Periodic Reporting for period 1 - CityRising (The City Rising: Inequality and Mobility in a Growing Metropolis of the 19th Century)
Berichtszeitraum: 2023-01-01 bis 2025-06-30
The nineteenth century marked a period of profound transformation for European cities. Industrialization, mass migration, and technological innovation turned modest towns into vibrant metropolises, generating both opportunity and disruption. Cities had to cope with the challenges of new technologies, the arrival of migrants, and the recurrent threat of epidemics, while becoming engines of social and economic mobility where new forms of work, education, and public health took shape.
In this project we study how the city of Munich, between 1823 and 1914, confronted these challenges. Using newly digitized, high-frequency individual-level archival data, we analyze how these forces interacted to shape the economic and social lives of urban residents.
We begin by studying the introduction of mass transportation as a technological shock that transformed the spatial and social structure of the city. We examine how occupations, businesses, and households reorganized across space, how patterns of accessibility reshaped neighborhoods, and how these changes affected opportunities for social mobility, as reflected in education and employment trajectories. We then investigate the integration of Munich’s Jewish population, a group long marginalized in earlier centuries but increasingly prominent in the industrial city. We study the initial conditions that determined their occupational specialization and eventual success: place of origin, religious current, residential segregation, human capital of ancestors. We also study assimilation strategies and identity choices, as evidenced by first name choices, human capital investments, and intermarriage. Finally, we analyze how investments in a core amenity – sanitation and clean water – redefined the social geography of the city. We analyze its consequences on child mortality, fertility choices, and human capital investments using linked individual data, and consider the confounding role of spatial sorting in this process.
By combining methods from economic history, urban economics, demography, and digital humanities, the project reconstructs the micro-foundations of urban transformation in unprecedented detail. Its originality lies in the systematic use of large-scale, individual-level historical data, rarely exploited at this depth in European history. Our goal is to provide an evidence-based understanding of how cities adapt to technological and demographic shocks. These insights speak directly to contemporary debates on sustainable urbanization, inequality, and public health.
In this project we study how the city of Munich, between 1823 and 1914, confronted these challenges. Using newly digitized, high-frequency individual-level archival data, we analyze how these forces interacted to shape the economic and social lives of urban residents.
We begin by studying the introduction of mass transportation as a technological shock that transformed the spatial and social structure of the city. We examine how occupations, businesses, and households reorganized across space, how patterns of accessibility reshaped neighborhoods, and how these changes affected opportunities for social mobility, as reflected in education and employment trajectories. We then investigate the integration of Munich’s Jewish population, a group long marginalized in earlier centuries but increasingly prominent in the industrial city. We study the initial conditions that determined their occupational specialization and eventual success: place of origin, religious current, residential segregation, human capital of ancestors. We also study assimilation strategies and identity choices, as evidenced by first name choices, human capital investments, and intermarriage. Finally, we analyze how investments in a core amenity – sanitation and clean water – redefined the social geography of the city. We analyze its consequences on child mortality, fertility choices, and human capital investments using linked individual data, and consider the confounding role of spatial sorting in this process.
By combining methods from economic history, urban economics, demography, and digital humanities, the project reconstructs the micro-foundations of urban transformation in unprecedented detail. Its originality lies in the systematic use of large-scale, individual-level historical data, rarely exploited at this depth in European history. Our goal is to provide an evidence-based understanding of how cities adapt to technological and demographic shocks. These insights speak directly to contemporary debates on sustainable urbanization, inequality, and public health.
During the first phase of the project, the team concentrated on building the digital infrastructure needed to carry out the analyses. This preparatory stage (“Part 0”) involved extensive collaboration with the Munich city archive and specialized digitization companies. It involved digitizing and transcribing 28 yearly directories of Munich’s residents, listing names, occupations, and addresses. These directories form the backbone of the project’s longitudinal data, allowing the tracing of individuals and families across time and neighborhoods. We also obtained digital photographs of 96 volumes of police registration files ("Polizeimeldebögen"), comprising around 20,000 individual records. These detailed documents provide information on birthplace, religion, occupation, and movements within the city. Finally, we have assembled new datasets on the expansion of water and sewer networks, school yearbooks, city council minutes, and fine-grained electoral data from the 1880s to 1933. These additions open new perspectives on the interplay between urban infrastructure, political behavior, and social mobility.
Beyond data collection, the project developed novel methodological pipelines for digitizing and harmonizing historical sources. Leveraging recent advances in artificial intelligence, custom text-recognition models are being trained to read 19th-century German handwriting. This collaboration with AI developers promises to multiply the speed and accuracy of data transcription.
The research team also created reproducible coding frameworks to clean, harmonize, and classify occupations, addresses, and names, ensuring long-term usability of the data.
Beyond data collection, the project developed novel methodological pipelines for digitizing and harmonizing historical sources. Leveraging recent advances in artificial intelligence, custom text-recognition models are being trained to read 19th-century German handwriting. This collaboration with AI developers promises to multiply the speed and accuracy of data transcription.
The research team also created reproducible coding frameworks to clean, harmonize, and classify occupations, addresses, and names, ensuring long-term usability of the data.
The project is already advancing beyond the state of the art in several ways. First, it demonstrates the feasibility of constructing large-scale, individual-level datasets for a European city across a century, something previously achieved only for the United States. Second, by applying AI-assisted transcription and data linkage methods, it sets a new benchmark for empirical research in economic history and the digital humanities.
Once fully operational, the resulting database will enable analyses that link technological change, social mobility, and health outcomes at the individual level. It will provide a new foundation for understanding how European cities managed modernization and diversity, and how urban policies shaped life chances.
The potential impact extends far beyond academia. The project’s data and methods will be valuable for public historians, archives, and digital heritage initiatives. They can inform discussions on data preservation, urban resilience, and the social consequences of technological innovation.
Future steps include refining the AI transcription models, completing individual-level linkages across sources, and expanding collaborations to comparative projects with other European cities.
Once fully operational, the resulting database will enable analyses that link technological change, social mobility, and health outcomes at the individual level. It will provide a new foundation for understanding how European cities managed modernization and diversity, and how urban policies shaped life chances.
The potential impact extends far beyond academia. The project’s data and methods will be valuable for public historians, archives, and digital heritage initiatives. They can inform discussions on data preservation, urban resilience, and the social consequences of technological innovation.
Future steps include refining the AI transcription models, completing individual-level linkages across sources, and expanding collaborations to comparative projects with other European cities.