Innovations in the use of territorial and individual data in analysis of Latvia ’s demographic development, 2011–2021
Keywords: Latvia, population censuses, administrative data, demographic development, territorial differences, family types
Language: In Latvian

The article is prepared by five scholars from the University of Latvia in the frame of National Research Programme’s Project “Towards Sustainable and Inclusive Society in Latvia: Response to Demographic and Migration Challenges (DemoMig)” which focuses on sustainable and inclusive regional development with a particular interest in migration and demographic aspects. The article summarises the research results based on the last available data from the Population Census 2021 and retrospective data analysis since 2011. Innovations in official population statistics over the last ten years — use of administrative registers, geospatial information, registered place of residence, and experimental statistics — allow scholars to perform an individual data linkage between big data.

This article covers three interrelated sections. In the section “Innovations in population registration and analysis” legal and methodological initiatives since 2011 in producing Census and current population statistics are discussed. The section “Use of territorial data — population size, spatial distribution, and demographic typology of counties” draws attention to emigration, immigration, and population changes by administrative territory and indicates the role of emigration and suburbanisation in concentration of population in the central part of country. Application of the use of non-hierarchical cluster analysis offers four county clusters: rapid development counties, stagnation risk counties, emigration counties, and depopulation risk counties. The section “Use of individual data — families with children: insight in emigration and mortality of parents” is prepared as a longitudinal follow-up of four types of families with children from the cohort from the Population Census 2011, based on linkages of individual data.