The multilevel approach can be a fruitful methodological framework in which to formulate the micro-macro relationships existing between individuals and their contexts. Usually, place of residence is taken as proxy for context. But individuals can be classified at the same level in more than one way. For example, not only may place of residence be relevant, but birthplace, household or working relations may also be taken into account. Contextual effects can be better identified if multiple classifications are simultaneously considered. In this sense, data do not have a purely hierarchical structure but a cross-classified one, and become very important to establish whether the resulting structure affects the covariance structure of data. In this paper, some critical issues arising from application of multilevel modelling are discussed, and multilevel cross-classified models are proposed as more flexible tools to study contextual effects. A multilevel cross-classified model is specified to evaluate simultaneously the effects of women's place of birth and women's current place of residence on the choice of bearing a second child by Italian women in the mid-1990s. © Springer-Verlag 2002.
- Contextual effects
- Cross-classified hierarchical structure
- Reproductive behaviour
- Micro-macro relationships