Current Urban Studies
2013. Vol.1, No.4, 92-101
Published Online December 2013 in SciRes (
Open Access
Urban Amenities and the Development of Creative
Clusters: The Case of Brazil
Ana Flávia Machado, Rodrigo Ferreira Simões, Sibelle Cornélio Diniz
Centro de Desenvolvimento e Planejamento Regional, Universidade Federal de Minas Gerais,
Belo Horizonte, Brasil
Received May 28th, 2013; revised July 5th, 2013; accepted July 13th, 2013
Copyright © 2013 Ana Flávia Machado et al. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the origina l w o rk is properly cited.
This paper describes the creative potential of Brazilian territories, including aspects pointed as cities’
comparative advantages in terms of creativity: cultural facilities, labor market and public expenditures in
culture. The paper uses clustering analysis, applied to secondary data from the Brazilian Demographic
Census (IBGE), Survey of Basic Municipal Information (MUNIC/IBGE) and municipal expenditures in
culture from National Treasury (FINBRA). Among the six clusters which were created, three are well de-
fined and the others are quite mixed. Cluster 1 includes the two largest and most developed cities in Brazil,
São Paulo and Rio de Janeiro. Cluster 2 is composed of capitals of important states in Brazil and cities
where large universities are located. We named this cluster as creative university centers. Cluster 3 com-
prises 99 municipalities and can be named as centers of cultural and ecological tourism.
Keywords: Urban Amenities; Crative Clusters; Brasil
Amenities are an old theme in Economics, particularly in Ur-
ban Economics. Its definition has gotten new dimensions.
Technically, amenities are understood as the set of public and
private goods and services which generate positive externalities
for the resident and visiting population. Until the mid-twentieth
century, transportation infrastructure and water and sewage
treatment systems were the most important amenities in the
conformation of industrial cities. Nowadays, given the occur-
rence of several economic transformations, and especially the
process of globalization, the most valued amenities include cul-
tural and entertainment activities.
In this context, the presence of coffee shops and art galleries,
parks and cultural institutions, as well as buildings of architec-
tural importance, are all emphasized as fundamental urban
amenities in the conformation of the so-called creative cities.
The term creative cities comes from this concern, either be-
cause they may enhance local development by means of small-
scale production based on creativity, or because they may be-
come locus of recovery of “obsolete” spaces in large urban cen-
These cities are urban complexes which present various cul-
tural activities and high concentration of creative employment.
Creativity would perform a fundamental role in urban dyna-
mism, the sector’s contribution being measured by its share in
the level of production, in employment generation, besides in-
direct effects, such as expenditures by tourists visiting the city.
Creative cities are defined according to the presence of com-
parative advantages in terms of cultural production. These ad-
vantages can be a combination of two or more conditions, such
as: significant presence of a creative class; existence of cultural
facilities; tradition in popular celebrations; high average income
of the population; high average schooling of the population;
presence of universities; previously adopted policies to foster
cultural activities and an environment of high “social self-es-
teem”, and “open minds” to innovation and to different demo-
graphic groups.
Given these concepts, the goal of this paper is to describe the
creative potential of Brazilian territories, including aspects
pointed as cities’ comparative advantages in terms of creativity:
existence of cultural facilities, tradition in popular celebrations,
“open minds” to innovation and to different demographic
groups, average schooling of the population, labor market and
public expenditures in culture. The paper uses clustering analy-
sis, applied to secondary data from the Brazilian Demographic
Census (IBGE), in order to measure the size of the creative
labor force; Survey of Basic Municipal Information (MUNIC/
IBGE) for the supply of cultural facilities; and municipal ex-
penditures in culture from FINBRA, a report by the National
Treasury based on information about expenditures and revenues
of each Brazilian municipality.
The use of clustering analysis can be justified as like Lazzer-
etti (2012: 5): “Creative Economies are those external agglom-
eration economies that can be explained in terms of both diver-
sity and specialization… Clustering also affects creative indus-
tries (…) and it is important to understand the reasons behind it,
and to single out the appropriate methods for the identification
and mapping clusters”.
The paper is divided in five sections, including this brief in-
troduction. In the second section, the literature on amenities is
presented. Next, we present the methodology and the data
sources. In the fourth section, the clusters results are presented
and, lastly, the fifth section presents some considerations about
this study.
Amenities and the Formation of
Creative Clusters
This paper’s main goal is to identify which elements (ameni-
ties) might contribute to transform productive agglomerations
into creative clusters, and hence describe the amenities with the
potential of creating creative clusters in Brazil. In spite of the
fact that the idea of creative cities has taken hold of the public
policies agenda, academic research has paid it insufficient at-
Recently, there has been an increasing consideration of urban
amenities as a determinant of both residential (Smith et al.,
1988) and productive locational decisions (Gottlieb, 1994, 1995;
Granger & Blomquist, 1999), as well as of aspects associated
with urban and regional growth and development. Sivitanidou
& Sivitanides (1995) relate amenities to the intracity distribu-
tion of R&D activities; Malecki (1984), Markusen et al. (1986)
and Angel (1989) identify amenities as a key factor in the at-
traction of qualified migrants, particularly scientists; Herzog &
Schlottmann (1993) and Blomquist et al. (1988) take amenities
as determinants of quality of life and even of the scale of urban
centers; Knapp & Graves (1989) analyze the relation between
amenities, migration and regional development. Clark & Kahn
(1988), in turn, tried to define the social benefits of particularly
cultural urban amenities. Vandell & Lane (1989) aim to identify
the influence of design and architecture in the dynamism and
valorization of urban areas. Glaeser et al. (2001) relate higher
rates of urban growth with the presence of high amenities in
selected urban regions. Recently, Clark (2004) edited a book
with a suggestive title (“The city as an entertainment machine”),
in which several authors deal with the topic of entertainment
industry taken as the main contemporary urban amenity, and
also discuss the limits and possibilities of taking amenities as a
drive for development. McGranahan & Wojan (2007) associate
regional development to the presence of cultural density (crea-
tive class as in Florida, 2002) and natural amenities. Ahlfeldt &
Maennig (2010) found a strong relation between housing prices,
quality of life and proximity to cultural amenities, particularly
to historic heritage sites.
In Brazil, there are few studies which address the relation
between urban amenities and development. Macedo & Simões
(1989) related urban amenities to the conformation of intracity
spatial structures and their growth potential. Silveira Neto &
Azzoni (2004) relate regional development and regional ameni-
ties. Hermann & Haddad (2011) associate urban amenities to
real estate quality and valorization. Rocha & Magalhães (2011)
aim to evaluate urban amenities, particularly natural amenities,
and associate them to quality of life in an intercity approach.
Golgher (2008 and 2011) analyzes, without using the concept
of amenities, the relation between “vibrant cities” and the pres-
ence of a creative class in Brazilian municipalities, starting
from the construction of clusters.
Due to these large movements, the city is no longer just an
agglomeration where the individual looks for jobs, and it be-
came the space of consumption of goods and, mostly, of ser-
vices. Individuals decide to live in cities because this is where
they find their source of income, by means of regular employ-
ment. However, they try also to reconcile this demand with
quality of life. According to Clark et al. (2004: 297) “There is a
relative decline in the explanatory variables affecting the eco-
nomic base, like distance, transportation costs, local labor costs,
and proximity to natural resources and markets—since air
travel, fax, the Internet, and associated changes have drastically
facilitated contacts among physically distant persons, globally.
This shifts the mix of inputs for location of households and
firms, increasing the importance of more subtle distinctions in
taste, quality of life concerns, and related considerations”.
Clark (2004) stresses that public managers, entrepreneu rs and
community leaders now recognize culture, entertainment and
urban amenities as important factors for people to choose their
places for living and for tourism. Several large cities, such as
London, New York and Chicago, present these activities as
their main sources of revenues and of employment and income
On the other hand, the enhancement of cultural and creative
activities may promote the recognition of local values and tra-
ditions, favoring a cultural legitimation which encourages com-
munity identity, self-expression, respect to diversity and vitality,
by means of characteristics and cultural practices which define
the locality and its population (Cwi, 1980; Bille & Schulze,
As Bille and Schulze (2008) point out, art and culture can
play a prominent role in regional and urban development, and
even a wider role if we expand the definition of development.
Cultural development needs to be accompanied by a compre-
hensive strategy of regional and urban development, which will
use the complementarities among its different areas.
As highlighted in this article’s objectives, we hereby intend
to build a typology of Brazilian municipalities in terms of their
cultural attributes—which comprise goods, equipment, services,
qualified and specialized labor etc. This is justified by the fact
that there are few works, in Brazil, that try to quantify this this
ever more relevant sector, which increasingly assumes a lead-
ing role in the global urban scenario. There are, in Brazil, mas-
sive regional and urban inequalities. They are not restricted to
income or human development-related indicators, but also en-
compass, to a strong extent, the development of urban hierar-
chies, attributes and amenities. These disparities ground the
attempt to develop a taxonomy of the Brazilian municipalities
(5570), in order to better understand their specificities, by cre-
ating categories of urban nuclei homogeneous in regard to the
creative sector. To this purpose, we employed an exploratory
multivariate analysis that combines two complementary meth-
ods—namely, Cluster Analysis and Discriminant Analysis. The
former creates categories of urban centers that are homogene-
ous in terms of the cultural sector. However, as the great num-
ber of municipalities and their internal differences tends to
create unbalanced clusters—viz., some well-defined ones and
others with a certain amount of heterogeneity—, we also per-
formed a Discriminant Analysis. The latter allows us to assess
each individual’s (in our case, municipalities) belonging to, or
how well he fits in, each category defined in the Cluster Analy-
sis. Garcia & Simões (2012) were the authors to initially pro-
pose this combination of multivariate methods, in an assess-
ment of the Brazilian urban network and its hierarchies. Later,
Monteiro et al. (2013) also employed it to characterize the pos-
sible changes to the urban network of the oriental section of the
Open Access 93
Brazilian Amazon.
Cluster Analysis
The clustering methods may be characterized as any statisti-
cal procedure which, using a finite and multidimensional in-
formation set, classifies its elements in restricted, internally
homogeneous groups, allowing the generation of significant
aggregate structures and the development of analytical typolo-
The technique used for obtaining the clusters was the k-
means non-hierarchical method. In the k-means method, each
sample element is allocated with the cluster which centroid
(vector of sample means) is the closest to the vector of ob-
served values for the respective element. The partition process
is performed considering k initial centroids, with which each
sample element is compared. k = 5 and k = 6 were tested, and at
the end we decided for six groups or clusters.
By construction, the definition of the initial centroids is ran-
dom and, after that, the algorithm grouped the elements ac-
cording to their proximity to the centroids. New centroids are
defined taking into account the new clusters which are formed,
and the process is repeated until no relocation is needed, i.e. all
the sample elements are “well allocated”.
There are various dissimilarity measurements which can be
used in the generation of clusters. The basic rule is that it
should follow the specificities of the data set, the statistical
characteristics of the variables and the classification purposes,
and it can be based on one or multiple features of the munici-
palities. In our case the measurement used was the Euclidian
distance, i.e., a multidimensional geometric distance:
ij jf
Hence, the classification of municipalities into homogeneous
groups allows for the creation of taxonomies, typologies, re-
ducing the number of dimensions to be analyzed and allowing
for a more direct understanding of the inherent characteristics
of the information.
Discriminant Analysis1
Discriminant Analysis is a statistical technique to differenti-
ate groups. By using a rule of derivation/discrimination, it is
possible to optimally designate a new object into the pre-exist-
ing classes; in other words, once the analysis groups have been
established and the characteristics of an individual are known,
the probability of this individual belonging to the pre-deter-
mined groups can be estimated. The technique can be used to
examine differences between groups and/or classify new
The objective is to find one or more dimensions that maxi-
mize the distinction between mutually exclusive groups, esti-
mating one or more discriminant functions that make it possible
to classify the observations into groups. The discriminant func-
tions are linear functions that combine the variables used. In
addition, they are equivalent to a reduction in the study size,
related to the analysis of the main components and to the ca-
nonic correlation. They are formally represented by the follow-
ing expression:
011 22kmkmkmp pkm
uuX uXuX
  (2)
Here, fkm is equal to the score of the canonic discriminant
function for use in case m in group k; Xikm is equal to the value
of variable Xi for the case m in group k; and ui are coefficients
that produce the desired characteristics of the function.
The assumptions for application of this technique require that
the number of independent variables be less than the number of
observations, and the discriminating power increases as the
number of observations expands (provided that the number of
independent variables remains constant). The independent vari-
ables should have normal distribution in the populations of each
group. However, empirical evidence shows that the analysis
continues to be robust if there are small deviations in normality
in relatively large samples. In addition, the internal variability
of the groups should be similar; in other words, the variance
and covariance matrixes should be homogenous (to guarantee
this homogeneity, it is sufficient to identify and remove the
outliers from the analysis).
After defining the dependent variable and the explanatory
variables (whether discrete or continuous), the discriminant
functions should be estimated. The results of this estimation
provide a matrix with the averages of each group and the intra
and inter group sums, which should be used to compare the
differences between the coefficients estimated. The correlation
(or covariance) matrix is used to evaluate how much each in-
dependent variable can be discriminated among the groups. It
should be emphasized that it is essential to standardize these
coefficients to avoid problems of scale among the independent
variables, which could lead to interpretation errors.
In our case, an objective discriminant variable—the hard
cluster analysis categories, is used as a parameter for reclassifi-
cations, making feasible the identification of individuals (in this
case, municipalities) that are likely to be classified at higher or
lower levels in the hierarchy of creative cities. The underlying
idea is that municipalities belonging to a typological category
and that have elements that allow, through a pre-established
rule of belonging, for example, 50% or 75% of likelihood of
belonging above their hard/crisp category, reclassify them into
another typology are differentiated in terms of creative potential
from those that were well defined previously. Simultaneously,
the municipalities that have potential attributed that give them
characteristics of lower levels in the creative ranking can be the
object of policies to avoid the loss of incipient power to in-
crease dynamics provided by the creative sector.
Data Sources
This study uses various data sources. The most important one
is the 2010 Demographic Census, which informs the following
indicators for all of the 5595 municipalities in Brazil: loca-
tional quotient of workers in the creative sector; proportion of
resident adults who finished high school; proportion of house-
holds in which the residents declare a conjugal union with indi-
viduals of the same sex2; proportion of households with Internet
access; proportion of households with sewage systems; resident
population. These indicators are collected from the Sample of
the Census, done every ten years by the Brazilian Institute of
2Like Florida (2002), we built a proxy for the index of presence of homo-
sexuals among the resident population with an indication of social openness
that is, a lower presence of prejudice, insofar as this information results
from self-declaration.
1This part is based on Mingoti (2007) and Simões et al. ( 20 12).
Open Access
Geography and Statisti cs (IBGE).
Another data source used in the study is FINBRA, a report
by the National Treasury based on information about expendi-
tures and revenues of each Brazilian municipality. The collec-
tion of accounting data is based on the Law of Fiscal Responsi-
bility. This law guarantees the existence of wider databases in
order to control the application of the norms and rules. Munici-
palities send their information, including expenses by function,
by means of a particular system (called SISTN—System for
Collection of Consolidated Accounting Data), from Caixa Eco-
nômica Federal. These data ate then collected and consolidated
by the Secretary of National Treasury, Minister of Finance. The
frequency of data is annual. From Finbra, we got the informa-
tion about municipal expenditures in culture, in 2010, which
was then weighted by resident population.
The Culture Supplement of the 2006 Basic Municipal Infor-
mation Survey (MUNIC/IBGE) contains crucial information on
the cultural sector in order to investigate aspects related to mu-
nicipal management—local government agency responsible for
culture, its infrastructure, human resources for culture in the
municipality, management instruments used, legislation, exis-
tence and functioning of councils, existence and characteristics
of a Municipal Fund of Culture, financial resources, existence
of a Municipal Culture Foundation, actions, projects and activi-
ties accomplished, as well as information on media vehicles,
existence and quantity of cultural and artistic facilities and ac-
tivities in the municipality (IBGE, 2007).
Public security is an important factor in the organization of
creative spaces, not only due to its positive effect on tourism,
but also for the residents to be able to attend the events which,
most of the time, take place in the evenings. Therefore, we
included in the analysis the rate of homicides of males between
15 and 29 years of age (by 100,000 inhabitants). Also, an indi-
cator regarding public health was included: the ifdm health
index (FIRJAN Index of Municipal Development—Health,
which is a weighted average of three indicators: Prenatal Care,
Undefined Death and Infant Death by avoidable causes. These
indicators were extracted from the Datasus website, responsible
for collecting such information.
Lash & Urry (1994) show that the city is the locus of innova-
tion in the information economy. For them, post-industrial
production differs from industrial production due to intense
changes and to the flexibility in the design of products. Sym-
bolic content demands differentiation which, in turn, requires
constant processes of innovation. Thus, if we consider the in-
novation system as an important factor for the development of
creative activities in the cities, information on indexed scien-
tific articles should be included in the cluster analysis. The
variable “published articles in 2010” comes from a database on
indexed papers by International Science Index (ISI).
In order to define the proportion of creative workers, we used
the typology described in Chart 1.
This section presents a description on the treatment of data,
the procedures for estimation of the clusters and of discriminant
analysis, its results and the analysis of the results.
Data Treatment
The method of principal components3 was used for the con-
struction of a continuous index which represents the occurrence
Chart 1.
Direct and indirect occupati o ns related to the creative class.
A—Core or direct occupations
A1 Performing arts: choreographer, ballet dancer, actor, show dir ector,
dancer, clown, acrobat, com p os er, musician and singer
A2 Writers: writer and editor
A3 Craftsmen: ceramist, blower, weaver, craftsman who works with
clothes, shoes, and leather or animal sk i n artifacts
B—Indirect occupatio ns
B1 Performing arts: show producer and presenter
B2 Visual arts: designer, sculptor, painter, decorator, set de s igner,
photographer and cameraman
B3 Information: libra ri an, archivist, curator, and museum t e c h n i cian
B4 Media and communication: journalist, editor, radio and televisio n
technician, sound and image te chnician , sales and marketing
worker, translator, interpreter, philologist, speaker, commentator
and broadcaster
B5 Graphic arts—graphic arts tec h ni cian, supe rvisor and general
graphic arts worker.
B6 Others: musical instruments builde r and repaires, leisure equipment
repairer a n d show and media fiscal.
Source: Elaborated by authors using COD 2010.
of media and cultural manifestations in the localities. In order
to build the index, the municipal data from MUNIC 2006 were
used as binary variables (1 = yes; 0 = no). The variables were
weighted by the population of the municipalities in 2006. The
first component explained approximately 42% of total variance,
originating the index (index_manifest).
The weights contribute almost uniformly to explain the vari-
ability of the municipalities in regards to the index calculation,
as shown in Chart 2. Presence of film clubs, of literary associa-
tion, of visual arts groups, of local printed magazine, and of
AM radio station has a weight of approximately 0.2, whereas
community radio gets a smaller weight (0.06).
Chart 3 describes the continuous variables representing
amenities, which were used for the estimation of the clusters.
Cluster and Discriminant Analysis
For comparison with the clusters formed by the k-means
method, we built another index, also using the principal com-
ponents technique, aiming to describe cultural amenities. In
terms of such amenities, we considered the number of existing
cultural facilities (libraries, museums, cultural centers, stadiums,
gymnasiums, movie theaters), the manifestation index—both
from MUNIC 2006—, the size of the cultural labor market
(Census of 2010), and per capita expenditures in culture (FIN-
3PCA—Principal Component Analysis—is a non-
arametric method, which
aims at expl aining the st ructure of var iance-covari ance through l inear com-
binations of the original variables. Each component explains certain per-
centage of the system’s variance, in descending order, i.e., the first compo-
nent explains a greater percentage than the second one, which, in turn,
explains a greater percentage than the third and so on until the com
Zp, so that the sum of the variance percentages explained by all components
is 100%. Once there are p variables, the method can have p to p compo-
nents. However, when there is correlation among such variables, the num-
ber of components necessary to the explanation of the totality or the great-
est part of the v ariance c an be lo wer than p . That means that the great er the
correlation among the variables—whether positive or negative—the ten-
dency is to a smaller number of components necessary to conserve practi-
cally as much in format io n as the o rig inal p var iab les (Mingo ti , 20 05) . Thus ,
ACP enables a reduction of data and facilitates the interpretation of the
correlations among variables.
Open Access 95
Chart 2.
Variables and weights used in t h e construction of the f irst component.
Variable Weight
School, workshop, or r egular cou rse for formation
in typical culture activities—existence 0.1534
Contests—existence of at least one (Cinema, Dance,
Photography, Litera ture, Music, Theater, Video, Other) 0.1177
Festivals—existence of at least one (Cinema, Dance,
Gastronomy, Music, Theater, Folk traditional
manifestations, Video, O t her) 0.1298
Fair—existence of a least one (Arts and crafts, books,
fashion) 0.1511
Exhibitions—existence of at least one (Fine arts,
visual arts, handicraft, historic collection, photography) 0.1668
Theater company—existence 0.1923
Folk traditional manifestation—existenc e 0.1377
Film club—existence 0.2004
Dance company—existence 0.1670
Music group—existence 0.1689
Orchestra—existence 0.1828
Band—existence 0.1576
Chorus—existence 0.1704
Literary asso ciation—e xist ence 0.2240
Capoeira g ro up—existence 0.1546
Circus—existence 0.1868
Samba school—existence 0.1936
Carnival group—existence 0.1453
Drawing and painting group—existence 0.1818
Fine arts and visual arts group—existence 0.2102
Handicraf t group—existence 0.1684
Other groups—existenc e 0.0958
Local printed d iary—existence 0.1879
Local printed magazine—existe nce 0.2128
Local AM radio—e xistence 0.2014
Local FM radio—existence 0.1702
Community radio—e xi st ence 0.0674
Community TV—existence 0.1457
TV Channel—existence 0.1743
Internet provider 0.1399
Colleges and universities—existence 0.1672
Video store—existence 0.1683
Discs, CDs, tapes and DVDs store—existence 0.1708
Bookstores—existence 0.1909
Clubs and recreational associations—exist ence 0.1599
In this case, the first component explained 49% of total data
variance. The weights of the variables included in the first
component, which originated the index, are presented in Chart
4. It can be noticed that only expenditures in culture, the num-
ber of stadiums and gymnasiums and the Locational Quotient
of creative workers (Ql_creative) did not present weight equal
or above 0.4 in the index calculation.
Among the six clusters which were created, three are quite
clear, and the others are quite mixed. Cluster 1 is formed by the
cities of São Paulo and Rio de Janeiro, whereas Cluster 2 is
formed by Curitiba, Brasília, Salvador, Ribeirão Preto, For-
taleza, Porto Alegre, Goiânia, Florianópolis, Santa Maria, Mar-
ingá, Piracicaba, Recife, Belo Horizonte, Viçosa, Campinas,
Lavras, Botucatu, São Carlos.
Cluster 1 includes the two largest and most developed cities
in Brazil. For that reason, these cities host a large portion of
creative industry such as audiovisual and publishing. Therefore,
they are well served in terms of cultural facilities and they show
higher proportions of creative workers.
Source: authors’ elaboration.
According to Table 1, which shows average and standard
error of the variables used in the construction of the clusters, we
observe that São Paulo and Rio de Janeiro present 53% of the
population having completed high school; they have on average
4394 published articles and they are well above the average of
the other clusters in terms of number of libraries and museums
(22), stadiums and gymnasiums (20), movie theaters (16.5), and
concentrate most of the workers in the creative sector (higher
QL, equal to 2.71) and of the greater presence of declaration of
homosexual unions (0.29% of the households). In terms of
sewage systems coverage, an indicator which differentiates
basic urban infrastructure in Brazil, over 90% of the households
are covered—a percentage which is higher than the observed in
the other clusters. On the other hand, the rate of homicides
among the youth is high (5731), although it is lower than the
rate in cluster 2. Given this configuration, cluster 1 may be
termed large Bra zilian creative centers .
Cluster 2, in turn, is composed of capitals of important states
in Brazil—Curitiba, Brasília, Salvador, Fortaleza, Porto Alegre,
Goiânia, Florianópolis, Recife, Belo Horizonte—and cities like
Ribeirão Preto, Santa Maria, Maringá, Piracicaba, Viçosa,
Campinas, Lavras, Botucatu, São Carlos, where large universi-
ties are located. The indicators, although lower than the ones in
cluster 1, are the closest ones to those. However, the indicator
which refers to crime is much worse, since the homicide rate
among young males is the highest one among all the six clus-
ters, due to the presence of Belo Horizonte, Curitiba, Recife,
Salvador e Florianópolis. We will name this cluster as creative
university centers.
In cluster 3, which comprises 99 municipalities, it is notice-
able the high per capita expenditure in culture (R$326.30), even
higher than the one in cluster 1, of the large creative centers.
Paulínia is one of the municipalities in this cluster, and has the
highest per capita expenditure in culture in Brazil. The city
hosts important cultural events such as a Movie Festival4.
Guaramiranga, in Ceará, is another municipality in this cluster,
and also hosts important festivals (jazz and blues, puppet thea-
tre, gastronomy). Other cities such as Araçaí and Catas Altas, in
Minas Gerais, are well-known for their stimulus to cultural
tourism based on music groups and handicraft, in the first case,
nd on historical heritage, in the second case. Cipó/BA, Arroio a
4It is a concern that the local government is questioning the continuity o
the aforementioned Movie Festival.
Open Access
Open Access 97
Chart 3.
Codes and concepts of t h e variables used for t he de f i ni t ion of clusters.
Variable Description Database Source
High_school Adults who finished hig h s chool—25 and older (%) Brazilian Demographic Census (IBGE)—2010
Sewage_rate Permanent private households with toilet l inked
to general sew age system (%) Brazilian Demographic C ensus (IBGE)—2010
Hom_rate_15_29 Homicide r ate for males between 15 a nd 29 years
of age (per 100,000 inhabitants) (*) Datasus– Sistema Ùnico de Saúde—2009
Tx_internet Proportion of households with internet access Brazilian Demographic Census (IBGE)—2010
Ifdm_healt h FIRJAN Index of Municipal Development—he alth Datasus– Sistema Ùnico de Sa úd e—2009
Articles Scientific art icles publish ed in 2010 International Science Index (ISI)
Libraries Number of libraries in the municipali t y Basic Munic i p al Information Survey ( M U N I C/IBGE)—2006
Museums Number of museums in the munic i pality Basic Municipal Information Survey (MUNIC/IBGE )—2006
Cultural_centers Number of cultural centers in the mun i cipality Basic Municipal Information Survey (MUNIC/IBGE)—200 6
Stad_gymn Number of stadiums and gymnasiums i n t he municipality Basic Munici p al Information Survey (M U NI C/IBGE)—2006
Movie_theaters Number of movie theaters in the municipality Basic Munici p al Information Survey (M U NI C/IBGE)—2006
Index_manifest ACP Index—existence of cultura l manifestations
and medi a vehicles in the municipality Basic Municipal I nformation Survey (MUNIC/IBGE)—200 6
Pc_culture_expend Tot al expenditures in culture—per capita FINBRA—report by th e Brazilian National Treasury—2010
Ql_creative People occupied in the creative secto r in the municipality/People
occupied in the creative sector in the country divided by t hose
occupied in the municipality/occupied in Brazil Brazilian Demographic Census (IBGE)—20 1 0
Florida index (presence
of homosex uals) Proportion of househo lds whose members declared
a conjugal union with i ndividuals of the s a me sex Brazilian Demographic C ensus (IBGE)—2010
Population in 2010 Popula tion in the municipality in 2010 Brazilian Demographic Census (IBGE)—2010
Acp weighted cultur e Culture index built bas ed on an analysis of the main components Basic Municipal Information Survey (MUN IC/IBGE)—2006;
Brazilian Demographic Census (IBGE)—2010;
FINBRA—report by the Brazi li an National Treasury—2010
Source: authors’ elaboration. (*) This variable was standardized so that it ranges from 0 to 100.
Chart 4.
Variables and weights in the for mation of the 1st component.
Variable Weight
Libraries 0.4293
Museums 0.4698
Stad_gymnas 0.2003
Movie theaters 0.4638
Index_manifest 0.4734
Pc_culture_expend 0.0485
Ql_creative 0.3366
Source: authors’ elaboration.
do Sal/RS, Itambé do Mato Dentro/MG, Santo Antônio do
Grama/MG, São Gonçalo do Rio Abaixo/MG, São Sebastião/
SP, Taboleiro Grande/RN also form this cluster and present
activities strongly based on natural amenities. Finally, we have
some cities in southern Minas Gerais, specialized in the pro-
duction of thread crafts. Given these characteristics, we can
name this cluster as centers of cultural and ecological tourism.
It is worth noting that the weighted culture index confirmed
the formation of clusters, since it presented higher values in
both the large Brazilian creative centers and in the university
centers. However, if we consider the weighted culture index,
the locational coefficient of creative workers and the Florida
index, cluster 5 presents the best results among the diffuse
groupings; that is, clusters 4, 5 and 6. According to Figure 1,
despite the disperse spatial distribution, the 1529 municipali-
ties which form this cluster are located mostly in the South and
Southeast regions.
Seeking to identify distortions in the definition of munici-
palities in the clusters, especially with diffuse characteristics, in
terms of the amenities worked on here, discriminant analysis
was conducted. As described in the methodology, this tech-
nique makes it possible to measure the probability of munici-
palities, given the characteristics considered, to position them-
selves in other groupings. According to Figure 2, the vast ma-
jority of the municipalities are not affiliated to the modified
agglomerate. However, 256 municipalities (shown in green in
igure 2) have the possibility of climbing on the scale of ag- F
Table 1.
Results of cluster estimat i o n (intra-cluster averages/standard errors in parenthesis).
Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6
Number of observation s 2 18 99 860 1536 3050
High_school 53.5 51.8 24.0 20.7 28.0 19.5
(2.6) (6.0) (8.0) (7.7) (9,1) (6.9)
Sewage_rate 91.4 81.8 44.5 32.8 68.4 8.0
(0.7) (15.1) (31.7) (29.7) (17.6) (11.1)
Hom_rate_15_29 5731.0 14682.7 19.5 43.2 299.1 46.1
(4719.9) (25595.7) (66.7) (162.4) (1425.1) (201.4)
Ifdm_health 0.87 0,81 0,84 0,80 0.83 0.77
(0.03) (0,21) (0,80) (0,10) (0.08) (0.11)
Articles 4394.5 837,9 0,5 0.8 7.4 0.3
(1608.7) (428.7) (2.9) (7.6) (35.5) (2.6)
Libraries 22.5 14.1 1.8 2.3 3.3 2.1
(4.9) (8.6) (2.9) (3.9) (5,1) (3,6)
Museums 22.0 12.8 0.3 0.6 1,5 0.4
(1.4) (5.4) (1.0) (2.4) (3.8) (1.6)
Cultural centers 14.0 9.8 14.4 14.9 13.1 15.6
(4.2) (6.7) (7.9) (7.4) (8.2) (6.9)
Stadiums and gymnasiums 20.0 16.6 6.1 7.6 13.0 7.3
(21.2) (13.6) (8.3) (9.6) (10.9) (9.4)
Movie theaters 16.5 13.2 0.0 0.1 1.0 0.1
(3.5) (6.8) (0.1) (0.6) (3.1) (0.6)
Index_manifest 6.1 5.9 1.8 2.1 2.9 2.1
(0.2) (0.5) (1.0) (1.0) (1.4) (1.0)
Pc_culture_expend 45.60 31.30 326.30 108.60 28.09 18.90
(17.61) (21.44) (144.21) (36.10) (22.05) (19.23)
Ql_creative 2.71 2.17 0.84 1.08 1.20 0.87
(0.19) (0.46) (0.85) (1.84) (1.21) (1.23)
Florida index (presence of homosexuals)0.29 0.21 0.05 0.05 0.07 0.04
(0.08) (0.10) (0.12) (0.11) (0.13) (0.12)
Population in 2010 8786975 1093140 7670 14216 56068 17836
(3488198) (943799) (12557) (25636) (124177) (29259)
Weighted acp culture 0.56 0.44 0.12 0.12 0.16 0.10
(0.08) (0.05) (0.05) (0.08) (0.09) (0.06)
Source: authors’ elaboration.
glomerates, insofar as the probability of being located in higher
categories (clusters, in this case) exceeds half the probability of
remaining in the agglomerate of origin. None of these munici-
palities was classified in cluster 2, and obviously, in 1.
On the other hand, we see that for 212 municipalities, the
probability of being in lower categories is greater than half the
probability of remaining in the cluster of origin. These results
show that only 10% of the municipalities were not well defined
by the traditional cluster analysis.
Final Remarks
This paper aimed to evaluate the Brazilian municipalities fo-
using on their potential in terms of “cultural amenities”—some c
Open Access
0500 1.000
Clus ters
1 (2)
2 (18)
3 (99)
4 (860)
5 (1536)
6 (3049)
Figure 1.
Amenities clusters—Brasil.
Positive change (256)
No change (5096)
Negati ve change (212)
Figure 2.
Location of municipalities with the potential for agglom erates—B rasil .
Open Access 99
kind of “welfare amenities” capable of influencing choices to
live and work in a given locality. In general, the presence of
proper conditions for cultural and artistic activities gives dyna-
mism to the regions, since it may improve their image, and thus
these regions may become a destination for capital inflows and
for the attraction of new business ventures (Perloff, 1979;
Throsby, 2001). Furthermore, those activities allow for the in-
clusion of local populations and contribute to processes of self-
recognition, cohesion and respect to diversity (Cwi, 1980; Bille
& Schulze, 2008).
Notwithstanding the importance of cultural resources being
presented in the territories, the main reasons for cluster strategy
are based on the concept of “agglomeration economies”. In this
context, such economies can be translated into cost reductions
and/or quality improvements, given the spatial concentration of
productive resources. Creative industries are affected by ag-
glomeration economies.
The centrality of the cultural sector might stimulate “related
variety” (Frenken et al., 2007; Lazzeretti, 2013)—i.e., the (ef-
fective and potential) exchange of competencies, innovations
and the transfer of knowledge between manufacturing sectors
and economic activities. This contributes towards a greater
capacity of absorbing innovations from the surroundings, which
Lazzeretti (2013) called “cross-fertilization”.
Considering, therefore, the relationship between large en-
dowments of creative resources, which identifies creative
places (such as creative industries, the creative class, a creative
atmosphere), and the presence of a network of economic, non-
economic and institutional actors, the results indicate that, in
terms of amenities, there is still a lot to be accomplished in
order to achieve reasonable conditions for good quality of life
in the municipalities, particularly for the ones in the North and
Northeast regions of Brazil. Such conditions may be seen as
bases for development of creative cities or regions, given the
close relation between those conditions and the presence of
transportation and leisure infrastructure, of skilled labor, and of
environmental quality, among others.
Despite dealing with aggregate analysis and using secondary
data, the cluster analysis shows that cultural and natural ameni-
ties, as well as technological development, contribute to the
formation of creative regions. In terms of public policies, the
orientation of the actions should consider the specificities of
these areas, some of which have been pointed out. In the case of
the large creative centers, where the creative industry in Brazil
is concentrated, issues of accessibility of the population should
be stressed, such as transportation infrastructure, public security,
prices of tickets. Regarding the creative university centers, the
cities may benefit from the interaction between universities and
cultural centers, so that the production in the sector can incor-
porate technological innovations which would increase the
value added of the cultural products, in addition to the recogni-
tion and validation of the local traditions. Finally, in terms of
the centers of cultural and ecological tourism, actions aiming at
the preservation of spaces and sustainability of the events
should be prioritized, as well as mechanisms of advertising the
places and the events in the national and international tourism
The authors acknowledge funding from PDE-ANPEC/
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