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Cash-for care policies are contested in many contexts, as they represent an incentive for childrearing over work that may reduce labour market participation, especially among immigrant women. From 1 July 2017, immigrants (both the mother and the father) from outside the European Economic Area must have at least 5 years of residence in Norway to be entitled to cash-for-care benefits. Previous research indicates that this reform did not lead to increased labour market participation of mothers and fathers treated by the reform. In this article, we examine whether the changes in the cash-forcare benefits policy have resulted in a substantive change in income and if the reform had an impact on the childbearing behaviour among those affected by the reform. Our descriptive analyses indicate no change in employment rates and household income. To detect possible changes in fertility, we employ a Difference-in-Difference approach, in which we compare the treatment group with four comparison groups. Overall, we find no substantial effect of the cash-for-care reform on childbearing behaviour. This work was funded by the Ministry of Labour and Social Inclusion

Regjeringen har oppnevnt et utvalg som skal lage ny utredning om kvinners helse og helse i et kjønnsperspektiv. Utvalget ble oppnevnt 5. mars 2021 og ledes av Christine Meyer. Målet er å få en oppdatert oversikt over kvinners helse i Norge og kjønnsforskjeller i helse. Utvalget skal se på utfordringer for kvinner når det gjelder risiko og forekomst av sykdom og bruk av helse- og omsorgstjenester. Mandatet er å undersøke hvordan kjønnsforskjeller og kjønnsperspektivet blir håndtert i arbeidet med folkehelse, i helse- og omsorgstjenestene og i forskning og utdanning. Utredningen skal inngå i grunnlaget for en kommende kvinnehelsestrategi. Denne rapporten er svar på dette oppdraget og faller inn under delen som omhandler ‘helse i livsfaser’. Rapporten beskriver kvinnehelse, helsetjenestebruk og demografisk utvikling de siste 20 årene i ulike aldersgrupper og livsfaser, og forsøker å se kvinners helse i lys av samfunnsutviklingen ellers.

Additional file 3. Average predicted margins, advantaged family network.

Few producers of official population projections provide regular evaluations of past projection inaccuracies. This paper assesses deviations between the projected and registered total population for Norway (1996–2018), as well as deviations in the age structure, total fertility rate and number of births, period life expectancy at birth and number of deaths, and net international migration. Projected life expectancy was consistently lower than the real development. Few systematic deviations were observed for fertility up to 2009, but thereafter fertility has been consistently overprojected. However, the deviations between projected and realised trends in births and deaths have been relatively small as compared to those for net international migration. The projections produced between 1996–2005 underestimated long-term population growth due primarily to the unforeseen increase in immigration following EU expansion in 2004. More recent projections contain no consistent under- or overprojection of net migration and the deviations for the total population have been moderate.

Additional file 1. Older adults��� own characteristics and additional analyses of the role of family members��� individual sociodemographic characteristics.

Additional file 4. Average predicted margins, for advantaged (cf. Fig. 1) and disadvantaged family networks.

Additional file 2. Indicators used in the disadvantaged family network classification.

Additional file 5. Disadvantaged family networks.

Statistics Norway projects the population by age, sex and immigrant background at the national level. This paper examines the accuracy of the Norwegian population projections produced between 1996 and 2018. We assess deviations between projected and registered numbers, both for the total population and for several key components, such as age structure, total fertility rate and number of births, period life expectancy at birth and number of deaths, as well as net international migration. While fertility proved to be the most difficult component to project during the post-war period, net international migration has been the main source of inaccuracy in the national population projections produced since 1996. The projections produced in 1996, 1999, 2002 and 2005 underestimated longterm population growth due to the unforseen increase in immigration following EU expansion in 2004. Subsequent projections have not, however, produced a consistent under- or overprojection of net migration, and the deviations between the projected and registered total populations have been moderate. Overall, the projections for life expectancy at birth have proven to be consistently lower than the real development in life expectancy in Norway, at least until very recently. Fertility, on the other hand, has continued to be overprojected since observed fertility started to decline in 2009. Nevertheless, the deviations between projected and realised trends in births and deaths have been small compared to the observed deviations for net international migration.

Period life expectancy at birth (PLE0) is defined as how long – on average – a newborn baby could expect to live if current mortality rates do not change. It is one of the most widely used population health indicators in the world by academics, governments, statistical agencies, and international organisations. Yet, while estimates of PLE0 routinely factor immigrations and emigrations into population denominators and migrant residents form part of these population denominators, the effect of the unique mortality of international migrants on national PLE0 has almost never been studied. Here, our aim is to understand whether estimates and comparisons of national PLE0 in four Nordic nations – Denmark, Finland, Norway, and Sweden – are being affected by the mortality of their international migrant populations. We use register data for over three decades, from 1990 to 2019. We calculate PLE0 by sex for entire resident, native-born, and migrant populations, as well as the differences between them. Our analysis reveals a dynamic and increasing impact of the mortality of international migrants on national PLE0 that is already beginning to affect inter-country comparisons and rankings of mortality. Our unique findings should resonate strongly in all nations with substantial shares of international migrants and all of the aforementioned stakeholders that use PLE0 to drive and inform public health policy.

According to population projections, the number of immigrants in Norway will increase in the future, but exclusively in older age groups. The number of immigrants aged 55-66 years is expected to increase threefold within the next 20 years. What will characterize these older immigrants? Since emigration rates among immigrants above age 50 are relatively low, we explore the possibility for projecting likely characteristics of the older immigrants of the future (education, place of residence and employment) based on what we know about today’s younger immigrants. Our results suggest that future older immigrants in Norway are likely to be lower educated and have lower labour market participation rates than natives of the same age.

National statistical offices responsible for population projections should regularly evaluate their work. Norway is currently considering changing the way fertility is projected. To establish a solid basis for deciding the way forward, this paper describes the different ways various European countries project fertility in their national population projections. Data were collected in two steps: First, statistical offices in Europe were asked to respond to a questionnaire regarding their current practices. The results were summarized qualitatively and quantitatively. The different methods used by the participating countries were categorized into four broad groups: 1) Model-based deterministic projections; 2) Model-based stochastic projections (frequentist and/or Bayesian); 3) Expert-based projections; 4) Other. A descriptive analysis of similarities and differences was performed to assess which methods were most common, how satisfied the statistical offices were with their method, the public availability of documentation, and the extent to which the accuracy of the projections was regularly assessed. Second, eight countries were selected for a more in-depth analysis. These countries take different approaches to projecting fertility, illustrating the range of options available and in use across Europe. We examined readily available information and documentation online, as well as reports and journal articles. For comparison purposes, this study also includes the fertility projection methods utilized by Eurostat and the UN. Some strengths and weaknesses associated with the different methods are presented, discussing both comments and feedback from statistical offices as well as those which emerge as part of the comparisons made in this study. In summary, a wide variety of methods are currently used. Whereas some countries are satisfied with their methods, documentation and results, others are actively working to improve their projections and outputs. It is hoped this study will act as a useful resource for individuals and agencies considering changing the way they project fertility, while perhaps also facilitating cross-national learning and knowledge exchange.

This work is jointly financed by the Ministry of Health and Care Services, Ministry of Children and Families, Ministry of Labour and Social Affairs and the Ministry of Education and Research in Norway, through a grant to the Norwegian Institute of Public Health. Hart’s contribution is partly supported by the Research Council of Norway through its Centres of Excellence funding scheme, project number 262700. Poor health may constrain women’s capacity for active leisure, including family life and childrearing, for participation in the labor market and potentially affect preferences. Still, health remains remarkably understudied as a fertility determinant. We explore the association between health and fertility, using uptake of doctor-certified sickness absences and long-term health-related benefits as proxies for health. We examine whether compositional changes in health distributions and/or changes in the health-fertility association have contributed to the distinct fall in the total fertility rate in Norway since 2009. We use nationwide registry data on women aged 16-45 from 2004-2018. We analyse first, second and third births separately, and use annual observations with lagged timevarying covariates for education, sickness absence and long-term benefits. Income, employment and partnership status are also included in some subanalyses. Long-term benefit uptake is negatively associated with fertility, and the association weakens over time. In addition, such uptake is relatively rare, but increases slightly over time. The use of sickness absence is positively associated with fertility, and the association strengthens over time. Sickness absence uptake is common but decreases over time. It is thus unlikely that changes in women’s health and/or changes in the health-fertility association can help explain the observed decline in fertility observed after 2009. However, if the decrease in sickness absence uptake reflects a stronger labor market preference among women in fertile ages, it might help explain parts of the observed decline. Overall, the decline in fertility is most pronounced for healthy women. Health as a fertility determinant warrants further research, from other countries and with other proxies for health.

Denne rapporten gjennomgår hvordan den norske befolkningen ble framskrevet på nasjonalt nivå i 2020, og gir en beskrivelse av resultatene. Rapporten dokumenterer framskrivingsmodellen BEFINN og beskriver hvilke forutsetninger som ligger til grunn for årets framskrivinger. Mer detaljerte beskrivelser av forutsetninger og resultater er tilgjengelig på engelsk, i rapport 2020/25. Mer informasjon om og resultater fra befolkningsframskrivingene finnes på www.ssb.no/folkfram