“ICT in Colombia”

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By María Juliana Tobón
Master of Latin American Studies Candidate, 2013
Center for Latin American Studies - University of Florida
November 2011
ABSTRACT
The area of information and communications techno-
logy has occupied a privileged position in development
strategies in order to combat poverty and to empower
people.Knowledgeandaccesstoinformationareconcei-
ved critical for these purposes; and telecommunications
arepresentedasthebestplatformtoconnectpeopleand
to encourage interchanges of information. However, the
access to the platform seems to be unequal along the
world, the “Digital Divide” prevents the purposes outli-
ned.
In that sense, this study examines the main factors that
determine access to the Information and Communi-
cations Technology in Colombia. The study applies re-
gression techniques to Colombia Lapop data 2010 as a
means to Information and Communications Technology
by income and race; conceived, for the purposes of this
paper, the primarily determinants to access. The main
findings pointed out that income is by far the single most
important factor limiting the digitalization of Colom-
bian population.
Key words:
InformationandCommunicationsTechnology,Colombia, access,
inequalities,digitaldivide,income,Afro-Colombians.

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INTRODUCTION
Since the arrival of the new millennium, the Informa-
tion Technologies and Communications – ICT – has
become a development priority across the world. In
diverse scenarios, non-governmental agencies and
governments from developed countries have shown
that the approach to ICT increases access to informa-
tion and basic services. The International actors also
contend that the ICT encourages the development
of markets, thereby enabling an economic empower-
ment. In particular, “Information and content avai-
lability over the Internet is seen as critical to enable
greater inclusion, empowerment and human develo-
pment” (World Bank Group, 2011: 12). Therefore the
expansion of ICT in developing countries is viewed
as a way to address the social inequalities that prevail
among their citizens.
Colombia is no exception. Government efforts have
been translated into policies as the Agenda for Con-
nectivity in 2000, the National ICT Plan in 2008 and
the recent “Plan Vive Digital” (2011); as well as social
programs like “Compartel”, “Computadores para Edu-
car”,“Gobierno en línea ”, among others. Despite these
initiatives, access to ICT occurs only in certain popula-
tions in Colombia, based on place of residence, loca-
tion (urban or rural areas), income and race.
The purpose of this paper is to assess the relationship
between the access to ICT with the facts of living in ur-
ban areas in opposition to rural places, reside in cities
or regions different than Bogota, household income
and being Afro-Colombian. These tests initiate from
two essential statements based on the inequalities
observed over the years in Colombia. The first hypo-
thesis is that People in urban cities, predominantly in
Bogota, the higher the income the greater the access
to ICT. And, the second, net of the effect of sex, age,
place of residence, location and income level, Afro-
Colombians will be less likely to access ICT.
The next section presents a discussion about the role
of ICT to enhance economic growth and to reduce po-
verty and its implication in Colombia.The next section
describes the data and the methodology employed,
followed by the results of the models conducted. The
final section summarizes the findings and analyses.

ICT in Colombia: Closing gaps or reproducing inequality?
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Corporación Colombia Digital
ICT’s vital role in economic and social
development
According to the Global Economic Prospect from
2008, since 1990, technological progress has lifted
more than 10 percent of the world’s population out
off poverty.Technologies have begun to be conceived
as a major force behind economic growth.“ICT is thus
no longer a luxury good but an essential utility inclu-
ding those in low – income countries… its vital role
in advancing economic development and reducing
poverty has been expanded and increasingly recogni-
zed”(World Bank, 2011: 4).
Certainly, knowledge has become the fundamental
driver of increased productivity and global compe-
tition. And, ICT provides a foundation for applying
knowledge. Five billion subscriptions (World Bank,
2011) in Internet is the world largest platform to de-
liver and to find useful information, like prices of agri-
culture products, public policies, and commercial
agreements, among thousands of other topics, as well
as wide range of public and social services such as
education programs and health care. In sum, Internet
is conceived as the access to global knowledge.

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1. Target 18. In cooperation with the private sector, make available the benefits of
new technologies, especially information and communications technologies.
In other words, ICT offers major opportunities for de-
velopment and global integration. It increases the so-
cial well – being of poor peoples and empowers in-
dividuals and communities. “ICT is central to building
the climate for investment and sustainable growth
and empowering and investing in poor people”(Vidal,
2003: 421). In that sense, ICT offers an innovative and
an unprecedented tool to directly reduce poverty. It
provides access to information, it makes markets more
efficient, fosters social inclusion, equalizes opportu-
nities in rural areas and promotes more effective, ac-
countable, democratic governments especially when
coupled with effective freedom of information and
expression. In fact, Menzie Chinn and Robert Fairlie
established in 2006 that the acceleration of produc-
tivity growth in the United States since 1995 appears
to be connected with greater investments in ICT. The-
refore, developing countries must acquire the ICT in
order to leapfrog traditional methods of increasing
productivity.
In that sense, goals and targets have been established
on different global agreements like the Millennium
Development Goals1
, the World Summit on the Infor-
mation Society –WSIS, and the ICT for Development
Platform, among others. Through this settlements,
three areas for immediate action were defined: the
integration of ICT with poverty reduction strategies,
the need to promote nationwide ICT programs and
the creation of new types of partnerships involving
all major stakeholders – government, civil society, and
the private sector. E-strategies may prioritize and gui-
de national ICT development in order to promote and
coordinate ICT investments to ensure its benefits to
the larger segments of the country’s people. Govern-
ments must take into account that what really matters
is not only the telecommunication infrastructure and
the computer network but also the applications for
education, health, government and business.

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However, gaps in access remain large, ICT’s access is
highly unequal across and within countries. The di-
gital divide has become a worldwide phenomenon.
“Growth of ICT use in developing countries during the
1990´s has been impressive but inequitable among
and within countries” (Vidal, 2003: 421). Unfortuna-
tely, Internet penetration is related to the prosperity
of a country, and at the individual level, related to the
household income. Coupled with income, geographi-
cal determinants are evident; in many countries there
is a rift between ICT provision in urban and rural areas.
Apparently, ICT suppliers are not interested in provi-
ding telecommunications services in the countryside,
as rural areas do not represent sufficient financially re-
turns. On the other hand, Serrano and Martinez note
that divisions by race are also important in the United
States.They point to the concept of“Digital Apartheid”
to refer to the vast disparity in access to technology
among the European Americans and Asian against La-
tino and African. Finally, other determinants signaled
are education, age and physical weaknesses.
As it is said by Patterson and Wilson, “Internet is con-
tributing to an ever – widening gap between rich and
poor which has now reached grotesque proportions”.
ICT are unequivocally an engine of inequality among
countries and within countries, it seems that the Glo-
bal Digital Divide has been transferred into a National
Digital Divide. Is Colombia experiencing these digital
inequalities or access to ICT is helping to deal with po-
verty rates, education enrolment, access to health care
and the empowerment of Colombian people?

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BOGOTÁ D.C.
ANTIOQUIA
RISARALDA
SANTANDER
QUINDÍO
ATLÁNTICO
VALLE DEL CAUCA
CALDAS
META
NORTE DE SANTANDER
BOLÍVAR
CUNDINAMARCA
TOLIMA
HUILA
MAGDALENA
CESAR
CASANARE
SUCRE
BOYACÁ
CÓRDOBA
ARAUCA
CAUCA
NARIÑO
GUAJIRA
CAQUETÁ
CHOCÓ
PUTUMAYO
SAN ANDRÉS Y...
AMAZONAS
VICHADA
VAUPÉS
GUAINÍA
GUAVIARE
13,29%
9,82%
8,51%
8,19%
6,79%
6,77%
6,54%
6,23%
5,30%
4,42%
4,23%
4,20%
4,09%
2T-2011
3,52%
3,01%
2,81%
2,37%
2,18%
2,16%
1,99%
1,96%
1,96%
1,71%
1,45%
1,35%
1,33%
1,28%
0,82%
0,50%
0,16%
0,09%
0,06%
0,06%
Figure 1
Ranking of internet suscribers by department
Colombia - August 2011
Source: ICT Ministry, Colombia, Newsletter - August 2011

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According with ICT Ministry, in the second trimester
of 2011, Colombia has 5.522.039 Internet connec-
tions. However, as Figure 1 illustrates, the access is not
equal across the territory. Bogotá has 13.29 percent of
connections while departments like San Andrés and
Providencia, Amazonas, Vaupes and Vichada have less
than 1 percent of connections. Access to the Internet
predominates in the mayor cities and departments
like Antioquia, Santander, Risaralda, Quindío and Valle
del Cauca, leaving behind the inhabitants of the re-
mote areas of the country like the Amazon, the Llanos
Orientales and the Colombian Pacific.
Colombia has long been characterized as an unequal
country. In 2010 the GDP per capita was 6,2252
(World
Bank Data, 2010) but more than 45 percent of its po-
pulation lives in poverty. Its Gini coefficient is 0.54 in
a scale from 0 to 1, where 0 means equal society and
1 unequal (International Human Development Indica-
tors). And rural areas are far different from urban areas
in electricity, drinking water and sanitation provisions
. In other words, taking into account that electricity
could be an indirect determinant to the ICT access, it
can be expected that the access in rural areas is less
than in urban.
Additionally, racial disparities have been present in
Colombia from the beginnings. Afro-Colombians are
estimated as 10.5 million inhabitants, representing
more than 20 percent of Colombians, and figure pro-
minently among the poor. “The average per capita
income of the Afro-Colombian population varies bet-
ween 500 and 600 dollars annually, while the natio-
nal average income is 1.500” (Davis, S. and Sánchez,
E., 2003: 790). The inequalities are also reflected in the
literacy rate, which is around 43 percent while for Co-
lombian total population is 98 percent. They present a
lack in access to education, health care among other
basic needs. Based on the inequalities above, a racial
disparity in ICT access can be expected.
In Colombia despite of the government efforts and
public policies, ICT access seems to reproduce the
social and economic inequalities along the national
territory, between rural and urban areas and among
whites and Afro-Colombians.
2. Current US Dollar.

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Method, data and variables: how to
approach these hypotheses?
In order to test the hypotheses posed, this research
note is based on data produced by the 2010 edition
of the Democracy Survey of the Americas Barome-
ter, conducted by Vanderbilt University’s Latin Ame-
rican Public Opinion Project’s – LAPOP. This survey is
generated almost every two years in countries of La-
tin America, included Colombia. I use the results of a
sample of 1,506 Colombian citizens.
I used the results of specific questions posed to the
respondents, accordingly to the abstract concepts
involved in the hypotheses: “People in urban cities,
predominantly in Bogota, the higher the income the
greater the access to ICT”; and“Net of the effect of sex,
age, place of residence, location and income level,
Afro-Colombians are less likely to have access to ICT”.
The relational theory described above predicts, first,
a positive association between two abstract concepts
– income and access to ICT: the higher the income,
the greater the access to ICT. Thus, access to ICT is the
dependent variable and household income is the in-
dependent variable. The concepts in this theoretical
proposition are operationalized in terms of Internet
use, having a computer at home and having Internet
at home with the condition to have a computer; and
income, respectively.
Secondly, the theory predicts a negative association
between the other two abstract concepts – Afro-
Colombians and access to ICT: Afro-Colombians will
have a less probability to access to ICT than whites.
Hence, access to ICT is again the dependent variable
and Afro-Colombians the independent variable. The
concepts are operationalized also in terms of Internet
use, having a computer at home and having Internet
at home with the condition to have a computer; and
race, respectively. I assumed that the five operational
definitions are valid measures of the abstract concepts
and that they are reliable. It is important to emphasize
that the units of analysis are individuals.

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Table 1
Description variables
Source: Lapop Colombia 2010
*If having computer at home
Type of variables Name of variables Description Cases
Internet use 30 days a month 1492 18,2
8 days a month 15,5
4 days a month 7,0
No use 59,3
Total 100,0
Computer at home 1506 Mean 0,32
Internet at home* 1506 Mean 0,2211
No income - $180.000 1350 15,0
Among $181.000 - $360.000 19,6
Among $361.000 - $720.000 30,2
Among $721.000 - $1.000.000 14,4
Among $1.000.001 - $1.500.000 8,1
Among $1.500.001 - $2.000.000 5,8
Among $2.000.001 - $3.000.000 3,3
Among $3.000.001 - or more 3,6
Total 100,0
White 1455 84,9
Black 10,4
Other 4,6
Total 100,0
Age In years 1504 Mean 37,22
1506 % male 40,90%
% female 50,10%
Total 100,00%
Urban 1506 73,70%
Rural 26,30%
Total 100,00%
Atlantica 1506 21,6
Bogotá 15,3
Central 23,2
Oriental 18,4
Paciﬁca 17,9
Antiguos territorios nacionales 3,6
Total 100,0
%
Dependent
Independent
Control
%
Afro-Colombians
Income (Colombian pesos)
%
%
%
Place of Residence
Sex
Location
Measure

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Table 1 shows the nine measures that were selected.
As dependent variables and operationalizing the con-
cept access to ICT, I choose three variables:
• “Could you tell me if you have computer in your
house?”The question was coded into a dummy va-
riable where 1 means owns a computer and 0 do
not own a computer.
• “Could you tell me if you have Internet in your
house?” The question was coded into a dummy
variable where 1 means has Internet at home with
the condition to have computer at home and 0
does not have Internet at home.
• “How often do you use Internet?” This variable
looks to include also those Colombians that have
access to Internet, in spite of not having Internet
or a computer at home. It was recoded into days of
use by month: 30 days mean “Daily”, 8 days “A few
times a week, 2 days “A few times a month” and 0
“Rarely”and“Never”.
The independent variables are household income and
race. Income had eleven different values and taking
into account the frequency of the values. I recoded it
into eight values. The race variable was recoded in a
dummy variable where 1 means being Afro-Colom-
bians (black and mulato) and 0 beingWhite (white and
mestizo). Four measures were selected as dependent
and controlling variables:
• Age, a continuous variable, usually determinant of
the access to ICT.
• Sex, recoded in a dummy variable when 1 indica-
tes being a male and 0 a female. It was selected in
order to control for a possible digital gender gap.
• Location, recoded as a dummy variable such that
1=urban, 0=rural.
• Place of residence, distinguishing seven areas of
Colombia: Atlantica, Bogotá, Central, Oriental, Pa-
cifica y Antiguos territorios Nacionales. Bogotá is
taken as the value of reference looking to confirm
if there are differences among the country in refe-
rence to the capital city.

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Once I selected the variables, I executed two different
models for each one of the three dependent variables:
Having a computer at home, having Internet with the
condition to have a computer and use of Internet. For
the variables “Having a com-
puter at home” and “Having
Internet”I did Logistic Regres-
sions, first, by Income, contro-
lling for age, sex, location and
place of residence. And, then,
I did the same method by
Afro-Colombians controlling
for age, sex, location, place of
residence and income.
For the measure “Use of In-
ternet” I executed Ordinary
Least Squares regression,
first, by Income, controlling
for age, sex, location and pla-
ce of residence. And, then, I
did the same technique by
Afro-Colombians controlling
for age, sex, location, place of
residence and income. Howe-
ver, before launching into the
regression models, I perfor-
med different frequencies in
order to test two primarily
discriminatory factors to ICT access, the“Geographical
Digital Divide” (Gutiérrez L. and Gamboa L., 2008: 23)
and the“Digital Apartheid”(Santoyo, A. and Martínez,
E., 2003: 83).

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Since the largest inequalities in Colombia have been
subscribed to the geographical factor, Figure 2 illus-
trates the difference to accede to ICT between urban
and rural areas. As it can be seen, in all the different va-
lues considered, the percent of urban people “having
a computer”, “having Internet”and the different times
of Internet use by month are higher than in rural areas.
And, among people living in rural areas, 81.89 percent
never use Internet.
In other words, access to ICT, measured by the varia-
bles above, can be added to the other inequalities
present in Colombian rural areas, such as access to
electricity, freshwater, sanitation, food supply, among
others. On the other hand, these inequalities can also
be part of the explanation of the gap between rural
and urban areas. Power consumption and telecom-
munication infrastructure are the main determinants
of Internet use (Chinn M. and Fairlie, R., 2007).
Findings: access to ICT and socioeconomic inequalities.
Figure 2
Access to ICT in Urban Vs Rural areas
Colombia 2010

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As a result, if those conditions are not accomplished,
access to ICT is not even considered.
Instead, I want to draw the attention to the Internet
use.The differences in those values between the areas
are not so strong compared to having a computer
and having Internet. Almost the same proportion of
people in both areas uses Internet four times a month.
That might suggest that social government programs,
as Compartel, emphasizing in the countryside, are ha-
ving positive impacts.
On the other hand, in spite of the possibility to access
to ICT in a cybercafé or in a telecentro , household
income is supposed to be the main factor that deter-
mines this access. It is reasonable to expect that the
more money I earn the more I am likely to be able to
acquire luxury items as computers and Internet. The-
refore and taking into account that for the purpose of
this research note to test the effect of race is one of the
main idea, before testing if being Afro-Colombian has
an independent effect on having access to ICT, Table 2
indicates the mean access to ICT among Afro-Colom-
bians.

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As the Table 2 shows, for all variables considered, In-
ternet use, having a computer at home and having In-
ternet, the differences, in mean values, between Afro-
Colombian and Whites, must be highlighted. Even
more remarkable is that Afro-Colombians´ means are
lower than the mean for the total three samples.
For Internet use, the mean for the total sample is 6.9,
while for Afro-Colombians is 4.7 and for Whites is 7.2.
For having a computer, the mean for the total sample
is 0.32 and for Afro-Colombians is 0.22 compare to
Whites that the mean value is 0.34. Finally, for having
Internet, the mean for the total sample is 0.22 while
for Afro-Colombians is 0.16 and for Whites 0.23. In this
sense, Table 2 shows a nearly consistent pattern bet-
ween race and Internet use, having a computer and
having Internet: as people are Afro-Colombians, the
ICT access decrease.Thus, the Apartheid divide can be
expected.
Table 2
ICT access by Race
Colombia 2010
*If having computer at home

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Table 3 presents the three regressions models testing,
first, the access to ICT by income, controlling for age,
sex, location and place of residence; and next, the ac-
cess to ICT by being Afro-Colombian, controlling for
age, sex, location, place of residence and income. Mo-
del 1 shows that being older and living in the Atlantic,
in the Central, in the Oriental, in the Pacifica and the
Antiguos Territorios Nacionales regions, in reference
to Bogota, are negatively associated with the Internet
use.
For each increase in age we would expect a decrea-
se in 0.23 days a month of Internet use. Also, being in
the Atlantica region is associated with a decrease in
2.16 days a month of Internet use in reference to be in
Bogota. In the same way, living in the Central region
is connected with a reduction of 2.2 days a month of
Internet use compared to Bogota. And, finally being in
the Pacifica region is related with a decrease of 3.1 day
a month of Internet use in reference to be in Bogota.
Living in the Oriental and in the Antiguos Territorios
Table 3
Internet Access Regressed on Race, Income, Location, Sex and Age
Colombia 2010
(OLS regression coefficients and LS Logistic Regression)
**If having computer at home
*Statistical significant at .05 or less

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Nacionales regions are not affecting Internet use in re-
ference to be in Bogota, the results are not statistical
significant, they may be due to chance.
Additionally, being a man and residence in an urban
area are positively related with Internet use and statis-
tical significant. Men are expected to use Internet 1.15
day a month more than women; and people from ur-
ban areas are estimated to accede to Internet 3.5 days
a month more than people in rural areas.
Finally, household income is positively associated
with Internet use. People earning more than $721,000
Colombian pesos are expected to use at least 5.5 days
a month more than people with no salary or with wa-
ges less than $180,000. As the salary increases, the
days a month expected to use Internet increase too,
in contrast with people who do not have income or
earn less than $721,000 Colombian pesos. People with
incomes greater than $1,500,001 are supposed to ac-
cede to Internet from 12.2 to 15.2 days a month more
than people who do not have income or earn less than
$721,000 Colombian pesos. By the way, people with
income among $181,000 and $720,000 Colombian Pe-
sos in reference to people who do not have income or
earn less than $721,000 Colombian pesos do not cau-
se any affect in Internet use. The results are not statis-
tical significant, they may be due to chance.
In conclusion, the results in model 1 indicate that con-
trolling for age, sex, location and place of residence,
people with incomes higher than $721.000 Colombian
Pesos are expected to use much more days a mon-
th Internet. So, household income explains 32.1 per-
cent of the variance of Internet use. In fact, in model
2, I added Afro-Colombians to the equation but the
variance explained does not change. So, controlling
for age, sex, location, place of residence and income,
being Afro-Colombian do not have an independent
effect on Internet use. Accordingly, people in urban ci-
ties, predominantly in Bogota, the higher the income
the greater the Internet use.
On the other hand, model 3 displays that being older
and living in the Atlantic, in the Central, in the Orien-
tal, in the Pacifica and the Antiguos Territorios Nacio-
nales regions, in reference to Bogota, are negatively
associated with having a computer at home. In addi-
tion, it illustrates that location, gender and household
income are positively related with having a computer
at home.
Net of the effects of gender, location, place of residen-
ce and household income, the probability of having
a computer at home decreases with age. For every
increase in age, the probability of having a compu-
ter at home is multiplied by 0.986. However, place

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of residence, in reference to Bogota, does not cause
any effect on the probability of having a computer at
home; none of those variables are statistical signifi-
cant, their results should be due to chance in referen-
ce to live in Bogota.
Also, controlling for age, gender, place of residence
and income, the probability of having a computer at
home increases with living in an urban area by 2.58. In
this model, being a man does not cause any effect on
the probability of having a computer at home compa-
re of being a woman.
Finally, controlling for age, gender, location and place
of residence, the probability of having a computer at
home increases as the income rises. People with in-
come higher than $361,000 Colombian pesos have,
at least, more than three times more possibility to
have a computer at home. For instance, the probabi-
lity is multiplied by 148 for people earning more than
$3,000,000 Colombian Pesos. Instead, income among
$181,000 and $360,000 does not cause any effect on
the chance of having a computer at home in reference
to income less than $181,000 Pesos.
Accordingly, the results in model 3 indicate that net of
the effects of age, sex, location and place of residen-
ce, people with incomes higher than $361,000 Colom-
bian Pesos will have a higher probability of having a
computer at home. So, household income explains 27
percent of the variance of having a computer. In fact,
in model 4, I added Afro-Colombians to the equation
and the proportion of the variance explained increa-
ses to 28 percent. In other words, by including Afro-
Colombians, I add 1 percent to the variance explained.
The effect of being Afro-Colombian is negative and
statistically significant associated with the probability
of having a computer at home. As a result, controlling
for age, gender, location, place of residence and inco-
me, the probability of Afro-Colombians of having a
computer at home is 60 percent less than Whites.
So, people in urban cities, the higher the income the
greater the probability of having a computer at home.
And, net of the effects age, gender, location, place
of residence and income level, Afro-Colombians will
have a less probability of having a computer at home.
Finally, model 5 shows that being older, being a man
and living in the Atlantic, in the Central, in the Oriental,
in the Pacifica and the Antiguos Territorios Nacionales
regions, in reference to Bogota, are negatively associa-
ted with having Internet at home with the condition
of having a computer. In addition, it illustrates that
location and household income are positively related
with having Internet at home.

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Net of the effects of gender, location, place of residen-
ce and household income, the probability of having
Internet at home decreases with age; for every increa-
se in age, the probability is multiplied by 0.985. Also,
controlling for age, gender, location and income the
probability of having Internet decreases when being
in the Pacifica region in reference to be in Bogota.
The probability of having Internet is 55 percent less
for people living in the Pacifica region than for those
living in Bogota. However, being a man and living in
the others regions mentioned before, in reference to
Bogota, does not cause any effect on the probability
of having Internet at home; none of those variables
are statistical significant, their results should be due
to chance.
Controlling for age, gender, place of residence and in-
come, the probability of having Internet at home in-
creases with living in an urban area by 2.98. Finally, con-
trolling for age, gender, location and place of residence,
the probability of having Internet at home is higher as
the income increases. People with income higher than
$361,000 Colombian pesos have, at least, more than
three times more possibility to have Internet at home.
Indeed, the probability is multiplied by 292.5 for people
earning more than $3,000,000 Colombian Pesos. Ins-
tead, income among $181,000 and $360,000 does not
cause any effect on the chance of having Internet at
home in reference to income less than $181,000 Pesos.
Therefore, the results in model 5 indicate that net of
the effects of age, sex, location and place of residence,
people with incomes higher than $361,000 Colombian
Pesos will have a higher probability of having Internet
at home if you have a computer. So, household income
explains 28 percent of the variance of having Internet.
Although, in model 6, I added Afro-Colombians to the
equation but the variance explained does not differ.
As a result, controlling for age, sex, location, place of
residence and income, being Afro-Colombian do not
affect having Internet at home. People in urban cities,
the higher the income the greater the Internet use.

22
Page
Conclusion
Summing up, income is the main determinant of ha-
vingacomputerandInternetathomeandtheInternet
use, as expected. Also, being in urban areas affects the
three variables of interest. Instead, the effect of living
in other places rather than in Bogota is only evident
for Internet use. That may implied that Bogota has a
major offer of cybercafé or telecentros. Instead, the
geographical digital divide must be accepted for the
fact of living in an urban place comparing with being
in a rural area. Age, as a demographic variable, must
be highlighted by its effect on access to ICT.“A higher
proportion of youth is associated with greater use of
computer, while a lower rate will occur with a higher
proportion of seniors”(Chinn and Fairlie, 2007: 28).
Additionally, men do not have a higher probability of
having computer and Internet at home, but they do
have a greater chance to use Internet. In other words,
the evidence shows that the gender gap is not so evi-
dent in Colombia. Finally, when controlling for age,
sex, location, place of residence and income, being
Afro-Colombian does not have an independent effect
on Internet use and having Internet at home, but the
fact of being Afro-Colombian affects the probability of
having a computer at home.
In conclusion, the six models presented on Table 3
provide the information to accept undeniably that
people in urban cities, predominantly in Bogota, the
higher the income the greater the access to ICT. Ins-
tead, the hypothesis net of the effect of sex, age, place
of residence, location and income level, Afro-Colom-
bians will have a less probability to not access to ICT,
is not so evident and must be rejected. On the whole,
the effect of income is predominant, while the effect
of race is correlated to it.
In Colombia, ICT are far from achieving its goals of uni-
versal access and social inclusion. Instead, they cons-
titute a source of inequalities and they may reinforce
other types of exclusion; the Global Digital Divide has
been transferred into a National Digital Divide. The
appearance of ICT is posing new parameters of discri-
mination, given the gap that exists between groups
that have access to new technologies and those that
are excluded.
i. Since 1999, Colombian government has established different strategies like Com-
partel, a social telecommunications program. This project is developed all around
the country. In particular, it covers the main cities of the municipalities of the country
and rural localities of Colombian municipalities. The Compartel Program pretends
to generalize the access to the ICT services, achieving universal coverage of these
services.
Among the strategies, Computadores para Educar, a technology reuse program ai-
med to provide access to ICT to public educational institutions of the country through
the refurbishment and maintenance of donate equipment. Also, the program promo-
tes meaningful use and exploitation in educational processes through the implemen-
tation of educational tools and appropriation of ICT.
Also, Gobierno en línea, a strategy for online government account in national and
local level has been taken place in Colombia. Those programs have been framed by
different public policies like Agenda for Connectivity (2000), the National ICT Plan
(2008) and the recent Plan Vive Digital.
ii. The concept Digital Divide has received multiple definitions. In this paper, the Digi-
tal Divide refers to the division in a society between people with access and using ICT
and people without access to them.
iii. According to the census conducted in 2005, national coverage of electricity is
93.6%, where urban areas show a 98.4% coverage compared to 77.7% in rural areas.
For access to drinking-water the national coverage is 92% and use of sanitation from
74% in 2008: However, the gap between rural and urban areas continues, the 27% of
rural population still lacks access to safe and adequate water, and the 45% cannot
access to adequate sanitation methods.
iv. Telecentres are meeting places, to learn and to communicate through ICT. They
claim to improve the living conditions of communities. Those have been promoted
by the national government and local authorities but also by private and non-gover-
nmental organizations.
22
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23
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