Neighborhood Social Mix and Adults' Income Trajectories: Longitudinal Evidence from Stockholm

Abstract

We investigate the relationship between neighborhood income composition and income trajectories of adults, employing annual panel data from Stockholm over the 1991–2008 period and multiple measures of neighborhood income mix. We advance the human geography literature in three ways by quantifying neighborhood effects that: (1) are unusually precise due to our large sample size; (2) are arguably causal and unbiased due to the econometric techniques employed; (3) are potentially heterogeneous, varying according to gender, income group, and ethnicity. Our innovative, fixed‐effect change modeling indicates that neighborhood income mix affects subsequent one‐ and five‐year income trajectories of residents in highly heterogeneous ways according to gender, income and ethnicity, and for some groups this effect is substantial. The evidence supports on Pareto improvement grounds a social mix policy that attempts to reduce the incidence of lower‐income dominant neighborhood environments and replace them with more mixed or middle‐income dominant ones.

Using sibling data to explore the impact of neighbourhood histories and childhood family context on income from work

“…Most of these studies find evidence of neighbourhood effects (there are however also examples of studies finding no effects at all; see [19, 20, 21]). Studies have also found neighbourhood effects to vary by individual characteristics [22, 23], spatial scale [24, 25] and length of exposure to certain neighbourhood types [23, 26, 27].…”

Modelling Neighbourhood Effects in Three Dutch Cities Controlling for Selection

“…For employed household heads moving to a new neighbourhood, a change in their income can be caused primarily by the aforementioned social mechanisms, but also by a number of other neighbourhood characteristics. In their study of the influence of neighbourhood social mix on Stockholm's inhabitants' income, Galster et al (2016) describe the potential influence of local crime levels, institutional resources and job accessibility, widely studied in the literature. Neighbourhood average income tends to be a good proxy for these characteristics because of local self-reinforcing processes of spatial inequality-for example, well-connected neighbourhoods tend to have more expensive dwellings, which attracts richer inhabitants, who further profit from the easy access to jobs and services (Toft & Ljunggren, 2016).…”

Een ontspannen perspectief op residentiële segregatie

“…Ten aanzien van de intensiteit moet nog worden opgemerkt dat in Stockholm ook buurten met meer dan 40 procent lage inkomens meestal nog sterk gemengd zijn. In het buurttype dat gedomineerd wordt door lage inkomens vinden we gemiddeld 59 procent huishoudens met lage inkomens, maar ook nog altijd 28 procent met middeninkomens en 13 procent met hoge inkomens (Galster, Andersson & Musterd, 2016).…”