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AbstractSince the early 1990s, a number of researchers have put forward evidence of strong demographic effects on housing demands. More recently, a number of studies have pointed to the effect of housing market conditions on family formation. This implies that housing markets are influenced by population change, but also that the housing market conditions influence population change. In this study, a model of demographic effects on the housing market that has been estimated on regional panel data will be used to explore these interrelationships. First, it is shown that the age effects identified in sub‐national data are present also in cross‐national data. Second, it is shown that high demographic pressure on house prices is associated with low fertility. The findings are discussed in relation to the Easterlin's hypothesis about the effects of cohort crowding on fertility. In Easterlin's model, cohort effects on earnings drive fertility shifts. The analysis presented, herein, indicates that cohort effects in the housing market can be equally important. Finally, the estimated models are used to outline possible future trends in house prices and fertility. The results indicate that house price increases can slow down and that there can be some recovery from very low fertility rates.

The long-term effect of low birth rates is a decline in the population share of children and young adults. How will such changes in age structure affect the housing market? In this article, panel data sets for Swedish municipalities from 1981 to 2006 are used to answer this question. The use of panel data makes it possible to control for the effect of national-level policy shifts and macroeconomic events through the introduction of fixed time effects. The results show that population aging could lead to less rapid house price growth in the first decades of the twenty first century, compared to the last decades of the twentieth century. These results also hold when local population growth, income growth, and educational levels are controlled for.

This paper provides evidence of segregation-generated differences in political recruitment. Focusing on social-geographical differentiation in the urban landscape, we evaluate—in prior work largely neglected—contextual effects on requests for political participation. Consistent with previous research, our analyses suggest that political activists, who try to convince others to participate, systematically use a set of selection criteria when deciding whom to approach. However, using data based on a sample of inhabitants of Swedish cities and properties of their neighbourhoods, we also present evidence for aggregate-level social exclusion influences on individual-level recruitment efforts. Consistent with our theoretical framework, results indicate that the contextual effect stems both from the disproportional population composition in residential areas, and from recruiters' rational avoidance of areas marked by high levels of social exclusion. The net result, we conclude, is a reinforcement of urban inequalities when it comes to the chances to be invited to political life

This paper analyses whether a multi-scale representation of geographical context based on statistical aggregates computed for individualised neighbourhoods can lead to improved estimates of neighbourhood effect. Our study group consists of individuals born in 1980 that have lived in Sweden since 1995 and we analyse the effect of neighbourhood context at age 15 on educational outcome at age 30 controlling for parental background. A new piece of software, Equipop, was used to compute the socio-economic composition of neighbourhoods centred on individual residential locations and ranging in scale from including the nearest 12 to the nearest 25,600 neighbours. Our results indicate that context measures based on fixed geographical sub-divisions can lead to an underestimation of neighbourhood effects. A multi-scalar representation of geographical context also makes it easier to estimate how neighbourhood effects vary across different demographic groups. This indicates that scale-sensitive measures of geographical context could help to re-invigorate the neighbourhood effects literature.