The Scanian Economic-Demographic Database (SEDD) is a high-quality longitudinal data resource spanning the period 1646−1967. It covers all individuals born in or migrated to the city of Landskrona and five rural parishes in western Scania in southern Sweden. The entire population present in the area is fully covered after 1813. At the individual level, SEDD combines various demographic and socioeconomic records, including causes of death, place of birth and geographic data on the place of residence within a parish.
The Lee-Campbell Group has spent forty years constructing and analysing individual-level datasets based largely on Chinese archival materials to produce a scholarship of discovery. Initially, we constructed datasets for the study of Chinese demographic behaviour, households, kin networks, and socioeconomic attainment. More recently, we have turned to the construction and analysis of datasets on civil and military officials and other educational and professional elites, especially their social origins and their careers.
During the 19th and early 20th century about 220,000 Dutch born persons migrated to the USA. The Historical Sample of the Netherlands (HSN) contains about 85,500 persons born in the Netherlands between 1812 and 1922. In this article we report the way we have matched persons from the HSN with the American censuses from the period 1850 till 1940. For this purpose, a linking process was designed, comprising of three stages: harmonization, matching and validation. The different nature of the two datasets (HSN and the USA Censuses) asked for some harmonization prior to the matching.
The North Orkney Population History Project is a multidisciplinary data collection, digitization, and analysis effort that aims to reconstruct longitudinal demographic, environmental, and economic change. We describe the motivation, methodological approach, data sources, and some initial findings of the project. Detailed contextual information about a single community allows for the joint analysis of the changing population and changing landscape.
It has previously been shown that infant mortality clusters in a subset of families, a phenomenon which was observed in historical populations as well as contemporary developing countries. A transmission of death clustering across generations has also been shown in Belgium, but it is unknown whether such effects are specific to the studied context or are also found in other areas.
Studies conducted in historical populations and developing countries have evidenced the existence of clustering in infant deaths, which could be related to genetic inheritance and/or to social and cultural factors such as education, socioeconomic status or parental care. A transmission of death clustering has also been found across generations. One way of expanding the knowledge on intergenerational transfers in infant mortality is by conducting comparable studies across different populations.
Systematic research on urban-rural variation in demographic behavior is necessary to overcome dichotomous views resulting from studying cities and the countryside separately. After all, a web of interactions facilitating the diffusion of ideas and behavior connects cities and rural areas. That is why it is especially important to study the comportment of migrants moving between urban and rural environments.
Previous studies have consistently observed intergenerational continuities in childbearing. This study uses individual-level parish records to examine the intergenerational transmission of fertility over the life course of women in Sweden during the fertility transition in the second half of the nineteenth century. Bivariate correlations, event history analysis and Poisson regression models are estimated for a large number of indicators of reproductive behavior.
The Intermediate Data Structure (IDS) provides a standard format for storing and sharing individual-level longitudinal life-course data (Alter and Mandemakers 2014; Alter, Mandemakers and Gutmann 2009). Once the data are in the IDS format, a standard set of programs can be used to extract data for analysis, facilitating the analysis of data across multiple databases. Currently, life-course databases store information in a variety of formats, and the process of translating data into IDS can be long and tedious.