Project Summary

When people move between urban and rural areas, this often happens at specific stages of life and sometimes more than once over the course of their lives.

The INDUST project aims to identify typical characteristics of migration trajectories within Austria’s urban–rural system using microdata from Statistics Austria, and to examine how these have changed over time and across generations. The project’s goal is to disentangle processes of urbanisation at the individual level. It applies a longitudinal approach, comparing individual life courses over time in order to shed light on the complex interplay between residential decisions, contextual life-course factors, and macro-level (socio-spatial) conditions.

INDUST not only identifies the diversity of internal migration patterns, but also explains how these contribute to trends in urbanisation (as well as counter-trends). In addition, the project analyses related life events such as education, employment, and family dynamics, as well as economic and environmental spatial trends and their influence on migration trajectories across different age groups.

The project is guided by three research questions:

• What do typical internal migration trajectories along the urban–rural spectrum look like for different age groups, and how have they changed over the past 20 years?

• To what extent do migration trajectories correspond with processes in other sociodemographic life domains (family dynamics, education, labour-market participation)?

• How are migration trajectories influenced by spatial and socioeconomic macro-factors?

Methodology

The data are provided through the Austrian Micro Data Center of Statistics Austria and analysed using longitudinal methods, including sequence analysis. Sequence analysis is used to describe, visualise, and classify the temporal patterns contained in longitudinal data, allowing similarities and differences between sequences and the temporal progression of processes to be identified. A sequence is an ordered series of categorical states that can describe various statuses, conditions, or places, and thus different trajectories.

The project also applies multichannel sequence analysis as well as regression models to identify social and spatial influencing factors. The study of temporal-sequential phenomena is of central importance for understanding socio-spatial processes such as migration or urbanisation.