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ESRA 2023 Preliminary Glance Program

All time references are in CEST

Out of Touch - Potential of Spatial Structure Indicators to Analyse Social and Educational Inequality

Session Organisers Mr Jochen Wirsing (Deutsches Jugendinstitut e.V.)
Mr Andreas Fischer (Deutsches Jugendinstitut e.V.)
TimeWednesday 19 July, 09:00 - 10:30
Room U6-10

The study of spatial variance is an important part of empirical social research. It plays a major role regarding survey design issues, influencing for example sampling strategies and field operations among others. But regional variance also matters for substantial research interests, since spatial structures affect a great variety of social and educational opportunities and provisions. The reduction of spatial disparities has constitutional status both within the European Union and within the nation states (Dangschat, 2018, p. 425), and the German Grundgesetz stipulates the creation of equal living conditions (GG, Art. 72, 2022).

Against this background, it is surprising how little research projects apply spatial structure measurements in their study of social and educational inequality. Two reasons seem most likely. For one, many available indicators are not up-to-date. In the German case, the Bundesinstitut für Bau-, Stadt- und Raumforschung (BBSR) calculates the so-called Raumtypen (space types) (BBSR, 2020), which are based on data from 2009. The Thünen Institute calculates a numerical index for ruralness (Küpper, 2016), which includes data going back as far as 2011 in some cases. Moreover, available indicators are not easy to acquire. Fees often depend on data richness, spatial coverage and resolution, making this data rather expensive.

As a result, research on social and educational inequality suffers in several regards: Most important, there is a great lack of research taking regional variation into account. Second, construction rules of spatial structure indicators are often kept secret, contradicting good practice in Open Science. Finally, there are few replication studies comparing strengths and weaknesses of different indicators. The session aims to bring together papers studying social and educational inequality applying different (innovative) spatial structure indicators to evaluate their value for inequality research and possible ways forward which are in line with Open Science practices.

Keywords: AID:A, youth work, social inequality, educational inequality, spatial structure, isolation scale, rurality

Using Survey Data to develop agent-based models of segregation

Mr Daniel Schubert (Ruhr-University Bochum) - Presenting Author

Social inequality is inscribed in space in the course of segregation processes. Spatial Segregation research was mainly shaped by the model of Schelling (2006). Schelling (2006: 150ff.) designed a dynamic, self-regulating system to describe the emergence of segregation patterns. He attributed great importance to neighbourhood effects by assuming that actors prefer people as neighbours who are very similar to them. The model implies that actors are not aware of the consequences of their individual decisions. The fact that the traits of individual actors influence each other can lead to an interlinked process of spatial segregation. However, it is not always clear which factors cause the process and – more importantly – assumptions for modelling spatial segregation processes are sometimes far from real empirical circumstances. For example, Schelling (2006: 149) assumes a vacancy rate of 30% or a simple neighbourhood preference (avoid a minority position) that applies equally to all.
Agent-based simulation studies (ABM) provide a better understanding of the course of segregation processes. Through modelling, it is possible to observe how individual characteristics generate different macro phenomena (Flache & de Matos Fernandes 2021: 453). One way to make the spatial segregation model more realistic is to use survey data. The presentation will refer to a vignette-like question on preferences on foreigners in the neighbourhood in the ALLBUS. With the ALLBUS results, individual preferences about ethnic composition can be fed into the segregation model in a more complex but also empirically more realistic way. Simulations with simplistic and more complex behavioural assumption can be compared.

Enhancement of the Milan municipality's open source information system on the foreign migration phenomenon through regression models and top-down prediction at the neighborhood level

Dr Arianna Carra (Istat) - Presenting Author
Dr Flavio Verrecchia (Istat)
Dr Simona Mirabelli (none)

Open data from public administrations, in addition to guaranteeing transparency and contributing to the enrichment of the wealth of information available to citizens and businesses, can help optimize resources and improve the efficiency of the same administrations that make them available. From the vast and articulated open source database of the Municipality of Milan, it is possible to extract information of interest on the foreign population for the study of the migration phenomenon in terms of urban diffusion, transformations of statuses and acquisition of citizenship, demographic features and population structure, with purposes of social, housing and integration policies but also of statistical inference and planning. In particular, with respect to the latter point, the 20-year historical series and demographic projections regarding the foreign population residing in different city halls are available. By using regression models based on the least squares method and top-down forecasts, it is possible to further exploit the open data available on the foreign migration phenomenon by producing neighborhood-level forecasts. The aim of the work is to derive forecasts of particular population aggregates at a finer level of spatial detail that, as they are consistent with municipal projections, can add value to data deemed to be of strategic importance for local government. In retrospective analyses, and where possible, migratory background will be taken into account given the possibility of using available information on acquisitions of citizenship that makes it possible to distinguish whether a person is an immigrant or has acquired Italian citizenship by marriage, by residence in Italy for at least 10 years, or because he or she is a direct descendant of an immigrant who has acquired Italian citizenship, or because he or she was born in Italy and has reached the age of majority, etc.

Determinants of Job-to-Job Mobility in Germany – How Regions Encourage or Discourage Worker Mobility

Ms Katrin Rickmeier (Bielefeld University) - Presenting Author

This study investigates the effects of home region characteristics on job-to-job mobility and regional differences in worker mobility. Differences in the level of regional development may manifest themselves as regional differences in job mobility. Since job mobility is associated with career progression and an increase in income, regional differences in job-to-job mobility thus potentially reinforce and contribute to regional and social inequalities. This dynamic and increasing instability of career paths have provoked a great amount of literature on labor mobility.
Career researchers have generally limited their attention to individual and employer characteristics and found that both play a role in the decision for employer changes. Despite the finding that spatial structure factors affect job-to-job mobility as well, these have not received sufficient attention in the literature for the most part. However, it is important to examine the various structural factors and the broader context in which job mobility occurs.
I contribute to the literature on the determinants of job-to-job mobility by explicitly modeling the causal effect of home region characteristics and investigating the role of economic conditions, societal characteristics, and industry differences. In line with theoretical considerations of the importance of the social context for individual behavior, I argue that regions serve as opportunity structures for their inhabitants and thus influence their willingness to try new job mobility options.
I apply logistic regression models based on survey data from the German Socio-Economic Panel (SOEP) complemented by spatial structure indicators from the INKAR database.
First results show that good economic conditions in the home region are associated with a higher probability of job mobility for individual workers. Further analyses will contribute to a better understanding of the role of place of living in career progression and its contribution to social inequalities.

The Regional Political Climate and Spatial Inequalities: Causes of Internal Migration and Their Comparison

Mr Stephan Schütze (Bielefeld University) - Presenting Author

The intention to leave one's region is mainly a reaction to regional disparities in opportunities. Previous research has examined residential mobility primarily from a socioeconomic perspective. People decide to move away to improve their quality of life through new jobs with higher wages and income. Younger people, in particular, leave their region to find vocational training positions, take advantage of educational opportunities, and enter the job market.
What remains unconsidered, however, is the extent to which political aspects of a region play a role in the decision to migrate. Given the emergence of populist radical right parties in certain regions, this approach seems particularly relevant. This study examines the influence of the political climate in a region on people's intention to move while taking the structure of the local education system and the labor market into account. It investigates the question of how the political composition of a region influences migration intention when common migration incentives are controlled.
According to the Big Sort thesis, people prefer to live among like-minded people who share the same lifestyle and worldview. Consequently, the intention to move is increased among individuals who are a political minority in their region, and their intention rises the smaller the proportion of supporters of their party is.
Combining individual survey data from the German Socio-Economic Panel (SOEP) with aggregated regional data from official statistics, the research question will be answered with hierarchical logistic regression models. It is expected that people are more likely to move if there is a regional lack of opportunities and if the local political climate is contrary to their political attitudes. By comparing multiple contextual migration incentives, this study contributes new insights into spatial inequalities that foster internal migration and deepen political geography through regional sorting.