{"title":"《人口学研究中因果机制的识别》特刊社论","authors":"J. Huinink, J. Brüderl","doi":"10.12765/cpos-2021-17","DOIUrl":null,"url":null,"abstract":"Explaining demographic behaviour and population change means identifying the causal mechanisms which “drive” them over time. Based on theoretical modelling and guided by empirical fi ndings in prior studies, demographic and social research pursues the improvement of knowledge about those mechanisms and the relationships between the involved factors. In demography, as in the social sciences in general, theoretical and methodological advancements over the past 50 years have greatly contributed to accomplishing this goal. Methods of longitudinal data collection as well as individualand multilevel longitudinal data analysis have gained relevance. This trend was paralleled by the development of the life course perspective in the social sciences and conceptual refi nements in cohort analysis in demographic research. Meanwhile, collecting and analysing longitudinal data is a standard procedure in individualand multi-level demographic research. Many studies using this methodological inventory have been conducted, enriching our knowledge on individual decision-making and behaviour considerably. Compared to crosssectional data, longitudinal data signifi cantly improve the conditions for identifying the “true” effects of underlying causal mechanisms. While retrospective information is already of great use, prospective panel designs enable a more appropriate and manifold collection of relevant information, as well as more refi ned statistical modelling of the interdependence between individual behaviour, its dispositional and motivational drivers, its situational conditions, and its outcomes over time. Panel data are also useful for another prominent class of methods, i. e. techniques of event history analysis (Blossfeld/Rohwer 2002; Kreyenfeld 2021). In this Special Issue of Comparative Population Studies, we review the degree to which methodological innovations in panel studies have been useful in properly identifying causal mechanisms in the study of demographic behaviour, and ultimately population change. In the fi rst contribution, methodological issues of panel data analysis are discussed and illustrated by the example of estimating the effect of motherhood on life satisfaction. The next four articles address the core question of the Special Issue with regard to major fi elds of demographic research: Comparative Population Studies Vol. 46 (2021): 487-502 (Date of release: 24.11.2021)","PeriodicalId":44592,"journal":{"name":"Comparative Population Studies","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Editorial on the Special Issue “The identification of causal mechanisms in demographic research”\",\"authors\":\"J. Huinink, J. Brüderl\",\"doi\":\"10.12765/cpos-2021-17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Explaining demographic behaviour and population change means identifying the causal mechanisms which “drive” them over time. Based on theoretical modelling and guided by empirical fi ndings in prior studies, demographic and social research pursues the improvement of knowledge about those mechanisms and the relationships between the involved factors. In demography, as in the social sciences in general, theoretical and methodological advancements over the past 50 years have greatly contributed to accomplishing this goal. Methods of longitudinal data collection as well as individualand multilevel longitudinal data analysis have gained relevance. This trend was paralleled by the development of the life course perspective in the social sciences and conceptual refi nements in cohort analysis in demographic research. Meanwhile, collecting and analysing longitudinal data is a standard procedure in individualand multi-level demographic research. Many studies using this methodological inventory have been conducted, enriching our knowledge on individual decision-making and behaviour considerably. Compared to crosssectional data, longitudinal data signifi cantly improve the conditions for identifying the “true” effects of underlying causal mechanisms. While retrospective information is already of great use, prospective panel designs enable a more appropriate and manifold collection of relevant information, as well as more refi ned statistical modelling of the interdependence between individual behaviour, its dispositional and motivational drivers, its situational conditions, and its outcomes over time. Panel data are also useful for another prominent class of methods, i. e. techniques of event history analysis (Blossfeld/Rohwer 2002; Kreyenfeld 2021). In this Special Issue of Comparative Population Studies, we review the degree to which methodological innovations in panel studies have been useful in properly identifying causal mechanisms in the study of demographic behaviour, and ultimately population change. In the fi rst contribution, methodological issues of panel data analysis are discussed and illustrated by the example of estimating the effect of motherhood on life satisfaction. The next four articles address the core question of the Special Issue with regard to major fi elds of demographic research: Comparative Population Studies Vol. 46 (2021): 487-502 (Date of release: 24.11.2021)\",\"PeriodicalId\":44592,\"journal\":{\"name\":\"Comparative Population Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comparative Population Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12765/cpos-2021-17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comparative Population Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12765/cpos-2021-17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
Editorial on the Special Issue “The identification of causal mechanisms in demographic research”
Explaining demographic behaviour and population change means identifying the causal mechanisms which “drive” them over time. Based on theoretical modelling and guided by empirical fi ndings in prior studies, demographic and social research pursues the improvement of knowledge about those mechanisms and the relationships between the involved factors. In demography, as in the social sciences in general, theoretical and methodological advancements over the past 50 years have greatly contributed to accomplishing this goal. Methods of longitudinal data collection as well as individualand multilevel longitudinal data analysis have gained relevance. This trend was paralleled by the development of the life course perspective in the social sciences and conceptual refi nements in cohort analysis in demographic research. Meanwhile, collecting and analysing longitudinal data is a standard procedure in individualand multi-level demographic research. Many studies using this methodological inventory have been conducted, enriching our knowledge on individual decision-making and behaviour considerably. Compared to crosssectional data, longitudinal data signifi cantly improve the conditions for identifying the “true” effects of underlying causal mechanisms. While retrospective information is already of great use, prospective panel designs enable a more appropriate and manifold collection of relevant information, as well as more refi ned statistical modelling of the interdependence between individual behaviour, its dispositional and motivational drivers, its situational conditions, and its outcomes over time. Panel data are also useful for another prominent class of methods, i. e. techniques of event history analysis (Blossfeld/Rohwer 2002; Kreyenfeld 2021). In this Special Issue of Comparative Population Studies, we review the degree to which methodological innovations in panel studies have been useful in properly identifying causal mechanisms in the study of demographic behaviour, and ultimately population change. In the fi rst contribution, methodological issues of panel data analysis are discussed and illustrated by the example of estimating the effect of motherhood on life satisfaction. The next four articles address the core question of the Special Issue with regard to major fi elds of demographic research: Comparative Population Studies Vol. 46 (2021): 487-502 (Date of release: 24.11.2021)