Digital and Computational Demography
At a Glance
Migration and Mobility
Our societies increasingly face the challenges of managing vital migration flows and integrating migrants in the context of below-replacement fertility, slow population aging, and sudden crises or shocks.
Demographers have played a key role in developing theories and methods to explain fertility and mortality. The role of demographic science in the study of migration, by contrast, has received relatively limited attention. This is not because of lack of ideas or conceptual frameworks. It is mainly because of lack of adequate data that are necessary to test migration theories and to develop new ones.
The rapid spread of information and communication technologies and the increase in computing power have opened up new opportunities for breakthroughs to be made in the study of migration and mobility. The use of Internet, social media, and various forms of electronic communication are affecting migration choices and constraints. And the same technological changes that are transforming migration experiences are also generating digital trace data that researchers can leverage, with appropriate statistical tools, to address classic questions in migration studies.
Our main ambition is to combine traditional and novel data sources within a solid statistical framework, to measure and predict migration outcomes and the integration of migrants, and to evaluate the impact of the digitalization of life on migration and mobility. We aim to provide answers to the following questions: Why do people move? What are the consequences for host and sending regions? What factors facilitate the integration of migrants and their well-being? What patterns emerge? And how do they vary by demographic group? Addressing these questions improves our theoretical understanding of migration and mobility processes and informs policy decisions in a world that is increasingly connected.
Current projects are organized around three main clusters:
Measuring and Forecasting Migration
These projects advance methods to improve estimates of international and internal migration flows and stocks, and to make predictions for the future. They integrate a large number of data sources, including population registers, population surveys (e.g., labor-force surveys and passenger surveys), and digital trace data (e.g., geo-located social media posts, cellphone records), and often do so within a flexible Bayesian statistical framework. A key aspiration is to develop a solid statistical framework to measure migration at different levels of temporal and geographic granularity. Consistent and high-quality estimates can serve as the basis for testing and advancing migration theories and for the rapid assessment of responses to shocks, such as natural disasters.
High-skilled migration is central to the vitality of modern economies, but measuring its trends and determinants has been limited. We study the migration of professionals and scholars and use data sources such as surveys, LinkedIn, and large-scale bibliometric databases. A key goal is the development of a comprehensive and longitudinal database on the migration of scholars at different levels of geographic granularity. This will enable us to understand the dynamic relationships between the internal and international migration of scholars and the impact of policy measures on migration flows.
Integration and Segregation
Some of the key goals of the projects in this area are to understand the relationships between the migration discourse on social media platforms and the integration of migrants; to measure distance in cultural taste, using a combination of digital trace data and new forms of data collection; and to assess the ways in which different sociodemographic and economic groups have differential patterns of geographic mobility, with consequences in terms of exposure to other population groups, to pollution, and to green and cultural spaces.
Projects of this Research Area
Integrated Modeling of International Migration Flows Using Multiple Data Sources Project details
Temporal Effects in Migration Measurement: Evidence from Geo-Referenced Digital Trace Data Project details
Combining Digital Trace Data and Representative Surveys to Predict Migration Rates Project details
Assessing Migration Patterns in Latin America by Combining Traditional and Digital Trace Data Sources Project details
Modeling and Analysis of Migration and Mobility among Scholars Project details
Studying International Migration of High-Skilled Professionals Using Large-Scale Digital Trace Data Project details
Evaluating Immigrants’ Cultural Assimilation Using Digital Trace Data Project details
Measuring Cultural Distance and Cultural Diffusion between Countries Using Digital Trace Data Project details
Studying the Interplay between Social Media Discourse and Refugee Segregation Project details
Linking Social Stratification and Geographic Mobility through Geo-Referenced Data Collected via a Smartphone Application Project details