This study addresses issues of digital divide among households and individuals by using micro-data analysis of ICT usage patterns. The analysis includes data from 18 European countries (2008), Korea (2008) and Canada (2007). Inequalities in computer and Internet use are analysed in a two-step approach. First, the paper tries to better quantify and understand the factors that separate the ‘haves’ and the ‘have-nots’. Second, it tries to explain observed differences in the frequency and type of Internet use as a result of the socio-economic characteristics of households and individuals.
The study applies logistic regression and multi-linear regression models to measure the influence of one variable while controlling for the other variables. In particular, age, gender, educational attainment, employment situation, geographical location, household income and composition are used to explain the observed differences in computer and Internet access and use (first part) and Internet frequency of use, selected Internet activities, and Internet scope of use (second part).
The study proves the feasibility of performing micro data analysis of surveys of ICT usage in households and by individuals. It shows that:
Low income is the single most important factor for non access to a computer and to the Internet. On average, the odds that a high-income household in Europe has access to a computer and to the Internet are over 4 times higher than for a low-income household.
The presence of children is the second most important factor for the access to a computer and to the Internet: on average, the odds for a household with one or more children in Europe are up to 3.9 times higher than for a household without children.
Living in a town in Europe increases the odds to have access to a computer and to the Internet by over 30% as compared to living in the countryside.
Age and economic inactivity are by far the most important factors for having never used a computer or the Internet. The odds are over 4 times higher for European inhabitants aged 65-74 years and up to 2.6 times for those out of the labour force. (Low) income, gender (female) and (lack of) children do play a role but their effect is smaller.
Becoming unemployed is the most important factor for stopping using the Internet. The odds that a European inhabitant has not used the Internet over the last 3 months are about 2 times higher if he is unemployed or out of the labour force.
Education is the most important determinant of the intensity of Internet use. The odds that an individual uses the Internet everyday increases by 2.4 times in Europe and by 3.6 times in Korea if he has a university degree and above.
Being a student is the second most important determinant of the intensity of Internet use – the odds that a student uses the Internet every day are 2 times higher both in Europe and in Korea.
The third factor explaining the intensity of Internet use is income in Europe (the odds are over 70% higher for the high-income households) and broadband access in Korea (the odds are 2 times higher for households with a broadband connection).
Young age and higher education are the main determinants for the scope of Internet use in Canada, Europe and Korea.
Montagnier, P. and A. Wirthmann (2011), “Digital Divide: From Computer Access to Online Activities – A Micro Data Analysis”, OECD Digital Economy Papers, No. 189, OECD Publishing.OECD Digital Economy Papers.No. 189
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