LAUSANNE UNIVERSITY
ECONOMETRICS AND POLITICAL ECONOMY DEPARTMENT
MASTER OF SCIENCE IN ECONOMICS
Modern culture and some factors that influence its demand
PAOLA A. RODRIGUEZ P.
LAUSANNE, JULY 2003 (revised final version)
Modern culture and some factors that influence its demand Paola Rodríguez
2
ABSTRACT This paper develops an empirical approximation for the demand for "modern" culture of two samples of nineteen and thirty-two countries, respectively, based on the construction of a cultural index for each of them, using the principal components method and seven / eight indicators of culture according to the sample. At the same time, a third sample of twenty-two countries is employed to test the impact of a relative price, available for just one of the indicators. After having obtained the cultural index, the model determines some of the factors that influence the demand for culture among the countries, being the most determinant: income, the educational level of the population and the language spoken in each of them; while the relative price does not seem to be quite significant.
Modern culture and some factors that influence its demand Paola Rodríguez
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MODERN CULTURE AND SOME FACTORS THAT INFLUENCE ITS DEMAND
1. Introduction Discussing about culture has never been an easy task due to the subjectivity that it
involves; first, because of the unlimited number of aspects of human life that are
possible to be considered as cultural, and then because of the characteristics that each
one has. What is certain is that it comprises some of the most basic forms of human
expression and that at the same time it is an important commodity in economic terms.
This paper examines some determinants of the demand of what will be defined as
modern culture. The first part gives an introduction to the culture definition and the
cultural market; the second part explains the indicators considered and the principal
components method applied for the construction of a “modern cultural index”, as well
as the variables and data used; the third and fourth parts develop the estimation of the
model as well as its results; the fifth part gives some additional remarks about the
model and finally some conclusions are drawn.
1.1 Definition of Culture
Culture can include many aspects of the social, political, intellectual, religious and
artistic life of people, but even more, their history and their heritage. There are two
world-wide definitions of culture given by the Concise Oxford Dictionary (1990):
« The customs, civilization and achievements of a particular time or people » and
« The arts and other manifestations of human intellectual achievement regarded
collectively». As these, it is possible to find thousands of other concepts, depending
on the point of view of the person that gives them.
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Due to the difficulties that working with such an intangible subject involves, and
because -unlike most commodities which are readily definable in terms of a single
physical good or a specific identifiable service, cultural output and trade take many
forms-, the UNESCO established the concept of “cultural industries” for making more
“measurable” the idea of culture. These industries include the producction protected
by copyrights of publishing, printing, multimedia, music, video, cinema and crafts;
and for some countries it includes also architecture, visual arts, sports, musical
instruments, advertising and turism.
Even with this definition, it is hard to set up the proper parameters for measuring
these aspects. For example, in the case of the sports: how many people practice a
sport?, what is the average-time a person practices a sport?, how many sports are
practiced?, etc.
1.2 Why is culture important? Considering culture as the way that people live together, interact and co-operate,
together with how they justify such interactions through a system of beliefs, values
and norms, people’s culture is important not only because it enables them to live
together, but also because it enables them to live together well, as it comprises the
most basic forms of human expression, helping to conserve the world diversity and
the patrimony of the countries.
Besides, culture is quite important also in economic terms because: it comprises a
significant item in consumers’leisure, it provides a livelihood for countless workers
and employees and it is a key component in the globalised media and communications
industries.
In the first case, culture is usually identified with leisure activity and not with work.
The productive members of society have to generate enough of a surplus to support a
strata of artists, musicians, novelists, poets and other creative people whose works and
performances they can enjoy in their “free” time, where these activities are highly
demanded.
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But culture is not usually thought of as a desirable characteristic of work itself, but it
should be, as it is the economic support for millions of people all over the world. For
example, in the United States only the subsector of cultural activities developed by
non-profit organizations employs almost the same number of people as the building
sector and more than the mining, legal services, police or forestry sectors. In the same
way, in the United Kingdom the contribution of the cultural industries to employment
is higher than the ones from the automobile and food industries, and is the same as
those of the chemical and synthetic textiles industries.1
Finally, in today’s rapidly changing world, driven relentlessly by the so-called
information revolution, people run the risk of becoming marginalized if they are not
literate and do not have access to modern means of communication. The concept of
communication enriched to include authentic cultural communication- real dialogue
among people of differing ethnic, religious and linguistic backgrounds, upholds and
strengthen cultural diversity, for not letting the standard media standardize cultural
values, beliefs and lifestyles. In this case, culture helps communication to enhance the
quality of human life and expand human capabilities.
1.3 The market of cultural goods
In the last fifty years the general trend of the world economy has been to open
markets. The world exports have grown from 8% to 27% as a component of the world
GDP between 1950 and 1998 and the total trade in 1997 was fourteen times bigger
that the one in 1950.2 This expansion of the international trade has developed
parallelly to multiple bilateral trade agreements established for eliminating the tariff
and no tariff barriers to the circulation of goods, services and investments.
In addition, on the other hand, the end of the Uruguay Round of the GATT in 1994,
started a new age of globalized economy, characterized by the apparition and
formation of business blocks - from the European Union to other less strong as the
1 STOLOVICH, Luis, La Cultura da Trabajo: Entre la creación y el negocio: economía y cultura en el Uruguay, Montevideo, 1997, pg.289. 2 UNESCO, Culture, Trade and Globalisation, Questions and Answers, 2000.
Modern culture and some factors that influence its demand Paola Rodríguez
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ASEAN3, NAFTA4 or MERCOSUR5. And, more recently, the evolution of
telecommunications and new technologies has reduced drastically the cost of
providing trade services, while INTERNET has transformed the nature of products
and services.
In this way, the market integration has allowed to the consumers to buy goods from
everywhere of the world in their local markets. While the local firms have to compete
with these foreign products, they also have new opportunities for developing their
markets of export, selling in all the other countries.
Inside this new pattern of production, consumption and trade, the cultural goods and
services have not been an exception. The cultural markets have been in constant
growth determining that the trade of cultural goods were multiplied by five between
1980 and 1998.6 As the UNESCO published in its Study of International Flows of
Cultural Goods between 1980-1998, in 1996 for example, cultural products as films,
recorded music, TV programs, books, journals and software were the greatest export
industry of the United States, exceeding for the first time other traditional industries
such as: automobiles, agriculture, aerospace or defense.
These facts are key elements for understanding the market of cultural goods and
services, especially now when it is evident that the world is living an economic and
cultural "boom".
3 Asociation of South East Asian Nations 4 North American Free Trade Agreement 5 Mercado Común del Cono Sur 6 UNESCO, Culture, Trade and Globalisation, Questions and Answers, 2000.
Modern culture and some factors that influence its demand Paola Rodríguez
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World Trade of Cultural Goods 1980-1998
(millions US Dollars)
SOURCE: Study on International Flows of Cultural Goods between 1980-1998, UNESCO.
This fast expansion of international cultural trade has responded to rising demand for
cultural goods and services. For example, in 1990, American consumers spent USD 5
billion on admissions to theater, opera, galeries and other non profit arts events (more
than on admissions to spectator sports), USD 4.1 billion on movie admissions, and
USD 17.6 billion on books. Because of difficulties in defining boundaries around the
arts industry, statistics on its contribution to GDP are problematical, but available data
suggest that the arts (theater, music, opera, dance, visual arts, crafts, literature,
community and folk arts) account for a little under 1% of the United States GDP and a
little over 1% of the civilian labor force. If we define “cultural industries” as
including the arts, motion pictures, radio and television, and printing and publishing,
an aggregate value of output can be measured for 1988 of about USD 130 billion or
2.5% of GDP (National Endowment for the Arts 1992). Moreover, in 1995 French
households spent on average 3.5 % of their budget on cultural products.
Changing consumption patterns in industrial and developing countries, more leisure
time and spare income, together with cheaper products, have helped generate this new
demand and, at the same time, they are the building blocks of the emerging
information society.
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While the consumption of cultural goods and services has expanded in the world, the
production has tended to concentrate in a few countries, generating an oligopolical
market with an asymmetric structure.
The effects of this type of markets are ambiguous: while everybody is conscious that a
high proportion of the cultural products circulating in the countries are produced out
of them, there is a little knowledge of the impact of this cultural global market on the
citizens, the business or the governments.
In this sense, it is important to consider the follow factors:
� Culture is on the vanguard. Since the late eighties, it can be appreciated a
growing interest in culture, due to the combination of different phenomena as
the globalization and the processes of regional integration, and the people
claiming their right to express; all this in a context were cultural industries are
quickly replacing the traditional forms of creation and distribution and
changing cultural practices.
� The combination of "culture and trade" has acquired a particular strategic
meaning. The cultural goods and services communicate and build cultural
values, produce and reproduce the cultural identity and contribute to the
society integration, at the same time that constitute a key production factor in
the new economy of knowledge, what makes the negotiations in the cultural
field quite controversial and hard. As it is affirmed by many experts, there is
no other industry that have generated greater debate en the political,
economical and institutional limits in the processes of regional and global
integration or in their legitimation, than the industries related with culture.
� Governments have understood that the international trade laws are constantly
exerting pressure in their capacity to influence the production and distribution
of the cultural goods and services. This has generated a growing polarization
Modern culture and some factors that influence its demand Paola Rodríguez
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of the positions in the trade business when talking directly or indirectly about
cultural affairs.
� As it is established by the UNPD7 in its Human Development Report of 1999,
two thirds of the humanity are not benefited with the new model of economic
growth based on the expansion of international trade and on the development
of new technologies, and are excluded from the global information. This
situation reveals the distances that exist in terms of capacity and of resources
among the countries for producing and consuming cultural goods and services.
In many small and developing countries, these capacities are being reduced
quickly. As a consequence, the trade flows of cultural goods are not balanced,
too much concentrated in a few countries, and the cultural industries show
great disparities in their structures.
2. Methodology
2.1 The Indicators The cultural indicators used in this work to compose the modern cultural index that
will be the dependent variable of the model, do not pretend to measure the world
culture -the culture of the world is far more complex and multi-faceted. What these
indicators pretend, is to present those aspects of the world that are readily measurable.
With this purpose and due to data limitation, eight indicators were taken into account:
three related to communication and five related to arts. That is why this is called
“modern” culture index, because it considers as cultural components some media
indicators and not just art indicators.
This inclusion is based on the idea that to be able to live together well, people need to
communicate and understand one another’s culture. In this way, communication
7 United Nations Program for Development
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should be recognized as the basis of culture and so of cultural interchange, because it
facilitates the functioning of any multi-ethnic, multi-cultural society.
The indicators of communications that were considered are:
� INTERNET Users
� Number of Radios
� Number of Televisions In the case of the art indicators, traditionally considered as cultural expressions, there are:
� Cultural Paper Consumed
� Annual Cinema Attendances
� Music Unit Sales Retail Value
� Annual Museum Attendances
� Annual Attendance of Performing Arts Companies where the last one is given just for a sample of nineteen countries. These indicators were considered to build the cultural index, using the Principal
Components Method.
2.2 The Principal Components Analysis
The analysis of principal components is a technique used basically to summarize
several related series in one and consists in extracting from them one or some
common elements that explain a certain percentage of the variance matrix of the
group of series involved (a greater explanation is given in the appendix).
So long as all the constituent partial indicators are retained, a composite index may
serve the useful function of promoting discussion and debate about the relative
importance of the different dimensions involved in such an index. However, it is
sometimes objected that full aggregation does not make sense since very disparate
things, such as the consumption of music, films, etc. are being combined; or because
Modern culture and some factors that influence its demand Paola Rodríguez
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there may be a low correlation among the indicators constituing it, and indicators may
move in opposite directions as we try to compare countries. But these objections
would be valid if the primary purpose were to determine why the individual indicators
are moving in different directions; but this is not the case, as the principal aim of the
paper is to rank countries on the basis of their demand with respect to cultural aspects,
and so the risk of a lack of correlation among individual indicators is not particulary
problematic. Anyway, correlations in this case are not low as it can be seen in Table
1:
TABLE 1: CORRELATIONS AMONG THE COMPONENTS OF THE
CULTURAL INDEX
PAPER MUSIC CINEMA MUSEUMS INTERNET RADIO TV
PAPER 1 MUSIC 0.84524 1
CINEMA 0.53293 0.64129 1 MUSEUMS 0.53844 0.72036 0.38380 1 INTERNET 0.84481 0.85093 0.64764 0.70461 1
RADIO 0.79701 0.77694 0.67212 0.53291 0.77530 1 TV 0.68692 0.69300 0.51833 0.53611 0.68506 0.84190 1
Where it can be seen that all the cultural-index-components are very correlated.
2.3 The Explanatory Variables Again, due to the data limitation, just nine variables were used for explaining the
independent variable. Among these, five social and economic indicators were
considered:
� Real GDP per capita measured in PPP8
� Life expectancy at birth
� Adult literacy rate
� Combined first-second-third level gross enrolment ratio
� Urban population9
8 Purchasing Power Parity: the rate of currency conversion that corrects for the differences in price levels between countries. 9 In order to see the cultural index per country and its components for both samples see annex 2.
Modern culture and some factors that influence its demand Paola Rodríguez
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Other variables that were introduced in the model were four linguistic dummies
explaining the origin of the language spoken by the majority of people in each
country, as follows:
� D1, Germanic origins
� D2, Latin origins
� D3, Slav origins
� D4, all others10
In selecting indicators to explain cultural demand, emphasis should be placed on
people’s abilities and on people’s historical cultural consumption, because culture is
considered as being a kind of “addictive” merchandise, in the sense that an increase in
an individual’s present consumption of it will increase her future consumption. Such a
view can in fact be traced back to Alfred Marshall, who recognized that the taste for
“good music” was an acquired taste that would increase over time with exposure
(among others, through education).11
In this respect, basic adult literacy and the combined first-second-third level gross
enrolment ratio were considered because they reflect an outcome, not an input; and
they reflect a human capability, not the means of capability.
Besides, life expectancy, urban population and the GDP per capita were considered as
proxis of demographic and geographical distribution, and of people’s income,
respectively. Finally the dummies where chosen to include the linguistic
especifications of each country.
10 In order to see the explanation of each dummy see annex 3. 11 In Chapter III of Book III of his Principles, Marshall wrote: “It is therefore no exception to the Law (of diminishing marginal utility) that the more good music a man hears, the stronger is his taste for it likely to become” (Marshall 1891, p.151)
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2.4 Data Because of the lack of availability of the statistics, the data correspond to the period
1990 - 1996 and it was mainly obtained from the databases of the UNESCO, the
World Intellectual Properties Organization (WIPO) and the World Bank.
3. Estimating the model
For estimating the cultural index, the purpose was to collect data of eight indicators
for thirty-two countries, but because of data availability of the national statistics, it
was possible to find only seven indicators for all the countries and the eight indicators
just for nineteen countries.12
The cultural index was computed using the method of the principal components,
considering each of the indicators for the two samples, and it was important to find
that the first component explained in a 76% the variation of the original series, which
shows that this index is a very good condensation of its components.
Once calculated the cultural index, the model of depart was:
Cultural Index = � + �1 ln(real GDP pc) + �2 ln(life expectancy at birth) + �3
ln(adult literacy rate) + �4 ln(combined first-second-third gross enrolment ratio)
+ �5 ln(% of urban population) + �6 D1 + �7 D2 + �8 D3 + ��
The hypothesis were that the explanatory variables had a positive relation with the
cultural index.
12 In order to see the complete list of countries and indicators see annex 1.
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4. Results
From the cultural index obtained for each country in both samples, it could be seen
that the group of countries with higher cultural index was also the one with higher
human development index that includes, among others, indicators of income,
education and health.13
RELATION BETWEEN THE CULTURAL AND THE HUMAN DEVELOPMENT INDEX
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
2,5
3
NwyAsl
Jpn
SwzGer Aus Bel Ita RC
Spa Svk Mys Pol
Mex
Rom Tky
Cultural Index Human Development Index (1994)
SOURCE: UNPD and the Author.
As it is possible to see in the graph above, both series follow the same tendency, showing the great relation that exists among cultural and human development indexes. It is also interesting to notice that ten of the twelve countries with higher cultural index are countries whose languages come from Germanic roots, as can be seen on Table2:
13 In order to see the complete ranking of the sample see annex 4.
Modern culture and some factors that influence its demand Paola Rodríguez
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TABLE 2
CULTURAL
INDEX
HUMAN DEVELOPMENT
INDEX LINGUISTIC DUMMY 1
Norway 1.42945 0.943 1 Denmark 1.41033 0.927 1
Australia 1.38380 0.931 1
Canada 1.27531 0.960 1
Japan 1.24568 0.940 0
Sweden 1.22745 0.936 1
Switzerland 1.04903 0.930 1 Finland 1.01805 0.940 0
Germany 0.89540 0.924 1
Netherlands 0.81323 0.940 1
Austria 0.67733 0.932 1
New Zealand 0.61871 0.937 1
This fact is found again when we analyse the results of the run regressions.
When we have the sample of nineteen countries, GDP, life expectancy, adult literacy,
first-second-third level gross enrolment ratio, the percentage of urban population and
dummy 1, corresponding to the languages with Germanic origin, are the variables that
are significant in explaining the cultural index; as can be seen in equations 1 and 2
from Table 3.
Considering these equations, it results very interesting to see the negative relation of
the cultural index and the life expectancy and urban population indicators, given by
the negative signs of their betas.
In the first case this result is quite difficult to explain because it would mean
something like, for example, lower quality of health deals to higher demand for
culture; but in the other case, the result is comprehensible because it can be
interpreted as people that live in rural areas demand more of this modern culture
because of its level of media components, due to their need for communication given
by the less facilities that they usually have for living in non-urban areas. �
Modern culture and some factors that influence its demand Paola Rodríguez
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In the other hand, in equations 3 and 4 of Table 4, it can be seen that when the sample
is increased to 32 countries, GDP and dummies 1 and 2 are the only highly significant
variables.
This phenomenon could be explained because a larger number of countries adds more
heterogeneity to the sample and furthermore, the cultural index for this sample is
different from the one of the other simple as it excludes the art performing indicator,
that has more-educated consumers.
So, it is important to notice that no matter the sample, GDP and dummy 1, are always
significant to explain the cultural index, while dummy 3 is never important.
These facts appear again when working just with west-european countries where the
main explanatory variables are the GDP and the dummy of the latin origin. On the
other hand, when considering just the east-european countries, educational indicators
and life-expectancy at birth are also variables explaining the cultural index demand
(see annex 5 for these results).
So, these results show again that, for determining the cultural demand of a country,
what is mainly important is its income, and if the language spoken in the country has
Germanic or Latin roots; while education counts for the least developed countries.
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Modern culture and some factors that influence its demand Paola Rodríguez
19
The above results are not surprising if we consider:
� The demand for cultural goods is influenced by the income because the highest
the income, the highest the possibility to access to other sorts of merchandises. In
this case, given the way the cultural index was constructed including
communication and arts indicators, and due to the fact that a number of these
means of communication are luxury items, their users must be primarily those
individuals with moderately high income and the countries that concentrate the
majority of these industries. The richer the country, the more cultural goods it
usually produces and consumes. Not only did rich countries have more data, but
they “score” higher in the area of producing and consuming cultural goods
through market mechanisms; so the higher the GNP per head of a country, the
more prevalent such items are likely to be, and not as in poor countries where the
cultural goods are luxurious goods and consumers have to choose between
consuming them or satisfying other more prioritary needs.
An important example is the case of performing arts, that can be seen as luxury
items, associated with social status and the desires of the wealthy for conspicuous
consumption, where the phenomenon of “first nights”, at which attendees are
more interested in looking at each other than at what is on the stage, is common in
many countries.
� Considering the assumption that the more educated people are, the fuller and
richer their communication, the demand for cultural goods can be influenced by
the level of education of the people because the more people know, the more they
demand knowledge and try to enjoy the cultural environment around them.
� Finally, Germanic or Latin roots of the language spoken in the country can explain
its demand for culture because it is in English, Spanish, German or French in
which the majority of the cultural goods and services are offered and traded. In
addition, these languages are some of the more spoken in the world (not only as
mother tongue but as second-tongue) so it depends on the linguistic abilities of
their people, the diverse-origin cultural goods and services that they can afford.
Modern culture and some factors that influence its demand Paola Rodríguez
20
The assumption is that as people learn one another’s languages, they would be
better able to communicate and more inclined to respect one another’s culture.
5. Some Remarks
One explanatory variable that should have been important to introduce in the model,
is the relative price for each cultural component. The problem was that these specific
data were not generated or collected by any international institution, so it is difficult
to find countries statistics about.14 This is particularly explained by the fact that it is
hard to establish just one price that averages or represents hundreds of different types
of books, disks in all their sizes or how to measure the consumption of one hour of
radio or TV.
So, it was possible just to have an approximation of the price of a cinema ticket in a
sample of twenty-two countries for which the data were available, and this variable
was introduced in the model to see if it was significant or not in explaining the
cultural index.
Considering the results of equations 5, 6 and 7 of Table 5, price for cinema seems to
be not highly significant.15 This conclusion is similar to the one found by David
Throsby in his article “The role of music in international trade and economic
development”, published in The World Culture Report 2000, where he makes an
analysis of the per capita demand for music in 1994, for a sample of 35 countries.
Among his results, he concludes that although price differentials between countries do
appear to exert some influence on demand, it is primarily per capita incomes that
explain relative purchases, and that it is consumer incomes that principaly determines
the amounts spent on music recordings.16
14 For many of the cultural dimensions, human development data are sparse or simply do not exist.
One reason is that these dimensions have not been considered important. 15 In order to see the results of the model with and without the price of the cinema tickets see annex 6. 16 For having additional information about this model, check Chapter 12 of the World Cultural Report, UNESCO 2000.
Modern culture and some factors that influence its demand Paola Rodríguez
21
So, as when considering this sample the variable price seems to be not quite
explicative of the cultural index, it can be thought that this will not greatly change
when considering the samples of nineteen or thirty-two countries, and so their indexes
can be explained as before.
It is important to notice that in running the regression with this sample of twenty-two
countries, the origin of the languages spoken and the level of education are still key
factors for explaining the cultural index.
These results can be seen in Table 5, were equation 7 shows that a 1% change in the
adult literacy level, generates a positive 10% change in the demand for culture; while
a 1% change in the ticket price leads to an equal but negative change in the cultural
demand.
Mod
ern
cult
ure
and
som
e fa
ctor
s th
at in
flue
nce
its
dem
and
Pao
la R
odrí
guez
22
TA
BL
E 5
5 6
7 D
epen
den
t V
aria
ble
L
CIN
EM
A
��
stan
dar
d
erro
r t
p-v
alu
e ��
stan
dar
d
erro
r t
p-v
alu
e ��
stan
dar
d
erro
r t
p-v
alu
e
Co
nst
ant
-75,
9209
6 24
,210
34
-31,
3589
0 0.
0086
-7
2,29
473
18,9
1416
-3
,822
25
0.00
15
-46,
8128
20
7,40
2788
-6
,323
674
0.00
00
L
TP
-1
,365
256
0.89
1393
-1
,531
598
0.15
15
-1,5
2454
6 0.
4985
14
-3,0
5818
0.
0075
-1
,138
762
0.43
3119
-2
,629
215
0.01
70
L
GD
P
-0.8
8429
9 0.
6243
15
-1,4
1643
2 0.
1821
-0
.655
843
0.55
1831
-1
,188
49
0.25
20
L
LE
7,
3251
11
5,71
3126
1,
2821
55
0.22
40
6,22
0586
4,
6915
29
1,32
5919
0.
2035
LA
L
12,9
0651
6,
1322
12
2,10
4708
0.
0571
11
,928
13
44,2
0783
2,
6981
95
0.01
58
10,7
2861
0 1,
6510
61
6,49
8014
0.
0000
LF
ST
-0
.727
089
1,29
2315
-0
.562
625
0.58
40
L
UP
-0
.162
989
0.71
3633
-0
.228
393
0.82
32
D
1 0.
3595
28
0.35
4155
1,
0151
70
0.33
01
D
2 0.
2183
18
0.33
0113
0.
6613
43
0.52
09
D
3 -1
,371
626
1,17
2089
-1
,170
240
0.26
46
-1,4
4616
5 0.
6850
18
-2,1
1113
3 0.
0508
-1
,207
897
0.36
6740
-3
,293
601
0.00
40
Adj
uste
d R
² 0.
6257
21
0.
6710
16
0.
6650
49
S
.E. o
f reg
ress
ion
0.36
6084
0.34
3218
0.34
6317
Dur
bin-
Wat
son
stat
istic
1,
9992
84
1,
7318
46
1,
9369
11
A
kaik
e In
fo C
riter
ion
1,13
1048
0.92
6101
0.88
0042
Sch
war
z C
riter
ion
1,62
6976
1,22
3658
1,07
8413
F-s
tatis
tic
4,90
0876
9,56
6579
14,8
9857
0
Red
unda
nt V
aria
ble
Tes
t for
TP
F
-sta
tistic
2,
3457
92
9,
3524
50
6,
9127
70
p-
valu
e 0.
1515
50
0.
0075
09
0.
0170
20
*
The
"L"
in fr
ont o
f the
nam
es o
f the
var
iabl
es m
eans
that
it is
the
loga
rithm
of t
he v
aria
ble.
Modern culture and some factors that influence its demand Paola Rodríguez
23
6. Conclusions In the process of global human development, culture plays a key role, as a language of
communication, as a mean of storage and transmission of cultural diversity, as a
vehicle for political and social comment and dissent, and as a source of economic
empowerment.
The challenge of this paper was how to consider the multicultural aspects of all
countries and try to determine the demand for them. For this purpose, the chosen
indicators had to reflect an important an measurable part of world culture. The aim
was to broaden the scope of the indicators so as to bring in cultural features that
existed in all countries, could be provided by all countries and could be presented in
indicator tables.
While trying to do this, it was evident the lack of basic cultural indicators because it
does not exist a rich, world-wide, comparable database for the majority of countries
and if it exist, it is not comparable or from recent years. This situation is particularly
worst in the poorest countries.
Due to this data limitation communication indicators where included and the concept
of cultural demand was changed for a “modern cultural demand”.
This demand function was expected to contain, among others, own price, price of
substitutes, consumer income, and other explanatory variables, but again it was
impossible due to data availability, and it was necessary to restrict these variables to
some other existing indictators.
When running the regressions and examining the most significant determinants of
demand, the results indicate that this demand depends mostly on income and
education levels as well as on the world importance of the most-spoken languge in the
country. Life expectancy, urban population and even the proxi for the relative price of
cinema (one of the cultural components) were not found to be statistically significant.
Modern culture and some factors that influence its demand Paola Rodríguez
24
Empirical studies of demand for cultural aspects undertaken over a number of years
have been broadly consistent with the above observations. At the outset, several early
studies identified for example, performing arts audiences as being of significantly
higher educational, occupational and income status than the community at large (W.
Baumol and Bowen 1966; Ford Foundation 1974).
Although most (but not all) studies have identified a significant positive coeficient on
consumer income in estimated demand equations, the corresponding elasticity
estimates have varied above and below 1. Because live arts consumption is time-
intensive, gains in attendances over the long run due to increasing incomes are likely
to be offset to some extent by the increasing price of leisure. Glenn Withers (1980)
confirmed this proposition using data covering all U.S. performing arts for the period
1929-1973, and he found a “pure” income elasticity of around unity, composed of a
“full“ income effect (imputing leisure time as part of income) of 2.7, offset by a
leisure price effect of about –1.6.
Considering the relative price, even if it was not possible to introduce it in the model,
the approximation obtained with the cinema indicator in this paper and some
empirical experience by Throsby -already specified-, show that they do not seem to be
quite significant for determining the consumers demand for culture. Particularly,
Throsby (1983) in another research, identified several quality characteristics of some
cultural performances, including standard of script, acting, and production, and found
consumer demand to be strongly responsive to variations in the expected quality of
these characteristics and not responsive to the ticket price.
Finally, there might be possible to find other factors that explain better the behaviour
of the consumers' demand. As Leo Goldstone writes in his paper "Measuring culture:
prospects and limits", there are thousands of factors that can help to determine the
cultural demand among which we can find the taxes on cultural goods and services,
the leisure-time use, the cultural tolerance and freedom, etc. so we may hope that in
the future this data could be available and new research could be developed.
Modern culture and some factors that influence its demand Paola Rodríguez
25
References
� CHATFIELD, C. and COLLINS, A.J., Introduction to Multivariate Analysis, Science Paperbacks, Cambridge Press, UK, 1980
� Culture, Trade and Globalization, UNESCO 2000
� Goldstone, Leo, Measuring culture: prospects and limits, World Cultural Report 1999, UNESCO 1999
� Human Development Report 1997, UNPD 1997
� Human Development Report 1999, UNPD 1999
� Johnson, J. and Lenartowicz, T. Culture, Freedom and Economic Growth: Do Cultural Values Explain Economic Growth? Journal of World Business 33(4)/1998
� McKinley, Terry, Measuring the contribution of culture to human well-being, UNESCO 1999.
� Rodríguez, P, Análisis de la Industria Editorial Ecuatoriana y su Potencial Productivo, Ecuador, 2001.
� Statistical Yearbook 1999, UNESCO Publishing and Bernan Press
� Stolovich, Luis, La Cultura da Trabajo: Entre la creación y el negocio: economía y cultura en el Uruguay, Montevideo, 1997
� Study on International Flows of Cultural Goods between 1980-1998, UNESCO 2000
� Throsby, David, Economics and Culture, Cambridge Press, UK, 2001
� Throsby, David, The Production and Consumption of the Arts: A View of Cultural Economics, Journal of Economic Literature, Vol. XXXII, March 1994
Modern culture and some factors that influence its demand Paola Rodríguez
26
� Throsby, David, The role of music in international trade and economic development, World Cultural Report 1999, UNESCO 1999
� World Cultural Report 1999, UNESCO 1999
� World Cultural Report 2000, UNESCO 2000
Databases from:
� United Nations Development Program
� UNESCO
� United Nations Organization
� World Bank
� World Intellectual Properties Organization
Modern culture and some factors that influence its demand Paola Rodríguez
27
APPENDIX
The Principal Components Method
This is a technique used to examine the relationships among a set of p correlated variables, transformed to a new set of uncorrelated variables called principal components. These new variables are linear combinations of the original variables and are derived in decreasing order of importance so that, for example, the first principal component accounts for as much as possible of the variation in the original data.17 The transformation is in fact, an orthogonal rotation in p-space. As the usual objective of the analysis is to see if the first few components account for most of the variation in the original data, this means that if some of the original variables are highly correlated, they are effectively saying the same thing and there may be near-linear constraints on the variables. It this case, it is hoped that the first few components will be intuitively meaningful and will help to understand the data better, and will be useful in subsequent analysis where it is possible to operate with a smaller number of variables. The main stages for calculating the principal components are:
� To decide if it is worth or not to include all the variables recorded in the original data matrix, and if any of the variables need to be transformed.
� To calculate the correlation (or covariance) matrix, bearing in mind that a correlation coefficient should generally not be calculated for a pair of variables whose relationship is obviously non-linear.
� To look at the correlation matrix and observe any natural groupings of variables with "high" correlations. However, if nearly all the correlations are "small", then there is probably not much point in carrying out the principal components method.
� To calculate the eigenvalues and eigenvectors of the correlation (or covariance) matrix.
� To examine the eigenvalues and to try to decide how many are "large". This should indicate the effective dimensionality of the data.
� To look at the groupings of the variables suggested by the components and consider whether the components have some meaningful interpretation.
� To use the component scores in subsequent analyses as a way of reducing the dimensionality of the problem.
17 As in the case of this work, where the first principal component explains almost the 80% of the variation of the original data.
Modern culture and some factors that influence its demand Paola Rodríguez
28
The derivation of the principal components: Suppose X T = [X1,...Xp] is a p-dimensional random variable with mean µ and
covariance matrix �. The problem is to find a new set of variables, say Y1, Y2,...Yp, which are uncorrelated and whose variances decrease from first to last. Each Yj is taken to be a linear combination of the X’s, so that:
Yj = a1jX1 + a2jX2 + ,... + apjXp (1)
= a Tj X
where a Tj = [a1j,...,apj] is a vector of constants. Equation (1) contains an arbitrary scale
factor. We therefore impose the condition that a Tj aj = �
�
p
k 1
a 2kj = 1. We shall see that
this particular normalization procedure ensures that the overall transformation is orthogonal, this means, that the distances in p-space are preserved.
The first principal component, Y1, is found by choosing a1 so that Y1 has the largest
possible variance. In other words, we choose a1 so as to maximize the variance of
a Tj X subject to the constraint that a T
1 a1 = 1. This approach originally suggested by
Harold Hotelling, gives equivalent results to that of Karl Pearson, which finds the line in p-space such that the total sum of squared perpendicular distances from the points to the line is minimized.
The second principal component is found by choosing a2 so that Y2 has the largest
possible variance for all combinations of the form of equation (1) which are uncorrelated with Y1. Similarly, we derive Y3,... Yp, so as to be uncorrelated and to have decreasing variance.
We begin by finding the first component. We want to choose a1 so as to maximize the
variance of Y1 subject to the normalization constraint that a T1 a1 = 1. Now,
Var (Y1) = Var (a T1 X) (2)
= a T1 � a1
that can be taken as the objective function. The standard procedure for maximizing a function of several variables subject to one or more constraints is the method of Lagrange multipliers. With just one constraint,
Modern culture and some factors that influence its demand Paola Rodríguez
29
this method uses the fact that the stationary points of a differentiable function of p variables, say f(x1,...,xp), subject to a constraint g(x1,...,xp) = c, are such that there
exists a number , called the Lagrange multiplier, such that
dx
df - �
dx
dg = 0� � � i = 1,...,p (3)
� � � ����������� at the stationary points. These p equations, together with the constraint, are sufficient to determine the co-ordinates of the stationary points (and the corresponding values of
, which, however, are usually of little interest). Further investigation is needed to see
if a stationary point is a maximum, minimum or a saddle point. It is helpful to form a new function, L (x), such that
L (x) = f(x) - �[g(x) - c]
where the term in the square brackets is of course zero. Then the set of equations in (3) may be written simply as
xd
dL = 0
Applying this method to the problem, we write
L (a1) = a T1 � a1 - (a T
1 a1 - 1)
Then, considering that the function has a quadratic form xT � x, where ��is a (p x p) symmetric matrix, we have
1da
dL= 2 � a1 - 2 a1
Setting this equal to 0, we have
(��� ���a1 = 0 (4)
Note the insertion of the unit matrix I into equation (4) so that the term in brackets is of the correct order, namely (p x p). We now come to the crucial step in the argument.
Modern culture and some factors that influence its demand Paola Rodríguez
30
If equation (4) is to have a solution for a1, other than the null vector, then (��� ���
must be a singular matrix. Thus must be chosen so that
��� �� ����
�
Thus a non-zero solution for equation (4) exists if and only if is an eigenvalue of �.
But ��will generally have p eigenvalues, which must all be nonnegative as � is positive semidefinite. Let us denote the eigenvalues by 1, 2,..., p, and assume for the moment that they are distinct, so that 1 > 2 > ... > p > 0. Now,
Var (a T1 X) = a T
1 � a1
= a T1 � a1 using eq. (4)
= �
�
As we want to maximize this variance, we choose to be the largest eigenvalue,
namely 1. Then, using equation (4), the principal component, a1, which we are
looking for must be the eigenvector of � corresponding to the largest eigenvalue.
The second principal component, namely Y2 = a T2 X, is obtained by an extension of
the above argument. In addition to the scaling constraint that a T2 a2 = 1, we now have
a second constraint that Y2 should be uncorrelated with Y1. Now,
Cov (Y2, Y1) = Cov (a T2 X, a T
1 X)
= E [a T2 (X - µ) (X - µ) T a1]
= a T2 ��a1 (5)
We require this to be zero. But since � a1 = 1 a1, an equivalent simpler condition is
that a T2 a1 = 0. In other words, a1 and a2 should be orthogonal.
In order to maximize the variance of Y2, namely a T2 ��a2, subject to the two
constraints, we need to introduce two Lagrange multipliers, which we will denote by
and , and consider the function
L (a2) = a T2 ��a2 - (a T
2 a2 - 1) - �a T2 a1
Modern culture and some factors that influence its demand Paola Rodríguez
31
As the stationary point(s) we must have
2da
dL= 2 (��� ���a2 - a1 = 0 (6)
If we premultiply this equation by a T1 , we obtain
2 a T1 ��a2 - �= 0
since a T1 a2 = 0. But from equation (5), we also require a T
1 ��a2 to be zero, so that �is
zero at the stationary point(s). Thus equation (6) becomes,
(��� ���a2 = 0
With a little thought, we see that this time we choose to be the second largest
eigenvalue of ��and a2 to be the corresponding eigen vector.
Continuing this argument, the jth principal component turns out to be the eigenvector associated with the jth largest eigenvalue. There is no difficulty in extending the above argument to the case where some of the
eigenvalues of ��are equal. In this case there is no unique way of choosing the
corresponding eigenvectors, but as long as the eigenvectors associated with multiple roots are chosen to be orthogonal, then the argument carries through. Let us denote the (p x p) matrix of eigenvectors by A, where
A = [a1,...,ap]
and the (p x 1) vector of principal components by Y. Then Y = A T X (7)
The (p x p) covariance matrix of Y will be denoted by and is clearly given by
Modern culture and some factors that influence its demand Paola Rodríguez
32
=
�
�
�
�
�
�
p ...
0 ... 2
0 ... 0 1
...
�
��
00
0
(8)�
Note that the matrix is diagonal as the components have been chosen to be uncorrelated.
Using the fact that E (A T X) = A T µ and Var (A T X) = A T �A we can also express
Var (Y) in the form AT�A, so that
= A T �A (9)
gives the important relation between the covariance matrix of X and the corresponding principal components. Note that equation (9) can be rewritten as
������ A T (10)
since A is an orthogonal matrix with � A T = I. We have already noted that the eigenvalues can be interpreted as the respective variances of the different components. Now the sum of these variances is given by
��
p
i 1
Var (Yi) = ��
p
i 1
i ��trace ( ��
But
trace ( ��= trace (A T �A)
� � � � ����= trace (��A T )
� � � � ����= trace (���
� � � � ��������
p
i 1
Var (Xi)
Modern culture and some factors that influence its demand Paola Rodríguez
33
Thus we have the important result that the sums of the variances of the original variables and of their principal components are the same. It is therefore convenient to make statements such as "the ith principal component accounts for a proportion
i / ��
p
j 1
j of the total variation in the original data", though it should be emphasized
that this is not an analysis of variance in the usual sense of the expression. We will
also say that the first m components account for a proportion ��
m
j 1
j / ��
p
j 1
j of the
total variation.
�
Modern culture and some factors that influence its demand Paola Rodríguez
34
INDICATORSThe 8 indicators (7 + 1)
1 Cultural Paper Consumed kilos per person 1994
2 Annual Cinema Attendances per person 1990 - 1995
3 Music Unit Sales Retail Value USD / per capita 1996
4 Annual Museum Attendances per 100 people 1988 - 1994
5 INTERNET users per 10,000 inhabitants 2000
6 Radios per thousand people 1995
7 Televisions per thousand people 1995
8 Annual Attendance of Performing Arts Companies per thousand people 1980 - 1985
COUNTRIESWith 8 indicators, 19 countries
1 Egypt
2 Turkey
3 Chile
4 Mexico
5 Canada
6 Belgium
7 Denmark
8 Finland
9 Germany
10 Greece
11 Hungary
12 Italy
13 Netherlands
14 Norway
15 Poland
16 Portugal
17 Romania
18 Sweden
19 Switzerland
With 7 indicators, 32 countries (19 + 13)
20 Zimbabwe
21 Japan
22 Australia
23 Malaysia
24 New Zealand
25 Costa Rica
26 Austria
27 Czech Republic
28 France
29 Latvia
30 Russia
31 Slovakia
32 Spain
ANNEX 1
Mod
ern
cult
ure
and
som
e fa
ctor
s th
at in
flue
nce
its
dem
and
Pao
la R
odrí
guez
35
Cu
ltu
ral P
aper
A
nn
ual
Cin
ema
Mu
sic
Un
it S
ales
A
nn
ual
Mu
seu
m
INT
ER
NE
T U
sers
Rad
ios
Tele
visi
on
sA
rts
Co
mp
anie
sC
ult
ura
l In
dex
Cu
ltu
ral I
nd
ex(k
ilos
per
per
son
)(p
er p
erso
n)
(US
D /
per
cap
ita)
(per
100
p.)
(per
10.
000
p.)
(per
100
0 p
.)(p
er 1
000
p.)
(per
100
0 p
.)(7
ind
icat
ors
)(8
ind
icat
ors
)19
9419
90 -
199
519
9619
88 -
199
420
0019
9519
9519
80 -
198
5E
gypt
50.
30.
47
70.8
931
211
016
-1.2
5832
9-3
.520
637
Tur
key
60.
32.
611
304.
4116
418
944
-1.2
7715
3-3
.368
625
Chi
le16
0.6
6.3
516
57.6
534
821
579
-0.7
7501
3-2
.462
888
Mex
ico
110.
74.
411
274.
3126
321
925
-1.1
3155
5-2
.944
702
Can
ada
962.
837
.494
4130
.07
1053
714
385
1.27
5310
3.06
0784
Bel
gium
105
1.9
4424
2289
.41
790
454
144
0.61
3626
0.86
6647
5D
enm
ark
751.
758
.821
536
58.5
210
3457
454
71.
4103
283.
0279
24F
inla
nd16
61.
128
.872
3722
.95
1008
519
545
1.01
8050
2.04
0544
Ger
man
y10
31.
539
.211
529
17.6
944
554
503
0.89
5400
1.92
2643
Gre
ece
341
12.3
2393
9.41
430
220
205
-0.6
8822
1-1
.911
77H
unga
ry18
1.4
7.4
7214
51.4
164
343
366
4-0
.347
892
-0.4
0167
66Ita
ly63
1.6
1170
2303
.75
822
446
229
0.11
6459
0.17
3884
6N
ethe
rland
s93
142
.714
924
39.4
793
749
723
50.
8132
311.
3552
46N
orw
ay98
2.7
6119
149
05.2
480
843
328
11.
4294
523.
0624
65P
olan
d12
0.4
2.9
4172
2.3
454
311
609
-0.8
3255
8-1
.896
265
Por
tuga
l33
0.8
1651
2494
.11
245
326
61-0
.462
449
-1.5
1678
5R
oman
ia4
0.7
0.6
2935
8.31
211
220
649
-1.2
2091
6-2
.485
686
Sw
eden
941.
745
.721
245
58.2
988
247
845
31.
2274
542.
6613
26S
witz
erla
nd12
22.
256
.712
629
62.2
285
141
951
81.
0490
292.
3375
69Z
imba
bwe
2.1
0.2
0.3
137
.08
8929
-1.5
2737
8Ja
pan
106
1.1
53.3
5937
09.4
591
668
41.
2456
79A
ustr
alia
873.
944
.710
234
45.2
213
0449
51.
3837
97M
alay
sia
272
513
1590
.03
432
164
-0.7
0105
2N
ew Z
eala
nd54
3.9
34.5
921
66.6
599
751
40.
6187
07C
osta
Ric
a11
0.5
2.5
2262
1.43
263
143
-1.1
3402
7A
ustr
ia72
1.5
51.3
228
2557
.54
620
497
0.67
7333
Cze
ch R
ep.
180.
99.
188
976.
1863
848
2-0
.388
866
Fra
nce
792.
239
.824
1443
.32
895
589
0.52
9112
Latv
ia17
0.4
5.1
5061
8.81
678
477
-0.5
0891
1R
ussi
a5
0.9
1.5
5421
0.98
340
377
-1.0
1109
4S
lova
kia
131.
12.
553
1202
.59
570
476
-0.5
3358
8S
pain
512.
414
.973
1327
.04
314
404
-0.5
0396
4
SO
UR
CE
: UN
ES
CO
, WIP
O
AN
NE
X 2
CU
LT
UR
AL
IND
EX
AN
D IT
S C
OM
PO
NE
NT
S F
OR
EA
CH
SA
MP
LE
Modern culture and some factors that influence its demand Paola Rodríguez
36
GDP Real Gross Domestic Product per capita
LE Life expectancy at birth
AL Adult literacy rate
FST
UB Urban population
D1 GERMANIC DANISHDUTCHENGLISHGERMANNORWEGIANSWEDISH
D2 LATIN FRENCHITALIANPORTUGUESEROMANIANSPANISH
D3 SLAV CZECHHUNGARIANPOLISHRUSSIANSLOVAK
D4 ALL THE OTHERS
Source: INTERNET and the Author.
ANNEX 3
THE EXPLANATORY VARIABLES
Combined first-second-third level gross enrolment ratio
Mod
ern
cult
ure
and
som
e fa
ctor
s th
at in
flue
nce
its
dem
and
Pao
la R
odrí
guez
37
lingu
istic
dum
mie
s
Rea
l GD
P p
er c
apita
(P
PP
$) 1
994
Life
Exp
ecta
ncy
at
birt
h (y
ears
) 19
94A
dult
Lite
racy
Rat
e (%
)
199
4
Com
bine
d 1s
t, 2n
d an
d 3r
d Le
vel G
ross
E
nrol
men
t Rat
io (
%)
1994
Urb
an
Pop
ulat
ion
(%)
19
96
CU
LTU
RA
L IN
DE
X
HU
MA
N
DE
VE
LOP
ME
NT
IN
DE
X
19
941
23
4N
orw
ay21
346
77.5
9992
74.0
61.
4294
520.
943
10
00
Den
mar
k21
341
75.2
9989
85.1
41.
4103
280.
927
10
00
Aus
tral
ia19
285
78.1
9979
84.7
1.38
3797
0.93
11
00
0C
anad
a21
459
7999
100
76.7
81.
2753
10.
961
00
0Ja
pan
2158
179
.899
7878
.24
1.24
5679
0.94
00
01
Sw
eden
1854
078
.399
8283
.14
1.22
7454
0.93
61
00
0S
witz
erla
nd24
967
78.1
9976
67.7
1.04
9029
0.93
10
00
Fin
land
1741
776
.399
9764
.98
1.01
805
0.94
00
01
Ger
man
y19
675
76.3
9981
86.7
0.89
540.
924
10
00
Net
herla
nds
1923
877
.399
9189
.08
0.81
3230
60.
941
00
0A
ustr
ia20
667
76.6
9987
64.3
80.
6773
329
0.93
21
00
0N
ew Z
eala
nd16
851
76.4
9994
85.4
0.61
8706
50.
937
10
00
Bel
gium
2098
576
.899
8697
.06
0.61
3626
10.
932
01
00
Fra
nce
2051
078
.799
8974
.88
0.52
9111
70.
946
01
00
Italy
1936
377
.898
.173
66.6
80.
1164
590.
921
01
00
Hun
gary
6437
68.8
9967
63.2
-0.3
4789
170.
857
00
10
Cze
ch R
epub
lic92
0172
.299
7074
.54
-0.3
8886
570.
882
00
10
Por
tuga
l12
326
74.6
89.6
8158
-0.4
6244
90.
890
10
0S
pain
1432
477
.697
.190
76.7
2-0
.503
9641
0.93
40
10
0La
tvia
3332
67.9
9967
69-0
.508
9112
0.71
10
01
0S
lova
kia
6389
70.8
9972
57.0
8-0
.533
5884
0.87
30
01
0G
reec
e11
265
77.8
96.7
8259
.38
-0.6
8822
10.
923
00
01
Mal
aysi
a88
6571
.283
6254
.44
-0.7
0105
230.
832
00
01
Chi
le91
2975
.195
7284
.66
-0.7
7501
310.
891
01
00
Pol
and
5002
71.2
9979
64.0
8-0
.832
5578
0.83
40
01
0R
ussi
a48
2865
.798
.778
76.2
6-1
.011
094
0.79
20
01
0M
exic
o73
8472
89.2
6673
.6-1
.131
555
0.85
30
10
0C
osta
Ric
a59
1976
.694
.768
47-1
.134
027
0.88
90
10
0R
oman
ia40
3769
.596
.962
55.1
6-1
.220
916
0.74
80
10
0E
gypt
3846
64.3
50.5
6944
.56
-1.2
5832
90.
614
00
01
Tur
key
5193
68.2
81.6
6370
.42
-1.2
7715
30.
772
00
01
Zim
babw
e21
9649
84.7
6832
.5-1
.527
378
0.51
31
00
0
SO
UR
CE
: UN
ES
CO
, UN
DP
, WB
AN
NE
X 4
RA
NK
ING
OF
TH
E C
OU
NT
RIE
S B
Y T
HE
IR C
UL
TU
RA
L IN
DE
X
Mod
ern
cult
ure
and
som
e fa
ctor
s th
at in
flue
nce
its
dem
and
Pao
la R
odrí
guez
38
Dep
end
ent
Var
CU
LT
UR
AL
IND
EX
�
stan
dar
d
erro
rt
p-v
alu
e�
stan
dar
d
erro
rt
p-v
alu
e�
stan
dar
d
erro
rt
p-v
alu
e�
stan
dar
d
erro
rt
p-v
alu
e
Co
nst
ant
0.07
6264
26.2
3685
0.00
2907
0.99
78-1
5.38
596
4.80
7577
-0.3
2003
60.
0084
-28.
7270
02.
6421
34-9
.035
387
0.07
02-2
5.31
169
1.44
2552
-17.
5465
0.00
04
LG
DP
2.50
8279
0.95
5325
2.62
5576
0.03
931.
6600
310.
4843
473.
4273
580.
0056
0.13
3318
0.06
3184
2.11
0010
0.28
180.
1122
850.
0505
442.
2215
50.
1129
LL
E3.
3177
967.
3866
900.
4491
590.
6691
2.28
5244
0.71
8793
3.17
9280
0.19
402.
8507
810.
4123
876.
9128
80.
0062
LA
L-1
0.13
926
9.19
2303
-1.1
0301
70.
3123
5.72
2058
0.61
7931
9.26
0027
0.06
855.
3676
970.
2017
5826
.604
60.
0001
LF
ST
0.69
5514
1.15
8502
0.60
0356
0.57
02-3
.087
223
0.21
8352
-14.
1387
70.
0450
-3.0
4305
90.
1630
98-1
8.65
780.
0003
LU
P1.
3148
750.
9439
081.
3930
120.
2130
-0.1
4412
70.
1639
72-0
.878
976
0.54
09
D1
-0.5
8496
40.
4973
02-1
.176
274
0.28
40
D2
-1.2
9361
10.
5853
73-2
.209
891
0.06
92-0
.737
634
0.17
4049
-4.2
3807
30.
0014
-1.0
2184
90.
1010
40-1
0.11
329
0.06
27-0
.949
641
0.04
4766
-21.
2134
0.00
02
D3
-0.0
5705
30.
0863
60-0
.660
638
0.62
83
Adj
uste
d R
²0.
7906
160.
8110
740.
9899
730.
9927
16
S.E
. of r
egre
ssio
n0.
2863
920.
2720
420.
0349
600.
0297
97
Dur
bin-
Wat
son
stat
.2.
7413
281.
7981
310.
8000
001.
4297
27
Aka
ike
Info
Crit
erio
n0.
6326
510.
4216
91-4
.288
685
-3.9
5407
7
Sch
war
z C
riter
ion
0.99
7826
0.55
8631
-4.1
1337
4-3
.822
594
F-s
tatis
tic8.
0124
3028
.904
9211
3.83
7021
9.05
42
* T
he "
L" in
fron
t of t
he n
ames
of t
he v
aria
bles
mea
ns th
at it
is th
e lo
garit
hm o
f the
var
iabl
e.
SA
MP
LE
OF
TH
E W
ES
TE
RN
EU
RO
PE
AN
CO
UN
TR
IES
SA
MP
LE
OF
TH
E E
AS
TE
RN
EU
RO
PE
AN
CO
UN
TR
IES
AN
NE
X 5
Mod
ern
cult
ure
and
som
e fa
ctor
s th
at in
flue
nce
its
dem
and
Pao
la R
odrí
guez
39
CI
GD
PL
EA
LF
ST
UP
D1
D2
D3
CI
1
GD
P0.
9072
7798
6869
1
LE
0.72
4796
2659
870.
8447
6280
4223
1
AL
0.57
9342
5742
480.
5179
2568
683
0.71
9999
2126
841
FS
T0.
7719
8014
9607
0.72
3142
2457
990.
6914
0004
4889
0.41
3369
6557
611
UP
0.52
9893
6867
440.
5895
8563
9962
0.54
7649
4479
610.
5194
8746
1853
0.41
4794
8484
361
D1
0.80
7691
6062
970.
7331
3600
8236
0.53
2605
1791
870.
3365
9312
8242
0.54
9312
5911
050.
5012
3253
2205
1
D2
-0.4
0252
4580
948
-0.1
8760
3518
674
0.01
3056
1539
017
0.03
4339
7059
857
-0.3
7245
3416
660.
0428
1474
3076
4-0
.518
8745
2166
31
D3
-0.1
6739
3356
64-0
.409
4832
1192
6-0
.369
1389
5282
20.
1511
6017
4814
-0.1
9842
9726
21-0
.218
6918
4759
3-0
.261
9684
1599
8-0
.233
0206
9121
41
CI
GD
PL
EA
LF
ST
UP
D1
D2
D3
CI
1
GD
P0.
9228
8072
4864
1
LE
0.67
0964
0655
60.
7517
6092
0179
1
AL
0.49
6875
7965
690.
4432
9165
0067
0.50
7321
6269
761
FS
T0.
7219
8515
9738
0.72
4571
7965
30.
5539
0808
2361
0.41
2870
7650
911
UP
0.62
9726
7635
910.
6104
0514
6828
0.59
9145
6915
40.
5069
9415
1414
0.50
7946
2199
291
D1
0.62
9658
1551
020.
5566
6221
1432
0.12
0462
5787
440.
2153
2547
9155
0.47
1830
8859
130.
2807
7320
2642
1
D2
-0.2
8530
5522
315
-0.0
4848
5340
6201
0.21
0184
3137
990.
0320
9353
6544
3-0
.123
8928
1089
20.
0247
1696
9802
-0.4
5273
4960
103
1
D3
-0.3
0001
2426
066
-0.4
9632
3972
653
-0.3
2611
5191
613
0.20
8862
6788
18-0
.283
5455
5449
-0.0
9111
0426
3355
-0.3
4767
6747
683
-0.3
0050
1253
482
1
AN
NE
X 6
CO
RR
EL
AT
ION
S M
AT
RIX
OF
TH
E S
AM
PL
E O
F 1
9 C
OU
NT
RIE
S
CO
RR
EL
AT
ION
S M
AT
RIX
OF
TH
E S
AM
PL
E O
F 3
2 C
OU
NT
RIE
S