IS RETIREMENT A GOOD MOMENT FOR BECOMING COMPUTING LITERATE?

Given that 2012 has been labeled as the “European Year for Active Ageing and International Solidarity”, we address the issue of how older people embody computer science to their lives. The aim of this study is to disentangle the characteristics of older people who know computer science and test if older people consider retirement as a good moment for learning this issue. We use data from the Survey of Living Conditions of Older People (2010) carried out by the IMSERSO to individuals aged 65 and older. This is the most updated available information. This dataset allow us to differentiate among three categories of users: (1) “pre-users”, who knew computer science before getting retired (6.79%), (2) “post-users”, who became computer literate after retirement (2.76%) and (3) “never users”, who have never expressed interest in it (90.45%).
As compared to “never users”, people qualified as “pre-users” or “post-users” are to a large extent male, aged 65-69, with high school or college education, income higher than 900 €/month and, they tend usually combine this activity with others such as tourism, sports and volunteerism.
The level of education is significantly different among groups. Around 62% of computer users (“pre-users” or “post-users”) have finished high school of college, whereas 76% of “non-users” have not even finished elementary education. On the other hand, 32% of users know one foreign language (English, French, German or Italian) as opposed to only 3% of “non-users”.
To determine which variables affect the probability of becoming “post-user” we consider a two-period sequential model. The first period correspond to the stage prior to retirement, while the second one refers to the post-retirement phase. We use a bivariate probit selection model because it allows for correlation between the unobservable variables affecting the probability of being “not-user” in the first step and the unobservable variables that are meaningful for the probability of becoming “new-user” in the second phase. The probability of becoming “post-user” increases by 151% for those who consider that retirement is “an opportunity for pursuing one’s particular hobbies” and it increases by 71% for those who report that their main fear for the future is to lose memory. However, living in a municipality with less than 5,000 inhabitants or being housekeeper during working life decreases this probability.
On the other hand, we conclude that the best moment for becoming computer literate is just after retirement because the probability of becoming “post-user” increases by 245% for the cohort aged 65-69 years.
As final recommendations, we consider that computing courses should broaden their geographical coverage so that they could reach to older people living in small and rural municipalities. Second, the design of these courses should include topics of interest for different profiles of students according to their level of education and previous relation with economic activity.