The 20 millions phenomenon: how low- and middle-income Brazilians changed their consumption during the economic boom

UNIVERSITÀ COMMERCIALE LUIGI BOCCONI - MILAN
Graduate School
Master of Science in Economics and Management for
Public Administration and International Institutions
The twenty millions phenomenon: how low- and middle-income
Brazilians changed their consumption during the economic boom
Advisor
Eliana La Ferrara
Discussant
Rubera Gaia
Master of Science Thesis of
Niccolò Natali
ID 1610518
Academic Year
2012/2013

iii

To
nonna
Marta
and
nonno
Sesto.

Thanks
to
my
family,
my
friends
and

Veronica,
to
whom
I
owe
the
inspiration
for
this
work.

v

1.
INTRODUCTION
1

2.
LITERATURE
REVIEW
5

3.
SOCIO-‐ECONOMIC
CLASSES
IN
BRAZIL
17

3.A
COMMISSION
FOR
THE
DEFINITION
OF
THE
MIDDLE
CLASS
IN
BRAZIL
18

3.B
ABEP
AND
THE
CRITÉRIO
BRASIL
22

4.
THE
“20
MILLIONS
PHENOMENON”
25

4.A
THE
MACROECONOMIC
FRAMEWORK
25

4.B
MICRO
PERSPECTIVE
26

5.
METHODOLOGY
30

5.A

DATASET
PRESENTATION:
POF
AND
PNAD
30

5.B

POF
METHODOLOGY
32

5.B.1
GENERAL
CONSIDERATIONS
32

5.B.2
DEFINITION
OF
SOCIO-‐ECONOMIC
CLASSES
32

5.B.3
COMPARISONS
33

5.B.4
TABLES
36

5.C
PNAD
METHODOLOGY
41

5.C.1
TABLES
AND
COMPARISONS
41

6.
BUDGET
SHARES
ANALYSIS
43

6.A
INTRODUCTION
43

6.A.1
PRELIMINARY
CONSIDERATIONS
43

6.B
EVOLUTION
OF
BUDGET
SHARES
45

6.B.1
FOOD
AND
DRINK
45

6.B.2
PERSONAL
CARE
51

6.B.3
HOUSING
53

6.B.4
TRANSPORTATION
56

6.B.5
HEALTH
58

6.B.6
EDUCATION
61

6.B.7
CULTURE
AND
LEISURE
TIME
63

6.B.8
HOUSE
PURCHASING
AND
DEBTS
66

6.C
PORTRAITING
NEW
CONSUMPTION
HABITS
67

6.C.1
EXTREMELY
POOR
68

6.C.2
POOR
69

6.C.3
VULNERABLE
70

6.C.4
LOWER
MIDDLE
AND
MIDDLE
71

7.
DISCUSSION
72

7.A
COMMON
HABITS
73

7.A.1
FOOD
AND
DRINK
73

7.A.2
PERSONAL
CARE
75

7.A.3
MOBILE
PHONES
76

7.A.4
HEALTH
77

7.A.5
LEISURE
ACTIVITIES
79

7.A.6
DEBTS
79

7.B
CLASS-‐SPECIFIC
HABITS
82

7.B.1
FOOD
AND
DRINK
82

7.B.2
HOUSING
83

7.B.3
TRANSPORTATION
85

7.B.4
EDUCATION
86

7.B.5
CULTURE
AND
LEISURE
TIME
88

vi

8.
INTER-‐CLASS
GRADIENTS
ANALYSIS
AND
DISCUSSION
89

8.A
FOOD
AND
DRINK
90

8.B
LEISURE
TIME,
PERSONAL
CARE
PLUS
OTHERS
93

9.
CONCLUSIONS
97

REFERENCES
109

ANNEXES
115

ANNEX
I:
2008
MEAN
PER-‐HOUSEHOLD
EXPENDITURES
COMPLETE
TABLE
115

ANNEX
II:
PNAD
ANALYSIS
117

ANNEX
III:
EXPENDITURES
CATEGORIES
EXPANDED
(IN
PORTUGUESE)
118

ANNEX
IV:
INTER-‐CLASS
GRADIENTS
120

1

1. Introduction

Brazil has achieved the first Millennium Development Goal (MDG) set for 2015 four
years earlier, by reducing extreme poverty by half, achieving full and productive
employment and decent work for all and finally reducing hunger by half. The
extraordinary performance of the Brazilian economy during the years of the
commodities boom played a relevant role and, as a result, millions of Brazilian
households across the first ten years of this century joined higher standards of living.
With respect to this topic, much of the attention of the economic and political
sciences research has been focused on the mechanisms through which so many
people have been lifted up from poverty; for instance, the Bolsa Família program, a
governmental program of conditional cash transfer, is still the object of numerous
studies. Development studies are mainly concerned with all the aspects of poverty
ranging from its structural causes to possible solutions for its eradication. Less
attention has been given to what there is after poverty, or in other words, when
poverty just ends. In developing countries such as Brazil, India, China, South Africa
and Indonesia, extreme poverty has been seriously tackled down by a combination of
government-driven social programs and positive economic outlooks. Whichever
definition we may adopt to define the middle class of each of these countries, a
migration of millions of poor households – if not to the middle class – towards the
middle class has taken place. During this transition, we can suppose that households
have changed their behaviour as economic agents, mainly due to their better
financial prospects. We could start by saying that once-poor households increased
their number of interactions with the public sector and with the (formal and informal)
economic system.
With regard to the increased interaction with the public sector, some examples
could be: the official registration of a new business activity, children attending to
public schools, the use of public transportation to go to work, taxes, hospitalizations
etc. New relevant fluxes of people direct towards public infrastructures and services

2

that are often not structured for the new size of the demand, results in congested
accessibility and lowered quality. Consequences like these seem to have been
underestimated by the Brazilian government, as to the booming demand for public
services has not corresponded an equal increase in related investments. Last
summer, the fuse of the violent protests that took place all over the country, was a
slight plus 20 centavos (less than € 5 cent) of the bus fare in the cities of São Paulo
and Rio de Janeiro (in which metropolitan areas live respectively 12 and 20 millions
people). Protesters were asking to the Brazilian government the end of corruption,
better health, education and public transportation instead of massive investments for
the World Cup and for the Olympic Games. They were perceived as a clear signal of
the malcontent of the population for low quality public services, a quality
compromised mainly by the increased number of users.
Moving now to the economic system, once-poor households, due to their
augmented income, can now exchange money for a new variety of goods and/or
services or, alternatively, purchase more of the previous ones. The act of consuming
coming from a relatively worse-off condition contains information that go beyond the
quantified monetary disbursement or the modalities akin to the transaction. When an
individual become a consumption entity he/she automatically acquires bargaining
power or, literally, purchasing power, towards the products offer: he/she has money
and decides how to spend it. He/she now carries the responsibility/enjoys the
opportunity of taking much more purchasing decisions than before when
consumption was limited to a restricted number of possibilities. For some, new
consumption options will integrate basic necessities such as food or the acquisition of
some essential goods like a fridge or a washing machine. For some others it is the
very first time they deal with, and give a name to, a surplus; the first time they are
finally less constrained in their purchasing decision; the first time they can think about
a loan; the first time they experience a contemporary version of freedom. It does not
matter how little the discretionary income might be; it has a strong symbolical value,
being an important sign of having finally crossed the poverty line. As underlined by
Van Binsbergen ‘Consumption - and the attainment of income levels by specific

3

individuals, households, and social groups that will enable them to engage in more
than mere virtual or symbolic consumption (e.g. ethnic and religious fundamentalism)
- is the necessary implication of a development discourse aiming to alleviate poverty’
(Van Binsbergen 1999).
This said, how Brazilians ex-poor new consumption habits do look like? Are
them a surrogate of what richer classes are consuming or are they tailored to new
needs and wanting? Has consumerist life-style rooted up to the poor? This work will
address these questions by exploring which are the most purchased items by
extremely poor to middle class Brazilian households, what are their needs and
wanting and it will try to give possible explanations to why certain products whether
than others have been purchased. With these information we will be able to gain
some insights on what implies for Brazilians being out from poverty from a
consumption perspective, of what is finally constituted (object and services) such
desired freedom.
In order to answer the above cited questions, we have analysed households
expenditures data available for two years, 2002/2003 and 2008/2009, covering a
period that perfectly suites our research scope. Along those years, in fact, millions of
households have improved their wealth status passing from being poor to joining the
middle class. Unfortunately these are not longitudinal data, and the principle
limitation of our study is that, even by analysing households’ consumption just up to
the middle class, we cannot totally attribute changing in consumption trends to new
consumption choices made by once-poor households. On the other hand, the quirk of
analysing Brazilian households expenditures is that no such country in the world
have lifted up from poverty so many people in such a short time. Therefore, the
impact of the entrance of twenty millions people (distributed in 6 years) in the
consumer market is, in our opinion, the principle cause in explaining changing in
consumption trends. Nonetheless, this is just a hypothesis and further studies are
needed to confirm it.

4

We now pass to briefly illustrate the backbone of this work anticipating, in
short, the contents of the following chapters. In chapter two we will review the
literature concerning the analysis of household expenditures, adopting a wide angle
and, thus, not limiting our analysis just to low-income household within the Brazilian
scenario. Then, critical for this study is finding a criteria for the definition of
socioeconomic classes and, being itself a puzzling issue, we dedicated chapter three
to illustrate two different ways to define them and explain the choice made for this
study. In chapter four we explain the mechanism through which millions of families,
the so called “twenty millions phenomenon”, were lifted up from poverty and started
to enjoy higher standards of living. In order to have the most satisfying picture
possible, we will analyse this issue from two perspectives: a macro economic
perspective and a micro economic perspective. Follows chapter five where we
present the data, its limits and the methodology adopted, which lastly results in two
kinds of analysis each one appropriately commented. In chapter six we present the
first kind, consisting in the analysis of which fraction of households’ mean total
disbursement is dedicated to the purchasing of a battery of expenditures items
previously selected. Then, in chapter eight we proceed with the second analysis,
performed for both years, where we define consumption aspirations by calculating
every spending variation (in percentage terms) that occurs from one class to the next
upper class. Finally chapter nine is where we explain our final opinion about the
study’s results and, lastly, we conclude with some “policy”1
suggestions that we
found consistent with the quirks related to low-income Brazilians’ consumption
highlighted throughout the analysis.

1
More than policies we could say that are ideas or best practices

5

2. Literature Review

The analysis of household expenditures has been and still is the focus of
several different branches of the economic and sociologic literature. Depending on
the field of interest we have, for example, marketing studies using longitudinal data to
evaluate households expenditures in order to describe the evolution of consumer
preferences; analysis that depict consumer behaviours of specific households;
epidemiological surveys focusing on food expenditure to study diabetes, obesity and
other pathologies coming from an unbalanced diet; development economics studies
aiming at understanding the economic lives of low-income individuals and purely
descriptive studies, mainly produced by research centres, to support and orientate
policy makers. Moreover, anthropological and sociological studies inspect
households or individuals’ budget with the intention to understand peculiar aspects of
their lives through the objects they purchase or they want to purchase.
Our analysis is focused on the evolution of consumption patterns during a
period of economic expansion. We are interested in looking at all the possible
aspects describing the act of consuming, from the pure amount of monetary
disbursement to the symbolic meaning it has. Therefore we have decided to proceed
with our literature review by adopting two discriminating factors: first, being low-
income Brazilian households our subject, we explored the literature dealing with any
analysis of Brazilian households expenditures; second, since we have decided to
analyse a period of strong economic expansion (2000-2009), we have studied
publications on this period. Nonetheless, we have expanded our research to non-
Brazilians subjects and to periods of economic crisis too, aiming at having a larger
picture of the phenomenon.
Two milestone studies over low-income household expenditures are those of
Duflo and Banerjee, published in 2007 and 2008. By analysing households
expenditures of individuals living with two or less dollars a day in thirteen different

6

countries (but Brazil), they present a clear picture of which are the purchasing
choices of those people. Their findings, although having some commonalities, differ
from country to country not only for cultural and geographical reasons, but also for
the diverse provision of public services that depend on the characteristics of each
welfare system. In all the countries analysed public schools are present and are free
of charge, therefore, poor households spending on education is usually small, and
despite these schools being often dysfunctional, households are normally lacking the
competencies to judge if their offspring is learning or not (Duflo and Banerjee 2007).
For this reason, and for the fact that in least developed areas of the world private
schools are not necessarily better than public ones, poor households keep sending
their kids to public schools, although valuing considerably education (Duflo and
Banerjee 2007). With regard to food their spending reveals a curious pattern: ‘Even
for the extremely poor, for every 1 percent increase in the food expenditure, about
half goes into purchasing more calories, and half goes into purchasing more
expensive (and presumably better tasting) calories’ (Duflo and Banerjee 2007). This
finding is in line with what previously observed by Deaton: ‘Even if the expenditure
elasticity of food were unity, the elasticity of calories need not to be, since the
composition of food will change as the income rise’ (Deaton 1997). Continuing their
analysis, they notice that poor households seem to dedicate large fractions of their
spending to festivals and ceremonies or alternatively to purchase a TV and/or a
Radio. Moreover, they do not show propensity to save but for acquiring these leisure
items (or services) (Duflo and Banerjee 2007). For their living in precarious hygiene
conditions, lacking of food, and under the risk of the occurrence of a natural disaster,
poor people are subject to strong stress pressure, and, probably this is the case of
why their alcohol and tobacco consumption is usually high2
(Duflo and Banerjee
2007). Duflo and Banerjee in 2008 further extended their research to middle-income
individuals (from 4 to 10 dollars a day) by using the data of the same thirteen
countries. They showed how when income rises, on the one hand expenditures on

2
When is not is because sometimes other locally more diffuse intoxicants may be preferred
(Duflo and Banerjee 2007).

7

food decrease and on the other those for entertainment rise with an impressive surge
in TV purchasing (Duflo and Banerjee 2008). From a certain point of view this could
be seen as an expansion of the Engel’s law that states that the poorer the household
the more it will spend on nourishment (Engel 1857): here the richer the household
the more will spend on TV. Middle-income people seem to be aware of the problems
affecting public services and for this reason they start spending on private education
and private healthcare (even though their quality often remain a conundrum) (Duflo
and Banerjee 2008). It seems, then, that their savings are mostly dedicated to the
purchasing of durables and to private health and education instead of to the
acquisition of assets to expand their business activity (Duflo and Banerjee 2008).
Moreover, they found that a salaried, stable job is much preferred, and somehow,
more typical of middle class individuals than the activity of running a business (Duflo
and Banerjee 2008). This is in sharp contrast with Acemoglu and Zilibotti’s ideas
about the entrepreneurial spirit of the middle class being a source of employment and
productivity growth (Acemoglu and Zibilotti 1997).
Moving to analyse how consumption changes during economic shocks,
Micheal Hurd and Susan Rohwedder (2011) have analysed how Americans have
adjusted their consumption during the current economic crisis. 2500 people who
reported to be unemployed or to have their partner unemployed have been asked to
explain how they coped with their limited budget. 85% answered that their response
to the crisis was that of reducing spending instead of, for example, dissaving (Hurd
and Rohwedder 2011). Some expenditures categories have been then individuated
as being easier to ‘cut’ than others. Food, clothing and gasoline were among the
most reduced while highly priced durables, cars and contracted services (insurance,
mobile phones, etc.) were at the opposite (Hurd and Rohwedder 2011). The reason
for highly priced durables inflexibility is their usage, which is distributed over a long
period of time (Hurd and Rohwedder 2011). Conversely, Dutt and Padmanabhan
(2010) analysed households’ expenditures during the economic crisis of 2008 for 22
OECD countries and 32 non-OECD countries and their findings are in sharp contrast

8

with those of Hurd and Rohwedder (2011). In OECD countries they observed a fall in
the expenditure shares of Durables (audio-visual equipment, furnitures, carpets,
households appliances, jewellery, medical appliances etc.) and an increase in the
share of Services (financial, telecommunication, transport, recreation, insurance etc.)
while the shares of Non-durables (alcoholic drinks, food, tobacco, electricity,
household maintenance etc.) and Semi-durables (clothing, footwear, households
utensils, recreational equipment, personal care items) are not affected (Dutt and
Padmanabhan 2010). In non-OECD countries they observed a significant drop in the
share of Durables, Semi-durables and a significant surge in Non-durables (Dutt and
Padmanabhan 2010). From their work, it seems that a common strategy emerged to
cope with the effects of the economic crisis for both sets of countries: postponing
(renouncing to) the consumption of Durables. Moreover, their results indicate that for
OECD countries Services are considered as necessities while in non-OECD
countries are Non-durables. This implies that consumers in developing countries
substitute, for instance, clothing for food. In line with this conclusion is the work of
Browning and Crossley (1999) that by analysing the expenditures of unemployed
individuals during a period of unemployment spell, they found that ‘agents who have
to cut back temporarily on total expenditure will choose to postpone replacing worn
but serviceable clothing (socks, for example) rather than go hungry’ (Browning and
Crossley 1999). McKenzie (2006) too found support to this hypothesis analysing
Mexican household expenditures during the 1994 crisis. He found that: ‘households
were reducing their expenditures on clothing, glassware, bedding and entertainment
equipment, in order to allocate a relatively higher share of their budget to basic foods,
such as cereals and grains, eggs, oils and fats and vegetables’ (McKenzie 2006).
The most complete Brazilian publications concerning households expenditure
are probably those issued in 2003 and in 2009 by the IBGE (Brazilian Institute for
Geography and Statistics) that is also responsible for the production of the most
comprehensive database containing information on Brazilian households
expenditure: the POF (Pesquisa de Orçãmentos Familiares). POF is the database

9

upon which this study is based, and, for this reason, the analysis of the IBGE
publications will be presented in details. We have two kinds of IBGE publications:
one over some specific clues resulted from a first data analysis and the other is the
complete analysis of all the expenditure voices. Unfortunately in year 2002/2003 just
commentaries and not the complete analysis were produced which, instead, was
produced (together with commentaries) for the year 2008/2009. The complete
analysis of 2008/2009 presents a detailed picture of household expenditures divided
by income classes with the only limitation that the poorest class had an upper
boundary relatively too high (R$840) for the aim of this study. Moreover, even by
having the poorest class split in more classes, the study ignores their 2002/2003
counterparts, making it impossible to compare expenditures across time.
Commentaries for 2002/2003 and for 2008/2009 show some expenditure analysis
done according to classes of income, but not consistent with our main research
scope since they systematically exclude the income distribution segments we are
interested in. On the other hand, many authors have used the POF dataset to
describe the evolution of household expenditures. An interesting work from the
Boston Consulting Group (BCG) (2013), studied Brazilian household expenditures in
relation to their income for the year 2008/2009. By putting on the Y-axis average
spending and on the X-axis household income, they individuated four groups of
products that have the same average spending-income relation3
. The first group
accounts for the 39% of the total spending and shows continuous growth with
income. Typical products are: salty snacks, fresh fruit and vegetables, wine,
children’s clothing, health insurance, small appliances and skin care products (BCG
2013). The second group accounts for the 32% of the total expenses and it presents
a trend to plateau, which means that individuals increase their spending in relation to
income with a steeper slope, until they reach a threshold where spending is levelled
off. Products from this group are: fresh meat, biscuits, beer, beverage concentrates,
sneakers and deodorants (BCG 2013). The third basket of items represents the 27%

3
In short, they create a series of Engel curves

10

of spending for Brazilian households and this is better described by a line with
multiple inflection points, meaning that consumers will keep buying this product until
their basic needs are met then, when they can afford it, suddenly increase their
spending for the same product. Women’s clothing, language schools, ice creams,
ready-to-drink juices, perfumes, imported automobiles, medical consultations, private
education belong to this category (BCG 2013). The last group contains products
whose purchasing remains stable with income. They are flour, starches, pasta, sugar
and sweeteners, cereals, pulses, oilseeds, powdered milk, eggs for example (BCG
2013). Furthermore, by using a sample of 1440 households they concluded that
when households enter new income segments spending on certain products surges.
For example, households earning les than $3000 a year, when they pass to earn
from $3000 to $15000 they start spending in white goods, electronics, juice
concentrates, fresh foods, prepaid mobile and motorcycles (BCG 2013).
Another study, still on the POF database, done for the FeComercioSP4
(2012)
focuses on the evolution of the middle-class and its impact on the retail market. By
dividing the Brazilian society in classes according to the minimum salary, it highlights
how the middle class5
expansion occurred from 2000 to 2010 was accompanied by:
first, increased purchasing of home appliances, electric appliances and cars (mostly
via credit); second, increased spending on services such as cable-TV subscriptions,
mobile phones contracts, private health services, private education, beautician
services and holiday trips (FECOMMERCIOSP 2012). Dos Santos (2013) too, in his
analysis over the expansion of the credit sector among low-income households
showed how, between 2009 and 2011, purchasing of consumer durables blew up
(Dos Santos 2013, pp. 39). Spers, Wright and Castro (2007) analysed changes in
consumptions among individuals earning from 2 to 5 minimum salaries in the 2003-
2007 period. Their results highlighted a conspicuous raise in spending in the car

4
FeComercioSP is the Federation for Commerce in São Paulo. It represents many different
company unions.
5
Here defined as those households earning from R$1400 to R$7000 monthly

11

sector, culture, education and tourism; minor increasing accounted for hygiene and
personal services (Spers et al. 2008).
In their study Da Silva and De Paula (2003) explored how food consumption
changed after the implementation of the Plano Real (1994) that led to sensible price
stability after years characterized by hyperinflation. They conclude that, thanks to the
effects of augmented minimum salary and the already mentioned price stability,
household consumption increased and to a certain extent homogenized against class
differences (Da Silva and De Paula 2003). In addition, they registered a strong
demand for quality and healthy food accompanied by the explosion of frozen and
ready-packed food. In particular, chicken meat and yogurt products increased
impressively in sales (Da Silva and De Paula 2003).
Monteiro, Levy, Claro, de Castro and Cannon have classified food items
present in the POF according to three criteria: unprocessed or minimally processed
food, processed food and ultra-processed food products6
(Monteiro et al. 2010). They
then have analysed food consumption with the aim at seeing how consumption of
these three food groups was distributed along the percentiles of the income
distribution, and found that in 2002/2003 consumption of ultra-processed food
increased with income (Monteiro et al 2010). In a later study they compare their
results with older data on food consumption and they conclude that In Brazil, ready-
to-eat or ready-to-heat ultra-processed foods are displacing unprocessed/minimally-
processed foods and processed culinary ingredients (Monteiro et al. 2010). In the
authors’ view, one of the principal reasons explaining this behavior is the ‘amplified
and aggressive advertising and marketing of branded products belonging to group
three, many of which are produced by transnational companies and many other by
very big manufacturers and caterers’ (Monteiro et al. 2010). Levy, Claro, Mondini,
Sichieri and Monteiro (2011) have used the POF database of 2008/2009 to describe

6
Group one products examples are: fresh fruits, vegetables and meats, etc. Group two:
vegetables olis, butter, noodles, food containing preservatives, etc. Group three: cakes and
pastries, ice-cream pre-prepared meat, hot dogs, oil canned fish etc. The first group is the
healthier, the third the unhealthier.

12

the regional and socioeconomic distribution of households food availability in Brazil.
Their findings reveal that if on the one hand the amount of energy from protein was
adequate in all regional and socioeconomic strata, on the other an excess of free
sugars and fats was observed in all the regions of the country especially in the
Southern and Southeastern. Finally they observe an increase in the fat content and
reduction in carbohydrate content of the diet with the increase in income (Levy et al.
2011). Their conclusions are in line with those of Bueno, Marchioni, César e Fisberg
that reveal how in São Paulo added sugar intake is higher among younger adults of
higher socioeconomic level, with soft drinks and table sugar accounting for 50% of
the sugar consumed (Bueno et al. 2012).
As we said at the beginning of this chapter, consumption is a multifaceted
concept and among the aims of this study there is to understand the key
determinants that drove the purchasing decisions from low- to middle-income
Brazilians households. If we think at the act of purchasing as the final result of a sum
of exogenous and endogenous forces operating at an inner level of every individual,
we could attribute these forces to two macro-elements: one is individuals’ past as
consumer entities and the second is their future, meaning with that the “ever-coming”
new modalities and new products that shape their consumer behaviour. Looking at
the past, Brazilians were coming from a period of deep recession and hyperinflation,
which characterized the last years of the 80’s and the first half of the 90’s. During
those years the high volatility of prices induced consumers, especially those who
were responsible for frequent buying—women7
, to elaborate complex purchasing
strategies in order to cope with prices that were changing within the same day
(O’Dougherty 2002). Moreover, according to O’Dougherty, the effects of
hyperinflation, would have fostered the practice of “immediatism” setting people’s
mind on a short-period vision of time (O’Dougherty 2002, pp. 72). The act of

7
According to Scirè among Brazilian households, purchasing decisions were this structured:
the “woman of the house” (dona da casa) was responsible of everyday acquisition typically
items for the kitchen and food; the man, in turn, was in charge of asset-purchasing decisions
such as durables or a car (Scirè 2009, pp. 40)

13

consuming during those years was constrained when not totally impeded, causing a
severe frustration among Brazilians households who saw in this, as O’Dougherty
noted, ‘a serious threat to the foundation of their identities’ (O’Dougherty 2002 pp.
53). With the advent of the Plano Real in 1994, prices stabilized, the Brazilian
economy was at the very beginning of its path of growth and companies offering new
products and services were mushrooming, searching new and safe market
segments. As a consequence, O’Dougherty reported a popular support for the trends
into small business, services and sales at the expenses of “nobler” professions for
which a higher cultural level was required. (O’Dougherty 2002 pp. 92). This brief
summary is useful to understand the background of the consumerist thirst of the
Brazilian society approaching the late 90’s which will subsequently exert a strong
influence on consumers.
During the first years of the XXI century companies started to look for the first
time at low-income households as a potential target for their products. Lemos and
Santos (2010) proved it by showing how advertisement campaigns directed towards
low-income consumers started to intensify exactly in those years (Lemos and Santos
2010, pp. 55-58). They further expand this concept analysing in 2007 two
advertisement campaigns created by two different companies selling the same
product: a computer. The most effective advertisement campaign had this successful
mix of elements: a testimonial who was very popular among low-income consumers;
a short list of advantages coming from the acquisition of the machine; the creation of
a “club” of satisfied consumers; an instalment strategy that allowed them offer the
product for less R$2 per day (R$ 57 per month) (Lemos and Santos 2010, pp. 53-
65). In only one advertisement the company concentrated the principal desiderata of
a low-income consumer: sense of inclusiveness and reliability; the symbolic
opportunity of social ascension and a captivating pricing strategy (Lemos and Santos
2010, pp. 60-65). Regarding this latter issue, Godoy and Nardi (2006) have showed
how among people coming from the lower classes and older than 25, instalment
values and modalities of payments are respectively the second and the third most

14

important things to consider when they decide to buy something—the first is discount
(Godoy and Nardi 2006).
McKinsey&Company (2012) has tried to depict low-income Brazilians
consumer behaviour through a series of interviews conducted with consumers on
one side, and executives of large companies, retailers and owner of small shops on
the other. Their findings reveal that contrarily to common thoughts, low-income
consumers do not seek just low-priced products (McKinsey 2012). In line with their
conclusion is the work done by Kantar World Panel that in 2008 showed how over a
basket of 65 categories, 31% of low-income consumer purchased leading premium
brands with prices that were 10% higher than the average for that category (Kantar
2008). The rationale behind this apparently illogical behaviour is their need to
compensate for a dignity deficit and often low-self esteem, which sublimates through
the act of buying in better furnished, more expensive supermarkets (McKinsey 2012).
The Economist (2014) reports a curious phenomenon currently going on in the
outskirts of the main Brazilian cities called rolezinho. It basically consists in large
group of youngster (thousands) gathered via social network, to meet in big shopping
malls to do collective shopping (even though sometimes it ended up in robbery). As
the Economist points out: ‘As well as air-conditioning, shopping centres also confer
something no open-air space can: status’ (The Economist 2014). The shopping
experience seems to be one of the few possibilities that low-income individuals have
to choose a better treatment for a relatively smaller marginal cost. For example in
their everyday life poor people have to deal with low-quality public services, and
switching to the private sector would cost too much leaving them with no options,
therefore, whenever they can choose what to buy their aspirations expand greatly
(McKinsey 2012). Moreover, personalised relationships, face to face contact8
and

8
In this merit we must say that the advent of the e-commerce is changing the relationship
retailer-customer, at least for young cohorts and for specific items, transforming it into a face
to interface contact where the web design plays a crucial role in making customers
comfortable.

15

social inclusiveness make them feel at home, transmitting serenity and thus willing to
buy (McKinsey 2012).
Another important determinant in shaping the consumer behaviour of low-
income Brazilians is the expansion of the credit market towards this sector of society.
According to Zouain and Barone (2007) Brazil has an extensive penetration of credit
cards when compared to other countries of South America. In 2004, Brazil had a
penetration of 0.293 credit card units per capita, while Chile, that has a higher
income per capita, had a penetration of 0.166 per capita (Zouain and Barone 2007).
In order to understand the dimension of this phenomenon, the number of credit
cards9
issued in Brazil passed from being 127 millions in 2004 to 628 millions in 2010
(BFA 2012). The rapid penetration of this new payment method among low-income
households, has drastically changed the way in which they manage their budgets
and, consequently, has a strong influence over their consumption practices. As Scirè
points out in her work, credit cards by giving the possibility to pay in installments and
by having generous credit limits, seem to have fused a process of ever-postponing
payments, sacrificing the well known delayed gratification to the immediateness of
possession (Scirè 2009, pp. 53). She continues saying that by using credit cards this
kind of “virtual money to spend” entered into their budget as if it were an actual
source of income (Scirè 2009, pp. 53). Debts, therefore, are no longer perceived as a
flaw, a shortcoming or a deficiency, but they constitute the element that structures
consumption practices and, lastly, the life of low-income households. Since
households’ initial financial situation is that of having debts, all the calculation
required to manage their total income, is, in a certain sense, altered. Given these
conditions, having access to credit seems to impact on popular consumption
practices with, at least, an instigation effect. (Scirè 2009, pp. 54). A proof of this fact
comes from a study done for the Bankable Frontiers Association (BFA) that has
followed financial transactions of two low-income households, Brazil and South Africa

9
Including credit card issued by retailers that, as Scirè explains in her work, allows
cardholders to make payments also in other stores up to a certain threshold.

16

and then compared it. In their graph (see Figure 1) is clearly showed how for the
Brazilian household, payday allows for debts to be repaid and new debts to begin
accumulating. Saving to meet daily cash flow needs is much less common. In
contrast, they have found that in South Africa, a household tends to receive a large
income inflow, such as a monthly salary or government grant payment, which the
recipient saves and spends down slowly as consumption needs arise over the month.
(BFA 2012)
Figure 1: Consumer spending in Brazil and in South Africa among households with similar income levels
Source: BFA 2012
At minimum, a constant and accurate calculation is thus required in order not
to be insolvent and to continue spending, but as Dos Santos (2013) highlights in his
study, low-income households are lacking the cultural capital that would enable them
to plan and effectively manage their debts (Dos Santos 2013, pp. 104). A previous
study from CNDL10
(2012) further proofs this by showing how 60% of the total low-
income individuals surveyed have demonstrated to have no planning skills (CNDL
2012). This would lastly demonstrate the impulsivity and the irrationality that often
lies behind the consumer behavior of low-income Brazilians probably driven by what
Dos Santos called the joy of a momentary euphoria (Dos Santos 2013, pp. 28).

10
Confederação National de Dirigentes de Lojistas—National Association of Business
Executives

17

3. Socio-economic classes in Brazil
Dividing the society in socio-economic classes had always been a
controversial issue in social sciences. Literature is split in two main branches using
either a subjectivist or an objectivist approach. The subjectivist approach considers a
class as a socially constructed attribute in which membership is mainly determined
by the psychological attachment to it, that is part of an individual’s overall self-
concept (Walsh, Jennings and Stoker 2004). The idea of belonging to a certain class
is, in turn, dependent firstly on the individual’s knowledge of class options, and thus
class divisions, and secondly on the criteria with which these divisions place
him/herself in one specific class (Walsh et al. 2004). Aristotele, for example, was in
line with the subjectivist approach saying that membership in a class is mostly
generated by shared ways of thinking, shared opinions over major issues more than
other characteristics. In other words, classes are social categories sharing
subjectively-salient attributes used by people to rank those categories within a
system of economic stratification (Wright 2003).
Alternatively, the objectivist approach is based on the elaboration of
socioeconomic indicators such as income, education, occupation etc. to which are
attached qualitative information. This approach is thus double: first we have
quantitative indexes identifying one person’s social class, then the qualitative
properties of the various indexes ‘derived directly from some key modern
occupations in a society, such as private entrepreneurs of small/medium firms,
managerial personnel, white collar professionals etc.’ (Lu 2012). The definition of a
class in this sense is a gradational concept and the names are accordingly upper,
upper middle, middle, lower, lower, and under. There is another branch of the
objectivist approach based on indexes that explain inequalities in economically
defined life chances and material standards of living (Wright 2003). Classes in this
sense are relational more than gradational concepts, where individuals are classified
according to their relation with income-generating resources or assets of various

18

types. This concept is characteristic of both the Weberian and Marxist traditions of
social theory.
We decided to use a Brazilian publication (Commissão para a Definição da
Classe Media no Brasil) that first defined the middle class and then divided the entire
society in the other socio-economic classes. We can ascribe the methodology used
by these researchers as purely objectivist, of the first type. It is, in fact, based on an
index that results through the combination of three indicators. Nonetheless, we will
also illustrate another classification method, also developed by a Brazilian institution
(Associação Brasileira de Empresas e Produtores-ABEP), which we found interesting
for our research purpose and which is recalling the relational approach.
3.a Commission for the definition of the middle class in Brazil
The Brazilian government have commissioned to its Secretary of Strategic
Affairs (Secretaria dos Assuntos Estrategicos-SAE), a project which aim was to
define the middle class in Brazil. Many experts and researchers on the Brazilian
society, coming from the most prestigious Universities of Brazil, had participated and
their final work was published in paper issued in 2012; given its relevance we here
summarise how they proceeded.
First, income had been judged to be the more synthetic, wealth-related
indicator possible (even though in low-income countries, due to problems related with
income registration/annotation, expenditures are often taken as a better proxy of
income). Then the question was what to choose between per-capita income or per-
family/household total income. Researchers affirm that in Brazil a purely per-capita
income would underestimate the real wealth of an individual since most of the
Brazilians live in communities, being them a family or a little neighbourhood, and
because whoever is the “bread-winner” will share his/her money/assets/food,

19

whenever possible, with his/her reference community. These communities are
peculiar among lower-medium and low-income households and account for more
than half of the whole Brazilian population. On the other hand, per-family/household
income would be subjected to other biases, we know for example that members of a
household vary in numbers and age across the different segment of the society and
that families do have economies of scale. The decision of the Commission was to
sum up all the income sources of a family and then divide it for the members of the
household obtaining what they called a household per-capita income.
Once established the correct indicator to be linked with wealth, they passed to
explore different possibilities for measuring and dividing the Brazilian society
according to this value. A relevant branch of the socio-economic literature uses the
median of the income distribution and define the middle class as in between half and
two times the median income value. This is a relative measure that, against a non-
reduction in inequalities (Gini index), follows the economic growth of a country
leaving classes dimension as they are. What they needed was an absolute measure
capable of capturing the evolution of the classes even without drastic reduction of the
Gini Index. The rationale is that within a society that has not equalized its income
distribution, but in which people improved their relative (compared to the past) well
being, a relative measure would register just slight (if any) changes in class
composition, all due to reduction in inequalities. Conversely an absolute measure is
needed to precisely describe changes.
An absolute measure can be calculated, for example, individuating income
limits for a set year and then taking them as reference limits to be applied in other
years (adjusted for inflation). The choice of the commission was the latter and the
criteria upon which limits had been chosen were based on the concept of
vulnerability. Vulnerability is a key concept in poverty studies that had just recently
entered the academic arena11
. Poor people are usually characterized by scarce

11
In this merit we suggest the reading of Lopez-Calva, L. F. and E. Ortiz-Juarez (2012). ‘A
Vulnerability Approach to the Definition of the Middle Class’ Journal of Economic Inequality

20

capacities of future planning and an accentuated short-term vision of life. The
explanation is that since poverty (here intended as a status where is necessary to
struggle for life) stays one step back the present condition of an individual, it is
unlikely for him/her to be a risk taker and to invest, or save, in synthesis, to make
plans. The primary objective among vulnerable individuals is to make end meets,
living day by day. A sudden shortage of money would pose them in serious troubles
so that, there is always the possibility for them, due to some exogenous factor, to fall
back into poverty again.
At a psychological level this makes them acting cautiously and similarly to their
poorer counterparts. In the report, the poverty line is defined according to the income
limits required to participate the two major social programs Brasil sem Miseria and
Bolsa Família at 162 R$ of household per-capita income normalised at 2012 level.
Vulnerability, thus, is the probability (that can be expressed in percentage terms), of
falling under this line. When income is sufficiently high, and thus vulnerability is
lowered, individuals leave their past-poverty burden and acquire a different mind-set
making plans and possibly investments.
In order to establish income limits, vulnerability has been realistically
transposed over three different time ranges: probability of falling back the poverty line
in one year, in five year and of being structurally poor12
. The first had been
extrapolated by data taken from PNAD that although not being panel data, has the
peculiarity of being a survey done each year in the same census sector13
. They
calculated household whose income fell under the poverty line in the subsequent
year in the period 2004-2008. The same had been done for households falling back
the poverty line in a five-year period from 2005 to 2009. They then correlated each of
the above-mentioned indicators to income through a logistic regression and based on
this equation, for every respondent in PNAD it was possible to obtain the chance of

12
Here for structurally poor we intend permanently poor.
13
A census sector is defined as a unit of 200 households that can be distributed in different
ways (e.g. two buildings, ten floors each floor with ten apartments, a portion of an urban slum
of 200 settlements).

21

becoming poor as a function of per-capita income, in other words, their vulnerability
to poverty.
According to vulnerability measures the commission split the population in
three groups: high, medium and low vulnerability. The limits defining the three groups
were taken following a polarization method minimizing the distance within groups and
maximizing that between groups. Since the definition of distance could be arbitrarily
chosen and since distances (for minimum and for maximum) have to be the same,
the commission decided to use the Theil index that defines distances as the reason
between the arithmetic and the geometric mean. By doing this they obtained one
upper limit and one lower limit of vulnerability per each time range/period. The upper
limit is representing the low vulnerability group, expressed in percent, upon which the
risk of falling back to poverty is close to zero. The lower limit is the opposite: is the
edge between poverty and the middle class, under which households are concretely
exposed to the risk of falling back the poverty line (R$140) and upon which they are
sufficiently relaxed to start developing a long-period vision.
The final outputs were two limits generating three income brackets for each
period analysed (one year, five years and structurally poor). Since they were very
similar14
the final decision of the commission was to take only one household per-
capita income interval: between R$ 291 and R$ 1019 (at 2012 level). Consequently
individuals whose household per-capita income is downwardly approximating R$ 291
are increasing their degree of vulnerability from medium to high while those nearing
the R$1019 threshold are decreasing it from medium to low.
Since the degree of heterogeneity of the created classes was still high, the
decision of the commission was to operate a final subdivision; individuals falling
under the poverty line were split in two classes: extremely poor from R$81 – R$162
and poor R$162- R$291. We then have the vulnerable class whose income range
from R$162 and R$291. The middle group and the high group were divided using the

14
R$ 303- R$ 1056 : vulnerability for one-year period; R$ 291- R$ 1019 vulnerability for five-
years period; R$ 290- R$ 981 structural vulnerability

22

polarization method above mentioned generating three middle classes and three high
classes as shown in Table 1.
Table 1: Income brackets defining socioeconomic classes in Brazil
15
.
Income Brackets 2012 Class
x<81 Extremely poor
81<x<162 Poor
162<x<291 Vulnerable
291<x<441 Lower-middle class
441<x<641 Middle class
641<x<1019 Upper-middle class
1019<x<2480 Lower-high class
2480<x<6448 Upper-high class
x>6448 Extremely rich
Source: SAE 2012
3.b ABEP and the Critério Brasil
ABEP stays for Brazilian Association of Research for Companies specialized
in doing market researches and providing a series of other strategic services useful
to help private business flourishing in the country. The purpose of their classification
of the Brazilian society into economic classes is thus market-oriented and does not,
at least directly, describe the social aspects that this division implies. Their aim is
looking at the purchase power of urban residents, for the obvious implications that
such information has from a business perspective. They created a classification
system based on points were points are distributed according to the possession, or
not, of specific items plus the educational profile as shown in Table 2 and 3.
They then created a scale from A1 to E, based on scored points, in which they
collocate households depending on their scores. By so doing they also individuated
which was the average income corresponding to each class. In Table 4 we present
the last mentioned scheme of class distribution with related mean income.

15
The inflation rate considered by SAE to deflate the income-boundaries that define the
classes is the INPC – Indice Nacional de Preços ao Consumidor (National Price Consumer
Index) at 2012 price level

23

Table 2: Household characteristics and related points
Source: CCEB 2012
Table 3: Educational profile and related points
Education Points
Illiterate/ Not completed elementary school 0
Elementary completed/ Primary not completed 1
Primary completed/ Secondary not completed 2
Secondary completed/ Tertiary not completed 4
Tertiary completed 8
Source: CCEB 2012
Table 4: Classes subdivision and related per-household income
Classes Points Income
A1 42-46 12926
A2 35-41 8418
B1 29-34 4418
B2 23-28 2565
C1 18-22 1541
C2 14-17 1024
D 8-13 714
E 0-7 477
Source: CCEB 2012
The battery of items may vary in the years to come, according to the
availability of the data and, evolution of the Brazilian society and the advent new
goods and services. The object (and services) spectrum is widening and items are
Items 0 1 2 3 4 or <4
Color-TV 0 1 2 3 4
Radio 0 1 2 3 4
Bathroom 0 4 5 6 7
Car 0 4 7 9 9
Maidservant 0 3 4 4 4
Washing machine 0 2 2 2 2
VHS or DVD player 0 2 2 2 2
Fridge 0 4 4 4 4
Freezer 0 2 2 2 2

24

being redistributed respecting differentials in income so that what was typically
consumed by a certain class in 2008 will not be the same of 2014.
What is interesting is that, probably without having this in mind, they used a
concept that is at the core of the sociological literature about consumption. Although
the criteria for the object selection aimed at dividing the population according to their
purchasing power, the idea of creating socio-economic classes depending on the
possession of certain object and/or services is also present in Baudrillard (1997). He
affirmed that the act of buying something and, consequently, of possessing it has
intrinsically embedded the purchasing power of an individual (real or supposed) upon
which our cultural system is based on. The reason for purchasing certain items is
extended beyond the pure necessity: objects are means charged with the purchasing
power information and thus have the power of regulating social relations (Baudrillard
1997). The author is never explicitly referring to socio-economic classes however he
individuated in the purchasing power a discriminant for regulating interactions among
individuals. In its classification, ABEP is using a system of objects (and services) to
define the purchasing power of individuals with which dividing the society in
economic classes, that is theoretically in line with Baudrillard thought.

25

4. The “20 millions phenomenon”
4.a The macroeconomic framework
After the implementation of the Plano Real, the Brazilian economy entered a
new phase of growth. The end of uncontrolled inflation, the establishment of an
optimal inflation level with limits to primary deficit, the reformation of the banking
system, laws about fiscal responsibility and trade liberalization were the basis upon
which the growth experienced between 2002 and 2009 was rooted on. Parallel to this
we assisted to the emergence, in early 2000, of a new global player, China, whose
growth, based on exporting low-added value products, had lifted up its energetic and
commodities needs. Consequently, due to the dimension of the Chinese economy,
the world demand for these resources (and their related prices) raised consistently.
Brazil is a country rich in commodities especially soya, oil and steel and in those
years China became one of the first three Brazilian commercial partners, sharply
accelerating the country’s economic growth.
In the same years, in 2002, Luiz Lula Inacio da Silva succeeded to Henrique
Fernando Cardoso and during the early phases of his government investors were
suspicious of the monetary policies that Brazil’s new leftish president might
implement. As a consequence, the Real depreciated while exportations increased,
granting a solid economic base to the Brazilian economy. Lula de facto followed the
monetary policy previously started by his predecessor Cardoso, reassuring investors:
by so doing he started to accumulate foreign currency reserves while lowering the
interest rate. Through the fiscal system the government improved the distribution of
wealth through the implementation of social programs directed towards low- and
lowest-income families. Moreover, in the years 2002-2008 world economy also was
in expansion and Brazilian private companies registered in those years double digits
growth and business expansion in many different sectors.
In synthesis, the government (stable inflation, social protection programmes),
the private sector (ripping world economic growth, job creation) and finally the advent

26

of the credit market, were the principle contributors of the economic ascension of
millions of low-income families to the middle-class status.
4.b Micro perspective
“O fenomeno dos 20 milhões” is a Brazilian expression that means “The 20
millions phenomenon” and it refers to the ascension of millions of low-income
individuals to the middle class between 2002 and 2009. This way of saying includes
a figure: 20 millions. By analysing different sources we conclude that the “20 millions
phenomenon” is not only a popular say since it is close to the figures found in the
more important works dealing with this issue with differences that depends on the
economic classes definition adopted. The real numbers are around 29 millions of
individuals (Neri 2009; SAE 2010) and SAE further specifies that, by splitting this
value in two, 8 millions are due to the natural demographic growth of the “old” middle
class and 21 millions had entered the middle class from the lower strata (SAE 2010).
With regard to the causes researchers from SAE (SAE 2010) individuate four main
determinants that contributed to the growth of the Brazilian middle class, although
with different weights, as discussed below in detail:
i. Demography: leveraging on the demograp hic dividend.
ii. Government transfers: Bolsa Família, Beneficio de Prestação
Continuada, Previdência Rural.
iii. Job creation: low unemployment.
iv. Gains in labour productivity.
(i) From 2000 to 2009 the percentage of adults (more than sixteen years old)
in the country was of 79%. The age structure of Brazil that after decades of high

27

fertility rates experienced a gradual downfall (below replacement level in 200916
), left
the country with a low dependency ratio calculated as the ratio of dependents
(people with less than 15 years old and more than 64 years old) over the rest of the
population. Brazilians were enjoying the economic benefits of what in the
Demography literature is called a Demographic Dividend. In the authors’ view this
alone had contributed to explain the 20% of the growth of the middle class. (SAE
2010)
(ii) Brazil witnessed the advent of several government programs aiming at
reducing poverty that were mostly based on government transfer so that the part of
per-capita income not originating from work had risen from R$ 85 to R$ 134 on
average17
. Rather surprisingly, SAE researchers found that the government transfers
were responsible for just the 20% of the differential in income between the middle
class and the poor class18
. while accounted for the 30% of the middle class growth.
(SAE 2010)
(iii) The expansion of the Brazilian economy by creating jobs sustained the
demand for workers and significantly lowered the unemployment rate. The
importance of the income from work is still preponderant among middle class, being
three quarter of their total income and this contributed to explain slightly more than
10% of the middle-class expansion (SAE 2010)
(iv) Income from work is dependent on two elements: unemployment rate and
productivity. A good measure for productivity is the average salary that has been
growing yearly at a 1.7% rat since 2000 accounting for 40% of the middle class

16
It passed from being 3.5 in 1985 to 1.9 in 2008. Source: World Bank
17
We refer to the 2000-2009 period
18
As Mourão and de Jesus point out in their research over the effectiveness of the Bolsa
Familia program, often non-recipients’ income are lower than recipients’ income and there is
still a large number of peole who is potentially a beneficiary but do not receive the transfer
due to lack of availability. (Mourão, de Jesus 2011)

28

income variation (SAE 2010). According to the authors the origin of the new Brazilian
middle class actually resulted from a solid process of inclusiveness in the production
side of the economy more than on generous government transfers, resulting to be its
major driver (60%). This also explains the real difference between a poor and a
middle class individuals, the latter increasing productivity factor of more than double.
Moreover, in a subsequent paper of 2012 they show that the income growth of the
poorer classes more than doubled the national average growth rate, while the income
change of richer classes has been half the national average.
Neri, from Fundação Getulio Vargas, adopts a different perspective. In his
opinion the middle class expansion is a consequence of the redistribution of wealth
as demonstrated by the GINI Index variations that passed from 0.5886 in 2002 to
0.5486 in 200819
showing a constant negative trend throughout the reference period.
Neri, although dividing the Brazilian society in five economic classes with income
thresholds different from those adopted by SAE, reports strong interclass movements
in our study period20
. In agreement with Hoffman and Soares, Neri showed that inter-
class movements were explained to a large extent (67%) by variations in income
from work with programs of government transfer (mostly Bolsa Família and Bolsa
Escola) accounting for the 17% and social security programs for the 16 % (Hoffmann
2005; Soares 2006; Neri 2009). Neri continues his analysis by indicating that
education and consequently the enhanced qualification of workers contributed
substantially to enhance their productivity. This is in line with the analysis made by
SAE in 2010.
In a 2009 paper studying the consumption of Brazilian lower classes, Spers,
Wright and Castro gave a similar explanation for the inter-class movements that
occurred between 2003 and 2007. According to the classification of the economic

19
Source: Neri, IBGE-CPS-FGV
20
He calculated that on average the upper three classes together A/B/C grew of 35% and
the lower two shrunk of 29%. Source: Neri, PNAD-IBGE

29

classes made by ABEP21
the ascension of households belonging to the lowest
classes (E and D) was associated with a reduction of the upper-middle classes (B1
and B2). The reason behind the first transition (E towards D) is the well-known
program of government transfers of Bolsa Família. In the authors’ view the amount of
money transferred by this program is sufficient to elevate households to the
subsequent class. The remaining transitions are due to the effect of augmented
minimum salary that, if on one hand had increased the purchasing power of the D
class, on the other had diminished that of the B1 and B2 classes. The reason is that
the effect of augmented minimum salary is faster in the lower part of the income
distribution where salaries are close the minimum level. In fact, adjusting salaries of
the richer classes to the augmented minimum wage is a process that takes time,
therefore, until salaries are not adjusted their purchasing power is relatively reduced.

21
See
above

30

5. Methodology
5.a Dataset presentation: POF and PNAD
In order to analyse Brazilians’ consumption choices we decided to use the
POF - Pesquisa de Orçamentos Familiares (Brazilians Household Budget
Expenditure) – a database available for the years: 2002/2003 and 2008/2009.
Surveys administration was conducted in a 12 months period, and prices were
corrected for the on-going inflation level and adjusted for regional disparities. In order
for the respondents to give the most detailed list of expenditure possible, surveys are
organized following a peculiar methodology. Expenditure items were first grouped
according to two dimensions: frequency of purchasing and monetary value. Normally,
expenditures of small value are more frequent than expenditures of large value, since
they capture everyday expenditures such as food, bus fares, drinks etc. Conversely
large value expenditures are occasional, often related to the acquisition of durables
and/or occasional services (ceremonies, holidays etc.) and remembered for longer
period of time by households. According to these two dimensions, they were set four
different time-periods (one week, one month, one and half month and one year)
where to distribute the complete list of expenditure items. This way we find, on the
one hand, surveys that contain items which acquisition is more uncommon (e.g.
parties and ceremonies) that ask the respondent to register (remember) the
purchasing in one and half month period and, on the other hand, others asking
spending occurred in a one-week period for more common items (e.g. food and
drink). At a later stage, monetary values of disbursements, registered in different time
periods, were proportionated to monthly expenditures.
The total number of household observations for 2002/2003 is 48,084 and for
2008/2009 is 55,532. The original database containing the answers to the survey’s
questions, was divided into sub-groups by researchers of the Brazilian Institute of
Statistics and Geography (IBGE), each one functional to a specific kind of study. In

31

this study we are using the unidade consumo (consumption unit) group, created to
analyse consumption expenditures.
The dataset selected contains detailed information on household’s
characteristics (income, sources of income, total disbursement etc.) and on the
following class of expenditures: Food and Drinks, Housing and related items, Clothes
and Personal Accessorizing, Transportation (services and products), Hygiene,
Healthcare (services and products), Education (services and products), Leisure Time
(services and products), Personal Care (services and products) and Current
Expenditures. Every expenditure item of every class is an aggregate of one or more
products/services (an example can be found in Annex IV). Finally, to each household
was given a weight - based on the demographic structure of Brazil - in order to allow
extrapolations to the whole population.
The period in which the 2 surveys were conducted fits particularly well with our
research question for the reasons explained in the previous chapters22
.
The other database we used is the PNAD – Pesquisa Nacional por Amostra
de Domicílios (Household Survey) available for different years, including the study
periods in which we are interested. Similar to POF is surveys-based but data
collection and elaboration was done during the last three months of each year. What
is interesting about this database is that is divided in two datasets: DOM and PES:
i. DOM: household survey. Contains information about the characteristics of the
house in which a household is living in, plus some basic information about the
income, total number of people living in the house, geographical position etc.
ii. PES: individual survey. Contains socio-economic information such as number
of years studied, type of work, occupational sector in which the subject is
employed etc.

22
See
Chapter
3

32

The utilization of these datasets is aimed at integrating some of our analysis
whenever we are lacking data from the POF.
5.b POF Methodology

5.b.1 General Considerations
Is not really the scope of this research to explore the origins of households’
consumption choices made in 2002 and in this respect we consider them as given.
Nevertheless, in the previous chapters we have provided a short insight over a period
of time of almost 15 years before 2002, in order to have a framework in which we
could insert our work. Summarizing we can say that, consumer confidence in 2002
was growing in parallel with a strong retail sector backed by an expanding economy.
The growth of the demand was about to start being fuelled by the entrance in the
market of the so-called bottom of the pyramid.
5.b.2 Definition of Socio-Economic Classes
The income-based subdivision of socio-economic classes operated by SAE23
,
creates nine income-based categories (Table 5). We decided to focus our analysis
on the lower 5 classes from the extremely poor to middle class.
With the aim of reducing the noise we trimmed the samples at the top 1% total
expenditure of each class. By doing so, we wanted to exclude households who
registered extraordinary expenditures in order to obtain more homogenous (and
representative) samples.
Our research focus being on changes in consumption choices of households
that range from extremely poor to middle class, we deliberately decide to exclude
upper classes. On the other hand, the choice of extending the analysis from the
extremely poor to the subsequent upper four different subclasses will allow us not

23
See Chapter 3

33

only to look at middle class variations in consumption habits, but also to highlight the
differences occurred among poorer classes from 2002 to 2008, and, given that
poorer classes of 2002 represent the pool from where the “new” Brazilian middle
class of 2008 originated (and where a large fraction of the current middle class
comes from), by including them we might gain a better insight on the evolution of the
wants and needs of the Brazilian middle class which is at the very centre of the
contemporary political discourse in Brazil. As shown in Table 6 the size of samples
reflects the structure of the whole Brazilian population.
Table 5: Income brackets defining socioeconomic classes in Brazil
24
.
Income Brackets 2002 Income Brackets 2008 Class
x<120 x<182 Extremely poor
120<x<343 182<x<518 Poor
343<x<546 518<x<824 Vulnerable
546<x<816 824<x<1232 Lower-middle class
816<x<1020 1232<x<1540 Middle class
Source: SAE 2012
Table 6: Number of observations per each class of household
Classes
# and (%) of
observations
2002
# and (%) of
observations
2008
Extremely poor 857 (1.8) 686 (1.2)
Poor 7388 (15.4) 5612 (10.0)
Vulnerable 8166 (17.0) 8857 (16.0)
Lower-Middle 8499 (17.7) 10848 (19.5)
Middle 4307 (9.0) 5956 (10.7)
Source: Author’s own elaboration using POF 2002/2003
5.b.3 Comparisons
Our way to look at the data is essentially based on comparisons of values of
2002 with values of 2008. Aiming at exploring households’ expenditures25
in two

24
The inflation rate considered by SAE to deflate the income-boundaries that define the
classes is the INPC – Indice Nacional de Preços ao Consumidor (National Price Consumer
Index) at 2012 price level
25
Prices were assumed to be the same for all households as conventionally done according
to Deaton (Deaton 1997).

34

different periods and across classes, we made the following comparisons:
i. Inter-year variation of shares of total expenditure of the 5 classes
a. For each main item
b. For individual goods or services present in each main item
ii. Intra-year variation of actual expenditure across classes
a. Food and drinks
b. Mixed Items
The first comparison verifies whether within the same class, but across
years, there was a shift in spending on specific goods. This is essentially describing
how consumption habits changed during the economic boom. The second kind of
comparison individuates consumption trends from extremely poor to middle class
households, that once superimposed 26
from year to year allows to estimate
differences induced by class mobility. We create consumption trends by calculating
every spending variation (in percentage terms) that occurs from one class to the next
upper class; these variations will represent the “wishes” of hypothetically every
household that passes to an upper class in the same year. It answer the following
question: how much would spending on item x change (in percentage terms) if a
household moved from class p to class p+1 in the considered year?
A further clarification has to be made for the two kinds of comparisons above
proposed. First, in order to be able to compare the same classes in different years,
we need an absolute measure expressing spending preferences. In fact, if we apply
this analysis to actual per-households expenditures, it would suffer from bias due to
the different minimum salary and related prices set
in 2002 and in 2008. Spending
preferences expressed in terms of share of total budget, or total income, instead, are

26
When we want to compare consumption patterns we must always take as reference year
the 2002.

35

weighted to the once on-going minimum salary and prices level, letting us to make
comparisons between same classes in different years. We decided to take shares of
total disbursement instead of shares of income because, especially when we are
dealing with extremely poor households, income measurement are often
underestimated due to the high volatility of that part of income that derives from
working in the informal sector27
. In Table 7 we observe how mean income and mean
total disbursement for the least two classes of households differs substantially in both
years. As a consequence, when we analyse expenditures for extremely poor
households, values of mean income are so small that when we calculate its shares
for many of the diverse items it unrealistically scores more than unity. For this
reason, results will be expressed in the form of percentage increment of 2002 shares
of total expenditures
Table 7: Mean Total Income and Mean Total Disbursement for the two years divided by classes
Year Mean per-household exp Poor Vulnerable Lower-Middle Middle Upper-Middle
2002
Mean Total Income 85.04 250.96 447.30 673.75 913.19

Mean Total Disbursement 391.70 406.94 581.65 795.06 988.21
2008

In contrast, when we perform intra-year analysis we will directly use mean per-
households expenditure since salaries and related prices are set in the same year
allowing us to make direct comparisons.
Our limitation is that we are unable to totally attribute changing in consumption
habits to a change in class composition due to the highly heterogeneous origins of
the members forming each class and to the multiple causes that can describe such a
complex phenomenon (exogenous consumer trends, prices’ variations, the entrance
of new products, etc.). Indeed, part of the causes rely in the world’s commodities
boom that in that years permitted to Brazil to grow and to its people to gain access to

27
See chapter 6 for a detailed explanation of this phenomenon

36

higher conditions of living that possibly brought new consumption habits among
same classes of households.
5.b.4 Tables
Tables were generated with a standard format: each row is an expenditure
item plus some extra items that will vary according to the analysis performed; each
column is a different class. Table 8 shows a subsection of a chart to give the reader
an idea about how is the standard structure.
Table 8: Sub-section of 2002 Mean per household expenditure divided by class
Mean per-household
expenditures Extremely poor Poor Vulnerable Lower-Middle Middle
Food and Drink 136.24 140.24 175.67 223.26 237.23
Alimentation at Home 114.35 124.83 151.89 190.23 197.19
Rice 13.32 12.82 14.40 15.88 14.01
Item x ….. ….. …. …. …..
Source: Author’s own elaboration using POF 2002
Our procedure winds around four main steps:
• first, we have created two “roots” tables, where is shown the mean per-
household expenditure of each item contained in the dataset, divided by
classes;
• second, from those charts we have derived two new tables, still indicating
mean per-household expenditure, but this time within a range of selected
items;
• third, from the charts with selected expenditure items we have created another
important table to be created in each year describing each expenditure in
terms of shares over total disbursement;

37

• fourth, we have finally generated charts that are obtained from the elaboration
of the previous tables which aim is to illustrate expenditures’ variations across
classes and across time.
In Figure 2 we present a graphical scheme summarizing the methodology
explained up to now using/with the structure of a genealogical tree. We further add
miniaturized samples of the graphs that will be created, linked to the different
analysis proposed.
Figure 2: The genealogical structure of the tables created with relative graphs (in miniature)
Source: Author’s own elaboration

38

We started performing a first descriptive statistics analysis to create the two
“root” tables, one per year, showing for each expenditure item the mean per-
household expenditure divided by classes. We then selected the most relevant
expenditure items according to two criteria:
i. Items that are present in both years
ii. Items more representative of each macro-categories of expenditure
(transportation, health, food, etc.)
Items present in both years have been automatically selected, problems arouse
when we analysed the Food and Drink category. The biggest and most detailed class
of expenditures in the database is, in fact, that related to food. The list of more than
70 different edibles, unfortunately, lacks of aggregates that cluster similar food
products in one item (diaries, vegetables, fruit) named in the same way over the two
years. Food denomination too is sometimes changing over time. As an example, in
2002 we find the item Milks that is the aggregate for the dairy products consumed in
that year. In 2008 this expenditure item is missing, but they are present some (not all)
of the products forming the 2002 aggregate for Milks. We will provide two examples
in order to shed a light on our selection criteria. First: we opted to choose cow milk
and cheese because they resulted to be the most purchased among other diary
products28
across the different classes and because they are present in both years. A
second intuitive example is that we judged being more important to know household
expenditures for rice than for pasta, based on the fact that one of the pillars of the
Brazilian diet is rice with beans.
The majority of the remaining items stay constant over time both at an
aggregate and a disaggregated level, with few exceptions. We discarded a small
number of items that we considered as neither symbolic nor relevant for our analysis.
As an example, in the category Hygiene, we considered not important to know the

28
Source: Author’s own calculation using POF 2002/2008

39

expenditure for hand soap if we already knew its aggregate and some similar
products. Still in the Hygiene category we conversely decided to choose the Hair
Products item due to its symbolical value. It is known that afro-descendants invest a
lot in purchasing hair products and in Table 9 we show how the most common ethnic
profile among the lower five classes is mulatto, with a significant percentage of black
skin people too.

Table 9: Ethnic profiles by class
Ethnic Profiles 2002 2008
Black Mulatto Black Mulatto
Extremeley Poor 6% 61% 8% 62%
Poor 6% 57% 8% 59%
Vulnerable 7% 47% 8% 45%
Lower-Middle 6% 39% 5% 29%
Middle 6% 31% 4% 24%
Source: Author’s own elaboration using PNAD 2002/2008
The final output of the first elaboration are two tabs, one per year, showing
mean per-household expenditure for selected items plus two additional information:
mean income and mean total expenditures29
. The last tabs produced can be
considered our starting point from where all the subsequent analysis will follow.
The subsequent tables shows which fraction of mean total expenditure is
dedicated to each item in percentage points according to the following formula:
𝑖 𝑆ℎ𝑎𝑟𝑒! =
!"#!
!"#!
!
∗ 100

29
Due to the large basket of items present in the database, we opt for a colour-driven
representation that helped us while reading the tables. Each colour is associated to an
aggregate of expenditures and colours remain constant from year to year. See Annex I.

40

Where (𝑎) corresponds to one item of the analysed class of expenditures. This
gives us important information about the relative weight that each item has over the
total expenditure for different classes of households.
Summarizing, we have created four tables (two per year) analysing two
different aspects of consumption: mean per-households expenditure and shares of
mean total disbursement dedicated to expenditure items. The next step was to
generate two final tabs that show the evolution of each expenditure item according to
the different comparisons proposed at the beginning of this chapter30
.
In the first we have calculated difference in percentage terms of fraction of
mean total disbursement as follows:
𝑖𝑖
𝑆ℎ 𝑎𝑟𝑒!
!""#
– 𝑆ℎ 𝑎𝑟𝑒!
!""!
𝑆ℎ 𝑎𝑟𝑒!
!""! ∗ 100
Where (𝑎) corresponds to one item of the analysed class of expenditures.
From this table we derived the graphs used for our analysis. We acknowledge that
this formula, when, for example, we pass from a 0.15% of total spending for mobile
phones in 2002 to 0.50% in 2008, calculates an increment of plus 260%. Even
though we recognize that in absolute terms is not weighing in a significant way on the
overall households budget, we consider this information as revealing a new spending
trend. We need also to consider the fact that the mean values calculated are
weighted down by those who did not buy the item. This, even though it could be
considered a signal of the diffusion of the item and thus of its importance among the
class of household analysed, led us to appreciate even little differences in shares on
the overall budget. The principle aim of this work is, in fact, to analyse consumer
trends and not how much single expenditures weigh on the overall budget; for this
kind of information what matters is the differential.
The second tables are based on the following formula:

30
See above

41

𝑖𝑖𝑖
𝐸𝑥𝑝!
!!!
– 𝐸𝑥𝑝!
!
𝐸𝑥𝑝!
! ∗ 100
Where (𝐸𝑥𝑝) is mean expenditures, (𝑎) corresponds to one item of the
analysed class of expenditures and (𝑝) to a class of households. This formula is to
be applied in both years and for each class of expenditures we are interested in.
Results have been plotted in a summary table with two columns where each column
corresponds to the consumption pattern for class p of that year, defined as the
collection of variations in expenditures from class p to class p+1.
5.c PNAD Methodology
5.c.1 Tables and Comparisons
In order to be coherent with the class subdivision made while analysing the
POF database, when we use the DOM dataset we opt to choose the same income
brackets used in POF to define the various classes. When we approach the PES
dataset, which is individual based, we will follow the instruction provided in the same
SAE’s publication (SAE 2012) from which we derived our per-household income
levels31
.
We perform the second data-analysis with the DOM dataset creating one tab
per year showing the percentage of households, divided in our five socio-economic
classes, sharing the same house characteristics. The structure is similar to that of the
tables created using the POF: in each row we have an asset or something related to
the physical structure of the house; in each column we have a different class (see
Appendix II for examples).

31
See Annex II to find individual income brackets used with PNAD.

42

Regarding the PES dataset, after having created the same socio-economic
classes used in the previous analysis, we explore some points that give us important
additional information about members of every class. The methodology is the same
illustrated above.
Our aim at using PNAD is to integrate the POF analysis, therefore,
comparisons made will coincide case by case with those forming the backbone of the
previous study.

43

6. Budget shares analysis

6.a Introduction
Our aim is to analyse what changed and how during the 2002-2008 period.
We have adopted a methodology similar to that proposed by Ester Duflo and Abhijit
V. Banerjee in their “What is Middle Class about the Middle Classes around the
World?” (Duflo and Banerjee 2008) where they explore variations in household
expenditure following an ad hoc division per kind of expenditure: Food and Drink,
Domestic Infrastructure, Entertainment etc. They then analyse each of the categories
created and, when possible, provide explanations about why expenditures for certain
items increased or decreased. We decided not to strictly attain to their expenditures
subdivision and we opted for one that is following the POF’s structure taking some
category’s name from Duflo and Banerjee.
The analysis will be this structured as follows: we will first show how dedicated
shares of total budget evolve across time and across classes with related
commentaries; next, we pass to mean per-households expenditures creating and
examining consumption patterns.
6.a.1 Preliminary Considerations
What we have immediately noticed when we started our analysis is the
discrepancy in mean total income and mean total disbursement in both years and for
all the classes of households. Higher differentials are registered among poor and
extremely poor households and they reduce while we near the middle class.
Poor households declared income is often underestimated for two reasons:
first, as showed in Figure 3, poor and extremely poor households are mostly
employed in the informal sector that is commonly characterized by irregular
payments; second, correctly tracking down yearly financial records often requires

44

good mathematical skills that are rare challenged by both low educational level and
the complexity of the calculation due to intermittent jobs. More seemingly household
will multiply their last monthly income times twelve.
Figure 3: Fraction of the occupied population working in the informal sector in 2002 and 2008
Source: Author’s own calculation using PNAD
It could be also probable that the least two classes of households recurred to
borrowing money from relatives, friends or other informal lenders32
and that this
borrowing is not captured by any of the items present in the households’ sources of
income. Despite the variable we are using to calculate households’ total income is
including the balance of monthly financial transactions, informal borrowing would
most probably not enter this calculation due to its unofficial nature. For these two
reasons we thought the value of mean total disbursement as being more explanatory
of a household real financial effort.
In Table 10 we plotted mean per-household expenditure and mean augmented
income variations (in 2002 percent terms) among same classes in different years.
What we first notice is that the extremely poor in 2008, given augmented income of
57% at 2002 level, increased their total spending of just 18%. The others classes
show a markedly different behaviour augmenting their total spending at around 8%

32
In her work Sicrè noticed how among low-income individuals in the outskirt of São Paulo,
is really common borrowing from relatives and friends by asking them to use their credit
cards. (Sicrè 2009). See Chapter 2 and Chapter 7.b for a detailed explanation.
0

20

40

60

80

100

Extremely poor Poor Vulnerable Lower-Middle Middle
%ofinformalworkersoveremployed
Classes of housholds
2002
2008

45

points less their augmented income with the exception of the lower-middle class that
it is increasing 14% points less than its augmented total income.
Table 10: Increment in 2002 percentage terms of Mean Total Income and Mean Total Disbursement divided by
classes
Extremely poor Poor Vulnerable Lower-Middle Middle
Mean Total Income 57.06% 52.00% 49.43% 52.15% 51.01%
Mean Total Disbursement 18.37% 45.94% 37.34% 38.31% 44.29%
As stated above, poor households are more likely to be employed in the
informal sector than their richer counterparts and irregular payments coming from
those jobs not only impede a good calculation of monthly income, but also put them
in a condition of high uncertainty when forecasting future income. The consequence
is that in order to be able to deal with eventual adversities (namely a member of the
household got sick and need health assistance or a sudden shortage of food etc.),
they will probably save money until a buffer-stock level judged sufficient to cope with
diverse kinds of shocks. Given their initial condition of scarce financial assets, when
they are working toward accumulating their target level of buffer-stock savings, their
spending is depressed (Chatterjee 2009; Carrol 1997; Deaton 1991). Extremely poor
households total disbursement is not following the pace of increased income
because they are still far from their target level of savings required to start spending
more. Coherently, what we see is that the other classes behave as if they were
closer to their buffer-stock level, increasing total spending quasi at the pace of their
increased income.
6.b Evolution of budget shares
6.b.1 Food and Drink

46

The first chart (Figure 4) shows mean spending shares on food and drinks
calculated as in 𝑖 33. On the X-axis we put economic classes for the two years
analysed; on the Y-axis we plotted the selected aggregate item’s spending share in
percent.
Figure 4: Shares of total disbursement for Food and Drink
Source:Author’s own elaboration using POF 2002/2008

At first glance Food and Drink expenditures shows a decline through the
classes. As first suggested by Engel a decline in the share of income spent on food is
expected when financial disposability increases (Engel 1857). The Poor class takes
exception since in 2008 dedicates a slightly larger share of their disbursement to food
when compared with their extremely poorer counterparts. We also observe that in
2008, the mean fraction of total spending is reduced by 5 points on average for all
the economic classes considered. While Eating at Home follows a similar pattern,
Eating Out, which indicates food and drinks consumed out from home, registered a
markedly different trend, drastically diminishing for the extremely poor households in
2008 and consistently increasing in the remaining classes, with the poor and the
middle class showing the highest gradients (+30%).

33
As above anticipated, histograms charts originate from the following formula (i):

𝑆ℎ𝑎𝑟𝑒! =
𝐸𝑥𝑝!
𝐸𝑥𝑝!
!
∗ 100

0
10
20
30
40
Extremely
Poor
Poor Vulnerable Lower-Middle Middle
Shareoftotaldisbursementin%
Classes of households
2002
2008

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