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Netherlands Interdisciplinary Demographic Institute (NIDI)
Activities and Programs

Research in the Social Demography department
             
Research in the Social Demography Department has three aims. First, it seeks to describe demographic changes by monitoring changes in the occurrence and timing of separate demographic events and in the interrelatedness of events. Second, it wishes to explain these changes by using the life-course perspectives as a theoretical framework to integrate contributions from several scientific disciplines, by applying state-of-the-art methodology and by collecting and analysing longitudinal datasets. Third, it seeks to illuminate the social impacts of these changes by focusing on both the micro- and the macro-consequences of changing life courses.

Theoretically, the programme is inspired by the life-course perspective that serves as a general theoretical framework to lend coherence to the research activities of the department. Within this perspective, emphasis is on the fact that demographic behaviour occurs within different time dimensions (biographical time, historical time, social time) and in connection with events in the lives of important others (linked lives). Inspired by these ideas, the research programme pays attention to such topics as the individual life-course precursors of demographic events, the impact of institutional arrangements on life-course decisions and the influence of family members on demographic behaviour. Methodologically, the programme uses state-of-the-art data-analytic procedures to arrive at answers to pertinent demographic questions. A wide variety of multi-variate techniques are applied, including event history analysis, multi-level analysis, simultaneous equation analysis and sequence analysis. With regard to data, the programme uses a double strategy. On the one hand, it uses official data and large datasets collected by other institutions. On the other hand, data are collected by NIDI itself. These data-collection efforts often include a longitudinal and multi-actor dimension.

The activities of the Social Demography department are structured into four research strands. The first two strands focus on the study of two demographically and socially dense periods in the life course: the early stages of the life course, with the transition to adulthood at its core, and the later stages of the life course, with the so-called ''third age'' i.e. the life phase starting with retirement at its core. The third strand focuses on intergenerational relationships. The common denominator of these strands is the ''linked lives'' dimension of the life-course perspective. A fourth strand addresses the interplay of population trends and policies (the ''social time'' and ''historical time'' dimension of the life-course perspective).

Research in the Projections, Migration & Health department
            
The life course perspective serves as a common denominator in the research projects of the Projections, Migration & Health department. The department''s overall theme of ''Lives in Contexts'' is elaborated in three related research strands: Population Projections and Models, Migration and Integration, and Health. The models and methods that are developed and applied in the department serve to improve population and health projections and to estimate international migration flows and the impact of health and other interventions.

Demographic changes are closely related to the economic, social, cultural and political contexts. Changes in the social context have major consequences for changes in fertility, mortality and migration and thus have an impact on the outcomes of projections. Similarly, changes in the size and composition of the population have major consequences for society in the next decades. Population growth, population ageing and the growing number of migrants have significant implications for economic growth, labour markets, healthcare, pensions, housing, integration, social cohesion, infrastructure, the environment and the like. For this reason our research focuses on interdisciplinary analyses that take the multiple causes and consequences of demographic change into account. This is the core of the research strand Population Projections and Models. Making projections requires models describing demographic changes as well as substantive knowledge about the causes of these changes. Therefore, the research activities include the development and application of demographic models as well as analyses of the causes of demographic changes. The models are applied both to demographic projections and to assessing the economic and social consequences of demographic changes. The projection models developed are multistate models.

International migration is set to play a major part in shaping the demographic future and thus the second research strand focuses on international migration and the integration of migrants in Europe. Both substantive and methodological issues are addressed. International comparative data on the process of integration is scarce. Our research on the rapidly increasing numbers of second-generation migrants in large European cities will seek to add to our knowledge on this issue. International comparisons may also help to identify best practices of policies aimed to foster integration. To improve the reliability and completeness of international migration statistics, NIDI will also be engaged in developing and applying estimation methods to yield estimates of international migration flows and population numbers by nationality and country of birth. The third research strand focuses on health. Emphasis is placed on the study of health systems and how they affect the availability and affordability of healthcare. Affordable healthcare means the provision of care at a reasonable cost, both for governments and for the private sector (companies, households). Financial information is crucial to understanding the performance of health systems. The impact of risk factors on health and healthcare costs is also analysed. The focus on data analysis and the development of models (for health indicators and intervention analysis) is in line with studies in the Projections strand.
 
 
 

 
 
 

 
 
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