The New Middle-Class · The New Middle-Class Rio de Janeiro, August 05, 2008 Version 2.0: August 8,...

1

The New Middle-Class

Coordination: Marcelo Cortes Neri

August 2008

2

The authors take full responsibility for the ideas published here. The opinions expressed do not

necessarily reflect Fundação Getulio Vargas´ point of view.

The New Middle Class (A Nova Classe Média) / Marcelo Côrtes Neri. Executive

Summary / Marcelo Côrtes Neri (coord). - Rio de Jan eiro: FGV/IBRE, CPS, 2008.

[70] p.

1. Middle-class 2. Income 3. Poverty 4. Inequality 5. Social mobility. I. Neri, M.C. II. Fundação Getulio Vargas, Instituto B rasileiro de Economia. Centro de Políticas Sociais.

© Marcelo Neri 2008

3

The New Middle-Class

Rio de Janeiro, August 05, 2008

Version 2.0: August 8, 2008

Centro de Políticas Sociais

Instituto Brasileiro de Economia

Fundação Getulio Vargas

Coordination: Marcelo Cortes Neri [email protected]

CPS’ Staff: Luisa Carvalhaes Coutinho de Melo

Samanta dos Reis Sacramento André Luiz Neri

Carolina Marques Bastos Celio Maymone Pontes

Ana Lucia Salomão Calçada Ana Beatriz Urbano Andari

Celso Henrique Fonseca

4

Table of Contents

1. Motives

2. Methods

3. Mean income, inequality and poverty

4. Defining the middle-class

5. Changes in the distributive pie

6. The distributive dance

7. The return of the C from “carteira de trabaho” (employment

registration booklet)

8. Conclusions

9. Bibliography

Appendix I – Portrait of the Middle-Class

Appendix II – Regional Variation

Appendix III – Multivariate Exercises

5

The New Middle-Class1 August 2008

1. MOTIVES

Brazil received an “investment grade” by the international rating agencies in the first

semester of 2008. In 2007, Brazil also joined a group of countries with a high Human

Development Index (HDI). The present study reveals these events’ daily effects on the

human anatomy’s most sensitive part: the pocket. Class “C” share increased 22.8%

from April 2004 to April 2008, while classes “A” and “B” grew 33.6% in the same

period. Therefore, if one assumes that the middle-class is richer than Brazil’s class “C”,

the conclusion that the middle-class has grown remains unaltered. Another point is that

all substantive and symbolic indicators show the occurrence of a boom in class “C”:

access to housing, car, computer, credit and formal employment are at their historical

highs.

Class “C” is the central class, below A and B e above D and E. In order to quantify

these levels, we calculated the household per capita income from work and then express

it in terms equivalent to the total household incomes from all sources. The central Class

C refers to household incomes between R$ 1064 and R$ 4561 at today’s prices from

São Paulo Metropolitan region. Class C is immediately above the 50% poorest and the

10% richest at the turn of the century. Illustratively, class C is limited by the Indian

border on one side and to the Belgian border on the other side in the so-called Belíndia.

Some see class C as the low-middle class, and class B as the upper-middle class. We are

not the USA, but this is also a free country. It is more important to have a well-defined

and consistent criterion. Our class C receives the average income in society, that is, it is

the middle class in the statistical sense. Given the income inequality, the average

1 Two years ago, Fundação Getulio Vargas president, Mr. Carlos Ivan Simonsen Leal, proposed that we went beyond the statistics relating to poverty and studied the Brazilian middle-class. This study is a direct consequence of this challenge; hence we would like to thank his guidance and encouragement. The responsibility for the methodological choices and the results of the research rests with the author.

6

income is high in relation to our median. In relation to the rest of the world: 80% of the

people in the world live in countries with lower per capita income levels than the

Brazilians. Our Class C is thus the closest image to the Brazilian society.

If we want to understand Brazil, it is necessary to quit looking only at the rear-view

mirror that focuses on obsolete data, and start looking ahead through the windshield of

the current Brazilian scene. Even before looking ahead and forecasting, given the

uncertainty as a result of the current American crisis, it is useful to explore more recent

data. Here, we inform the public debate by providing unpublished data on 2007 and

2008. As a function of the continuous improvement in the social conditions with the

successive reductions in inequality and poverty rates presented here, the study unveils

the emergence of a new middle-class in Brazil. This research defines and details the

economic rise of this new middle-class in the main Brazilian cities. The emphasis will

be on income from work in the six main Brazilian cities as a result of the greatest data

availability of recent Monthly Employment Survey (PME/IBGE) microdata (up to April

2008). Apart from being more recent, this data also allow us to monitor the same

families through time and to observe their transitions into- and out of poverty and

middle-class statuses. Roughly, while the traditional studies based on PNAD, and even

on the PME, provide static snapshots of society groups in different moments, the PME

also makes it possible to capture the trajectory of the same families, isolating the

emerging ones from those that already belonged to the middle-class, or alternatively,

identifying the new destinations of those who were living in old-time poverty. In order

to make the current scenario as complete as possible, we also count on data from

Caged/MTE (Cadastro Geral de Emprego e Desemprego do Ministério do Trabalho e

Emprego – General Record of Employment and Unemployment from the Ministry of

Labour and Employment) available for all national territory until June 2008. This data

refers to formal employment rates, which have reached a record high in the last months.

The so-called return of the employment registration booklet (carteira de trabalho) may

be the most symbolic element in the reappearance of the new Brazilian middle-class.

Overall, much has been said in this decade in terms of inequality (since 2001) and

poverty reduction (since 2004); the role of official income transfer programs to the

poorest has been emphasized; but little attention has been paid to the structural advances

7

that resulted from the labor expansion observed for all layers of society. Since 2004

until now, there has been an increase in the income from work in general and in the

creation of formal job posts, in particular. And since the last statistical snapshot on

Brazil, taken through the PNAD 2006 lenses, income from work has been its most

striking feature. This research, based on most recent data, shows the continuity of this

phenomenon coupled with some acceleration in the pace of meaningful decreases in

poverty and inequality in Brazil until now. After two lost decades in terms of income

and labor, the combination of faster growth with a marked reduction in inequality for a

longer period is remarkable – making this a story worth telling, especially for being

unprecedented in the documented history of Brazilian statistics.

After years of crises in metropolitan areas, the main finding concerns the growth of a

middle-class and the reduction of poverty in these same areas; and how much of it can

be attributed to the growth in population’s income from private work. In many cases,

the analyses give emphasis either to the role of large public transfers of income to the

population, as an expansion of the Bolsa Família, or the social security transfers,

contributory and non-contributory, related to adjustments in the minimum wage. We

argue that, since 2004 at least, an increase in income from work rivals with those

transfers in explaining the improvements in income for the population as a whole (and

that since 2001, for the poorest segments in the population). This is well documented in

the PNAD series until October 2006. The recent labor return and the absolute growth of

the middle groups of the population have not yet been considered in detail.

Beside the prevalence of private earnings derived from work over public transfers; the

metropolitan areas vis-à-vis the rest of the country; and the emergence of the middle-

class; the change in the international context must also be understood. Until mid-2007,

despite a stronger growth in the Brazilian GDP since 2004 compared to the previous

two lost decades, Brazil was chasing the growth rates of central and emerging

economies such as India and China. Since then, Brazilian GDP caught up with these

rates in the international context. As it has been reported by the main international

newspapers, Brazil is in evidence in terms of growth. This paper substantiates this new

sense of prosperity through objective data on the improvement in the aspects that were

central to the previous crises, namely: income from work, formal employment,

8

metropolitan areas and the so-called middle-class. Another novelty well spotted by Mac

Margolis from Newsweek in his blog is that for the first time in more than twenty years

living in Brazil, the word crisis is pronounced here referring to somewhere else.

The present paper explores the movements in income distribution in the statistical sense,

encompassing changes in inequality, as well as in the average growth of household

income. We give special emphasis to the analysis of two phenomena, namely: poverty

at the lower end of per capita income distribution; and, the so-called middle-class at the

center of total household income. The work plan is as follows: in the second section, we

analyze the recent evolution of the distribution indicators based on per capita income

from work; in the third section, we detail the regional evolution of indicators such as the

median, average and poverty rates; in the fourth chapter, we take advantage of PME’s

longitudinal aspect in order to assess the frequency of movements into- and out of

poverty, which are associated with the minimum wage movements in the following

section. The sixth and last sections present the main conclusions for this study.

10

2. METHOD

It is traditional amongst the research institutions like IBGE to use data from the

Monthly Employment Survey (PME) at the individual’s level, as opposed to the

households’ level, particularly placing focus on indicators such as unemployment rate

and the average income from work. Nevertheless, PME is a household survey

comparable to the National Household Survey (PNAD) and can be used as such. This is

noteworthy because the evaluation of the socio-economic conditions must take into

consideration the process of allocating resources within the household. For instance,

how income from an adult worker may benefit other members of the family, such as the

children. In this sense, the most adequate variable to measure the level of poverty would

be the household per capita income, which is the sum of income from all members of

the household divided by the total number of members. Similarly, when trying to define

the size of the middle-class in order to assess the purchasing power of family goods

such as a house, the adequate variable is the total income received by all household

members. Both concepts sum up a series of factors that influence all members of a

family, such as the level of occupation and income, measured formally or informally,

but whose effects can be shared by the total number of household members (BARROS

et al.,1996).

The main question here is how to improve the monitoring of our population’s living

conditions. How do we assess the social and economic performance based only on the

data from PNAD, whose information is on average 18 months old? For instance, it has

been almost two years since the last national snapshot based on PNAD. The increase in

speed is a necessary requirement to design an effective social target evaluation system.

This includes managerial systems within public administration, as well as the

monitoring of poverty levels by society itself. This is no less urgent from the standpoint

view of private companies that want to adapt their business cycle fluctuations in order

to target their demand. In view of these needs, we propose to process the PME

microdata, which – given its agile nature – allows us to reduce that 18-month lag down

to 3 months (NERI; CONSIDERA, 1996).

Apart from this benefit derived from an increased speed in the dissemination of

information, using PME/IBGE data on a monthly basis allows capturing the determinant

factors of the distribution of income from work, observed in Brazil through time. The

11

series of average household per capita income and of inequality captured by the Gini

index, presented on graphs 1 and 2 below, and detailed ahead, indicate that the greatest

part of the growth of per capita income from work among the poorest classes observed

in the last four years occurred between March and June 2004; but it remains

uninterrupted ever since.

GRAPH 1 - Poverty Series

2425262728

293031

3233

343536

3738

Mar-02

Jun-02

Sep-02

Dec-02

Mar-03

Jun-03

Sep-03

Dec-03

Mar-04

Jun-04

Sep-04

Dec-04

Mar-05

Jun-05

Sep-05

Dec-05

Mar-06

Jun-06

Sep-06

Dec-06

Mar-07

Jun-07

Sep-07

Dec-07

Mar-08

Source: CPS/IBRE/FGV based on PME/IBGE microdata.

Criterion: Usual per capita income

GRAPH 2 - Gini’s Index Inequality Evolution

0,58

0,59

0,60

0,61

0,62

0,63

0,64

Mar-02

Jun-02

Sep-02

Dec-02

Mar-03

Jun-03

Sep-03

Dec-03

Mar-04

Jun-04

Sep-04

Dec-04

Mar-05

Jun-05

Sep-05

Dec-05

Mar-06

Jun-06

Sep-06

Dec-06

Mar-07

Jun-07

Sep-07

Dec-07

Mar-08

Source: CPS/IBRE/FGV based on PME/IBGE microdata. Criterion: Usual per capita income

Roughly, if social scientists were astronomers and the income distribution were a

celestial body in movement, PNAD would be like a super-telescope in the right place to

capture that body’s passage. Nonetheless, we need more than snapshots of the

12

phenomenon in several years, such as those given by PNAD, in order to precise the

factors that determine the trajectory of social indicators based on income, such as

poverty and inequality. It would be necessary to use a sort of film based on a series of

monthly snapshots, such as those from the PME, which allows us to identify the effect

of discreet changes on policy variables, such as abrupt changes in interest rates, in the

exchange rate or, more bluntly, the role of minimum wage adjustments (NERI, 1995).

Thirdly, PME uses a rotating panel methodology similar to that adopted by the Current

Population Survey (CPS) in the US, which monitors the information of the same

individuals and their families during consecutive observations. In other words, in our

analogy with the movies, we are not only following the story of sub-groups in society,

but developing a film for each person in the sample. In particular, we explore data

collected in four consecutive months (example: March, April, May and June in 2008

given year) and so forth – as this period is especially interesting to identify the effects of

the minimum wage in each year and the rapid reduction in poverty and inequality

occurred in 2004, as mentioned above. The approach used in this work consists in

calculating the likelihood of transition into - and out of poverty (or of middle class), as

well as the non-transition within four consecutive months. The individuals most

affected will be identified through the microdata, which will also help to reconstruct

their respective household per capita work income trajectories (BARROS et al., 1996).

Finally, it is important to highlight two PME limitations, as follows: it does not consider

income unrelated to work, such as those from government income transfer programs

and income from interest gains for the groups with a financial wealth stock; it only

covers the six main metropolitan areas in Brazil. In short, this research only provides

evidence of labor in the metropolitan areas. (RAMOS; BRITO, 2003). Our

methodology will address this limitation.

13

3. MEAN, INEQUALITY AND POVERTY MEAN

The usual or normal income concept smoothes transitory fluctuations of income, such as

the income from the so-called “décimo terceiro salário” (an extra monthly wage paid at

Christmas time), holiday bonus and overtime work. The concept of effective income

also surveyed by the PME presents marked seasonal fluctuations as the year begins as

shown by the graphs, but – these peaks aside – the data series are relatively close2. We

have chosen to work with the usual concept of income not only because it eliminates

erratic fluctuations – which can create an upward bias towards the mobility measures –

but it is also advantageous because the PNAD uses it, enabling a direct comparison

between the results with the main database of the Brazilian household survey system.

GRAPH 3 - Evolution of Per capita average income

450

475

500

525

550

575

600

625

650

675

700

725

750

Mar

-02

Jun-

02

Sep

-02

Dec

-02

Mar

-03

Jun-

03

Sep

-03

Dec

-03

Mar

-04

Jun-

04

Sep

-04

Dec

-04

Mar

-05

Jun-

05

Sep

-05

Dec

-05

Mar

-06

Jun-

06

Sep

-06

Dec

-06

Mar

-07

Jun-

07

Sep

-07

Dec

-07

Mar

-08

Usual Effective Source: CPS/IBRE/FGV based on PME/IBGE microdata.


A first approach is to look at the evolution of the income distribution in the statistical

sense, including the evolution of the usual per capita income average and inequality.

We have decided to present the graphs with a moving average in order to better isolate

the trends. The income average gives continuity to the expanding trajectory observed at

the end of the 2003 recession, as the monthly data have already suggested. The average

per capita income growth rate between April 2003 and April 2008 – thus discounting

2 Neri (1996) details the differences among the two concepts based on a comparison between PME collected in 1980 and 1982, before its reformulation. Another point is that the usual concept tends to be linked to the month of the survey, while the effective concept is linked to the previous one. In this sense, the effective concept would be more appropriate as a leader indicator in the PNAD. On the other nad, the effective concept of income is the most adequate to the PME series between 1982 and 2002, before its second reformulation

14

the population growth – is 5% per year. This pace is not inferior, for instance, to that

observed during the economic miracle in the 1960s’. Once the post-April 2004 period is

isolated, this rate reaches 6,5% per year, once again having discounted the population

growth.

GRAPH 4 - Evolution of Per capita average income 12-month moving average

450

475

500

525

550

575

600

Feb

-03

May

-03

Aug

-03

Nov

-03

Feb

-04

May

-04

Aug

-04

Nov

-04

Feb

-05

May

-05

Aug

-05

Nov

-05

Feb

-06

May

-06

Aug

-06

Nov

-06

Feb

-07

May

-07

Aug

-07

Nov

-07

Feb

-08



TABLE 1 - Per Capita Income – 15 to 60 years old (6 Brazilian metropolitan areas)

Level (R$) PER CAPITA INCOME– R$

abr/02 514,85 abr/03 480,51 abr/04 467,47 abr/05 513,04 abr/06 536,07 abr/07 574,69 abr/08 605,42

Evolution PER CAPITA INCOME

Moving Average

Variation(%) Variation(%) Difference(R$) Annual Evolution (12 meses) abril 03 / abril 02 -6,67 -34,34 abril 04 / abril 03 -2,71 -9,20 -13,04 abril 05 / abril 04 9,75 8,78 45,57 abril 06 / abril 05 4,49 3,87 23,03 abril 07 / abril 06 7,20 7,39 38,62 abril 08 / abril 07 5,35 4,14 30,73 Accumulated Evolution (desde 2002) abril 08 / abril 03 26,00 14,75 124,91 abril 08 / abril 04 29,51 26,37 137,95 abril 08 / abril 05 18,01 16,17 92,38 abril 08 / abril 06 12,94 11,84 69,35 abril 08 / abril 07 5,35 4,14 30,73

Criterion: Per capita Usual Income


15

Social classes, in general, are typically defined based on the total household income and

not per capita income, as in the case of poverty studies. In relation to the household total

income, there was a decline in the two first years, especially between April 2002 and

April 2003, with a decrease of 9% in the total real income. The highest level in the

whole series (R$ 1957 in 2008) occurred in 2008, 24,76% above the 2004 level in real

terms.

TABLE 2 - Household Income – 15 to 60 years old (6 Brazilian metropolitan areas)

Level (R$)

HOUSEHOLD TOTAL INCOME - R$


Evolution

HOUSEHOLD TOTAL INCOME

Moving Average

Variation (%) Variation (%) Difference (R$) Annual Evolution(12 months) abril 03 / abril 02 -8,74 -155,97 abril 04 / abril 03 -3,66 -10,00 -59,64 abril 05 / abril 04 8,69 7,91 136,27 abril 06 / abril 05 3,83 3,31 65,34 abril 07 / abril 06 6,57 6,87 116,28 abril 08 / abril 07 3,74 2,82 70,54 Accumulated Evoluation since 2002 abril 08 / abril 02 9,69 172,82 abril 08 / abril 03 20,19 10,25 328,79 abril 08 / abril 04 24,76 22,50 388,43 abril 08 / abril 05 14,79 13,53 252,16 abril 08 / abril 06 10,55 9,89 186,82 abril 08 / abril 07 3,74 2,82 70,54

Criterion: usual income


16

INEQUALITY

Before the analysis of inequality measures, it is worth emphasizing that, apart from the

geographical coverage and the income concept used, the per capita income concept used

includes the null income, which is fundamentally important to the inequality measures.

The most used measurement is the Gini index that varies from 0 to 1 and assigns weight

to income in an inverse order of their ranking. That is, the richest person in a society is

given the smallest weight, which increases as we move towards the smallest income

levels. In this sense, the person with a 0 income should be awarded the biggest weight

and not the smallest, null weight - when we would instead implicitly disregard them in

the analysis. These methodological restrictions notwithstanding, income inequality also

presents a noticeable retraction throughout the series. The Gini index falls from 0,627 in

April 2002 to 0,584 in April 2008, which is considerable given the scale of variation in

the index, particularly within the Brazilian context. The Gini index of per capita income

from all sources remains stagnated around 0,6 between the 1970 and 2000 Census. The

only impressive permanent change observed in the statistically documented series in the

country was the famous increase in the 1960’s when the Gini index for individual

income increased 0,07 point in a decade. Conceptual and geographical differences aside,

for comparison purposes, this absolute decrease in six years 0,0426 is exactly in the

same rhythm in the 1960s’.

GRAPH 5 - Inequality Evolution – Gini Index

12-month moving average

0,590

0,595

0,600

0,605

0,610

0,615

0,620

0,625

0,630

0,635

Feb-03

May-03

Aug-03

Nov-03

Feb-04

May-04

Aug-04

Nov-04

Feb-05

May-05

Aug-05

Nov-05

Feb-06

May-06

Aug-06

Nov-06

Feb-07

May-07

Aug-07

Nov-07

Feb-08



17

TABLE 3 - Labour Inequality – Total Population (6 Brazilian metropolitan areas)

Level

GINI

Apr/02 0,6270 Apr/03 0,6284 Apr/04 0,6258 Apr/05 0,6036 Apr/06 0,6011 Apr/07 0,5963 Apr/08 0,5844

Evolution

GINI

M. Móvel Variation (%) Variation (%) Difference (p.p.) Annual Evolution(12 meses) April 03 / April 02 0,22 0,001 April 04 / April 03 -0,40 -2,17 -0,003 April 05 / April 04 -3,56 -2,10 -0,022 April 06 / April 05 -0,41 -1,12 -0,002 April 07 / April 06 -0,80 -0,82 -0,005 April 08 / April 07 -2,00 -1,33 -0,012 Accumulated Evolution (since 2002) April 08 / April 02 -6,79 -0,043 April 08 / April 03 -7,00 -7,32 -0,044 April 08 / April 04 -6,62 -5,26 -0,041 April 08 / April 05 -3,18 -3,23 -0,019 April 08 / April 06 -2,78 -2,13 -0,017 April 08 / April 07 -2,00 -1,33 -0,012

Criterion: per capita usual income


POVERTY

Income distribution and labor poverty improve the function of the average income

accelerated growth , as well as the reduction in income inequality. Here, we present

estimates of metropolitan areas labor poverty using the poverty line of 135 Reais per

month per person at Sao Paulo metropolitan area prices, adjusted for spatial differences

in living costs, according to the Center for Social Policies at the Fundação Getulio

Vargas (Neri 2006 e Ferreira, Lanjouw e Neri 2003).

18

GRAPH 6 - Labor Poverty Series 12-month moving average

26

27

28

29

30

31

32

33

34

35

36

37

Feb

-03

May

-03

Aug

-03

Nov

-03

Feb

-04

May

-04

Aug

-04

Nov

-04

Feb

-05

May

-05

Aug

-05

Nov

-05

Feb

-06

May

-06

Aug

-06

Nov

-06

Feb

-07

May

-07

Aug

-07

Nov

-07

Feb

-08



TABLE 4 - Poverty – Total Population (6 Brazilian Metropolitan areas)

Level

Class E

Apr/02 34,93 Apr/03 37,13 Apr/04 37,17 Apr/05 32,58 Apr/06 31,61 Apr/07 29,09 Apr/08 25,16

Evolution

Class E

Moving average

Variation (%) Variation (%) Difference (p.p.)

April 03 / April 02 6,31 2,20 April 04 / April 03 0,11 3,60 0,04 April 05 / April 04 -12,34 -10,74 -4,59 April 06 / April 05 -2,99 -5,81 -0,98 April 07 / April 06 -7,97 -6,61 -2,52 April 08 / April 07 -13,50 -7,42 -3,93 Accumulated Evolution (since 2002) April 08 / April 02 -27,97 -9,77 April 08 / April 03 -32,24 -24,70 -11,97 April 08 / April 04 -32,31 -27,31 -12,01 April 08 / April 05 -22,78 -18,56 -7,42 April 08 / April 06 -20,39 -13,54 -6,45

Criterion: Per capita usual income


19

Labor Poverty – 15 to 60 years

TABLE 5 - Miséria Trabalhista – 15 a 60 anos

6 Regiões Metropolitanas brasileiras

Nível

Class E


Evolução

Class E Variation (%) Variation (%) Variation (%)

Annual Evolution (12 meses) abril 03 / abril 02 6,34 1,82 abril 04 / abril 03 -0,04 3,71 -0,01 abril 05 / abril 04 -16,51 -14,09 -5,03 abril 06 / abril 05 -3,42 -7,35 -0,87 abril 07 / abril 06 -11,54 -8,96 -2,83 abril 08 / abril 07 -15,30 -9,78 -3,32

Accumulated Evolution (since 2002) abril 08 / abril 02 -35,78 -10,25 abril 08 / abril 03 -39,61 -32,20 -12,06 abril 08 / abril 04 -39,59 -34,62 -12,05 abril 08 / abril 05 -27,64 -23,90 -7,03 abril 08 / abril 06 -25,08 -17,87 -6,16 abril 08 / abril 07 -15,30 -9,78 -3,32

Critério: Renda Per Capita Habitual


20

4. DEFINING THE MIDDLE-CLASS Defining the middle-class is like defining an elephant, if you have never seen one, it is

hard to visualize it. There are at least two perspectives to conceptualize the class. One is

through the analysis of people’s attitudes and expectations. Brazilian consumers’

survey, as released monthly by the Brazilian Institute of Economics at the Fundação

Getúlio Vargas, goes in that direction. This kind of approach was much developed in

the 1950s’ and 1960s’ by George Katona, a behavior psychologist who greatly admired

James Tobin. Following the same line, Thomas Friedman, international columnist at the

New York Times in his best-seller book “The world is flat”, defines middle-class more

than merely by its present living conditions and income, but also for its hoping to be in

a better position in the future. This upward social structural mobility would be just like

realizing the American dream, understood as the possibility of social ascension in each

country. The class is that group that shares a plan of individual progress.

Additionally, we propose (but do not release here) the use of measures of life quality

and other subjective questions from the new line of surveys as the Gallup World Poll,

IPSOS similar, whose advantage is its high international comparability for applying the

same questionnaire to a great number of countries. This advantage is also shared by the

regionally based surveys, such the LatinBarometer in Latin America and the

EuroBarometer in the old continent. In particular, we suggest the use of direct measures,

such as the expectation of happiness five years into the future in comparison with the

current level of happiness – by asking questions where the person may attribute a

subjective grade from 0 to 10 about their respective satisfaction with life. This kind of

analysis was used in the Future Happiness Index (FHI) that we developed for a project

with the Inter-American Development Bank, based on a sample of more than 132

countries covered by the 2006 Gallup World Poll. This index will be released shortly.

For now, we can say that the data indicate, measured by the difference between the

current and future happiness levels, is high in relation to other countries which is

consistent with the enlarging Brazilian middle class discussed here.

The second way to define the social classes (E, D, C, B2, B1, A2 and A1) is according

to their consumption potential, such as the Brazil Criterion in which the middle-class (r

for some the lower middle class) is called Class C. This stratification is implemented

according to the impact of access to durable goods and their respective amount (TV set,

21

radio, washing machine, fridge, freezer, DVD or video player), toilettes, servants and

level of education of the head of the household3. This criterion estimates the weights

from a mincerian equation (log of the total household income). CPS proposes a

complementary conceptualization to measure the evolution of the new middle class in

Brazil, also from a producer’s point of view – that is, the capacity to keep this

consumption potential through time. In this yet unpublished work, apart from testing the

measurement of the middle class based on a combination of elements such as income

and access to consumer goods traditionally used, we also propose to measure the middle

class based on the capacity of income generation and wealth sustainability in the longer

term. In the first aspect, there is access to public or private university, access to an

education of quality (private?) to resources of the Information and Communication

Technology era, such as computers with Internet connection; and, beyond the current

income, the permanent income based on fixed socio-demographic features (like gender,

age, region, etc. but especially education stock). Concerning the sustainable aspect of

the family financial situation in the longer term, there is access to formal jobs that

ensure a higher level of social protection, access to private pension, to housing credit,

lease or freehold (with a minimum standard of quality: toilettes, type of building, etc.),

health insurance. This kind of concern with education and work placement is present in

the criteria applied in England, Portugal and India. The innovating aspect of this

methodology is its capacity to look at symbolic aspects of the middle class, such as the

employment registration booklet, university entry, or access to ICT, as well as to

combine these with social status aspects related to the private demand for goods, which

were previously a quasi monopoly of the Brazilian State, such as social security, health,

education and housing credit. Another innovation is the capacity to measure on a

national scale each mentioned component, to study its interaction and the aggregation of

the same ones into synthetic indexes about the size and distribution of the middle class;

as well as to look deeper into the details of its determining factors (for instance, to go

beyond the statistics concerning access to education to see how much it costs) and to

consider the interaction of these diverse components, monitoring them through time. In

the present research, we explore some aspects that are associated with the two lines

above mentioned: generation of income from work and labor mobility.

3 These variables are measured by the demographic Census, which facilitates the spatial classification of the families’ purchasing Power, but it is not well covered by the PNAD, for instance. In the hierarchical model that imputes lacking income, as developed by IBGE, considered in the Census 2000 microdata, the most relevant variables are the level of instruction of the person taken as a reference for the household and the number of toilettes

22

QUANTIFYING THE SIZE OF SOCIAL STRATA

Contrary to the analysis of relative income distribution where we map the relative share

of each group in the total income (like, for instance, the 10% richest who own almost

50% of the income in Brazil, etc.), here we focus on the share of population which is

between fixed thresholds for the whole period. In other words, we are concerned with

the absolute income of each person. The current approach is similar to that used in the

analysis of absolute poverty, only that we are concerned also with other frontiers, such

as those that determine the entry into the middle class and the upward movement

towards the upper-class. In the relative approach, the sum of the parts totals 100% of

something relative per month, while in the absolute approach applied to the several

segments in the social pyramid, they are indexed by an absolute value applicable to all

months. These absolute values are parameters for what it is to live in poverty, in an

intermediate group between poverty and the middle class, which we call here the D

class – (“remediados” or remediated), C class (middle class) and the A and b Classes

(upper-class). As our work concerns a period of strong growth in average income, the

two approaches - relative and absolute - present truly distinguished results. Each one of

these situations tend to happen, respectively, at the beginning and at the end of a period.

To use an analogy, in the relative distributive analysis, we may use a graph of a fixed-

size pie, where for a group to win, another must loose its share. In the absolute analysis,

used here, apart from the distributive dance, the size of the pie can also change. What

lies behind the result is that, apart from people with lower income having gained a

greater share of the pie (reduction in inequality), the same cake has increased its size

(growth). The pie has grown to a medium-sized format; but for the optimists, this is now

a large cake. In the present analysis, we are not only concerned with its distribution, but

also with the amount of cake owned by the strata in society.

23

5. CHANGES IN THE PIE

The main feature of the approach used here is its level of disaggregation along three

income groups, where we look at the initial relative position first in order to probe them

further later on: the upper-class (the tenth richest part who owns almost half of the per

capita income); the poorest half how owns a little more than a tenth of the national

income (9,95%) including also the extremely poor; and the 40% intermediate group

whose share in the population and income virtually coincides with one another

(39,78%), making Brazil a medium income country, similar to Peru, and between the

rich Belgium and the poor India4. Heuristically, here we want to investigate the

migrations between these different Brazils, as we are concerned about quantifying the

population strata living in the pre-fixed and determined living conditions and their

evolution through time.

The tables and graphs below present the levels and trends of these series.

TABLE 6 – Economic Classes

Labor Earnings Distribution – 15 to 60 years old

(6 Brazilian metropolitan areas)

Level

Middle Class

C Class Upper Class A & B Class

Poor & Just above Poverty

E & D Class Just above Poverty

D Class

Moving average

Moving average

Moving average

Moving average

Rate (%) Rate (%) Rate (%) Rate (%) Rate (%) Rate (%) Rate (%) Rate (%) Apr/02 44,19 12,99 42,82 14,18 Apr/03 42,49 43,42 11,59 12,97 45,92 43,61 15,46 14,44 Apr/04 42,26 42,80 11,61 11,55 46,13 45,65 15,68 15,40 Apr/05 46,70 46,21 12,61 12,57 40,70 41,23 15,28 15,24 Apr/06 48,59 48,72 13,60 13,20 37,80 38,09 13,25 14,00 Apr/07 48,87 50,11 14,41 14,26 36,73 35,64 15,01 13,71 Apr/08 51,89 50,81 15,52 15,19 32,59 33,99 14,20 14,22

Obs: 12-month moving average ended in the period

4 Under this aspect, the distribution of labor earnings in metropolitan areas in the PME is more concentrated than in the national Pnad in all income sources.

24

Class C – New Middle Class Firstly and more importantly for the objectives of this study, is the middle class. This

group encompassed 44.19% of the population at the beginning of the series in April

2002, moved on to 51.89% in April 2008 (the last observation available), with an

overall increase of 17.03% in the importance of the middle-class. If we fix the initial

period for after the 2002 instability and the 2003 recession, straight into April 2004, the

middle-class reached 42.85% of the population and grew around 18.72% until April

2008.

That is, a growth of almost 4% per year above the population growth of the reference

group.

TABLE 7 - Share in Income – 15 to 60 years old – Household Labor (6 Brazilian metropolitan areas)

C Class

Moving average

Variation (%) Variation (%) difference (p.p.) Annual Evolution (12 months)

April 03 / April 02 -3,85 -1,70 April 04 / April 03 -0,54 -1,42 -0,23 April 05 / April 04 10,50 7,96 4,44 April 06 / April 05 4,06 5,43 1,90 April 07 / April 06 0,57 2,85 0,28 April 08 / April 07 6,18 1,41 3,02

Accumulated Evolution (since 2002) April 08 / April 02 17,43 7,70 April 08 / April 03 22,13 17,03 9,40 April 08 / April 04 22,79 18,72 9,63 April 08 / April 05 11,12 9,97 5,19 April 08 / April 06 6,79 4,30 3,30 April 08 / April 07 6,18 1,41 3,02

25

GRAPH 7 - Participation of C Class (%) - Middle Class

Class structure - 15 to 60 years old - Labor – 6 metropolitan regions (Brazil)

42

44

46

48

50

52

Mar

-02

Jun-

02

Sep

-02

Dec

-02

Mar

-03

Jun-

03

Sep

-03

Dec

-03

Mar

-04

Jun-

04

Sep

-04

Dec

-04

Mar

-05

Jun-

05

Sep

-05

Dec

-05

Mar

-06

Jun-

06

Sep

-06

Dec

-06

Mar

-07

Jun-

07

Sep

-07

Dec

-07

Mar

-08

Source: CPS/FGV based on PME microdata Criterion: Per Capita Usual income (40% intermediate PME)

GRAPH 8 - Participation of C Class (%) - Middle Class

Class structure - 15 to 60 years old 12-month moving average

42

44

46

48

50

52

Feb

-03

May

-03

Aug

-03

Nov

-03

Feb

-04

May

-04

Aug

-04

Nov

-04

Feb

-05

May

-05

Aug

-05

Nov

-05

Feb

-06

May

-06

Aug

-06

Nov

-06

Feb

-07

May

-07

Aug

-07

Nov

-07

Feb

-08

Source: CPS/FGV based on PME microdata

Criterion: Per Capita Usual income (40% intermediate PME)

26

TABLE 8 - Share in Income – 15 to 60 years old – Household - Labor

A and B Classes

Evolution

A & Br

Classes

Moving average


April 03 / April 02 -10,78 -1,40 April 04 / April 03 0,19 -10,95 0,02 April 05 / April 04 8,57 8,82 0,99 April 06 / April 05 7,89 5,01 1,00 April 07 / April 06 5,90 8,02 0,80 April 08 / April 07 7,73 6,56 1,11 April 08 / April 02 19,46 2,53 April 08 / April 03 33,89 17,13 3,93 April 08 / April 04 33,64 31,53 3,91 April 08 / April 05 23,09 20,87 2,91 April 08 / April 06 14,09 15,11 1,92 April 08 / April 07 7,73 6,56 1,11

Back to the upper class group, which corresponds to classes A and B of the studies of

consumption potential, it reached 12.99% of the population at the beginning of the

series in April 2002, moved on to 15,52% in April 2008, with an increase of 19.46% in

importance reflecting the good period of the middle class.

GRAPH 9 - Participation of A & B Class (%) Class structure - 15 to 60 years old - Labor – 6 m etropolitan regions (Brazil)

11

12

13

14

15

16

Mar

-02

Jun-

02

Sep

-02

Dec

-02

Mar

-03

Jun-

03

Sep

-03

Dec

-03

Mar

-04

Jun-

04

Sep

-04

Dec

-04

Mar

-05

Jun-

05

Sep

-05

Dec

-05

Mar

-06

Jun-

06

Sep

-06

Dec

-06

Mar

-07

Jun-

07

Sep

-07

Dec

-07

Mar

-08

Source: CPS/FGV based on PME microdata Criterion: Per Capita Usual income

27

GRAPH 10 - Participation of A & B Class (%)

Class structure - 15 to 60 years old - 12-month moving average

11

12

13

14

15

16

Feb

-03

May

-03

Aug

-03

Nov

-03

Feb

-04

May

-04

Aug

-04

Nov

-04

Feb

-05

May

-05

Aug

-05

Nov

-05

Feb

-06

May

-06

Aug

-06

Nov

-06

Feb

-07

May

-07

Aug

-07

Nov

-07

Feb

-08


Criterion: Per Capita Usual income

TABLE 9 - D & E Classes

Moving average


April 03 / April 02 7,24 3,10 April 04 / April 03 0,45 4,67 0,21 April 05 / April 04 -11,78 -9,69 -5,43 April 06 / April 05 -7,11 -7,62 -2,89 April 07 / April 06 -2,85 -6,43 -1,08 April 08 / April 07 -11,26 -4,60 -4,14 April 08 / April 02 -23,89 -10,23 April 08 / April 03 -29,03 -22,05 -13,33 April 08 / April 04 -29,35 -25,53 -13,54 April 08 / April 05 -19,92 -17,54 -8,10 April 08 / April 06 -13,79 -10,74 -5,21 April 08 / April 07 -11,26 -4,60 -4,14

Criterion: Per Capita Usual income Source: CPS/FGV based on PME microdata

Given our focus on the middle class and how we have already focused on the extremely

poor group in the section of the paper using the total population as reference, we restrict

this section to the sum of extremely poor and ´Just above Poverty´ groups, and then we

present the data for the D Class. The basis of the distribution formed by these two

groups corresponded to 42.82% of the population in April 2002, falling to 32,59%.

28

GRAPH 11 - Participation of D & E Classes (%)

Class structure - 15 to 60 years old - Labor – 6 metropolitan regions (Brazil)

32

34

36

38

40

42

44

46M

ar-0

2

Jun-

02

Sep

-02

Dec

-02

Mar

-03

Jun-

03

Sep

-03

Dec

-03

Mar

-04

Jun-

04

Sep

-04

Dec

-04

Mar

-05

Jun-

05

Sep

-05

Dec

-05

Mar

-06

Jun-

06

Sep

-06

Dec

-06

Mar

-07

Jun-

07

Sep

-07

Dec

-07

Mar

-08


GRAPH 12 - Participation of D & E Classes (%)


32

34

36

38

40

42

44

46

Feb

-03

May

-03

Aug

-03

Nov

-03

Feb

-04

May

-04

Aug

-04

Nov

-04

Feb

-05

May

-05

Aug

-05

Nov

-05

Feb

-06

May

-06

Aug

-06

Nov

-06

Feb

-07

May

-07

Aug

-07

Nov

-07

Feb

-08


TABLE 10 - D Class (only)

Moving average Variation (%) Variation (%) Difference (p.p.) April 03 / April 02 9,05 1,28 April 04 / April 03 1,40 6,61 0,22 April 05 / April 04 -2,58 -1,05 -0,41 April 06 / April 05 -13,24 -8,08 -2,02 April 07 / April 06 13,26 -2,08 1,76 April 08 / April 07 -5,42 3,68 -0,81 April 08 / April 02 0,11 0,02 April 08 / April 03 -8,20 -1,56 -1,27 April 08 / April 04 -9,47 -7,67 -1,48 April 08 / April 05 -7,07 -6,69 -1,08 April 08 / April 06 7,12 1,52 0,94 April 08 / April 07 -5,42 3,68 -0,81


29

As we separate them? from the analysis, we note a more erratic behavior of the D Class

through time inversely reflecting the middle-class trajectory, the other intermediate

group analyzed here. As a consequence, the participation of the group in the population

remains constant in comparison with the extremes in the series: goes from 14.18% in

april 2002 to 14.2% in April 2008.

GRAPH 13 - Participation of D Class (only) (%) Class structure - 15 to 60 years old

Labor – 6 metropolitan regions (Brazil)

12,5

13,0

13,5

14,0

14,5

15,0

15,5

16,0

Mar

-02

Jun-

02

Sep

-02

Dec

-02

Mar

-03

Jun-

03

Sep

-03

Dec

-03

Mar

-04

Jun-

04

Sep

-04

Dec

-04

Mar

-05

Jun-

05

Sep

-05

Dec

-05

Mar

-06

Jun-

06

Sep

-06

Dec

-06

Mar

-07

Jun-

07

Sep

-07

Dec

-07

Mar

-08


GRAPH 14 - Participation of D Class (only) (%)


13

13

14

14

15

15

16

16

Feb

-03

May

-03

Aug

-03

Nov

-03

Feb

-04

May

-04

Aug

-04

Nov

-04

Feb

-05

May

-05

Aug

-05

Nov

-05

Feb

-06

May

-06

Aug

-06

Nov

-06

Feb

-07

May

-07

Aug

-07

Nov

-07

Feb

-08


30

6. THE DISTRIBUTIVE DANCE PME uses the methodology of a revolving panel that seeks to collect information in the

same households in the months t , t+1 , t+2 , t+3 , t+12 , t+13 , t+14 , t+15, totaling 8

interviews along a period of 16 months. The initial approach used here consists in

calculating the likelihood of the transition into- and out of poverty of the four society

groups such as the middle class, D Class, and upper class, as well as the non-transition

among these groups in the consecutive 4 months from March 2002. The last analyzed

group covers the period between January and April 2008.

The longitudinal aspect of the data for the household per capita income from work will

provide empirical evidence about the pattern of social mobility observed in practice. To

begin with, we present the data concerning people who enter or leave the two main

statuses through time, namely the middle-class (14.87%) and poverty (11.34%). This

means that at each four-month period from 2002 to 2008, 14.87% of the people entered

or left the middle-class and another 11.34% entered or left poverty. The greatest

mobility in relation to the middle-class and from it towards the upper groups, as well as

the people who leave the upper strata towards the middle-class and from it to the lowest

strata. Now, entry and exit out of poverty only happen for upper groups, causing a lower

likelihood of transition in relation to the movements related to the middle-class, with a

total of four alternatives of changes. The table below details the mobility rate relative to

each social group and the probability of associated transitions.

In four years, the time series indicate that the poverty rate based on income from work

fell 19.8% or 4.6 percentage points, from 23.3% to 18.57%. The biggest part of the

decrease happened between April and July 2004. When working with a moving average,

it becomes clear that the change in the poverty threshold occurred exactly in this period.

We will initially focus on this period, taking advantage of the PME longitudinal aspect.

Longitudinal data allow to measure who gets into and out of poverty, in the same way

as who remains in it or out of it through time. Table 9 analyzes the four-month period

between April and July each year.

31

TABLE 11

E Class Mobility

Rate

Middle Class

Mobility Rate

E Class Exit Probability

E Class Probability of entering

C Class Exit probabiltiy

C Class Probability of entering

Total 11,34 14,87 24,47% 6,88% 14,97% 14,76%

Next, we present the evolution of these mobility rates through time. These series show that,

after the 2002 instability, there is a decrease in both the mobility rates between several society

groups until December 2005; then the series present some fluctuation with a marked upward

trend, especially in the middle-class mobility at the end of 2007 onwards. These data may be

capturing another type of risk in the case of income that affects the daily life of people. The

mobility peaks at the end of 2002 and since the 2007 coincide with the increased

macroeconomic uncertain conditions.

GRAPH 15 - Labor Mobility Rate (2002 a 2008)

6 Metropolitan Areas

7

9

11

13

15

17

19

21

Jun-

02

Oct

-02

Feb

-03

Jun-

03

Oct

-03

Feb

-04

Jun-

04

Oct

-04

Feb

-05

Jun-

05

Oct

-05

Feb

-06

Jun-

06

Oct

-06

Feb

-07

Jun-

07

Oct

-07

Feb

-08

E Class C Class

Source: CPS/IBRE/FGV based on PME/IBGE microdata

In the analysis of the relative social mobility between the Rio de Janeiro and Salvador

Metropolitan areas, they are presented as less risky in relation to both segments, while the

riskier ones differ. Belo Horizonte and Porto Alegre are singled out in the total probability of

entering or leaving the middle-class, while Recife is singled out in terms of movements towards

poverty.

32

GRAPH 16 - Labor Mobility Rate (2002 a 2008)

by Metropolitan Areas

17,8

10,3

14,9

8,511,0

13,9

19,5

10,7

16,1

19,3

16,8

10,3

Rec

ife

Sal

vado

r

Bel

oH

oriz

onte

Rio

de

Jane

iro

São

Pau

lo

Por

toA

legr

e

E Class C Class

Source: CPS/IBRE/FGV based on PME/IBGE microdata As we isolate the entry and exit movements of each status, we gain a clearer vision of

their nature. The risks of entering poverty have fallen slightly through time, while the

risks of leaving it not only have reached higher levels, but have also fluctuated a little

more. It is worth highlighting the two peaks in the series of poverty exit in mid-2004

recovery after the 2003 recession and the positive record observed in 2008. That is,

according to the Chinese hexagram that depicts the junction of two trigrams of risk and

opportunity, 2007 represents paradoxically a rise in the risk of finding good

opportunities.

GRAPH 17 - Labor Mobility Probability (2002 a 2008) – E Class

6 Metropolitan Areas

0%

5%

10%

15%

20%

25%

30%

35%

Jun-

02

Oct

-02

Feb

-03

Jun-

03

Oct

-03

Feb

-04

Jun-

04

Oct

-04

Feb

-05

Jun-

05

Oct

-05

Feb

-06

Jun-

06

Oct

-06

Feb

-07

Jun-

07

Oct

-07

Feb

-08

Probability of exit Probability of entering


33

Now, we move back to the open regional data according to the entry and exit of the

income lower end. The risks faced by Recife inhabitants in entering and leaving poverty

in the period are very close. In particular, the probability of entering poverty, although

lower than entry’s, is around three times as high if compared to Rio and more than 60%

higher than Belo Horizonte’s, which has the second highest probability of poverty

entry. On a positive note, the probability of poverty exit in Porto Alegre, Belo Horizonte

and São Paulo are in much higher stances compared to the three other areas.

GRAPH 18 - Labor Mobility Probability (2002 a 2008) – E Class

By Metropolitan Areas

20,4%17,1%

29,4%

19,1%

29,4% 30,8%

15,8%

6,8%9,4%

4,7%6,3%

8,7%

Rec

ife

Sal

vado

r

Bel

oH

oriz

onte

Rio

de

Jane

iro

São

Pau

lo

Por

toA

legr

e



Next, we present the probability of entering and leaving the middle-class by

metropolitan region, which for its bilateral aspect is more complex to be analyzed than

that of poverty, where it is clearer that he who enters poverty or leaves it may,

respectively, lose or gain purchasing power. Briefly, Recife is highlighted for its greater

probability of entering the middle-class; whereas Porto Alegre has the highest

probability of exit.

34

GRAPH 19 - Labor Mobility Probability (2002 a 2008) – C Class

By Metropolitan Areas

12,2%

8,4%

19,4%

11,4%

17,3%

20,6%

27,3%

13,6%

9,9%

18,0%15,0%

19,6%

Rec

ife

Sal

vado

r

Bel

oH

oriz

onte

Rio

de

Jane

iro

São

Pau

lo

Por

toA

legr

e



SOCIAL DESTINATIONS Finally, we uncover the destinations for each social strata transition per year. Once

more, 2004 and 2008 are remarkable in terms of poverty; only 71.96% of the poor

remained poor four months after the first observation in 2004. Such statistics fall to

67.57% in the period observed in 2008 – which saw the transitions from Class E ( poor)

towards classes D and C. That is, we analyzed the transition into and out of the different

income groups. In all cases, 2008 is the best point in the series. The reader is invited to

look at the destinations of the individuals from several social segments.

TABLE 12 - Destination Matrix - (Who was Class E initially)

Period2 (April)

E Class

D Class

C Class

A & B

classes January 2003 73,38 13,48 11,30 1,85 2004 71,96 14,13 11,52 2,38 2005 77,30 13,20 8,87 0,63 2006 76,86 12,65 9,66 0,83 2007 77,52 11,22 10,22 1,03 2008 67,57 16,46 14,53 1,45


35

TABLE 13 - Destination Matrix - (Who was Class D initially )

Period2 (April)

E Class

D Class

C Class

A & B

classes January 2003 23,66 53,30 22,72 0,33 2004 19,13 56,19 24,27 0,41 2005 16,03 62,28 21,56 0,13 2006 18,58 58,13 22,89 0,41 2007 14,75 65,00 20,26 0,00 2008 15,07 54,92 29,46 0,56


TABLE 14 - Destination Matrix - (Who was middle-class (Class C) initially )

Period 2 (April)

E Class

D Class

C Class

A & B

classes January 2003 8,82 10,02 78,78 2,39 2004 6,26 8,55 81,04 4,15 2005 4,20 6,35 86,95 2,50 2006 5,63 6,17 85,11 3,10 2007 3,76 6,52 86,35 3,37 2008 3,70 6,98 84,58 4,74


TABLE 15 - Destination Matrix - (Who was in the upper class in itially )

Period 2 (April)

E Class

D Class

C Class

A & B

classes January 2003 4,50 0,39 17,07 78,04 2004 4,68 0,74 16,95 77,64 2005 1,32 0,82 8,75 89,11 2006 1,96 0,19 12,34 85,51 2007 1,00 0,14 11,95 86,91 2008 1,60 0,55 15,47 82,38


36

7. THE RETURN OF THE “CARTEIRA DE TRABALHO” (EMPLOY MENT REGISTRATION BOOKLET) What is it to be part of the Class C? Having a computer, a car, credit access, a mortgage,

a mobile, being self-employed or an employer, making pension payments; having a

university degree, attending a private school, health insurance. But of all, the return of

the employment registration booklet may be the most representative element of the new

Brazilian middle class appearance. The final step was to analyze the evolution of formal

job posts in the country. This information is particularly important, since having a job

with a registration is a strong feature of the middle class. In this context, the recent

information is encouraging, with 309 thousand jobs in just a month, a record in the

historical series in June 2008 and 1.881 million new formal job posts in the last 12

months.

GRAPH 20 - Net Job Creation

-300.000

-200.000

-100.000

0

100.000

200.000

300.000

06_2

008

11_2

007

04_2

007

09_2

006

02_2

006

07_2

005

12_2

004

05_2

004

10_2

003

03_2

003

08_2

002

01_2

002

06_2

001

11_2

000

04_2

000

09_1

999

02_1

999

07_1

998

12_1

997

05_1

997

10_1

996

03_1

996

Source: CPS/IBRE/FGV based on CAGED/ M T E.

GRAPH 21 - Net Job Creation ( 12-month accumulated)

376.

325

531.

496

564.

069

642.

908

1.11

6.7

30

1.45

4.1

15

1.21

0.1

92

1.39

8.8

30

1.88

1.0

92

-624

.600-2

95.2

69

-45.

617

jun(

1997

)

jun(

1998

)

jun(

1999

)

jun(

2000

)

jun(

2001

)

jun(

2002

)

jun(

2003

)

jun(

2004

)

jun(

2005

)

jun(

2006

)

jun(

2007

)

jun(

2008

)


37

Next, we zoom into the 6 metropolitan areas in Brazil. The proportion of jobs created

there has grown, reaching 387 thousand posts in the first semester of 2008, around

28.5% of the total – the highest proportion in a historical series since 1992. In 2003, this

percentage was only 12.45%.

GRAPH 22 - Net Job creation (12-month accumulated)

298768

489641 491414539901

738461

493672

804250

956829

729148

858359

1125382

145437

jun(

2003

)

jun(

2004

)

jun(

2005

)

jun(

2006

)

jun(

2007

)

jun(

2008

)

6 RM s PM E Other Regions


In the next tables, we present a overview of the evolution in the different metropolitan

areas.

TABLE 16 - Net Job Creation

jan to june each year

TOTAL Other

regions TOTAL

RM PME RECIFE SALVADOR BELO

HORIZON R DE

JANEIRO SAO

PAULO PORTO ALEGRE

2008 1.360.645 973.458 387.187 7.371 19.505 57.108 56.896 217.076 29.231 2007 1.095.249 815.172 280.077 2.703 13.474 38.347 44.949 163.913 16.691 2006 923.937 695.830 228.107 809 5.400 40.190 33.615 138.280 9.813 2005 965.695 716.473 249.222 3.362 13.637 36.944 27.189 157.178 10.912 2004 1.033.289 814.786 218.503 1.305 6.900 30.037 30.708 121.136 28.417 2003 561.866 491.921 69.945 -6.894 -1.777 9.134 7.288 50.627 11.567 2002 680.443 567.642 112.801 -553 7.762 17.113 15.365 66.370 6.744 2001 573.544 443.050 130.494 1.754 4.728 14.026 14.553 80.917 14.516 2000 589.796 448.892 140.904 2.228 6.809 17.470 20.235 73.180 20.982 1999 18.055 104.921 -86.866 -9.660 -6.638 -3.469 -19.719 -42.559 -4.821 1998 61.267 132.495 -71.228 -9.190 -4.504 -2.353 -5.862 -41.926 -7.393 1997 321.989 292.842 29.147 -8.831 4.592 16.710 -3.436 13.740 6.372 1996 95.547 128.475 -32.928 -10.005 -3.983 8.128 4.145 -22.465 -8.748 Total 8.281.322 6.625.957 1.655.365 -25.601 65.905 279.385 225.926 975.467 134.283

Inhabitants 183.305.600 135.868.370 47.437.230 3.639.847 3.397.757 4.960.258 11.682.332 19.666.573 4.090.463


38

TABLE 17 - Net Job Creation (% Total)

jan a junho de cada ano

Other

regions TOTAL

RM PME RECIFE SALVADOR BELO

HORIZON R DE

JANEIRO SAO

PAULO PORTO ALEGRE

2008 71,54 28,46 0,54 1,43 4,20 4,18 15,95 2,15 2007 74,43 25,57 0,25 1,23 3,50 4,10 14,97 1,52 2006 75,31 24,69 0,09 0,58 4,35 3,64 14,97 1,06 2005 74,19 25,81 0,35 1,41 3,83 2,82 16,28 1,13 2004 78,85 21,15 0,13 0,67 2,91 2,97 11,72 2,75 2003 87,55 12,45 -1,23 -0,32 1,63 1,30 9,01 2,06 2002 83,42 16,58 -0,08 1,14 2,51 2,26 9,75 0,99 2001 77,25 22,75 0,31 0,82 2,45 2,54 14,11 2,53 2000 76,11 23,89 0,38 1,15 2,96 3,43 12,41 3,56 1999 581,12 -481,12 -53,50 -36,77 -19,21 -109,22 -235,72 -26,70 1998 216,26 -116,26 -15,00 -7,35 -3,84 -9,57 -68,43 -12,07 1997 90,95 9,05 -2,74 1,43 5,19 -1,07 4,27 1,98 1996 134,46 -34,46 -10,47 -4,17 8,51 4,34 -23,51 -9,16 Total 80,01 19,99 -0,31 0,80 3,37 2,73 11,78 1,62

Inhabitants 74,12 25,88 1,99 1,85 2,71 6,37 10,73 2,23 Source: CPS/IBRE/FGV based on CAGED/ MTE.

39

8. CONCLUSIONS This study was based on the PME microdata for their agile nature, which has enabled us

to diminish the average PNAD time lag of 18 months down to only four months. This

allowed us to assess the trajectory of the social indicators up to mid-2008. The increase

in speed is a necessary condition to foresee the continuity, or not, of the improvement in

distribution observed since the beginning of the decade. We observe the sustainability

of the pace of inequality reduction in the income from work between the end of 2006

and mid-2008. If the reduction in poverty were a competition among the workers of the

6 metropolitan regions in Brazil, these would be the award winning moments in the last

6 years: firstly the last 12 months: 2007-08 (-13,5%) followed by the same period in

2004-05 (-12,3%) and then 2006-07 (-8%). It is worth remembering that the last and the

first have not yet been considered by the official social statistics.

We focused on the greatest metropolitan areas as a result of their great availability of

recent data (until 2008). The core point concerns the finding that after years of crises in

these areas, the growth of a middle class there and how much of it is attributable to the

private job creation. The emphasis of the analysis is on the 6 biggest Brazilian

metropolitan areas that show a recovery from the so-called metropolitan unemployment

crisis. The research also emphasizes the social performance in these cities taken

isolately. In many cases, the analyses focus on the role of the high public income

transfers to the population such as the expansion of the Bolsa Familia and of the social

security contribution-related transfers associated with minimum wage adjustments. We

argue that, at least, the increase in the income from work rivals with these transfer in

explaining improvements in the income for the whole population (and that since 2001

for the poorest groups). This is well documented in the PNAD series that go as far as

October 2006. But since the end of the 2006 until now, the unprecedented aspect of the

empirical analysis, has been the leadership role of income from work in general and of

formal job posts created, in particular. That is, since the last statistical snapshot taken of

Brazil through the 2006 Pnad lenses, income from work has been the most important

aspect.

In effect, there is a lack of tune between the PNAD income and that from the national

accounts in the period since 2004 (Neri 2007 and 2005). In the period of 2005-06,

PNAD income grew at a Chinese-like rhythm of 16.4% 4.3 times higher than the Haiti-

40

like speed of per capita GDP. Pnad has not undergone any methodological change, nor

did the INPC used to deflate this calculation. The Asian looks of the PNAD growth is

reflected in other indicators in the 2005-06 period, such as commerce sales 11.8%, the

valuation of the stock markets, Ibovespa increased at 60%, and the creation of 4.6

million job posts, in particular, 2.5 million of new formal posts. Since 2001, Brazil

experiences a Chinese-like growth for the poorest (and only for them) but in 2005 and

2006 it experienced a Chinese-like growth for all social strata, compared to 2004. We

bring this discussion to 2007 and 2008 and afterwards.

In general terms, data point to a sustained decrease in poverty and an expansion of the

so-called middle class observed since the end of the 2003 recession. The rhythm in the

reduction of inequality observed since 2001, has not slowed down, and can be compared

in absolute terms with the famous concentration of income in the 1960’s, time of the

Brazilian economic miracle. The increase in average income keeps the pace of the

previous years as a result of the previous period, despite the slower rhythm observed in

the central economies and in the USA in particular. In short, the cake keeps growing

with more strength for the poorest classes for over 5 years, an unprecedented

combination in the Brazilian documented statistical history. Much has been said in the

decade about reduction in inequality and poverty, but much emphasis has been given to

the role of public income transfers to the poor and little attention to the structural

advances of the remaining segments in society.

The research reveals the recent rise of a new middle class despite the approaching signs

of external crises from the USA. Overall, the new PME data allow us to monitor the

social performance of different segments in the 6 metropolitan areas. After several years

of crises in these areas, they are back in the scene. The regional aspect which draws

more attention is the better performance of the Belo Horizonte area. Now, a question

related to the election period: which of the Brazilian metropolitan areas have had the

best reduction of poverty in the last six years? The answer would be Belo Horizonte (-

40,8%) , Rio de Janeiro (-30,7%) followed closed by Salvador (-29,8%). The

movements of improvements in the series of social indicators in the Great Belo

Horizonte region are relatively dispersed through 2002 to 2008, while the remaining

metropolitan areas have seen it more between April and June 2004. This geographical

and time aspects aside, a reduction in the distance between the average and the median

41

is present in all regions, representing the reduction in inequality that marks the recent

period.

Even in the period covered by the Pnads, the PME data provide revealing details of their

determinants through an analysis of the monthly dynamics of the indicators based on

income. In particular, we note a marked growth in the incomes of the poorest classes

between March and June 2004. Although this is the time when the minimum wage is

readjusted, there was not a real gain in the minimum wage during 2004. PME allows

assessing the details of entry and exit of several segments of the population, as it

follows the trajectory of the same individuals and their families through time.

To complete this recent scenario, we also counted on the Caged/MTE data (Cadastro

Geral de Emprego e Desemprego do Ministério do Trabalho e Emprego) from all

national territory. In this context, recent information is encouraging, with 309 thousand

jobs in a month reaching a record in the historical series now in June 2008 and 1,881

million of new formal job posts in the past 12 months. Then we zoomed into the 6 main

metropolitan areas. The proportion of jobs created there has grown, with 387 thousand

posts in the first semester of 2008, or 28.5% of the total, the biggest proportion in the

historical series (since 1992). In 2003, this was only 12.45%.

We begin this research from two perspectives about class definitions. Firstly, the

analysis of people’s attitudes and expectations. This kind of approach was developed in

the 1950s and 1960s’ by George Katona, behavioral psychologist. Following this line,

Thomas Friedman defines middle-class as having a well-defined social ascension plan

for the future. CPS proposes measurements in this subjective line: our Future Happiness

Index (IFF) will be released soon. We may already say that the index is high in Brazil

vis-à-vis other countries, which is consistent with the emergence of a middle-class in

the country.

The second way to define the economic classes E, D, C, B and A is according to their

consumption potential. The Brazil Criterion uses access to - and number of durable

goods (TV sets, radio, washing machine, fridge and freezer, video or DVD player),

toilettes, housemaid and the level of education of the head of the household. This

criterion estimates the weighs based on a Mincerian income equation. Beside measuring

42

all this, we suggest a complementary conceptualization to measure the evolution of the

new middle-class in Brazil also from the producer’s standpoint - in other words, based

on his/her capacity to keep this consumption potential through time. Since Robert

Hall’s 1977 classic work, we’ve known that the current consumption contains

information about the future patterns of consumption, whereas the analysis of these

expenses composition is useful by separating hedonism from the productive capacity, to

the same level of personal expenses. In the same terms as La Fontaine’s fable, one must

distinguish the ants from the consumerist grasshoppers.

The always tuned IBGE is now carrying out an excellent Family Budget Survey (POF)

and has announced the monitoring of family consumption expenses on a regular basis.

As we haven’t got there just yet, we implemented a methodology to explore IBGE’s

microdata. PME covers 40 thousand households per month in the six main metropolitan

areas in Brazil. Apart from its geographical limitations, the survey focuses exclusively

on income from work. Beside the sample size, the survey’s strength resides in its recent

aspect as PME brings us as far as April 2008; while POF, 2002/03 and PNAD,

September 2006. Income inequality follows the same decreasing trend observed since

2001. There is nothing statistically similar in the Brazilian documented history (since

1960). Another PME’s advantage is to measure changes in income levels from the same

families through time.

Class C is the central class, below A and B and above D and E. Brazil’s class C grew

from 42% in 2004 to 52% in 2008. According to the Pew Institute, 53% of the North-

Americans consider themselves to be part of the middle class. The new Brazilian

criterion pointed to 43% of Brazilians in the Class C in 2005, close to the 2004’s 42%.

In order to quantify the levels, we calculated the household per capita income from

work and then expressed it in terms equivalent to the total household income from all

sources. The central C class has an income between R$ 1064 and R$ 4561 at today’s

prices from the São Paulo Metropolitan region. International studies vary in what

concerns the upper monthly limit of the middle-class income from US$ 6000 (World

Bank), US$ 500 (Goldman Sachs) to US$300 (Barnajee & Duflo, MIT). Ours is within

their limits; that vary greatly. Our class C is located immediately above the 50% poorest

and the 10% richest at the turn of the century. Illustratively, class C is limited by the

43

Indian border on one side and by the Belgian border on the other side in the so-called

Belíndia. (Fn Belíndia is an aphorism created by Edmar Bacha to illustrate the Brazilian

income inequality).

We do not hold anything against those who see Brazilian class C as the lower middle

class and class B as the upper middle class. We are not the USA but this is also a free

country. It is indeed more important to have a well-defined, consistent criterion; but the

middle class label can be shared by other strata. All in all, our class C gets society’s

average income, that is, it is the middle-class in the statistical sense. Given the Brazilian

inequality, the average income is high in relation to our median. In relation to the rest of

the world: 80% of people in the world live in countries with a per capita income lower

than Brazilians’. Now, those who think that class C’s income is low must awaken

because this is the closest image to the Brazilian society. The Brazilian elite who take

themselves to be part of the middle-class should search for the words Made in USA

behind their mirrors.

44

9. BIBLIOGRAPHY

BACHA, E. L., AND TAYLOR, L.. “Brazilian income distribution in the 1960s: Tacts’ model results and the controversy.” Journal of Development Studies, Vol. 14, Issue 3, pages 271 – 297, 1978 BANERJEE, ABHIJIT V. AND DUFLO, ESTHER ”What is middle class about the middle classes around the world?”December 2007. BARROS, R.P. de; MENDONÇA, R. A evolução do bem-estar e da desigualdade no Brasil desde 1960. Rio de Janeiro: IPEA, 1992. (Texto para discussão, nº. 286). BARROS, R.P. de; HENRIQUES, R.; MENDONÇA, R. Desigualdade e pobreza no Brasil: a estabilidade inaceitável. In: HENIQUES, R. (Ed.). Desigualdade e pobreza no Brasil. Rio de Janeiro: IIPEA, 2000. BARROS, R. P. Foguel, M. N. ULYSSEA G. (Orgs.). Desigualdade de Renda no Brasil: uma análise da queda recente. Rio de Janeiro: IPEA, 2007. BARROS, Ricardo Paes; MENDONÇA, Rosane; NERI, Marcelo C. The duration of poverty spells. In: III Encontro Nacional de Estudos do Trabalho, ENABET, Anais..., 1996. BARROS, Ricardo Paes; MENDONÇA, Rosane; NERI, Marcelo C. Pobreza e inflação no Brasil: uma análise agregada. In: Economia Brasileira em Perspectiva 1996, Rio de Janeiro: Ipea, 1996, v.2, p.401-420. BIRDSALL, NANCY, CAROL GRAHAM, AND STEFANO PETTINATO “Stuck In Tunnel: Is Globalization Mudding The Middle Class?” Brookings Institution, Center on Social and Economic Dynamics WP No. 14, 2000. BOOT, H. M. (1999) “Real Incomes of the British Middle Class, 1760-1850: The Experience of Clerks at the East India Company”, The Economic History Review, 52(4), 638-668. BONELLI, R.P. de; SEDLACEK, G.L. Distribuição de renda: evolução no último quarto de século. In: SEDLACEK, G.L.; BARROS, R.P. de. Mercado de trabalho e distribuição de renda: uma coletânea. Rio de Janeiro: IPEA, 1989. (Série Monográfica 35). CARDOSO, E.; BARROS, R.; URANI, A. Inflation and unemployment as determinants of inequality in Brazil: the 1980s, Chapter 5. In: DORNBUSCH, R.; EDWARDS, S. (Eds.), Reform, recovery and growth: Latin America and the Middle-East, Chicago: University of Chicago Press for the NBER, 1995. DOEPKE, M.AND F. ZILIBOTTI (2005)”Social Class and the Spirit of Capitalism”, Journal of the European Economic Association 3, 516-24. DOEPKE, M AND F. ZILIBOTTI (2007)”Occupational Choice and the Spirit of Capitalism”, NBER Working Paper.

45

ESTERLY, WILLIAM (2001) “The Middle Class Consensus and Economic Development”, Journal of Economic Growth, 6(4), 317-335. FERREIRA, F.; LANJOUW, P.; NERI, M. A Robust poverty profile for Brazil using multiple data sources. Revista Brasileira de Economia 57 (1), p. 59-92, 2003. FISHLOW, A. (1972): “Brazilian Size Distribution of Income”, American Economic Association: Papers and Proceedings 1972, pp.391-402 Frederick, Jim (2002) “Thriving in the Middle Kingdom ”, TIME Magazine, Nov 11. GASPARINI, L. Different lives: inequality in Latin America the Caribbean, inequality the state in Latin America the Caribbean World Bank LAC Flagship Report 2003. Washington, D.C.: World Bank, 2003. Mimeografado. HOFFMAN, R. A evolução da distribuição de renda no Brasil, entre pessoas e entre famílias, 1979/86. In: SEDLACEK, G.; BARROS R.P. de. Mercado de trabalho e distribuição de renda: uma coletânea. Rio de Janeiro: IPEA/Inpes, 1989.

HOFFMANN, R. As transferências não são a causa principal da redução da desigualdade, Econômica 7, no.2, 335-341: Rio de Janeiro, Brazil, 2005. IPEA. Sobre a queda recente da desigualdade no Brasil, 2006. (Nota técnica). KAKWANI, N., SON, H. Measuring the Impact of price changes on poverty. International Poverty Centre, Brasília, 2006. (Working paper # 33). KAKWANI, N.; NERI, M.; SON, H. Linkages between pro-poor growth, social programmes labour market: the recent brazilian experience. International Poverty Centre, Brasilia, 2006a. (Working paper # 26). ______. Desigualdade e Crescimento: Ingredientes Trabalhistas em Desigualdade de Renda no Brasil: uma análise da queda recente. Ricardo Paes de Barros, Miguel Nathan Foguel, Gabriel Ulyssea (orgs), Rio de Janeiro, 2007. vide http://www.fgv.br/cps/pesquisas/propobre/ Landes, David. The Wealth and Poverty of Nations. New York: Norton, 1998. LANGONI, C. Distribuição da renda e desenvolvimento econômico do Brasil. Rio de Janeiro: Fundação Getúlio Vargas (FGV), 3a edição 2005, 1973 MURPHY, KEVIN M., ANDREI SCHLEIFER AND ROBERT VISHNY (1989) “ Industrialization and the Big Push”, Journal of Political Economy, 97(5), 1003-1026. NERI, Marcelo C.; CONSIDERA, Cláudio; PINTO, Alexandre. A evolução da pobreza e da desigualdade brasileiras ao longo da década de 90. In: Revista Economia Aplicada, Ano 3, v. 3, p.384-406, jul.-set. 1999.

46

NERI, Marcelo C. O reajuste do salário mínimo de maio de 1995. In: XIX ENCONTRO BRASILEIRO DE ECONOMIA, SBE, Recife. Anais... dez. 1997, v. 2, p. 645-666. NERI, Marcelo C.; CONSIDERA, Cláudio. Crescimento, desigualdade e pobreza: o impacto da estabilização. In: Economia Brasileira em Perspectiva 1996, Rio de Janeiro: Ipea, 1996, v.1, p. 49-82. NERI, M. C. Diferentes histórias em diferentes cidades. In: REIS VELLOSO, J.P.; CAVALCANTI, R. (Eds.). Soluções para a questão do emprego. Rio de Janeiro: José Olimpio, 2000. ______. Eleições e Expanções, mimeo, vide http://www.fgv.br/cps/pesquisas/pp2/, 2006a. ______. Miséria em queda: mensuração, monitoramento e metas. mimeo Rio de Janeiro: FGV, vide: http://www3.fgv.br/ibrecps/queda_da_miseria/inicio_q.htm . 2005. ______. Miséria, desigualdade e politicas de rendas: o Real do Lula, mimeo, Rio de Janeiro: FGV, 2007. ______. Miséria, desigualdade e estabilidade in Desigualdade de Renda no Brasil: uma análise da queda recente. Ricardo Paes de Barros, Miguel Nathan Foguel, Gabriel Ulyssea (orgs), Rio de Janeiro, 2007a. see: <http://www.fgv.br/cps/pesquisas/site_ret_port/ ______. A Dinâmica da Redistribuição Trabalhista em Desigualdade de Renda no Brasil: uma análise da queda recente. Ricardo Paes de Barros, Miguel Nathan Foguel, Gabriel Ulyssea (orgs), Rio de Janeiro, 2007b. ______. (org) Microcrédito, o mistério nordestino e o Grameen brasileiro: perfil e performance dos clientes do CrediAMIGO”, Editora da Fundação Getulio Vargas, 370pag, Rio de Janeiro, 2008 NERI, M. C.; CAMARGO, J. Distributive effects of Brazilian structural reforms. In: BAUMANN, R. (Ed.). Brazil in the 1990s: a decade in transition, Palgrave. Macmillan's Global Academic Publishing, UK, 2001. NERI, M. C.; GIOVANNI F, Negócios nanicos, garantias e acesso a crédito in Revista de Economia Contemporânea, Rio de Janeiro, v.9, n.3, pp 643-669, setember-december 2005. RAMOS, Lauro; BRITO, M. O funcionamento do mercado de trabalho metropolitano brasileiro no período 1991-2002: tendências, fatos estilizados e mudanças estruturais. Boletim Mercado de Trabalho, Conjuntura e Análise, Rio de Janeiro: Ipea, nº 22, p. 31-47, nov. 2003. ROCHA, S. Pobreza no Brasil: afinal do que se trata? Rio de Janeiro: Ed. FGV, 2003.

47

SOARES, S. “Análise de bem-estar e decomposição por fatores da queda na desigualdade entre 1995 e 2004.” Econômica, v. 8, n. 1, p. 83-115. Rio de Janeiro, 2006. WILSON, DOMINIC AND DRAGUSANU, RALUCA “The Expanding Middle: The Exploding World Middle Class and Falling Global Inequality” - Goldman Sachs Economic Research/Global Economics Paper nº 170, July 2008

48

APPENDIX I. PORTRAIT OF THE NEW MIDDLE CLASS

In this section, we present the evolution of the Brazilian middle-class according to

different socio-economic characteristics since 2002.

Gender

Income Groups – Labor (6 Brazilian metropolitan areas) C Class – New Middle Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Gender Men 18,89 44,88 44,36 46,18 49,76 51,57 51,74 53,36 Women 17,53 42,51 41,75 43,51 46,63 48,45 48,51 49,96

E Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Gender Men -38,07 27,14 28,43 25,71 22,50 20,76 18,68 16,81 Women -30,55 30,18 31,73 29,30 26,26 24,60 22,52 20,96


Age Income Groups – Labor (6 Brazilian metropolitan areas) C Class– New Middle Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Age 15 to 19 20,01 40,42 38,56 40,24 43,41 46,40 47,01 48,51 20 to 24 19,33 46,72 45,92 47,93 51,68 53,84 54,93 55,75 25 to 29 21,72 45,19 44,83 46,72 49,90 52,03 52,57 55,01 30 to 35 17,17 43,53 42,16 43,93 47,80 49,23 48,81 51,00 36 to 39 16,26 43,85 42,29 43,81 47,56 49,52 49,53 50,99 40 to 44 18,82 44,31 43,68 45,58 48,88 50,98 51,11 52,65 45 to 49 14,90 45,08 45,79 47,62 49,69 50,88 50,96 51,79 50 to 54 16,35 42,65 43,32 45,11 48,64 49,78 48,80 49,62 55 to 59 20,33 37,95 38,96 40,48 43,49 44,07 43,49 45,67

E Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Age 15 to 19 -28,02 34,83 37,12 34,46 31,63 29,13 26,42 25,07 20 to 24 -37,02 27,01 28,68 26,20 23,16 20,76 18,38 17,01 25 to 29 -42,14 26,19 27,93 25,42 21,94 19,67 17,70 15,15 30 to 35 -37,20 27,44 28,78 26,61 23,42 21,74 19,57 17,23 36 to 39 -29,72 26,88 29,10 26,82 23,32 21,83 20,02 18,89 40 to 44 -35,81 27,06 28,65 25,30 22,32 20,94 18,98 17,37 45 to 49 -31,90 25,56 26,57 23,97 21,71 20,76 18,76 17,41 50 to 54 -34,32 29,92 29,73 27,37 24,05 22,85 21,33 19,65 55 to 59 -28,64 36,90 36,88 33,95 30,35 29,85 27,96 26,33


49

Education Income Groups – Labor (6 Brazilian metropolitan areas) C Class– New Middle Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Education (years of schooling) Without instruction, less than 1 year 32,44 28,63 27,98 28,68 31,18 33,74 35,04 37,92 From 1 to 3 years of schooling 22,48 35,88 32,87 34,41 38,07 40,57 41,32 43,95 From 4 to 7 years of schooling 19,97 41,11 38,74 40,61 43,86 46,51 47,62 49,32 From 8 to 10 years of schooling 16,10 48,22 46,54 47,67 51,37 53,75 53,80 55,98 11 or more years of schooling 14,51 45,46 46,68 48,43 51,30 52,02 51,22 52,06

E Class (%) Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Education (years of schooling) Without instruction, less than 1 year -23,08 52,12 52,07 51,01 48,74 46,27 43,36 40,09 From 1 to 3 years of schooling -25,81 43,77 46,48 44,50 40,82 39,27 35,67 32,47 From 4 to 7 years of schooling -25,23 37,40 39,32 37,00 34,60 32,36 29,61 27,97 From 8 to 10 years of schooling -26,86 28,02 30,23 28,36 25,58 23,93 21,94 20,49 11 or more years of schooling -34,06 18,24 19,67 17,37 14,49 13,79 13,06 12,03


Job post

Income Groups – Labor (6 Brazilian metropolitan areas)

C Class– New Middle Class (%) Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Job post Formal employees 13,69 56,51 56,66 58,48 62,20 63,48 63,23 64,25 Informal employees 17,12 49,24 48,09 51,03 53,57 56,18 55,99 57,66 Employees military -2,41 50,78 50,89 52,71 53,99 52,38 49,97 49,55 Self-employed 18,77 47,04 46,45 47,97 51,20 53,63 53,88 55,87 Employer 8,58 35,85 38,61 40,67 41,55 41,32 39,37 38,93 Non-paid worker 10,86 49,91 47,71 49,18 57,00 52,84 52,19 55,33 Unemployed 31,98 28,49 27,20 28,66 30,55 33,32 34,33 37,60 Inactive 14,72 33,21 31,63 32,51 35,45 36,93 36,79 38,11

E Class (%) Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Job post Formal employees -55,11 12,48 13,54 11,05 8,64 7,39 6,42 5,60 Informal employees -42,65 21,95 23,65 20,49 17,54 15,58 13,85 12,59 Employees military -54,68 9,63 11,73 9,38 6,06 5,50 5,25 4,36 Self-employed -42,51 23,12 26,00 23,43 19,67 17,75 15,24 13,29 Employer -50,22 10,78 13,92 10,05 5,77 5,71 6,94 5,37 Non-paid worker -30,92 21,40 29,45 25,44 18,16 20,68 17,96 14,78 Unemployed -22,78 51,78 52,80 50,31 49,03 46,15 42,87 39,99 Inactive -17,88 44,40 46,10 44,43 41,82 40,50 38,21 36,46


50

Ethnicity


C Class– New Middle Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Ethnicity White 11,79 45,89 46,07 47,69 50,23 51,15 50,26 51,31 African 29,61 39,24 38,80 39,80 44,38 46,81 47,14 50,87 Asian -1,98 35,92 35,05 38,97 40,03 36,42 35,31 35,21 Mixed African-brazilian 26,96 41,31 39,14 41,56 46,03 49,08 50,74 52,44 Native indian 6,84 49,05 47,36 44,70 48,31 48,57 49,17 52,41

E Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Ethnicity White -32,14 22,99 24,16 21,60 18,96 18,22 16,90 15,60 African -38,84 38,55 39,33 36,65 32,72 30,21 27,74 23,58 Asian -17,85 18,47 22,98 14,56 11,88 13,77 15,34 15,17 Mixed African-brazilian -35,26 35,50 37,91 34,99 30,95 28,12 24,75 22,98 Native indian -24,57 29,88 28,92 30,81 27,37 29,25 29,65 22,54


Position in the household Income Groups – Labor (6 Brazilian metropolitan areas)


Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Position in the household Head 17,63 42,45 41,97 43,60 46,89 48,40 48,31 49,94 Spouse 17,46 45,30 44,31 46,44 49,88 51,36 51,37 53,22 Child 19,24 43,80 43,35 44,99 48,41 50,76 51,15 52,23 Relative 21,56 42,74 41,29 43,78 46,25 49,08 49,70 51,95 Non-related member 1,21 44,96 44,54 43,81 48,94 52,16 48,53 45,51

E Class (%)

Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Position in the household Head -32,64 29,26 30,58 28,05 25,12 23,58 21,47 19,71 Spouse -38,00 25,71 27,45 24,40 21,40 20,04 17,72 15,94 Child -33,59 30,07 31,17 28,96 25,55 23,43 21,43 19,97 Relative -29,80 33,19 36,12 33,20 29,66 27,27 25,76 23,30 Non-related member -30,55 29,74 26,91 23,08 20,64 19,30 20,20 20,66

Source: CPS/IBRE/FGV based on PME microdata

51

Number of people in the household



Period

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Number of people in the household From 1 to 2 14,63 45,60 45,87 47,39 50,51 51,68 50,96 52,26 From 3 to 4 20,95 42,71 41,16 43,19 46,64 49,05 50,01 51,66 From 5 to 6 23,16 37,36 34,27 35,66 38,93 41,87 43,39 46,01 More than 6 20,44 20,66 17,47 18,65 19,63 23,09 24,36 24,89

E Class (%)

Periodo

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Number of people in the household From 1 to 2 -31,77 25,25 26,26 23,81 21,06 20,03 18,52 17,23 From 3 to 4 -34,85 30,84 32,82 30,21 26,86 24,63 22,12 20,09 From 5 to 6 -28,53 38,28 41,03 39,00 35,99 32,97 29,69 27,36 More than 6 -16,63 58,85 62,98 62,72 60,58 56,50 52,79 49,06

Source: CPS/IBRE/FGV based on PME microdata Contributes to social security Income Groups – Labor (6 Brazilian metropolitan areas)


Periodo

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Contributes to social security Yes 12,31 53,52 53,72 55,58 58,78 59,88 59,36 60,11 No 20,19 47,71 46,44 48,78 52,11 54,83 55,12 57,34

E Class (%)

Periodo

2008* / 2002 2002 2003 2004 2005 2006 2007 2008

Contributes to social security Yes -54,55 12,37 13,54 10,97 8,41 7,21 6,46 5,62 No -39,17 25,23 27,73 24,80 21,36 19,46 17,18 15,35

Source: CPS/IBRE/FGV based on PME microdata

52

APPENDIX II. REGIONAL EVALUATION

We observe that the general trend of decrease in poverty and increase of the middle

class are present in all Brazilian metropolitan areas. In general, São Paulo Metropolitan

Region has the Best rates in all years, with the lowest poverty rates, followed by the

highest proportions of individuals in the middle-class. Meanwhile, the Belo Horizonte

Metropolitan region presents the best relative performance, gaining new positions in the

rankings of (lower) poverty and middle class. Next, we detail the evolution of these two

groups in each one of the 6 metropolitan regions.

1. Poverty in the Metropolitan Regions We present next an evolution of the poverty middle class in the main Brazilian

metropolis. As seen, when considering the last 6 years, all the cities present an

accumulated decrease of the poverty rate.

TABLE 1 - Poverty Rate

TOTAL 2002 2003 2004 2005 2006 2007 2008* Total 25,20 28,74 30,17 27,60 24,49 22,78 20,70 19,00 Metropolitan area Recife 44,06 46,64 52,26 51,89 42,99 39,15 35,91 34,64 Salvador 33,88 38,19 41,97 39,05 32,59 29,99 26,27 25,12 Belo Horizonte 26,48 33,32 33,56 28,51 26,03 22,37 20,09 18,64 Rio de Janeiro 25,73 31,22 29,38 27,16 25,10 23,59 21,29 19,74 São Paulo 19,93 21,90 24,00 21,70 19,30 18,38 16,83 14,78 Porto Alegre 22,91 24,49 27,81 24,25 21,97 21,25 19,93 18,36

TABLE 2 - Variation (in %) Poverty Rate

Annual Variation

2008*/ 2002

2007/ 2002 2003/02 2004/03 2005/04 2006/05 2007/06 2008*/07

Total -33,89 -27,97 4,97 -8,51 -11,28 -6,95 -9,13 -8,22 Metropolitan area Recife -25,73 -23,01 12,05 -0,71 -17,14 -8,93 -8,29 -3,53 Salvador -34,24 -31,22 9,89 -6,95 -16,55 -7,96 -12,42 -4,39 Belo Horizonte -44,06 -39,70 0,71 -15,05 -8,68 -14,07 -10,19 -7,22 Rio de Janeiro -36,75 -31,80 -5,87 -7,56 -7,58 -6,02 -9,77 -7,26 São Paulo -32,54 -23,15 9,59 -9,60 -11,07 -4,73 -8,44 -12,21 Porto Alegre -25,03 -18,64 13,54 -12,80 -9,38 -3,30 -6,22 -7,86

* until April Source: CPS/FGV based on PME microdata

53

2. Middle Class

With the decreases in the rate of poverty in all metropolitan areas, the next step is to

analyze how this reflected in another population group. Therefore, we will analyze the

growth of the middle class in each one of the metropolitan areas that reach the highest

levels in all of the series now in 2008.

TABLE 3 - Proportion of the C Class – New Middle Class

TOTAL 2002 2003 2004 2005 2006 2007 2008* Total 47,01 43,64 42,99 44,77 48,11 49,93 50,04 51,57 Metropolitan area Recife 30,35 27,94 24,69 25,60 31,10 34,00 35,62 36,67 Salvador 35,16 31,69 29,24 31,58 35,65 38,60 40,75 41,28 Belo Horizonte 46,98 40,71 41,00 44,91 47,20 51,09 52,53 53,90 Rio de Janeiro 47,92 43,15 45,44 46,22 48,96 50,76 50,37 52,42 São Paulo 51,00 48,70 47,20 48,96 52,48 53,45 53,17 54,68 Porto Alegre 50,60 48,77 46,50 49,20 52,08 53,30 52,03 53,67

TABLE 4 - Variation (in %) in the Proportion of the C Class – New Middle Class

Annual variation

2008*/ 2002

2007/ 2002 2003/02 2004/03 2005/04 2006/05 2007/06 2008*/07

Total 18,17 14,67 -1,49 4,16 7,44 3,78 0,22 3,05 Metropolitan area Recife 31,25 27,48 -11,63 3,68 21,48 9,31 4,77 2,96 Salvador 30,28 28,58 -7,73 8,00 12,88 8,30 5,55 1,32 Belo Horizonte 32,39 29,03 0,71 9,52 5,11 8,24 2,82 2,60 Rio de Janeiro 21,48 16,72 5,29 1,72 5,93 3,67 -0,77 4,08 São Paulo 12,26 9,17 -3,08 3,72 7,19 1,86 -0,53 2,83 Porto Alegre 10,05 6,69 -4,66 5,82 5,85 2,34 -2,39 3,15

* until April Source: CPS/FGV based on PME microdata

54

APPENDIX III: Multinomial Logit Models Estimated

I) Probability of Being in Different Economic Class es

– Base (E Class)

Resposta Parameter Category Estimate Standard

Error Wald

Statistic P-value Odds Ratio

Class A & B Intercept -6.5238 0.2336 779.6691 <.0001 .

GENDER Male 0.6822 0.0319 456.6774 <.0001 1.9783

COR Asian 1.6670 0.1442 133.5769 <.0001 5.2961

COR White 1.4112 0.0661 456.0550 <.0001 4.1008

COR Native 0.0404 0.7413 0.0030 0.9566 1.0412

COR Afro-brazilian 0.0271 0.0706 0.1478 0.7006 1.0275

AGE 15 TO 19 -0.3849 0.0789 23.8273 <.0001 0.6805

AGE 20 TO 24 -0.5800 0.0717 65.3576 <.0001 0.5599

AGE 25 TO 29 -0.3032 0.0677 20.0362 <.0001 0.7385

AGE 30 TO 35 -0.2391 0.0650 13.5208 0.0002 0.7874

AGE 36 TO 39 -0.3057 0.0713 18.3925 <.0001 0.7366

AGE 40 TO 44 0.0264 0.0667 0.1571 0.6919 1.0268

AGE 45 TO 49 0.3506 0.0673 27.1312 <.0001 1.4199

AGE 50 TO 54 0.2865 0.0684 17.5676 <.0001 1.3318

anoest 11 OR MORE 3.6702 0.1639 501.2025 <.0001 39.2604

anoest MISS 0.1249 0.7820 0.0255 0.8731 1.1330

anoest 1 TO 3 -0.2135 0.2088 1.0464 0.3063 0.8077

anoest 4 TO 7 0.5091 0.1699 8.9823 0.0027 1.6638

anoest 8 TO 10 1.8358 0.1670 120.8165 <.0001 6.2704

CONFAM Housemaid 0.9877 0.2956 11.1617 0.0008 2.6849

CONFAM Spouse 0.6985 0.0403 300.0847 <.0001 2.0107

CONFAM Child 0.1496 0.0454 10.8802 0.0010 1.1614

CONFAM Other relative -0.2280 0.0847 7.2412 0.0071 0.7961

NPES 1 2.9893 0.1404 453.0755 <.0001 19.8709

NPES 2 2.2959 0.1382 275.9951 <.0001 9.9335

NPES 3 1.6377 0.1412 134.5386 <.0001 5.1436

REG Recife -1.3906 0.0923 227.1840 <.0001 0.2489

REG Salvador -0.2162 0.0787 7.5491 0.0060 0.8056

REG Belo Horizonte 0.2517 0.0681 13.6604 0.0002 1.2862

REG Rio de Janeiro -0.1368 0.0572 5.7234 0.0167 0.8721

REG São Paulo 0.4516 0.0536 70.8615 <.0001 1.5708

ANO 2003 -0.6273 0.0503 155.6717 <.0001 0.5340

ANO 2004 -0.8833 0.0496 316.6122 <.0001 0.4134

ANO 2005 -0.5676 0.0480 140.0456 <.0001 0.5669

ANO 2006 -0.4815 0.0478 101.4135 <.0001 0.6179

YEAR 2007 -0.2421 0.0472 26.2899 <.0001 0.7850

55

Class C Intercept -1.3926 0.0854 266.0973 <.0001 .

GENDER Male 0.4522 0.0208 472.6205 <.0001 1.5718

COL Asian -0.3371 0.1296 6.7654 0.0093 0.7138

COL White 0.2297 0.0324 50.1747 <.0001 1.2582

COL Native 0.4194 0.2859 2.1528 0.1423 1.5211

COL Afro-brazilian -0.00558 0.0323 0.0299 0.8627 0.9944

AGE 15 TO 19 -0.0742 0.0496 2.2361 0.1348 0.9285

AGE 20 TO 24 0.1027 0.0471 4.7587 0.0292 1.1082

AGE 25 TO 29 0.2254 0.0454 24.6733 <.0001 1.2528

AGE 30 TO 35 0.0919 0.0430 4.5716 0.0325 1.0963

AGE 36 TO 39 0.1271 0.0462 7.5807 0.0059 1.1355

AGE 40 TO 44 0.2305 0.0441 27.2697 <.0001 1.2592

AGE 45 TO 49 0.3612 0.0452 63.8173 <.0001 1.4350

AGE 50 TO 54 0.2011 0.0457 19.4061 <.0001 1.2228

EDUCA 11 OR MORE 1.6028 0.0544 869.1895 <.0001 4.9669

EDUCA MISS 0.4064 0.2194 3.4322 0.0639 1.5014

EDUCA 1 TO 3 0.3927 0.0621 40.0399 <.0001 1.4810

EDUCA 4 TO 7 0.6900 0.0540 163.4437 <.0001 1.9937

EDUCA 8 TO 10 1.1805 0.0553 455.9569 <.0001 3.2560


CONFAM Spouse 0.4703 0.0267 310.6814 <.0001 1.6004

CONFAM Child 0.1106 0.0306 13.0621 0.0003 1.1170

CONFAM Other relative 0.0489 0.0485 1.0149 0.3137 1.0501

NPES 1 0.7923 0.0443 320.1382 <.0001 2.2085

NPES 2 0.8848 0.0393 506.9717 <.0001 2.4225

NPES 3 0.6237 0.0412 228.6499 <.0001 1.8657

REG Recife -1.0869 0.0501 470.0022 <.0001 0.3373

REG Salvador -0.5646 0.0487 134.3251 <.0001 0.5686

REG Belo Horizonte -0.0228 0.0449 0.2568 0.6123 0.9775


REG São Paulo 0.1564 0.0372 17.6551 <.0001 1.1693

YEAR 2003 -0.5227 0.0338 239.3131 <.0001 0.5929

YEAR 2004 -0.7797 0.0331 553.9593 <.0001 0.4585

YEAR 2005 -0.4379 0.0328 178.0187 <.0001 0.6454

YEAR 2006 -0.3407 0.0331 106.0295 <.0001 0.7113

YEAR 2007 -0.1574 0.0333 22.3963 <.0001 0.8544

56

Class D Intercept -1.1023 0.1033 113.8097 <.0001 .

GENDER Male 0.2241 0.0265 71.7247 <.0001 1.2512

COL Asian -1.2238 0.2581 22.4744 <.0001 0.2941

COL White -0.0192 0.0405 0.2261 0.6344 0.9809

COL Native 0.1164 0.3612 0.1039 0.7472 1.1235

COL Afro-brazilian 0.00283 0.0393 0.0052 0.9425 1.0028

AGE 15 TO 19 0.4296 0.0655 42.9797 <.0001 1.5367

AGE 20 TO 24 0.6132 0.0624 96.4759 <.0001 1.8464

AGE 25 TO 29 0.5300 0.0609 75.7098 <.0001 1.6989

AGE 30 TO 35 0.4956 0.0575 74.3061 <.0001 1.6415

AGE 36 TO 39 0.3227 0.0621 26.9741 <.0001 1.3809

AGE 40 TO 44 0.3465 0.0598 33.6003 <.0001 1.4141

AGE 45 TO 49 0.3360 0.0618 29.5260 <.0001 1.3993

AGE 50 TO 54 0.1481 0.0634 5.4608 0.0194 1.1596

EDUCA 11 OR MORE 0.3905 0.0644 36.7288 <.0001 1.4777

EDUCA MISS -0.1248 0.2796 0.1992 0.6554 0.8827

EDUCA 1 TO 3 0.3319 0.0721 21.1624 <.0001 1.3936

EDUCA 4 TO 7 0.3751 0.0630 35.5050 <.0001 1.4552

EDUCA 8 TO 10 0.5177 0.0649 63.6556 <.0001 1.6782


CONFAM Spouse 0.2310 0.0339 46.5183 <.0001 1.2598

CONFAM Child -0.1514 0.0392 14.9581 0.0001 0.8595


NPES 1 -0.6166 0.0544 128.3089 <.0001 0.5398

NPES 2 es 0.1255 0.0424 8.7684 0.0031 1.1337

NPES 3 es 0.0856 0.0447 3.6579 0.0558 1.0893

REG Recife -0.2742 0.0607 20.3752 <.0001 0.7602

REG Salvador 0.0214 0.0602 0.1263 0.7223 1.0216


REG Rio de Janeiro 0.0538 0.0509 1.1167 0.2906 1.0553

REG São Paulo 0.0443 0.0490 0.8160 0.3663 1.0453

YEAR 2003 -0.4655 0.0429 117.9358 <.0001 0.6279

YEAR 2004 -0.4859 0.0413 138.4398 <.0001 0.6151

YEAR 2005 -0.4122 0.0418 97.4091 <.0001 0.6622

YEAR 2006 -0.3618 0.0423 73.3239 <.0001 0.6964

YEAR 2007 -0.1372 0.0418 10.8006 0.0010 0.8718


57

b) Models with Interation dummies (YEAR*REGION)

Parameter Category Estimate Standard

Error Wald


CLASS A & B

Intercept -6.6631 0.2538 689.2008 <.0001 .

REG Recife -1.2068 0.1975 37.3217 <.0001 0.2991

REG Salvador -0.5404 0.1969 7.5286 0.0061 0.5825



REG São Paulo 0.6606 0.1258 27.5814 <.0001 1.9360

YEAR 2003 -0.5780 0.1708 11.4492 0.0007 0.5610

YEAR 2004 -0.5109 0.1663 9.4397 0.0021 0.5999

YEAR 2005 -0.3637 0.1717 4.4863 0.0342 0.6951

YEAR 2006 -0.3584 0.1644 4.7510 0.0293 0.6988

YEAR 2007 -0.1524 0.1616 0.8900 0.3455 0.8586

REG*YEAR Recife 0.1311 0.3000 0.1909 0.6622 1.1400

REG*YEAR Recife -0.5692 0.3256 3.0548 0.0805 0.5660

REG*YEAR Recife -0.0673 0.2964 0.0516 0.8203 0.9349

REG*YEAR Recife -0.5665 0.3247 3.0441 0.0810 0.5675

REG*YEAR Recife -0.0124 0.2879 0.0018 0.9657 0.9877

REG*YEAR Salvador 0.4179 0.2806 2.2183 0.1364 1.5188





REG*YEAR Belo Horizonte -0.1106 0.2370 0.2178 0.6407 0.8953




REG*YEAR Belo Horizonte 0.0669 0.2226 0.0903 0.7638 1.0692

REG*YEAR Rio de Janeiro -0.6103 0.2026 9.0773 0.0026 0.5432





REG*YEAR São Paulo 0.1341 0.1864 0.5175 0.4719 1.1435

REG*YEAR São Paulo -0.5002 0.1823 7.5300 0.0061 0.6064




58

CLASS C

Intercept -1.5841 0.1126 197.9410 <.0001 .

REG Recife -0.7739 0.1194 41.9823 <.0001 0.4612

REG Salvador -0.3549 0.1180 9.0506 0.0026 0.7012



REG São Paulo 0.4019 0.0934 18.4989 <.0001 1.4946

YEAR 2003 -0.3498 0.1160 9.0894 0.0026 0.7048

YEAR 2004 -0.4729 0.1166 16.4380 <.0001 0.6232

YEAR 2005 -0.0812 0.1175 0.4777 0.4895 0.9220

YEAR 2006 -0.1716 0.1165 2.1681 0.1409 0.8423

YEAR 2007 -0.0915 0.1174 0.6077 0.4356 0.9125

REG*YEAR Recife -0.2681 0.1675 2.5611 0.1095 0.7648

REG*YEAR Recife -0.9121 0.1784 26.1446 <.0001 0.4017

REG*YEAR Recife -0.5330 0.1671 10.1716 0.0014 0.5868

REG*YEAR Recife -0.3064 0.1670 3.3682 0.0665 0.7361

REG*YEAR Recife 0.0105 0.1671 0.0039 0.9500 1.0105

REG*YEAR Salvador -0.1648 0.1633 1.0187 0.3128 0.8480




















59

CLASS D

Intercept -1.3416 0.1424 88.7670 <.0001 .

REG Recife 0.0699 0.1470 0.2260 0.6345 1.0724

REG Salvador 0.3296 0.1450 5.1683 0.0230 1.3905



REG São Paulo 0.3952 0.1226 10.3924 0.0013 1.4847

YEAR 2003 -0.3425 0.1571 4.7547 0.0292 0.7100

YEAR 2004 -0.1982 0.1539 1.6582 0.1978 0.8202

YEAR 2005 0.0292 0.1535 0.0361 0.8494 1.0296

YEAR 2006 -0.1580 0.1563 1.0220 0.3121 0.8538

YEAR 2007 0.1506 0.1520 0.9820 0.3217 1.1625

REG*YEAR Recife -0.3879 0.2090 3.4435 0.0635 0.6785

REG*YEAR Recife -0.4425 0.2030 4.7526 0.0293 0.6424

REG*YEAR Recife -0.5336 0.2018 6.9916 0.0082 0.5865

REG*YEAR Recife -0.2599 0.2053 1.6023 0.2056 0.7711

REG*YEAR Recife -0.3757 0.2039 3.3951 0.0654 0.6868












REG*YEAR Rio de Janeiro 0.0979 0.1728 0.3208 0.5711 1.1028






REG*YEAR São Paulo -0.6584 0.1688 15.2221 <.0001 0.5177




60

II) Social Mobility - Probability of Entering, Exit ing and Permanence Being in

Classe E – Base those that Stay in Class E

Parameter Category Estimate Standard Error

Wald Statistic P-value Odds Ratio

CONTINUE OUT OF CLASS E

Intercept -0.7010 0.0859 66.5507 <.0001 .

GENDER Male 0.5344 0.0220 588.6950 <.0001 1.70642

COL Asian 0.0658 0.1325 0.2467 0.6194 1.06804

COL White 0.2983 0.0343 75.4891 <.0001 1.34757

COL Native 0.4955 0.3315 2.2338 0.1350 1.64135


AGE 15 TO 19 0.1102 0.0513 4.6119 0.0318 1.11646

AGE 20 TO 24 0.2977 0.0493 36.4707 <.0001 1.34681

AGE 25 TO 29 0.3396 0.0473 51.5281 <.0001 1.40434

AGE 30 TO 35 0.2459 0.0444 30.6513 <.0001 1.27883

AGE 36 TO 39 0.2164 0.0480 20.3271 <.0001 1.24160

AGE 40 TO 44 0.3531 0.0459 59.2935 <.0001 1.42349

AGE 45 TO 49 0.4879 0.0472 106.8374 <.0001 1.62895

AGE 50 TO 54 0.2661 0.0470 32.0624 <.0001 1.30489

EDUCA 11 OR MORE 1.8121 0.0524 1197.7525 <.0001 6.12327

EDUCA MISS 0.1620 0.2157 0.5641 0.4526 1.17589

EDUCA 1 TO 3 0.4052 0.0597 46.1022 <.0001 1.49964

EDUCA 4 TO 7 0.6691 0.0515 168.9233 <.0001 1.95244

EDUCA 8 TO 10 1.1897 0.0533 498.7744 <.0001 3.28622


CONFAM Spouse 0.5379 0.0283 360.1276 <.0001 1.71244

CONFAM Child 0.0130 0.0325 0.1586 0.6904 1.01304


NPES 1 0.6431 0.0436 217.1387 <.0001 1.90243

NPES 2 es 0.8008 0.0383 437.7412 <.0001 2.22735

NPES 3 es 0.4991 0.0403 153.2995 <.0001 1.64727

REG Recife -1.1197 0.0526 453.7187 <.0001 0.32638

REG Salvador -0.5191 0.0514 102.0210 <.0001 0.59504



REG São Paulo 0.1787 0.0417 18.3170 <.0001 1.19563

YEAR 2003 -0.6835 0.0371 339.7259 <.0001 0.50485

YEAR 2004 -0.8304 0.0362 527.1496 <.0001 0.43589

YEAR 2005 -0.6003 0.0359 280.1069 <.0001 0.54863

YEAR 2006 -0.5291 0.0363 212.4855 <.0001 0.58915

YEAR 2007 -0.3117 0.0365 72.8737 <.0001 0.73218

61

Parameter Category Estimate Standard Error


ENTERED CLASS E

Intercept -1.9066 0.1560 149.3652 <.0001 .

GENDER Male 0.2815 0.0394 51.0180 <.0001 1.32518

COL Asian -1.4179 0.3984 12.6667 0.0004 0.24223

COL White 0.0891 0.0638 1.9484 0.1628 1.09315

COL Native 0.8338 0.4698 3.1494 0.0760 2.30207


AGE 15 TO 19 0.1077 0.0950 1.2865 0.2567 1.11372

AGE 20 TO 24 0.2811 0.0906 9.6371 0.0019 1.32463

AGE 25 TO 29 0.2362 0.0877 7.2611 0.0070 1.26647

AGE 30 TO 35 0.2237 0.0826 7.3360 0.0068 1.25070

AGE 36 TO 39 0.1772 0.0890 3.9637 0.0465 1.19389

AGE 40 TO 44 0.1781 0.0861 4.2825 0.0385 1.19493

AGE 45 TO 49 0.2432 0.0885 7.5504 0.0060 1.27527

AGE 50 TO 54 0.1955 0.0884 4.8941 0.0269 1.21595

EDUCA 11 OR MORE 0.9181 0.0999 84.4287 <.0001 2.50447

EDUCA MISS 0.2874 0.3637 0.6244 0.4294 1.33293

EDUCA 1 TO 3 0.3373 0.1135 8.8330 0.0030 1.40121

EDUCA 4 TO 7 0.5228 0.0984 28.2094 <.0001 1.68675

EDUCA 8 TO 10 0.7094 0.1016 48.7869 <.0001 2.03274


CONFAM Spouse 0.2968 0.0507 34.3029 <.0001 1.34558

CONFAM Child 0.0440 0.0582 0.5713 0.4497 1.04500


NPES 1 0.1228 0.0830 2.1910 0.1388 1.13067

NPES 2 es 0.4619 0.0706 42.7909 <.0001 1.58705

NPES 3 es 0.4360 0.0734 35.3318 <.0001 1.54657

REG Recife -0.5877 0.0802 53.7520 <.0001 0.55559

REG Salvador -1.2763 0.0940 184.1910 <.0001 0.27906

REG Belo Horizonte -0.3105 0.0776 16.0002 <.0001 0.73310

REG Rio de Janeiro -0.9977 0.0707 199.2343 <.0001 0.36872

REG São Paulo -0.3897 0.0642 36.8005 <.0001 0.67727

YEAR 2003 0.0717 0.0624 1.3190 0.2508 1.07435

YEAR 2004 -0.2758 0.0639 18.6346 <.0001 0.75894

YEAR 2005 -0.5016 0.0667 56.6406 <.0001 0.60556

YEAR 2006 -0.1836 0.0642 8.1722 0.0043 0.83225

YEAR 2007 -0.3170 0.0670 22.3819 <.0001 0.72835

62

EXITED CLASS E

Intercept -1.6683 0.1428 136.4329 <.0001 .

GENDER Male 0.3474 0.0367 89.5744 <.0001 1.41535

COL Asian -0.1979 0.2213 0.7992 0.3713 0.82047

COL White -0.0128 0.0577 0.0490 0.8248 0.98731

COL Native 0.6975 0.4578 2.3207 0.1277 2.00865


AGE 15 TO 19 0.2208 0.0895 6.0843 0.0136 1.24710

AGE 20 TO 24 0.4889 0.0845 33.4422 <.0001 1.63056

AGE 25 TO 29 0.3036 0.0830 13.3885 0.0003 1.35473

AGE 30 TO 35 0.2894 0.0782 13.6869 0.0002 1.33558

AGE 36 TO 39 0.2896 0.0837 11.9766 0.0005 1.33588

AGE 40 TO 44 0.3568 0.0802 19.7860 <.0001 1.42868

AGE 45 TO 49 0.4274 0.0822 27.0397 <.0001 1.53319

AGE 50 TO 54 0.2556 0.0834 9.3810 0.0022 1.29119

EDUCA 11 OR MORE 0.8227 0.0884 86.5128 <.0001 2.27654

EDUCA MISS -0.2635 0.4065 0.4203 0.5168 0.76834

EDUCA 1 TO 3 0.2591 0.1008 6.6093 0.0101 1.29578

EDUCA 4 TO 7 0.3614 0.0872 17.1854 <.0001 1.43539

EDUCA 8 TO 10 0.5732 0.0901 40.4345 <.0001 1.77394


CONFAM Spouse 0.3249 0.0471 47.5334 <.0001 1.38395

CONFAM Child -0.0172 0.0541 0.1014 0.7502 0.98291


NPES 1 0.1443 0.0753 3.6720 0.0553 1.15526

NPES 2 es 0.4489 0.0645 48.4920 <.0001 1.56657

NPES 3 es 0.3014 0.0677 19.8186 <.0001 1.35179

REG Recife -0.6764 0.0807 70.1990 <.0001 0.50842

REG Salvador -0.9339 0.0861 117.5759 <.0001 0.39301



REG São Paulo -0.1395 0.0633 4.8545 0.0276 0.86980

YEAR 2003 -0.2926 0.0586 24.8908 <.0001 0.74634

YEAR 2004 -0.2237 0.0561 15.8816 <.0001 0.79958

YEAR 2005 -0.5154 0.0590 76.3713 <.0001 0.59724

YEAR 2006 -0.4887 0.0599 66.5757 <.0001 0.61342

YEAR 2007 -0.5214 0.0615 71.9612 <.0001 0.59366


63

b) com dummy interativa (YEAR*REGION)

Base:Porto Alegre and 2008.


Error Wald



Intercept -0.9995 0.1190 70.5240 <.0001 .

REG Recife -0.7829 0.1297 36.4174 <.0001 0.45708

REG Salvador -0.2630 0.1280 4.2209 0.0399 0.76875



REG São Paulo 0.6053 0.1066 32.2165 <.0001 1.83180

YEAR 2003 -0.3854 0.1321 8.5095 0.0035 0.68015

YEAR 2004 -0.3202 0.1332 5.7762 0.0162 0.72597

YEAR 2005 -0.2227 0.1305 2.9132 0.0879 0.80035

YEAR 2006 -0.2740 0.1297 4.4633 0.0346 0.76030

YEAR 2007 -0.0712 0.1310 0.2951 0.5869 0.93129

REG*YEAR Recife -0.4045 0.1801 5.0429 0.0247 0.66731

REG*YEAR Recife -0.8432 0.1825 21.3438 <.0001 0.43031

REG*YEAR Recife -0.3679 0.1753 4.4055 0.0358 0.69217

REG*YEAR Recife -0.3149 0.1775 3.1498 0.0759 0.72983

REG*YEAR Recife -0.0169 0.1804 0.0088 0.9253 0.98323


REG*YEAR Salvador -0.7809 0.1744 20.0447 <.0001 0.45798



















64


Error Wald


ENTERED CLASS E

Intercept -2.3248 0.2073 125.7219 <.0001 .

REG Recife 0.2386 0.1973 1.4635 0.2264 1.26953

REG Salvador -0.4249 0.2233 3.6211 0.0571 0.65382



REG São Paulo 0.1234 0.1751 0.4970 0.4808 1.13136

YEAR 2003 0.4596 0.1990 5.3331 0.0209 1.58341

YEAR 2004 0.2567 0.2066 1.5432 0.2141 1.29267

YEAR 2005 0.2970 0.2023 2.1568 0.1419 1.34587

YEAR 2006 0.1428 0.2052 0.4842 0.4865 1.15350

YEAR 2007 0.0114 0.2137 0.0029 0.9574 1.01148

REG*YEAR Recife -0.9960 0.2610 14.5630 0.0001 0.36937

REG*YEAR Recife -1.2494 0.2733 20.8935 <.0001 0.28669

REG*YEAR Recife -1.6819 0.2830 35.3322 <.0001 0.18602

REG*YEAR Recife -0.6978 0.2672 6.8205 0.0090 0.49766

REG*YEAR Recife -0.3321 0.2776 1.4308 0.2316 0.71742





















65


Error Wald


EXITED CLASS E

Intercept -2.0984 0.1938 117.2159 <.0001 .

REG Recife -0.2001 0.2008 0.9933 0.3189 0.81867

REG Salvador -0.3185 0.2077 2.3505 0.1252 0.72724



REG São Paulo 0.3791 0.1652 5.2681 0.0217 1.46102

YEAR 2003 0.2971 0.1956 2.3060 0.1289 1.34595

YEAR 2004 0.4467 0.1942 5.2908 0.0214 1.56319

YEAR 2005 -0.2054 0.2104 0.9525 0.3291 0.81436

YEAR 2006 -0.1232 0.2058 0.3584 0.5494 0.88409

YEAR 2007 -0.0464 0.2074 0.0501 0.8228 0.95463

REG*YEAR Recife -0.6803 0.2676 6.4650 0.0110 0.50647

REG*YEAR Recife -0.9778 0.2661 13.4997 0.0002 0.37613

REG*YEAR Recife -0.6321 0.2863 4.8740 0.0273 0.53148

REG*YEAR Recife -0.3777 0.2794 1.8278 0.1764 0.68544

REG*YEAR Recife 0.0268 0.2788 0.0093 0.9234 1.02718






















66

III) Mobility (Entry and Exit of Class E ) -

Resposta Parameter Category Estimate Standard Error



Intercept 1.5723 0.0814 372.6682 <.0001 .

GENDER Male -0.2583 0.0181 203.4517 <.0001 0.77237

COL Asian 1.0103 0.1050 92.6249 <.0001 2.74652

COL White 0.0989 0.0291 11.5502 0.0007 1.10391

COL Native -0.1902 0.2757 0.4757 0.4904 0.82682


AGE 15 TO 19 0.1827 0.0444 16.9177 <.0001 1.20051

AGE 20 TO 24 -0.1345 0.0415 10.4887 0.0012 0.87413

AGE 25 TO 29 -0.1591 0.0396 16.1146 <.0001 0.85290

AGE 30 TO 35 -0.00013 0.0381 0.0000 0.9973 0.99987

AGE 36 TO 39 -0.1053 0.0410 6.5973 0.0102 0.90005

AGE 40 TO 44 -0.1293 0.0390 10.9621 0.0009 0.87875

AGE 45 TO 49 -0.2043 0.0398 26.3844 <.0001 0.81519

AGE 50 TO 54 -0.1172 0.0407 8.2949 0.0040 0.88943

EDUCA 11 OR MORE -0.9111 0.0545 279.5938 <.0001 0.40207

EDUCA MISS -0.2422 0.2306 1.1033 0.2935 0.78489

EDUCA 1 TO 3 -0.4118 0.0629 42.8457 <.0001 0.66248

EDUCA 4 TO 7 -0.6483 0.0550 138.7110 <.0001 0.52296

EDUCA 8 TO 10 -1.0154 0.0557 331.8562 <.0001 0.36227

CONFAM Housemaid -0.1677 0.1697 0.9764 0.3231 0.84564

CONFAM Spouse -0.2743 0.0230 142.7288 <.0001 0.76012

CONFAM Child -0.1935 0.0263 54.0140 <.0001 0.82404


NPES 1 -0.6381 0.0420 230.3326 <.0001 0.52831

NPES 2 es -0.8462 0.0384 486.8656 <.0001 0.42904

NPES 3 es -0.6830 0.0401 290.5224 <.0001 0.50509

REG Recife 1.1455 0.0488 551.7870 <.0001 3.14389

REG Salvador 0.6525 0.0435 225.4463 <.0001 1.92041



REG São Paulo 0.000543 0.0324 0.0003 0.9866 1.00054

YEAR 2003 0.3265 0.0290 126.8949 <.0001 1.38604

YEAR 2004 0.4884 0.0286 291.5099 <.0001 1.62973

YEAR 2005 0.2124 0.0273 60.5157 <.0001 1.23665

YEAR 2006 0.1557 0.0274 32.2816 <.0001 1.16847

YEAR 2007 0.0862 0.0270 10.2309 0.0014 1.09003

67

ENTERED CLASS E

Intercept -0.8878 0.1471 36.3984 <.0001 .

GENDER Male -0.0852 0.0316 7.2838 0.0070 0.91833

COL Asian 0.5765 0.1746 10.9008 0.0010 1.77986

COL White 0.0120 0.0524 0.0527 0.8184 1.01211

COL Native 0.1575 0.4369 0.1300 0.7185 1.17059


AGE 15 TO 19 0.1363 0.0798 2.9185 0.0876 1.14607

AGE 20 TO 24 0.1856 0.0736 6.3645 0.0116 1.20397

AGE 25 TO 29 -0.0508 0.0722 0.4953 0.4816 0.95047

AGE 30 TO 35 0.0331 0.0696 0.2259 0.6346 1.03361

AGE 36 TO 39 -0.0118 0.0748 0.0248 0.8748 0.98829

AGE 40 TO 44 0.0355 0.0707 0.2521 0.6156 1.03616

AGE 45 TO 49 0.0816 0.0711 1.3159 0.2513 1.08501

AGE 50 TO 54 0.0746 0.0734 1.0325 0.3096 1.07746

EDUCA 11 OR MORE -0.3593 0.0991 13.1527 0.0003 0.69818

EDUCA MISS -0.8260 0.5494 2.2602 0.1327 0.43779

EDUCA 1 TO 3 0.0500 0.1120 0.1993 0.6553 1.05129

EDUCA 4 TO 7 -0.2040 0.1000 4.1600 0.0414 0.81549

EDUCA 8 TO 10 -0.3652 0.1011 13.0598 0.0003 0.69407


CONFAM Spouse -0.1033 0.0404 6.5232 0.0106 0.90186

CONFAM Child 0.0167 0.0458 0.1326 0.7158 1.01681


NPES 1 0.0434 0.0817 0.2823 0.5952 1.04438

NPES 2 es 0.0673 0.0752 0.8006 0.3709 1.06964

NPES 3 es -0.0837 0.0786 1.1342 0.2869 0.91971

REG Recife 0.3507 0.0758 21.3877 <.0001 1.42003

REG Salvador -0.6334 0.0800 62.7296 <.0001 0.53079



REG São Paulo -0.3480 0.0490 50.5037 <.0001 0.70608

YEAR 2003 0.0814 0.0476 2.9197 0.0875 1.08481

YEAR 2004 0.2673 0.0461 33.6806 <.0001 1.30645

YEAR 2005 -0.3292 0.0483 46.4616 <.0001 0.71949

YEAR 2006 -0.2388 0.0472 25.5815 <.0001 0.78754

YEAR 2007 -0.3270 0.0469 48.6995 <.0001 0.72110

68

EXITED CLASS C

Intercept -0.8390 0.1475 32.3761 <.0001 .

GENDER Male -0.1110 0.0323 11.7873 0.0006 0.89492

COL Asian 0.6437 0.1813 12.6050 0.0004 1.90344

COL White 0.1241 0.0555 5.0018 0.0253 1.13216

COL Native 0.9166 0.3453 7.0448 0.0079 2.50084


AGE 15 TO 19 0.0184 0.0810 0.0516 0.8203 1.01858

AGE 20 TO 24 -0.0628 0.0757 0.6884 0.4067 0.93909

AGE 25 TO 29 -0.0493 0.0725 0.4632 0.4961 0.95188

AGE 30 TO 35 -0.0159 0.0703 0.0510 0.8213 0.98425

AGE 36 TO 39 -0.0126 0.0750 0.0284 0.8663 0.98745

AGE 40 TO 44 -0.0217 0.0716 0.0920 0.7617 0.97851

AGE 45 TO 49 -0.0249 0.0727 0.1174 0.7319 0.97541

AGE 50 TO 54 -0.0493 0.0755 0.4274 0.5133 0.95185

EDUCA 11 OR MORE -0.2909 0.1016 8.1985 0.0042 0.74762

EDUCA MISS 0.3476 0.3568 0.9490 0.3300 1.41560

EDUCA 1 TO 3 -0.1082 0.1172 0.8525 0.3558 0.89746

EDUCA 4 TO 7 -0.1562 0.1025 2.3247 0.1273 0.85535

EDUCA 8 TO 10 -0.3339 0.1037 10.3748 0.0013 0.71610


CONFAM Spouse -0.1159 0.0414 7.8520 0.0051 0.89055

CONFAM Child 0.0237 0.0468 0.2577 0.6117 1.02403


NPES 1 -0.3780 0.0766 24.3754 <.0001 0.68522

NPES 2 es -0.2889 0.0686 17.7505 <.0001 0.74910

NPES 3 es -0.3618 0.0721 25.2116 <.0001 0.69639

REG Recife 0.6395 0.0744 73.8645 <.0001 1.89549

REG Salvador -0.4604 0.0803 32.8630 <.0001 0.63105



REG São Paulo -0.3532 0.0513 47.4403 <.0001 0.70242

YEAR 2003 0.3656 0.0483 57.3732 <.0001 1.44136

YEAR 2004 0.2441 0.0498 23.9783 <.0001 1.27642

YEAR 2005 -0.2132 0.0507 17.6668 <.0001 0.80796

YEAR 2006 -0.0428 0.0488 0.7687 0.3806 0.95814

YEAR 2007 -0.1488 0.0486 9.3742 0.0022 0.86177


69

b) Mobility (Entry and Exit of Class E )

Models with Interation dummies (YEAR*REGION)


Error Wald


CONTINUE OUT OF CLASS C

Intercept 1.6710 0.1017 269.9544 <.0001 .

REG Recife 0.8301 0.1096 57.3526 <.0001 2.29348

REG Salvador 0.4726 0.1011 21.8632 <.0001 1.60416



REG São Paulo -0.0532 0.0764 0.4848 0.4863 0.94819

YEAR 2003 0.1538 0.1034 2.2090 0.1372 1.16621

YEAR 2004 0.2924 0.1037 7.9545 0.0048 1.33963

YEAR 2005 0.0618 0.0998 0.3833 0.5359 1.06375

YEAR 2006 0.0776 0.0990 0.6138 0.4333 1.08067

YEAR 2007 0.1148 0.0989 1.3468 0.2458 1.12165

REG*YEAR Recife 0.4992 0.1664 9.0000 0.0027 1.64737

REG*YEAR Recife 0.8879 0.1775 25.0213 <.0001 2.43006

REG*YEAR Recife 0.3682 0.1554 5.6173 0.0178 1.44515

REG*YEAR Recife 0.4018 0.1599 6.3156 0.0120 1.49449

REG*YEAR Recife -0.0601 0.1552 0.1502 0.6984 0.94163





















70


Error Wald


ENTERED CLASS C

Intercept -1.0433 0.1717 36.9384 <.0001 .

REG Recife 0.4193 0.1620 6.6986 0.0096 1.52097

REG Salvador -0.2966 0.1677 3.1292 0.0769 0.74333



REG São Paulo -0.0859 0.1121 0.5868 0.4437 0.91773

YEAR 2003 0.2391 0.1477 2.6207 0.1055 1.27009

YEAR 2004 0.4217 0.1451 8.4409 0.0037 1.52450

YEAR 2005 -0.2645 0.1558 2.8824 0.0896 0.76758

YEAR 2006 -0.2035 0.1529 1.7697 0.1834 0.81591

YEAR 2007 0.1294 0.1434 0.8136 0.3671 1.13810

REG*YEAR Recife -0.1844 0.2499 0.5446 0.4605 0.83158

REG*YEAR Recife 0.2514 0.2496 1.0147 0.3138 1.28586

REG*YEAR Recife -0.3125 0.2592 1.4536 0.2280 0.73163

REG*YEAR Recife 0.2416 0.2459 0.9653 0.3259 1.27326

REG*YEAR Recife -0.2508 0.2321 1.1671 0.2800 0.77820





















71


Error Wald


EXITED CLASS C

Intercept -1.0248 0.1781 33.1248 <.0001 .

REG Recife 0.8246 0.1647 25.0649 <.0001 2.28093

REG Salvador -0.0392 0.1754 0.0501 0.8230 0.96152



REG São Paulo -0.0127 0.1240 0.0105 0.9184 0.98738

YEAR 2003 0.4742 0.1564 9.1937 0.0024 1.60665

YEAR 2004 0.4081 0.1610 6.4276 0.0112 1.50403

YEAR 2005 0.1333 0.1592 0.7016 0.4023 1.14262

YEAR 2006 0.0164 0.1622 0.0103 0.9193 1.01657

YEAR 2007 0.2060 0.1567 1.7281 0.1886 1.22880

REG*YEAR Recife -0.0761 0.2381 0.1023 0.7491 0.92669

REG*YEAR Recife -0.5862 0.2824 4.3087 0.0379 0.55642

REG*YEAR Recife -0.7193 0.2521 8.1427 0.0043 0.48710

REG*YEAR Recife 0.2345 0.2389 0.9636 0.3263 1.26427

REG*YEAR Recife -0.1848 0.2299 0.6465 0.4214 0.83126






















The New Middle-Class · The New Middle-Class Rio de Janeiro, August 05, 2008 Version 2.0: August 8,...

Documents

Transcript of The New Middle-Class · The New Middle-Class Rio de Janeiro, August 05, 2008 Version 2.0: August 8,...