Residential Context and Childbearing: Application of Multilevel Analysis to Study Individual and Contextual Determinants of Fertility

Fertility levels are below replacement level in most industrialised countries and have further declined in recent years. However, they vary significantly within countries by residential context. Fertility is high in rural areas and small towns and low in large cities. The reasons for spatial variation in fertility remain unclear. Some studies argue that fertility levels vary between places because different people live in different settlements. Others emphasise the importance of factors related to immediate living environment. The role of selective migrations has also been discussed.

This PhD project will investigate childbearing patterns by residential context in Britain, a country with a significant spatial fertility variation. The objectives are: First, to determine the extent to which spatial variation in childbearing patterns is attributed to compositional characteristics and selective migrations, and what role contextual factors play. Second, to investigate how contextual factors influence individuals' childbearing behaviour. Third, to develop a spatial multilevel multiprocess hazard model to properly measure the effect of living environment on individuals' childbearing behaviour. An understanding of how residential context influences fertility is essential to improve our understanding of the causes of low fertility in industrialised countries.

The project will develop and apply a spatial multilevel multiprocess hazard model to data from the ONS Longitudinal Study, the Scottish Longitudinal Study and the British Household Panel Survey to determine how contextual factors shape individuals' childbearing behaviour. The performance of the proposed approach will be compared to that of conventional methods using maximum likelihood and Bayesian methods. The project will provide rich and reliable information on spatial fertility variation in Britain and will improve our understanding of the causes of high fertility in some areas and low fertility in others. The developed method could be applied to study contextual determinants of other domains of individuals' behaviour (e.g. health, employment, residential relocations).