Lina Hedman

Neighbourhood Choice and Neighbourhood Reproduction

Although we know a lot about why households choose certain dwellings, we know relatively little about the mechanisms behind their choice of neighbourhood. Most studies of neighbourhood choice focus only on one or two dimensions of neighbourhoods: typically poverty and ethnicity. In this paper we argue that neighbourhoods have multiple dimensions and that models of neighbourhood choice should take these dimensions into account. We propose the use of a conditional logit model. From this approach we can gain insight into the interaction between individual and neighbourhood characteristics which lead to the choice of a particular neighbourhood over alternative destinations. We use Swedish register data to model neighbourhood choice for all households which moved in the city of Uppsala between 1997 and 2006. Our results show that neighbourhood sorting is a highly structured process where households are very likely to choose neighbourhoods where the neighbourhood population matches their own characteristics. We find that income is the most important driver of the sorting process, although ethnicity and other demographic and socioeconomic characteristics play important roles as well.

Intergenerational transmission of neighbourhood poverty: An analysis of neighbourhood histories of individuals

The extent to which socioeconomic (dis)advantage is transmitted between generations is receiving increasing attention from academics and policymakers. However, few studies have investigated whether there is a spatial dimension to this intergenerational transmission of (dis)advantage. Drawing on the concept of neighbourhood biographies, this study contends that there are links between the places individuals live with their parents and their subsequent neighbourhood experiences as independent adults. Using individual-level register data tracking the whole Stockholm population from 1990 to 2008, and bespoke neighbourhoods, this study is the first to use sequencing techniques to construct individual neighbourhood histories. Through visualisation methods and ordered logit models, we demonstrate that the socioeconomic composition of the neighbourhood children lived in before they left the parental home is strongly related to the status of the neighbourhood they live in 5, 12 and 18 years later. Children living with their parents in high poverty concentration neighbourhoods are very likely to end up in similar neighbourhoods much later in life. The parental neighbourhood is also important in predicting the cumulative exposure to poverty concentration neighbourhoods over a long period of early adulthood. Ethnic minorities were found to have the longest cumulative exposure to poverty concentration neighbourhoods. These findings imply that for some groups, disadvantage is both inherited and highly persistent.

The Impact of Residential Mobility on Measurements of Neighbourhood Effects

Neighbourhoods and cities are dynamic; their characteristics and relative positions change over time due to constant moves in and out. However, neighbourhood effect theory and most attempts to quantitatively estimate neighbourhood effects seem to treat neighbourhoods as if they were static. This paper argues that such a view is not only strange but may also result in biased estimates. Four methodological challenges are highlighted that are directly related to mobility: (1) measures of exposure time; (2) neighbourhood change; (3) selection bias; and (4) endogeneity. These are all topics worthy of scholarly interest in themselves, but also challenges that all neighbourhood effect studies must address to convincingly argue that their results are indicative of causal relationships—results of neighbourhood transmission mechanisms—and not just statistical correlations. The paper discusses how and to what extent these challenges have been met by the quantitative neighbourhood effect literature and gives directions to future research.

Neighbourhood Income Sorting and the Effects of Neighbourhood Income Mix on Income: A Holistic Empirical Exploration

An econometric model is specified in which an individual’s income and the income mix of the neighbourhood in which the individual resides are endogenous, thus providing a holistic model of phenomena that previously have been fragmented into neighbourhood effects and neighbourhood selection literatures. To overcome the biases from selection and endogeneity, the parameters of this model are estimated using instrumental variables in a fixed-effect panel analysis employing annual data on 90 438 working-age males in Stockholm over the 1995–2006 period. Evidence is found of both neighbourhood effects and neighbourhood selection, but more importantly, it is found that the magnitudes of these effects are substantially altered when taking selection and endogeneity biases into account, compared with when only controlling for selection. When taking endogeneity into account, the apparent impact of neighbourhood income mix on individual income is magnified and the effect of individual income on the percentage of high income in the neighbourhood is magnified.

Linking Integration and Housing Career: A Longitudinal Analysis of Immigrant Groups in Sweden

This study investigates the extent to which immigrant groups are integrated in the Stockholm region through an analysis of their housing careers. Housing conditions are linked to many important life course events, as well as to the resources and preferences of each individual family. Housing conditions influence integration, but factors related to integration can also be a cause of housing conditions. In the study, we take a truly longitudinal approach to housing careers by exploring differences in the timing of career-related events between several immigrant groups and native Swedes. The objective of the study is to explore whether the housing careers of immigrant groups follow family and work careers in a similar way as the native population. The data are derived from a longitudinal individual-level register-based data-set maintained by Statistics Sweden. The analysis is carried out by way of survival analysis. Our results confirm that there are substantial ethnic differences in housing careers that cannot be attributed to family composition or career. Our results also highlight three important factors that reduce the differences between native Swedes and immigrants groups in the tendency to enter homeownership: university degree, type of municipality and duration of stay in Sweden.

Measuring Neighbourhood Effects Non-experimentally: How Much Do Alternative Methods Matter?

European research attempting to quantify neighbourhood effects has relied almost exclusively on analyses of observational data. No consensus has emerged, perhaps because a variety of statistical procedures have been employed. We investigate this by exploring the degree to which alternative, non-experimental statistical methods yield different estimates of the relationship between neighbourhood income mix and individual work income when applied to the same longitudinal database. We find that results are highly sensitive to the statistical approach employed. Methods controlling for geographic selection bias generally reduce the negative association between low-income neighbours and individual earnings, but substantial differences across models remain. Controlling for both selection and endogeneity produces larger associations and evidence of non-linearity, something that is hidden in models only controlling for selection. All methods suffer shortcomings, so we argue for multi-method investigations to identify robust findings, with instrumental variables and fixed effects on non-mover samples being preferred. In our case, we find a substantial neighbourhood effect, regardless of the method employed.

Determinants of immigrants’ entry to homeownership in three Nordic capital city regions

Abstract The extent of homeownership among immigrants may be seen as an indicator of integration and as a determinant of ethnic residential segregation. Studies have shown differences in the determinants of homeownership between immigrants and natives, indicating that variation in homeownership is not only a function of differences in economic resources. These studies have largely focused on Anglo‐American contexts, using mostly cross‐sectional data. We apply survival analysis methods to analyse the determinants of entry to homeownership in the capital regions of three Nordic countries – Denmark, Finland and Sweden – utilizing longitudinal individual‐level register‐based datasets. We find that differences in entry to homeownership between natives and different immigrant groups cannot be explained by differences in socio‐economic background factors. We also find differences in the effects of these factors. Effects of income are generally weaker among non‐Western immigrants and immigrants are less responsive to changes in household composition. The share of non‐Western immigrants in the neighbourhood is only weakly related to entry to homeownership, while immigrants and natives living in public rental housing tend to be slightly less inclined to move to homeownership. Weaker income effects among immigrants, weak effects of ethnic segregation and the importance of the public rental sector differentiate our results from earlier findings. Weaker income effects may indicate that uncertainty about the future also affects middle‐income immigrants. Differences between the three contexts in housing markets and policies do not seem to matter much, although the results indicate that difficult access to the private rental sector may push immigrants to homeownership.

The uneven distribution of capital gains in times of socio-spatial inequality: Evidence from Swedish housing pathways between 1995 and 2010

Housing wealth is the largest component of wealth for a majority of Swedish households. Whereas investments in housing are merely defined by income, the returns on this investment (capital gains) are dependent on local housing market dynamics. Since the 1990s, local housing market dynamics in Swedish cities have been altered by the upswing in levels of socio-spatial inequality. The simultaneous up- and downgrading of neighbourhoods is reflected in house price developments and exacerbates the magnitude of capital gains and losses. This article proposes that the selective redirection of housing pathways that causes an upswing in socio-spatial inequality translates into an uneven distribution of capital gains as well. A sequence analysis of the housing pathways of one Swedish birth cohort (1970–1975), based on population-wide register data (GeoSweden), is used to explain differences in capital gains between different social groups in the period 1995–2010. The results indicate higher capital gains for individuals with higher incomes and lower gains for migrants. When socio-spatial inequality increases, the more resourceful groups can use their economic and cultural capital to navigate through the housing market in a more profitable way.

Non-Linear Choice Modelling with Gaussian Processes: A Case Study of Neighbourhood Choice in Stockholm

We present a non-parametric extension of the conditional logit model, using Gaussian pro- cess priors. The conditional logit model is used in quantitative social science for inferring interaction effects between personal features and choice characteristics from observations of individual multinomial decisions, such as where to live, which car to buy or which school to choose. The classic, parametric model presupposes a latent utility function that is a linear combination of choice characteristics and their interactions with personal features. This imposes strong and unrealistic constraints on the form of individuals’ preferences. Extensions using non-linear basis functions derived from the original features can ameliorate this problem but at the cost of high model complexity and increased reliance on the user in model specification. In this paper we develop a non-parametric conditional logit model based on Gaussian process logit models. We demonstrate its application on housing choice data from over 50,000 moving households from the Stockholm area over a two year period to reveal complex homophilic patterns in income, ethnicity and parental status.