Quantitative Spatial Analysis of Micro and Macro Data: Methodological Challenges and Solutions 1 |
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| Chair | Professor Henning Best (TU Kaiserslautern ) |
| Coordinator 1 | Professor Corinna Kleinert (Leibniz Institute for Educational Trajectories) |
| Coordinator 2 | Mr Tobias Ruettenauer (TU Kaiserslautern) |
| Coordinator 3 | Dr Michaela Sixt (Leibniz Institute for Educational Trajectories ) |
A central idea of social sciences is that individuals are embedded in social contexts and are influenced by them. Many relevant social mechanisms can be expected to have spatial references. Researchers face the challenge of theoretically describing these spatial dimensions and their importance for the respective social processes. At the same time it has become evident that the conceptualisation of spatially structured contexts is nontrivial. In particular, research on the modifiable areal unit problem (MAUP) has shown that the definition of the area where the explanatory factors are measured typically affects the results, even when the definitions are relatively similar.
The aim of this paper is to theoretically specify adequate areas – given the particular research question – and to test these expectations by comparing different spatial operationalizations. Thereby we go beyond the classical approach of considering individuals within fixed structure of proximate contexts. While often justified, this approach is not suited for capturing flexible and overlapping individual contexts in terms of areas of individual action or perception. For this reason we make use of ego-centred areas of different radii to measure contextual indicators.
Applying this approach we assess the impact of social composition of the proximate living environment on young people’s educational aspirations. In previous research, neighbourhood conditions have frequently been considered as among the main explanatory factors for educational outcomes. Neighbourhood characteristics have often defined in terms of unfavourable neighbourhood conditions. Because of noticeable difference with regard to social policies and the level of socio-spatial segregation, research in (continental) Europe has studied neighbourhood effects rather from the perspective of living in advantaged neighbourhoods than from the perspective of consequences of living in the disadvantaged quarters. Our paper in particular investigates whether there is an effect on young people’s aspirations to attend higher education when living in an environment that is characterised by a high share of academics
Besides the substantial question on the existence of this effect we explicitly test our expectations of where to locate the assumed mechanisms. A further challenge is the possible heterogeneity of spatial context effects; previous studies have shown that there are significant differences in the degree to which various groups are susceptible to specific local context conditions. In our paper we investigate whether the effects of the living environment can be differentiated by individual characteristics such as social and migration background as well as sex.
Research on ethnic diversity effects suggests, by and large, negative relationships with indicators of social cohesion, such as social trust and civic engagement. Most of the studies in this regard have relied on cross-sectional survey data merged with neighborhood-level information on ethnic diversity. However, this type of research design remains short on the question whether residents are merely influenced by their neighborhood or rather gain information about ethnic diversity from contexts they spend time in other than their immediate residential environment. On the other side, studies on regional contexts have difficulties to convincingly link regional context and individual exposure. In this paper, we focus on cities as contextual units, which so far have largely been overlooked in research on contextual ethnic diversity. In addition, we consider residents’ assessment of city infrastructure as proxy of institutional capacity, which we expect to moderate the way immigration affects social cohesion. To do so, we use survey data on European cities from the European Commission Urban Audit and Large City Audit projects (5 waves; 2004-2015) combined with structural city-level information (e.g., proportion of immigrants). This empirical set-up further has two methodological advantages: (1) The large numbers of respondents per city-year allows aggregating individual-level information to reliable city-level indicators. (2) Using multi-level models with city fixed effects, we are able to gauge the longitudinal structure of macro-level indicators. Our results show that an increase in city-level immigration is negatively related to perceptions of neighborhood safety as well as trust in neighbors and community members. Moreover, the negative relationship is mitigated in cities with high institutional capacity.
Are people who live in homogenous neighborhoods that border ethnically diverse neighborhoods (or are even encircled by them) more xenophobic? This socio-spatial constellation, which is known as the ‘halo effect’ hypothesis, synthesizes two prominent explanations of xenophobia: as the direct neighborhood offers little opportunities for positive intergroup contact, the neighboring ethnically diverse neighborhoods can instill feelings of competition and group threat, which eventually result in xenophobia, with full force. Beyond classic hypotheses about the contextual effects of population shares (e.g., % immigrants, poor, or unemployed), this perspective emphasizes the importance of neighborhoods’ local embeddedness. Yet, analyses based on geo-coded ALLBUS 2014 data provide neither support for the halo effect hypotheses among the general population nor among xenophobia-minded subpopulations. Nevertheless, our study demonstrates the methodological characteristics and challenges of such a spatial analysis of the geocoded ALLBUS data and discusses plausible reasons why our results deviate from earlier American and European studies.
The analysis of environmental quality and socioeconomic composition on the level of spatial units has become a standard approach of empirical research on environmental inequality. The majority of prior studies relies on cross-sectional spatial data and hence cannot adequately study the causal mechanisms leading to the unequal distribution of environmental. Thus, it remains a puzzle whether selective move-in, selective move-out, selective siting by the industry or a combination of these factors lead to an uneven distribution of environmental hazards across different socio-economic groups. In addition, most of the research has been conducted in the US and empirical results from continental Europe and especially Germany are rare.
In this paper, we study the spatial distribution of air pollution emissions and the connection to socio-economic factors in Germany between 2001 and 2012. The analysis relies on a combination of data from the European Pollutant Release and Transfer Register (EPRTR) and socio-economic data on the level of 4,521 German municipalities. The amount of pollution from the EPRTR facilities is matched to the communities within a 5 km radius of the facility location proportionate to its spatial overlap. To investigate the causal mechanisms producing the unequal distribution of environmental pollution, we use a fixed-effects time-series approach with a correction for spatial autocorrelation (FE-SAR). The results identify selective siting and selective move-in as a cause of the unequal distribution of environmental harm, while contradicting the selective move-out explanation. However, we need to be aware of potential problems due to the use of spatially aggregated data.