“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. Knowledge and access to information are concei-

ved critical for these purposes; and telecommunications

are presented as the best platform to connect people and

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:

Information and Communications Technology, Colombia, access,

inequalities, digital divide, 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.


8Page


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?

9Page

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 1Ranking 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 1Description 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 18,28 days a month 15,54 days a month 7,0No 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 15,0Among $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 84,9Black 10,4Other 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 21,6Bogotá 15,3Central 23,2Oriental 18,4Pacifica 17,9Antiguos 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 being White (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.

Source: Lapop Colombia 2010

Figure 2Access to ICT in Urban Vs Rural areas

Colombia 2010

16 Corporación Colombia DigitalPage


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.

17Page

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 2ICT access by Race

Colombia 2010

Source: Lapop 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 3Internet Access Regressed on Race, Income, Location, Sex and Age

Colombia 2010(OLS regression coefficients and LS Logistic Regression)

Source: Lapop Colombia 2010

**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


20Page


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.

21Page

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.


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Conclusion

Summing up, income is the main determinant of ha-ving a computer and Internet at home and the Internet 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.

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“ICT in Colombia”

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