Grandchild care and welfare state arrangements in europe

As a consequence of increased life expectancies and the overall improved health status of elderly people in industrialized countries, grandparents and grandchildren are now sharing a longer period of their lives together, from which they can both actively benefit. In addition, grandparents help their children by looking after their grandchildren and are consequently an important service provider in the domain of childcare, especially for mothers active in the labour market. The analyses, which are based on the Survey of Health, Aging and Retirement in Europe (Austria, Belgium, Denmark, France, Germany, Greece, Italy, the Netherlands, Spain, Sweden and Switzerland), show significant country differences in the occurrence and intensity of grandchild care in Europe: whereas grandparents in southern Europe engage less often but more intensively in childcare, grandchild care is provided more often but much less intensively in northern Europe. Multilevel logistic regression models show that country-specific differences are associated with welfare state arrangements and, specifically, with public investments in childcare infrastructures. Public investments ‘crowd in’ grandparental willingness to engage in childcare but ‘crowd out’ the intensity of this intergenerational time transfer. Family and state thus complement one another, with grandparents taking over sporadic, less time-intensive care while public institutions provide regular, time-consuming childcare services

Parallel Problem Solving from Nature – PPSN X 10th International Conference Dortmund, Germany, September 13-17, 2008 Proceedings

Drift analysis is a powerful tool used to bound the optimization time of evolutionary algorithms (EAs). Various previous works apply a drift theorem going back to Hajek in order to show exponential lower bounds on the optimization time of EAs. However, this drift theorem is tedious to read and to apply since it requires two bounds on the moment-generating (exponential) function of the drift. A recent work identifies a specialization of this drift theorem that is much easier to apply. Nevertheless, it is not as simple and not as general as possible. The present paper picks up Hajek’s line of thought to prove a drift theorem that is very easy to use in evolutionary computation. Only two conditions have to be verified, one of which holds for virtually all EAs with standard mutation. The other condition is a bound on what is really relevant, the drift. Applications show how previous analyses involving the complicated theorem can be redone in a much simpler and clearer way. Therefore, the simplified theorem is also a didactical contribution to the runtime analysis of EAs