Using Survey Data for Spatial Analysis |
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| Chair | Professor Nina Baur (TU Berlin ) |
| Coordinator 1 | Ms Linda Hering (TU Berlin) |
| Coordinator 2 | Ms Cornelia Thierbach (TU Berlin) |
Often analyses of economic and social participation of individuals lack considerations about regional disparities. However, for a detailed description of current but also future occupation-specific developments concerning employment and activity, the regional dimension often captures valuable information. In the assessment of future labour market outcomes it is, for example, of particular importance in which regions the labour market is comparably tight and in which it is very concentrated on a few specific industries.
Just as industries are very different in terms of their economic development, they are even more so at the regional level. Both the supply and demand side of the labour market are subject to regional differences: On the one hand, the regional economic structure with its specific industrial composition, business size structure, and export orientation defines skill demand and the region’s exposure to structural change (for example by globalization and digitization). On the other hand, the regional population growth as well as their educational and occupational behaviour, determines the supply of skills. Furthermore, both sides are intertwined as, for example, the age and qualification structure of the population influences consumption, thereby steering employment and wages, which, in the end, alters consumption again. Eventually, through commuting and internal migration also the regional labour markets are connected.
Using the example of the German labor market, it can be shown that a combination of data from different levels (micro and macro) and perspectives can be useful to analyse economic and social participation at the regional level. In addition to micro level surveys of persons and employees (Microcensus, BIBB-BAuA Employee Survey, Socio-Economic Panel) and establishment surveys (IAB Establishment Survey, BIBB Qualification Panel), we make use of public structural data on the macro level (National Accounts, Input-Output Tables). With these we are able to represent the regional labour market structure by occupation and qualification as well as gender, age and nationality taking occupational flexibility and commuting flows into account. As part of the presentation, we show within the framework of the BIBB / IAB qualification and occupational field projections how regional submarkets in Germany could develop given constant trends and behaviours taking the available information into account. It illustrates divergence between labour demand and supply in specific regions, occupations, and qualifications and fosters a deeper understanding of the drivers of economic change and social participation by highlighting the persisting differences between the German regions.
Although there is increasing evidence for spatial externalities of one’s place of residence on various forms of life chances such as individual health, labor market involvement or educational achievement (for reviews see Jencks & Mayer 1990; Dietz 2002; Sampson et al. 2002; Galster 2012), the identification of the corresponding mediating social mechanisms is part of an ongoing debate. The well-known methodological challenges—namely the assessment of the spatial scale of “neighborhood”, the presence of unobserved (self-) selection processes and the reflection problem of endogenous effects (Manski 1993; Lupton & Kneale 2012)—hinder the evaluation of how, when, and for whom different social contexts matter (Sharkey & Faber 2014). There is, however, an additional methodological issue that—although associated with the mentioned challenges—has not yet been addressed in the literature on neighborhood effects. While most approaches stress the crucial importance of the social interdependence of individual action within a given context, the methods used to evaluate these theories assume just the opposite—namely independent and identically distributed observations (Beck et al. 2006).
We address this mismatch between the theoretical and the methodological framework in the study of neighborhood effects by using spatial econometric techniques that allow the modelling of spatial and social multiplier effects at the individual level (LeSage & Pace 2009; Vega & Elhorst 2013; Elhorst 2014). Using data from Switzerland, we analyze how the social composition of a neighborhood affects children’s educational achievement. On the one hand, it is demonstrated in which ways the incorporation of social interdependencies at the individual level can be used to reproduce and understand the results from contextual models that make use of aggregated data on given social entities. Hence, this approach allows us to adequately incorporate people’s everyday perceptions of “neighborhood” into our models. On the other hand, we present spatial Durbin models as an adequate way to directly assess the suggested social mechanisms (e.g., the positive impact of the interaction with high status neighbors). In this regard, we finally illustrate how such models can be used to incorporate spatial externalities into a rational action model of educational inequalities (Breen & Goldthorpe 1997). By means of spatial (Durbin) probit models, it can be shown that the decision related to which track to follow in secondary schooling is not only a function of the individual subjective assessment of the benefits, costs, and the likelihood of success of the different alternatives but also of one’s neighbors’ evaluation of the very same parameters. Thus, spatial econometrics bear the potential to greatly enhance our understanding of the mediating social mechanisms of neighborhood effects.