Brazil of 19.2 percent in 1970. Dabos and Psacharopoulos (1987) estimate a 16.4 percent return to general secondary schooling and a 19.8 percent return to vocational secondary schooling, for the overall male Brazilian labor force In 1980. Note that the latter report does not indicate whether these retums are statistically different.
13 In our study, the comparison between the coefficients of the years of schooling by type of curricula Indicates that there are no significant differences in the retums to schooling between academic and vocational fields of study, nor between the various vocational fields.

Results presented In Columns 2 and 3 Include controls for additional background and labor market variables as well as the education-occupation match dummies. A positive and signfficant sign on the match variable would indicate that vocational leavers employed In study-related fields of work eam more than those who do not, and also eam more than those who pursued academic studies. The actual coefficients show that matched workers do obtain higher earnings than their non-matched counterparts: by about 16 percent for the strict matchings, and about 28 percent for the wider matchings °. The results of the regressions presented in Columns 2 and 3 indicate that while there Is no difference In eamings between academic and vocational non-matched leavers, the eamings of those vocational leavers who work in study related occupations exceed those of their academic counterparts'°.

# Summary and Concluslons

In the now extensive literature evaluating the labor market outcomes of vocational schooling in relation to more academic education, most studies focus on eamings differences without considering other intervening variables, such as the relevance of vocational studies to the type of occupation performed. The results reported In this paper for Brazil, which are parallel to those in recent similar studies for other countries, are far more favorable with regard to vocational schooling than is the traditional evaluation literature, particularly for developing countries. We find that the type of curriculum received in secondary school does not, in itself, have a significant impact on eamings. Vocational school completers and their academic counterparts have similar eamings outcomes when the vocational school leavers are employed in occupations unrelated to their field of study. It is vocational schooling combined with relevant occupation that Is conducive to higher eamings. When vocational school leavers are employed in occupations related to their field of study, their eamings are significantly higher than those from the academic stream.

Our results point to the importance of broadening the scope of the evaluation studies on the labor market outcomes of vocational and academic secondary school leavers, to Include more Information on the occupation of vocational school completers, as well as on the employment environment generally. Yet while the traditional methodology can be criticized for generally failing to take 9 Given that we did not find significant differences in the retums to schooling between vocational fields, we did not test this relationship for each of the fields of study.

'° In a recent paper, published after this research was completed, Tannen (1991) found no significant differences between the eamings of vocational and academic secondary school completers; though based on the same deta set he did not draw the distinction matched and unmatched vocational school completers.
14 these issues into account, it does not necessarily follow that in all of these country case studies the negative findings regarding vocational education are faulty.

It is the case that in many developing countries, the employment environment is not favorable to vocational schooling1 ". Vocational schooling, by definiion related to fairly narrow job skills, requires conditions of employment growth and buoyant demand for training skills, in order to meet its objectives in the economic and wider social sphere. However, the lack of modem employment sector growth in general and llmited demand for specific vocational skills, together with higher unit costs of vocational schooling, combine to diminish the efficacy of vocational schooling In many developing countries. It would appear that an explanation for the more favorable outcomes for vocational education reported In recent studies for Hong Kong and Israel, as well as the results for the present study in Brazil, Is to be found In the more favorable economic and employment environments In these middle income, industrializing countries.

" These issues are discussed more fully in Middleton, Ziderman and Adams (1992).