ONLINE RESOURCES, POLITICAL PARTICIPATION AND EQUALITY
Eva Anduiza, Aina Gallego, Marta Cantijoch and Josep San Martin
Universitat Autònoma de Barcelona
Abstract
New information and communication technologies are reshaping political activity. The
Internet offers new opportunities for involvement online and access to the Internet and
online abilities are a new resource for political participation. In this paper we firstly
explore and compare the characteristics of online and offline participants along relevant
socio demographic characteristics for three participation modes that can be performed
both online and offline (contact, donation and petition). Secondly, we examine the role
of different kinds of participatory resources for those activities. Online resources are
essential to understand online participation. Using a Heckman selection model we find
that traditional resources such as income or civic skills determine the probability to have
access to the Internet, but they make little difference to sort participants and nonparticipants once access to the Internet is achieved. Having online resources in some
cases increases the probabilities to participate in traditional activities. Internet use does
not only increase the spectrum of possible activities, but it provides new resources that
can be used for participation and is reshaping the traditional inequalities found in
political activity.
Paper to be presented at the APSA annual meeting, Boston 28-31th August 2008
Work in progress, comments welcome ([email protected])
Keywords: Internet, political participation, resources, political equality
1
Introduction
For democracy to work properly, it is essential that citizens express their opinions to the
political system and that the system is responsive to those opinions. However,
participating in politics is a voluntary activity and not every person takes part equally
frequently or by the same means. Two central preoccupations in the political
participation literature are to establish who participates and to explain why there are
systematic differences in the characteristics of participants and non-participants. It has
been repeatedly found that political participation is disproportionately exerted by the
socially privileged, such as white middle-aged men, who are well educated and have a
high income (Verba, Kim and Nie 1978, Wolfinger and Rosenstone 1980, Parry Moyser
and Day 1992, Rosenstone and Hansen 1993, Teorell, Sum and Tobiasen 2007). One
key to explain why these biases exist is that some resources are necessary to participate
in politics effectively and that resources are unequally distributed among the population.
People who have more resources such as money, time and civic skills can more easily
afford the costs of participation and therefore they are overrepresented among
participants (Verba, Schlozman and Brady 1995). Besides resources, other important
factors predicting participation are political attitudes and motivation, and political
mobilization. In sum, two key statements of the core explanatory model of political
participation are that it is an unequal activity as the socially privileged participate more
and that this fact is partly attributable to the importance of resources to become active.
This is the established wisdom of accumulated research. However, in the new scenario
labelled as network or information society, characterised among other features by the
expansion of new information and communication technologies (Castells 2003), there
are reasons to assess the findings of the classical model critically. On the one side, there
has been an expansion of action repertoires which were previously not possible. Online
forms of action are more and more influential and widespread. It is reasonable to claim
that online participation has to be routinely included in academic assessments of
political participation (Best and Krueger 2005). There is still little research on online
participation and we do not know who participates in these new activities or whether the
typical participatory biases of traditional participation are reproduced, diminished or
reinforced in the digital world. On the other side, Internet access and abilities are key
2
individual characteristics that determine social inclusion and centrality in this new
society (Warschauer 2004). Therefore, it is necessary to question what relation they
have with political activities, with participatory equality and with the traditional
explanatory models of political participation.
This paper analyses the potential of Internet use for political participation in Spain. We
address two main questions. Firstly, we look at whether online participation is more or
less equal than offline participation regarding four relevant sociodemographic axes
(gender, age, education, and income). In other words, we examine who participates and
how unequal participation is. Secondly, we pay a closer look at how Internet use affects
the resource-based explanatory model of political participation. We argue that Internetbased resources should be incorporated to any explanatory model of online political
participation.1 However it is fundamental to make a clear distinction between the effect
of traditional resources over access to the Internet and over online participation. Only
when this distinction is made we can adequately asses the potential effect of online
resources over participation and political equality.
After presenting the basic theory, the paper is structured in three sections. First, we
describe the levels of online and offline participation in Spain in three political activities
and include some figures for the UK and the US for comparative purposes. Then we
analyse the socioeconomic biases of Internet users, offline and online participants for
three participation modes that can be performed both online and offline. Finally, we
analyse the relationship between inequalities, resources, and participation from two
different perspectives: (a) which resources are important for access and which for online
participation? (b) once we account for access, is the effect of socioeconomic variables
and resources larger for online or offline participation?
1
And probably to the resource-based model of offline political participation as well, though this would be
the subject of a different paper. In our exploratory analysis we have found significant effects of Internet
abilities on petition, demonstration, political consumerism and contact after controlling for socio
demographics, time and civic skills.
3
Resources, political participation and the Internet: the theory
Being active in politics is not easy. It is necessary to understand how the political world
works and what a single person can do in order to have an influence on it. Once the
decision to act is taken, it is necessary to devote some time, effort and/or money to
participate. Even voting, which is one of the easiest political acts, involves some costs
such as learning about the candidates and alternative options and actually going to the
polls. In fact, taking into account that being active is costly and that a single action is
not likely to change the outcome of an election or of any governmental decision, it is
surprising that some people bother to participate at all (Downs 1957, Riker and
Ordershook 1963).
Resources are a key factor to understand why some people participate in politics
whereas other people do not according to the civic voluntarism model (Verba,
Schlozman and Brady 1995). Some citizens have a lot of communicative and
organizational skills; some have plenty of money and free time. For that kind of
resource-rich people it is relatively easy to afford the costs of participation. This is why
the resource-rich, and more generally the socially privileged, are disproportionately
represented among participants, which leads to the existence of inequalities in political
participation. In this situation the voice of privileged groups is more present in the
public debate and their interests and points of view are therefore more likely to be taken
into account by policy-makers (Jacobs and Skocpol 2004).
The resource approach is also useful to distinguish among differences in the
composition of participants in different activities. For example, people who have a lot of
money can easily afford to donate for political causes and campaigns. However,
resources are not the same as demographic characteristics. Descriptive characteristics,
such as gender or age, are often related to the acquisition of resources which positively
influence participation, but they do not completely determine this acquisition (Burns,
Schlozman and Verba 2003). The civic voluntarism model distinguishes several main
resources for participation. First, having some free time is a necessary condition to
participate, particularly in time consuming activities. Money is relevant for donations
and for other activities that require at least some financial freedom. Civic skills, which
4
include the ability to organize, to process information and to communicate it effectively,
are relevant to most forms of participation because they reduce the cognitive and
information costs and make participation more effective. In sum, resources constitute
the basis of one of the main explanatory models of political participation, particularly
relevant in as long as they are related to the question of equality in participation.
The extension of Internet use poses a challenge to this civic voluntarism model
developed by Verba and his colleagues which needs to be revised and extended. Online
activities are a new form of political participation which is more and more relevant in
advanced industrial societies. The importance of online forms of action can be
illustrated with well known cases. For example journalistic accounts consider that the
intelligent use of the Internet was decisive to the victory of Barack Obama in the
Democratic Party primaries in the USA, and there is evidence that it was crucial for the
movement for global justice (Della Porta and Mosca 2005) and other protest movements
(Van de Donk et al 2004). Research on political participation has to examine who
participates in online activities and if participation in these new forms can be explained
with the traditional explanatory models of offline participation.
Firstly, there is still relatively limited empirical evidence on the “how much” and “who”
questions about online participation. We have just a few representative studies on levels
and inequalities in online participation in contexts other than the USA and the UK.
Regarding inequality there has been an important theoretical debate about the impact of
the Internet on participatory biases. From a relatively optimistic perspective,
mobilisation theories argue that the Internet can facilitate the participation and
mobilisation of people previously more likely to be excluded and particularly
youngsters (Delli Carpini 2000). It allows for direct citizen participation both in
decision making and in the definition of the material that appears on the web through
web 2.0 technologies. Internet is a convenient, cheap and innovative means for
gathering information, communication and participation that can, for different reasons,
be particularly attractive to certain segments of society: youngsters, disabled, ill, those
living in isolated rural locations or dispersed, single mothers, carers, those with less
social skills, those with specific issue concerns (Karakaya 2005). In this sense, Internet
could increase the equality of participation.
5
However, minimal effects or reinforcement theories argue that it is all politics as usual:
the Internet is not radically transforming patterns of political participation, Internet
activists are among the most politically resourceful and motivated citizens, and ICTs
may even worsen inequalities by reinforcing resource barriers that prevent the more
marginalised groups and individuals to participate (Weber Loumakis and Bergman
2003; Bucy 2000; Hill and Hughes 1998). The potential of Internet for enhancing
democratic participation has received similar reproaches as participatory democracy:
Internet increases the amount of potential participation but not the diversity of
participants since these are mostly those that already participate offline (Norris 2003,
Davis 2005).
Second, it is worthwhile to ask if the civic voluntarism model needs to be extended to
account for online activities. Resources specific to the Internet certainly need to be
incorporated in any resource-based explanation of online participation (Krueger 2002,
Gibson, Lusoli and Ward 2005). In order to be active online it is obviously necessary to
have access to the Internet. Further, being familiar with this medium should be an asset
that facilitates participation once the citizen has access to the Internet. Online resources
enable the preparation of political activity (information acquisition, searches of other
successful campaigns and experiences, etc). People who are online and have Internet
skills understand better how the information society works and can better assess how to
have an influence on it. For example, knowing how to advertise a campaign on the
Internet and develop attractive interactive material is useful in a campaign, and
mastering the digital sphere enables to deal with digital applications to send emails to
hundreds of representatives or to donate money. Online resources can be expected to be
a nuclear predictor in any model of online participation because people who have more
expert skills can more easily find out how to participate and do so effectively.
In this case another relevant question is to what extent the traditional resources are
relevant for online participation. Classical participatory resources, such as money, time
and civic skills are related to access to the Internet (Norris 2001, Best and Krueger
2005). Traditional resources may be related to online participation in two different
ways: they firstly enable to overcome the costs of having access to the Internet and,
then, they may or may not make it easier to participate online (Mossberger, Tolbert and
McNeal 2008, 68). Importantly, this is a two step process which needs to be modelled
6
as such in the empirical analyses of online political participation. In sum, online
resources need to be incorporated in explanatory models of online participation; and the
impact of traditional resources on access and on participation once access is achieved
needs to be distinguished.
Finally, there is debate as to whether Internet-related behaviours are relevant and should
be considered for predicting offline participation (Bimber 2003, Karakaya 2005,
Mossberger, Tolbert and McNeal 2008). After some initial research without significant
findings more recent evidence shows several interesting links between the uses of
Internet and offline political participation and engagement. According to instrumental
theories, there is a direct link between Internet use and participation because it decreases
the costs of information acquisition and other participation enhancing factors (Bimber
2003). Access is associated to increased propensity to vote even after controlling for
many other predictors, at least in the USA (Tolbert and McNeal 2003, Kenski and
Strout 2006). Other authors find it to have beneficial effects on political participation
more broadly (Zukin et al. 2006:148, Xenos and Moy 2007:711). According to
psychological theories, there are conditional effects of Internet use on participation. For
example, particular uses of the Internet, such as exposure to political information and
news increase engagement, measured as knowledge, interest, and political discussion,
particularly for the young (McDonald 2008, Lupia and Phipot 2005) which can
ultimately lead to more participation. Using political chat rooms, email, and online news
matter for turnout (Mossberger, Tolbert and McNeal 2008). Internet offers a wide
variety of options and thus the effects of its use can be contingent on elements such as
the levels of sophistication, motives or social context (Bimber 2003, Prior 2005, Shah et
al. 2001). Both approaches are not necessarily incompatible. Xenos and Moy (2007)
find both direct effects of Internet (seeing campaign information online) for information
acquisition and use, and civic participation, and contingent effects of the former on
political participation and talk depending on political interest.
We propose, as others have done (Krueger 2002, Best and Krueger 2005), that the link
between Internet use and political participation can be fruitfully theorised from a
resource perspective. Having access to and mastering the digital world is nowadays a
relevant asset for both online and offline political participation because having those
tools makes participation easier and more effective. Just like other resources such as
7
time, money or civic skills can be important for political participation, online resources
may be relevant too. We focus on online skills rather than just on access. Access and
skills tap two different dimensions that can be relevant in different stages of the
penetration of this technology. At an early stage of technological penetration access is
the main dividing line between the haves and have-nots. In a second stage, the abilities
are more important to shape digital inequality, particularly in terms of content creation
(DiMaggio and Hargittai 2001, Chadwick 2006).
It can be counter argued that even if Internet use is relevant for participation, access and
online abilities are not resources but an attitude or behaviour comparable to consuming
news in the television or being interested in politics. In our point of view, online skills
differ from political attitudes in the sense that they are not subjective dimensions. They
are not relatively stable as attitudes are supposed to be (one can and does acquire online
skills along time). They are abilities that can be used in order to achieve other relevant
aims in different spheres of life, such as finding a job, learning, or communicating with
others. The ability to access, manage and create knowledge using information and
communication technologies is critical to social inclusion nowadays (Warschauer
2004). Workers in information-intensive sectors develop specific skills in the medium
which are then made central to the production processes in the knowledge society
(Castells 2003). They have a relevant advantage that is highly valued in this society and
that can be used for multiple purposes. The digital divide and digital inequality is
increasingly considered as a source of inequality in this new scenario (DiMaggio and
Hargittai 2001). Having online resources or not are distinct situations consequential
enough to distinguish them from relatively innocuous behaviors which enter rather in
the realm of tastes and freedoms of the individual such as consuming news.
So just like other resources such as time, money or civic skills can be important for
political participation, online resources may be relevant too. This is expected to hold in
particular for online activities, but may also influence participation in traditional acts.
There are of course other important explanatory factors of political participation (mainly
related to attitudes and mobilization) which can in turn be related to the level of
resources. In this paper however we will not address this question, that would require a
8
whole specific analysis, but will focus on the importance of Internet related and
traditional resources for both online and offline political participation.
Data
We use data of a survey (N 3,907) carried out in November 2007 over the Spanish
population by the Centro de Investigaciones Sociológicas in the context of a project on
the effects of the Internet on political participation2. The sample included an
overrepresentation of citizens between 18 and 40 in order to increase the number of
Internet users.
As it is well known, political participation is a multidimensional phenomenon that
should be dealt with distinguishing modes. Not all modes of participation are performed
equally nor are they influenced by the same factors. We will consider only three
activities which can be performed both online and offline. These are donating money,
signing petitions and contacting. Focusing on them allows comparing differences in the
level of inequality and in the impact of resources in the online and offline arenas. 3 Thus
it seems as an adequate research design to answer the theoretical questions. We leave
aside some other types of Internet use that are not properly speaking political
participation, such as searching for political information, visiting political sites, or
emailing. Our cutting point for defining access to the Internet is use in the last 3 months.
We consider inequality along four different axes: gender, age, education and income.
They are politically relevant socio-economic and demographic characteristics which are
both sources of social inequality and predictors of participation. These four axes tap
important theoretical and empirical dimensions of inequality.4
Beyond those characteristics, the independent variables in the models are participatory
resources. We distinguish several types of resources, both traditional and technological.
2
The Project “Internet and political participation in Spain” is funded by the Spanish Ministry of Science
and Innovation (SEJ2007-60082). Further information on the project and the questionnaire of the survey
can be found at www.polnetuab.net
3
Consuming online and demonstrating online are possible but we expect these behaviours to be very rare
and therefore we did not include items in the survey measuring them.
4
There are theoretically other important distinctions such as religion, or race and ethnicity.. However,
these are not considered because in our data there is not enough variation along these axes (Spaniards are
mostly Catholics and the survey does not include immigrant population without the Spanish nationality).
9
- Time and money. Time is measured as reported time free from responsibilities, that is
time available in a normal day after doing all necessary activities such as sleeping,
working, eating, keeping the household and so on. Money is reported household
income. Missing data on income are imputed in the multivariate analysis.
- Civic skills5. We asked if in the course of normal activity such as work or associational
collaboration, the respondent writes letters, if she does oral presentations and if she
attends and organises meetings where decisions are taken. These are indicators of civic
skills that may help to cover the costs of social interaction in a complex social
environment and thus may facilitate offline political participation.
- Online skills. These were measured in two alternative ways. First, we adapted the civic
skills measures and asked if the respondent needs to have no, basic, or advanced
knowledge of ICTs in her current activities such as work or associational membership.
The reference category is people who do not need those abilities in their normal
activities. Secondly, we had a battery of nine online activities including using the email,
shopping online, searching information, telephoning online, or maintaining a blog or
website. People who are not users are coded as having no abilities, and for users the
items are aggregated in an additive index, with the expectation that people with few
online skills only do a few of the activities, whereas people with many skills do a lot of
activities This index is done in a similar way as that proposed by Krueger (2002) that
showed considerable construct validity6.
How much online participation in Spain?
The following table reports de levels of Internet use and political participation in Spain,
the UK and the USA.
5
This battery has been directly adapted from the Civic Participation Study used by Verba, Schlozman and
Brady (1995).We further follow these authors in that being a member of an association in itself does not
provide civic skills but that these depend on the activities that are done in the association (1995:340).
Thus our question measuring civic skills acquired at work also taps those obtained in association
activities.
6
Cronbach’s Alpha: 0,616.
10
Table 1. Offline and online political participation.
Spain
GB
USA
Offline
Online
Online
Offline
Online
Offline
Online
particip.
particip.
particip.
particip.
particip.
partici.
particip.
(% of
(% of
(% of
(% of
(% of
(% of
(% of
sample) sample)
users)
sample)
users)
sample) sample)
Internet users
51
49
73
Donation
25
4
8
6
Na
Na
Na
Petition
22
7
14
21
4
21
11
Contact
8
9
18
14
6
20
14
N
3716
3716
2169
1972
965
1003
1003
Data for Spain are own elaboration from CIS 2736 (2007). Data for the UK are from Gibson,
Lusoli and Ward (2005) except for online contact and offline petition (Di Genaro and Dutton,
2006, N 2,185). Data for USA are from Best and Krueger (2005) except for percent of Internet
users (data for 2006 http://www.pewinternet.org/PPF/r/182/report_display.asp, visited on July
25th 2008) and offline contactors (Zukin et al 2006).
51% of the Spanish population reports that they used the Internet in the last three
months. The figure is similar to the UK data7 and lower than the American. Spanish
citizens seem to be more likely to donate than the British (25%), but less likely to
contact (8%). Petition levels are strikingly similar across cases (22%). Online activities
in Spain seem higher than in Britain, in levels closer though still lower than those found
in the USA: 8% of users declare having donated money, 14% have signed petitions and
18% have contacted politicians or public officials.8
Equality in online and offline participation: the evidence
We analyse inequality in online and offline participation in Spain in order to provide
further empirical basis for the debate on the effect of Internet use on participatory
inequality. The database has been segmented in different socio-economic and
demographic groups. The following table reports the percentage of the population
belonging to each of those groups, and the percentage that they represent over Internet
users and over participants in online and offline contact, donation and petition.
7
Gibson et al (2005) do not specify exactly what being online means and of course the percentage may
have increased in the last two years.
8
Definitions of what online contacting is vary. Ours is restrictive (people that report having contacted
politicians, civil servants or associations in the last 12 months) but see Gibson et al 2005 for a wider
conceptualisation.
11
Table 2. Distribution of gender, age, education and income categories across the
population, Internet users, online and offline participants (column percentages)
Gender
Women
N (non weighted)
Age
18-24
25-34
35-44
45-54
55-64
65 or more
N (non weighted)
Education
Primary
Low second
Upper sec
Tertiary
N (non weighted)
Income
up to 1200
1201 to 1800
more than 1800
N (non weighted)
Popu
lation
Internet
use
Contact
Econtact
Dona
Tion
E-dona
tion
Petition
E-peti
tion
51
1864
46
2169
39
254
42
346
57
922
49
147
54
899
50
280
11
21
20
16
13
20
3716
18
31
25
16
7
2
2169
7
18
23
31
14
7
254
13
29
27
21
9
2
346
9
21
22
19
15
15
922
13
28
19
26
9
5
147
12
25
26
20
10
6
899
15
30
25
17
9
4
280
31
29
22
19
3708
6
27
33
34
2163
19
21
30
30
253
3
18
32
47
342
21
26
24
29
918
0
14
28
59
146
12
28
29
31
898
2
13
26
59
279
40
23
36
2655
19
25
56
1512
24
21
56
201
12
20
67
275
32
24
45
701
10
17
73
110
24
28
48
680
9
19
71
221
Source: Own elaboration from CIS 2736
A first descriptive approach to our data shows a mixed picture, leaning towards the
reinforcement theories. Gender categories show relatively small differences across
online and offline participation modes. Women are 51% of the Spanish population but
only 46% of Internet users. They are slightly overrepresented among petition signers
(54%) and more significantly among donators (57%). The online versions of these two
latter modes, e-petition and e-donation, show a smaller presence of women, but still
close to 50%. This is to be expected since women are underrepresented among Internet
users. Contacting is the mode of offline participation least preferred by women: only
39% acknowledge having contacted politicians, civil servants or associations in the last
12 months. However among Internet users the percentage of women that have econtacted increases to 42%, probably because among Internet users the level of
resources that facilitate this mode of participation is higher. In short, Internet does not
solve
the
underrepresentation
of
women
in
contacts,
but
eliminates
the
overrepresentation of women in offline petition and donation.
12
Age related differences between offline and online modes are larger. Younger adults are
underrepresented among voters, as it is usually the case: those between 18 and 34 are
31% of the population but only 25% of the voters (data not shown on tables/graphs).
Being over 50% of the Internet users, their presence in all online modes of participation
is much higher: they are over 41% of those that e-contact and e-donate (vs. only 25% of
those that do contact offline and 30% of those that donate). Younger adults are
overrepresented among petition signers, offline (37%) and particularly online (45%).
Thus, younger citizens are underrepresented in more traditional modes of participation
(vote, contact) but not on other less conventional offline modes (petition, demonstration
–data not shown-). In all three cases (contact, petition, donation) online activities seem
to attract a lager proportion of young adults than offline modes. In as long as the
younger age groups are more likely to be less active in traditional modes of
participation, online activities show a space for more political equality regarding age
differences.
However, by large the main problem of socioeconomic bias and thus inequality in
participation is not related to age, but to education and income. Education related
differences are significant but, unlike age, not in a more equalising direction. The two
lower educational categories are 60% of the population but they make up for only 47%
of donators, and just 40% of those that sign offline petitions, and contact offline. There
is here, a significant level of education-based political inequality among all offline
categories. The fact that these citizens with lower levels of education are only 33% of
Internet results in the fact that all online activities are even more skewed in terms of
education: only 21% of e-contacters, 15% of e-petition-signers and 14% of e-donators
are among those with lower secondary education or less. Thus not only more educated
people are overrepresented in offline activities, they are even more so in the online
modes of participation.
We find a similar picture regarding income. Those in the lower income categories are
heavily underrepresented in all offline modes of participation: while they are 40% of the
population they are only 32% of donators, and 24% of contacters and petition signers.
Access to Internet seems also an important barrier since they are only 19% of those who
use Internet and, consequently, a very small part of online participants (between 9 and
12% in all three modes).
13
The following figures describe inequalities in political participation graphically and
show clearly the extent to which each of those groups are over or under represented
among participants. The bars are the result from subtracting the percent of people that
belong to a group relative to the population, from the percentage of participant group
members relative to all participants. For example, if women are 51% of the population
but only 39% of those who contacted politicians the bar value is minus 12 percent. The
graphs also display the difference between the percentage of group members over
Internet users and over the population. We can firstly appreciate that gender inequality
is relatively moderate. Older people are clearly underrepresented among participants,
and particularly among online participants, whereas in the case of young people they
have more presence relative to their demographic weight in online activities. Finally,
the usual strong biases in favour of the well educated and well-off in offline
participation are much more acute for online participation forms.
14
Fig. 2: Participants and population by age
Internet use
40
Contact
20
E-contact
Donation
0
E-donation
-20
Petition
E-petition
-40
Women
% over population - % over
particip.
% over population - % over
particip.
Fig. 1: Participants and population by sex
Contact
20
E-contact
Donation
0
E-donation
-20
Petition
E-petition
-40
Men
18-34
Fig. 3: Participants and population by education
35-54
55+
Fig. 4: Participants and population by income
Internet use
40
30
20
10
0
-10
-20
-30
-40
Contact
E-contact
Donation
E-donation
Petition
E-petition
Primary
Low
second.
Upper sec.
Tertiary
Internet use
% over population - % over
particip.
% over population - % over particip.
Internet use
40
40
30
20
10
0
-10
-20
-30
-40
Contact
E-contact
Donation
E-donation
Petition
Up to 1200
euros
1201 to 1800
More than
1800
E-petition
15
In sum, as in other countries, (Gibson, Lusoli and Ward 2005, Di Genaro and Dutton
2006) in Spain too social inequalities in offline political participation tend to be
reproduced and magnified in online participation. The relevant exception is gender
(where online activities show a balanced distribution of genders) and particularly age:
young adults are (slightly) underrepresented among offline participants, but clearly
overrepresented among online participants. However the main problem related to
political equality is the underrepresentation of people with lower levels of education and
income. This happens in offline participation modes, and even more in their online
versions.
This bivariate analysis does not drain out the potential analysis of the implications of
online participation for political equality. Resources are related among themselves and
thus multivariate analysis is required in order to establish the origin of the main sources
of inequality. The potential reinforcement effect of Internet over political participation
may act on two grounds: by restricting use to a socially skewed part of the population or
by influencing actual online participation. We need to disentangle thus inequality in
Internet use and inequality in online participation. In the next section we address these
concerns.
Inequalities, resources and participation: the analysis
Differences in participation across social categories exist because resources and
motivations to participate are not evenly distributed across those: middle aged, highly
educated, wealthy men are more likely to have the time, the money and the skills to
process complex and abstract information, to make up their minds and to cover the costs
of participation. They also are more likely to be in centrally located social positions
more exposed to stimuli (information and communication flows, mobilisation efforts),
and more likely to develop attitudes favourable to participation (such as interest or
internal political efficacy). As we have seen in the previous section, this profile is
heavily overrepresented among Internet users and among online participants. In this
section we examine in detail the impact of traditional and online resources on political
participation. For this purpose it is necessary to broaden the classic resource-based
model of political participation in order to include Internet specific resources. In order
16
to test the validity of this enlarged model we first carry out a multivariate explanatory
analysis of online participation including traditional as well as Internet related
resources. We have seen in the previous section that Internet use is not evenly
distributed among the population but is dependent on socio demographic characteristics,
and so is political participation. We are interested in knowing whether, once access is
gained, resources and socioeconomic characteristics still have a significant effect. Thus
we first need to model explicitly Internet use and then online political participation. For
this purpose we use a Heckman selection model. Only then we can compare in the
following section the effect of resources and sociodemographic variables over online
and offline participation and asses the potential of online participation to reduce
political inequalities.
Are resources relevant for Internet use or for online participation?
How do online and traditional resources operate for online participation? Here we must
tackle in the first place a conceptual distinction with methodological implications: are
resources relevant because they facilitate Internet use or because they facilitate online
participation once access is granted? If resources are relevant only for use, there are
more chances that, once there is universal access, online participation will provide more
political equality.9 If resources are relevant for online participation once access is
granted then the perspectives for an increase in more equal political inputs through the
web are less clear.
A Heckman selection model allows to specify use and participation as a two-step
process and to distinguish the impact of each of the independent variables first on the
probability to use Internet and then on the probability to be politically active online.
This kind of model has two dependent variables and two equations which are related.
The first one is the selection equation and the second the regression equation. The
9
However as access expands to larger segments of society there will be more social heterogeneity among
users and thus some sociodemographic variables that have not been relevant for online participation so far
may become significant predictors. In any case inequalities in access and daily use persist (Mossberger et
al 2008). Moreover, even if access gaps will eventually close at least in postindustrial democracies, the
question is usage gaps (van Dijk 2005), since technology alone will not produce a more informed or
participatory society. The literature has found significant effects of sociodemographic variables in
physical access and use (vand Dijk and Haker 2003, Di Genaro and Dutton 2006).
17
dependent variable in the selection equation is a dummy variable and a condition that
needs to be fulfilled in order for the second action to be possible.10
In the case of online participation, Internet use is the dependent variable in the selection
equation. Online participation is the dependent variable in the regression equation,
because only those who use the Internet can participate online. This kind of model
allows including independent variables in both equation with one exception. For the
model to converge it is necessary to include one variable in the selection equation which
is not relevant and not included in the regression equation. This instrumental variable is
in our case living in a large city (coded as living in a city with more than 400.000
inhabitants), and it fulfils this condition. Living in a large city predicts Internet use, but
once a citizen uses to the Internet, it makes no difference in sorting between online
participants and non-participants.
The following table reports the results of three probit Heckman selection models for the
three modes of online participation analysed.
10
In a classical example in many US states voting is a two step process because people need first to be
registered to vote and only then are they able to cast a ballot. Registration is a necessary condition for
voting, and a selection model can measure the impact of different variables on the probability to register.
Once a person is in the electoral rolls, she may or may not vote, and we can examine the determinants of
this voluntary decision in the second model.
18
Table 3. The effect of resources on Internet access and online political participation
E-contact
E-donation
E-petition
Coef.
Std. Err.
Coef.
Std. Err.
Coef.
Std. Err.
Regression model:
online participation
Woman (0-1)
Age (18-95)
Education (1-4)
Write (0-1)
Meeting (0-1)
Expose (0-1)
Incomea (0-10)
Time (0-1)
Int. Abilities (0-9)
Some ict (0-1)
Advanced ict (0-1)
Constant
0,018
0,024***
-0,042
-0,410*
0,192*
0,150
-0,017
0,083
0,118***
0,147
0,342**
-1,937***
0,085
0,005
0,071
0,234
0,105
0,103
0,037
0,143
0,025
0,108
0,134
0,520
0,156
0,023***
0,190**
-0,555**
0,195
0,225*
0,016
-0,004
0,139***
0,062
0,083
-3,350***
0,108
0,007
0,091
0,277
0,140
0,130
0,046
0,180
0,031
0,170
0,204
0,663
0,219**
0,016**
0,151*
-0,156
0,246**
0,158
0,033
0,297*
0,138***
0,284*
0,407**
-3,418***
0,092
0,007
0,085
0,343
0,115
0,109
0,039
0,163
0,027
0,161
0,173
0,678
Selection model:
Internet use
Woman (0-1)
Age (18-95)
Education (1-4)
Write (0-1)
Meeting (0-1)
Expose (0-1)
Incomea (0-10)
Time01 (0-1)
Big city (0-1)
Constant
/athrho
Rho
N
-0,104
-0,040***
0,360***
1,400***
0,170
0,361**
0,160***
0,155
0,313***
-0,522**
-0,667*
-0,583
3009
0,080
0,003
0,051
0,092
0,135
0,168
0,030
0,132
0,107
0,227
0,343
0,226
-0,093
-0,039***
0,370***
1,396***
0,150
0,403**
0,155***
0,147
0,289**
-0,532**
-0,461
-0,431
3010
0,080
0,003
0,051
0,093
0,137
0,171
0,030
0,134
0,114
0,231
0,318
0,259
-0,108
-0,039***
0,365***
1,398***
0,154
0,385**
0,156***
0,139
0,318**
-0,533**
-0,353
-0,339
3001
0,083
0,003
0,051
0,094
0,135
0,167
0,030
0,133
0,115
0,230
0,425
0,376
Source: CIS 2673
* p<0,1; ** p<0,05; *** p<0,005
a
The variable income has many missing values and they have been imputed in order not to
loose information. The Stata command impute was used with 30 variables as income predictors.
The reference category for women is men, for advanced and basic ICT is no ICT knowledge
required at work or normal activities. See appendix for coding values.
Our findings for Internet use in Spain are consistent with the expectations: age,
education, writing and exposing skills, income and place of residence all matter in the
expected direction: the younger, the more educated, the richer, the more skilled, the
inhabitants of large cities, are more likely to use the Internet. On the contrary, gender,
available free time and attending meetings seem to be irrelevant here. The estimates are
very similar for all online participation forms which suggests that the results are valid.
19
The really interesting question is what happens once people use the Internet. Here, the
main predictor of online participation becomes Internet abilities in all three cases.11
Having an advanced use of ICTs at work also matters for e-contact and e-petition. 12 The
effect of age changes: once we have Internet use, the older the person is the more likely
to be active in online participation. Income is not significant but there is a small positive
effect of education on e-donation and e-petition. Being a woman is positively associated
to e-petition, and so is time. Civic skills are still significant in some cases: meeting for
e-contact and e-petition, exposing for e-donation. However writing at work or at other
usual activities is negatively associated, rather than positively as expected, to e-contact
and e-donation.
In sum, online resources and particularly online skills are important predictors of online
participation once access to the Internet is achieved. Taking into account that online
skills are coded in nine categories the impact of this variable seems sizeable 13.
Traditional resources are sometimes related to participation in the expected way,
sometimes unrelated and sometimes related in the unexpected direction.
Are resources more relevant for online than for offline participation?
Now we can finally go back to the equality question and compare the impact of
resources on online and offline participation. Once the effect of socio demographics and
resources has been properly estimated for online activities, the strength of the
coefficients can be compared with those of the regression analysis for offline
participation. We want to know if there are any significant differences in the type of
resources that explain online and offline participation. Previous research has stated that
the type of resources at play is different. Best and Krueger (2005) found that race and
political interest were important for both, while age and civic skills were important only
for offline participation and gender, and internet skills (together with online
mobilization) were important for online participation. This question is addressed in
table 4 which displays the estimates of the effects of these variables on online
11
This is similar to what di Genaro and Dutton (2006) find using number of years using the Internet, self
rated abilities, and actual proficiency with a different more descriptive technique.
12
However, physical resources (home access to Internet) is not significant (not reported).We share with
Best and Krueger (2005) this finding.
13
The results have not been transformed into predicted probabilities or displayed graphically because of
the difficulties of doing this for a Heckman selection model. We found no such transformation in the
literature.
20
participation (i.e. the results of the regression equation of the Heckman selection model)
and new regressions with socio demographics and resources predicting offline
participation. The impact of those explanatory factors can be therefore compared for the
same modes carried out online and offline.
Table 4. Comparison of the effect of resources for online and offline participation
Contact
Woman
Age
Education
Income
Time01
Write
Meeting
Expose
Int. Abilities
Some ict
Advanced ict
Constant
N
Pseudo R2
Coef.
-0,415**
0,183
0,022***
0,007
-0,039
0,112
-0,002
0,074
-0,163
0,277
0,447*
0,268
1,065***
0,291
0,229
0,232
0,023
0,048
0,528**
0,261
0,398
0,320
-4,077***
0,573
3013
0,0521
Econtact
Coef.
0,018
0,024***
-0,042
-0,017
0,083
-0,410*
0,192*
0,150
0,118***
0,147
0,342**
1,937***
Donate
Coef.
0,463***
0,107
0,014***
0,004
0,248***
0,073
-0,042
0,042
0,058
0,171
-0,060
0,160
0,327**
0,150
0,634***
0,150
0,036
0,028
0,242
0,151
0,050
0,203
-2,666***
0,336
3003
0,092
Edonation
Coef.
0,156
0,023***
0,190**
0,016
-0,004
-0,555**
0,195
0,225*
0,139***
0,062
0,083
-3,350***
Petition
Coef.
0,342***
0,106
-0,001
0,004
0,206**
0,075
0,019
0,041
-0,170
0,181
0,263
0,166
0,575***
0,152
0,022
0,147
0,058**
0,028
0,144
0,158
-0,022
0,204
-2,365***
0,336
3005
0,085
Epetition
Coef.
0,219**
0,016**
0,151*
0,033
0,297*
-0,156
0,246**
0,158
0,138***
0,284*
0,407**
-3,418***
Source: CIS 2673
* p<0,1; ** p<0,05; *** p<0,005
a
The variable income has many missing values and they have been imputed by multiple
imputation in order to avoid loosing information. See table 3.
Standard errors are below the coefficient for offline modes (for online modes see table 3). The
reference category for women is men, for advanced and basic ICT is no ICT knowledge
required at work or normal activities.
In online participation the gender bias in contact is smaller, and so is the positive effect
of being a woman that we find in petition and donation. Age shows a similar effect in
online and offline modes, the older the more likely to participate, except for offline
petition where there is no significant effect. The effect of education is not significant for
21
contacting once controlling for other factors, both offline and online. The education
coefficient is slightly smaller in the online modes of donation and petition.
Income does not seem to have any significant effect in any of the modes considered.
This implies that the association found in the bivariate analyses can entirely be
attributed to the fact that people in well off families have more traditional and
technological participatory resources, and that they have different socio economic
characteristics. Time is positively related in a statistically significant way only with epetition. The effect of civic skills is smaller in online forms of participation, for meeting
and exposing. The effect of writing is more difficult to interpret: more writing abilities
facilitate offline contact and petition, but affect negatively online contact and donation14.
As we have seen in the previous section Internet resources, and in particular Internet
abilities, are important to predict online participation. But they are not irrelevant to
predict offline participation. Needing knowledge of ICTs at work or usual activities has
a strong positive impact on the probability to contact politicians offline and Internet
abilities foster involvement in petitions.
The general picture is that there are strong similarities in the factors predicting online
and offline participation in different activity modes, once we control for the impact of
socio demographics and resources on the probability to use the Internet. There are
however a few exceptions. Gender, education and meeting and exposition skills are
somewhat less influential on online participation and Internet skills are clearer
predictors of online involvement.
Conclusion
In this paper we have addressed several related questions. First, online participation is
increasingly widespread in Spain, as it is in other countries. The levels of activity are
not as high as in traditional offline activities, but they are not negligible. As they can
only be expected to grow as Internet access and presence in daily life increases, there
14
This fact is probably due to the introduction of the control for needing basic or advanced knowledge of
ICTs at work. People who write at work but do not use ICTs there probably write by hand and work in
non-qualified jobs.
22
are reasons to claim that they should be routinely studied in academic accounts of
political participation.
Participation in online activities is highly skewed towards the better educated and the
better off. In these instances inequalities in participation due to education and income
are even stronger than in the offline activities. On the contrary, gender biases are less
visible. Young people participate disproportionately more than expected due to their
demographic weight among Internet users. Of course, this is partly due to the fact that
older citizens barely take part in this kind of online activities, but this finding gives
more counterevidence to scholars who claim that the young generations are increasingly
disengaged. Young people are participating in online activity forms which are not
always considered as political participation, and this might be a way to transmit their
voices and opinions to the political system.
The multivariate analysis has lead to two interesting results. On the one hand, we have
been able to distinguish the impact of socio demographics and resources on Internet use
and on online participation. Most of these variables are relevant to predict Internet use,
but less so for political involvement. Online resources, and in particular abilities, are the
single more important predictors of online participation and therefore have to be
included in explanatory models of this kind of activities. On the other hand, the
determinants of online and offline participation in the same activity modes have more
similarities than dissimilarities. The innovative research design used in this paper
allowed to compare the impact of resources and socio-demographics in the same modes
of activity but in different ways, once the impact those on access to the Internet is taken
into account. The findings point out that there are clear continuities of the
characteristics of offline activities in the digital world. However, the impact of some
traditional sources of inequality is somewhat more limited in the online sphere where,
on the other hand, there are new sources of inequality. Online resources are very
relevant to predict all modes of online participation, but only have a positive impact on
certain offline activities.
23
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Variable coding
For question wording see www.polnetuab.net
E-contact: 1= has contacted a politician or administration by email in the last 12
months; 0= has not contacted
E-donation: 1= has donated money to an organization via the Internet in the last 12
months; 0= has not donated money
E-petition: 1= has signed an online petition in the last 12 months; 0= has not signed an
online petition
Contact: 1=has contacted a politician or administration by email in the last 12 months;
0= has not contacted
Donation: 1= has donated money to an organization in the last 12 months; 0= has not
donated money
Petition: 1= has signed a paper petition in the last 12 months; 0= has not signed an
petition
Woman: 1= woman; 0= man
Age: 18 to 95 years
Education: 1= primary; 2= lower secondary; 3= upper secondary; 4= tertiary
Big city: 1=lives in a city with more than 400.000 inhabitants; 0= lives in a city with
less than 400.000 inhabitants
Write: 1= writes letters and reports at work or normal activities; 0= does not write
Meeting: 1= attends or organizes meetings at work or normal activities; 0= does not
attend meetings
Expose: 1= exposes in public and makes oral presentations at work or normal activities;
0= does not expose in public
Income: 1= 300 euros or less; 2= 301 to 600 euros; 3= 601 to 900 euros; 4= 901 to 1200
euros; 5= 1201 to 1800 euros; 6= 1801 to 2400 euros; 7= 2401 to 3000 euros; 8= 3001
to 4500 euros; 9= 4501 to 6000 euros; 10= more than 6000 euros.
Time: free time in minutes each day, ranging from 0 (60 minutes) to 1 (7 hours)
Internet Abilities: summatory index from 0 (makes no use of the Internet to 9 (searches
information, buys, deals with the bank, uses email, chat, calls online, shares files,
maintains a web or blog, and navigates with no purpose)
Some ICTs: 1= needs basic knowledge of ICTs at work or normal activities; 0= does not
need it
Advanced ICTs: 1= needs advanced knowledge of ICTs at work or normal activities; 0=
does not need it
26
27