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The current surge in forced migration to Europe is probably the largest and most complex since the Second World War. As population aging accelerates and fertility falls below replacement level, immigration may be seen as a key component of human capital to address labor and skill shortages. Receiving countries are, however, hesitant about the contribution that forced migrants can make to the local economy. Coupled with increasing pressure on welfare services, they are associated with increased job competition and crime. Underutilization of immigrants’ skills is, however, a waste of resources that countries can scarcely afford. Understanding the labor market integration process of forced migrants is thus critical to develop policies that unleash their full skills potential and ultimately foster local economic productivity. While prior studies have examined the employment and salary outcomes of these immigrants at a particular point in time post-migration, they have failed to capture the temporal dynamics and complexity of this process. Drawing on administrative data from Sweden, we examine the occupational pathways of forced migrants using sequence analysis from their arrival in 1991 through to 2013. Findings reveal polarized pathways of long-term labor market integration with over one-third of refugees experiencing a successful labor market integration pathway and an equally large share facing a less fruitful employment outcomes. Our findings suggest education provision is key to promote a more successful integration into the local labor market by reducing barriers of cultural proximity and increasing the occurrence of entrepreneurship activity.

Several countries nowadays and in the past face a birth rates below replacement level. To what extent should the fertility of this shrinking population be increased during a given planning period such that it approaches stationarity at the end as close as possible? Both immediate adaptation to the replacement level as well as delaying it to the end of the planning period are suboptimal. Distributed parameter optimal control theory provides an appropriate tool to ascertain the efficient intertemporal trade-off between costly birth control and zero population growth. It turns out that the optimal adaptation rate of the net reproduction rate (NRR) balances between unacceptable adjustment costs for fertility and huge deviations of the terminal age composition from the desired stationary one. The optimal adaptation rate is monotonically increasing with a curvature that depends on the growth rates of the NRR, the fertile population, and the value of newborns.

We describe a Bayesian projection model to produce country-specific projections of the total fertility rate (TFR) for all countries. The model decomposes the evolution of TFR into three phases: pre-transition high fertility, the fertility transition, and post-transition low fertility. The model for the fertility decline builds on the United Nations Population Division's current deterministic projection methodology, which assumes that fertility will eventually fall below replacement level. It models the decline in TFR as the sum of two logistic functions that depend on the current TFR level, and a random term. A Bayesian hierarchical model is used to project future TFR based on both the country's TFR history and the pattern of all countries. It is estimated from United Nations estimates of past TFR in all countries using a Markov chain Monte Carlo algorithm. The post-transition low fertility phase is modeled using an autoregressive model, in which long-term TFR projections converge toward and oscillate around replacement level. The method is evaluated using out-of-sample projections for the period since 1980 and the period since 1995, and is found to be well calibrated.

The Total Fertility Rate (TFR) is the below replacement level for a population without migration throughout Europe. The population growth implications of low fertility combined with non-zero migration remain widely misunderstood. This paper proposes new measures which may enhance understanding of the relationships between TFRs and population growth for open populations. For 22 European countries in 2019, the method adjusts the familiar ‘typically just below 2.1’ replacement level for effects of constant non-zero immigration counts and emigration rates. The long-run perspective on zero growth the ‘Migration-Adjusted Replacement TFR’ provides is supplemented with near-term perspective by also presenting the TFR that would produce zero population growth immediately. The Migration-Adjusted Replacement TFR for 2019 ranges between 0.86 for Spain and 2.44 for Croatia. The variation is associated with the differences in migration between these countries. Its value is below 2.1 in 18 countries. For nine countries, the 2019 TFR is above the Migration-Adjusted Replacement level. The ‘Immediate Population Replacement TFR’ ranges from 0.26 for Sweden to 2.83 for Bulgaria, and for most countries lies below the Migration-Adjusted Replacement TFR. For most of the European countries, the TFRs that are coherent with zero population growth, immediately and long run, are below 2.1. A major advantage of this paper’s version of the ‘Migration-Adjusted Replacement TFR’ is its applicability to contexts with negative current net migration. The new measures proposed in this paper can better guide assessment of the relationships between fertility levels and population growth for European and other countries with non-zero immigration and emigration.

The total fertility rate in Iran has declined to below replacement level recently, and a new approach has been taken to tackle this issue. Thus, this study aimed to identify the involved stakeholders and their characteristics in the new population policy change in Iran. We employed a qualitative approach using the purposive sampling of key informants and the identification of relevant documents. The main stakeholders were divided into seven key groups: religious, political, governmental, professional, international sectors, media, and nongovernmental organizations. In addition, there was no centralized, clear, and comprehensive mechanism to guide the activities of stakeholders to coordinate and bring the total fertility rate to the replacement level in Iran. Despite the importance of the new population policy in Iran, in recent years, we still experience dispersion and inconsistency among various actors in this area. It is imperative to go through a consensus and coalition at macro-level authorities alongside evidenced-based population policymaking.

This paper consolidates two previously disconnected literatures. It integrates R&D-based innovations into a unified growth framework with micro-founded fertility and schooling behavior. The theory suggests a refined view on the human factor in productivity growth. It helps to explain the historical emergence of R&D-based growth and the subsequent emergence of mass education and the demographic transition. The model predicts that the erstwhile positive correlation between population growth and innovative activity turns negative during economic development. This \"population-productivity reversal\" explains why innovative modern economies are usually characterized by low or negative population growth. Because innovations in modern economies are based on the education of the workforce, the medium-run prospects for future economic growth—when fertility is going to be below replacement level in virtually all developed countries—are better than suggested by conventional R&D-based growth theories.

Summarising earlier publications, I draw a rather optimistic picture of the human future on this planet, if priority is given to universal education, and, in particular, to female education. The benefits of a greater focus on education range from a lower desired family size and empowerment to reach this goal, to better family health, to poverty reduction, to greater resilience, to expanded capacities to mitigate and adapt to climate change, and, ultimately, to the emergence of better institutions and social values that are less obsessed with material consumption and violent nationalism and more concerned with cooperation, care and wellbeing. I also show that extended periods of below replacement level fertility are beneficial for long-term human wellbeing, and that the human population is on the path to peaking during the second half of this century and then declining to 2–4 billion people by 2200. As this smaller population will be well-educated, they should be healthy and wealthy enough to be able to cope fairly successfully with the already unavoidable (moderate) effects of climate change.

Functional Urban Areas (FUAs) leads to a better knowledge of urban spatial organisation, which may play a significant role in regional policy making and may be helpful in understanding the connection between urbanisation and demographic development. An explanation of population change in urban regions can be associated the second demographic transition comprising fertility decline below replacement level and postponement of births.The aim of this paper is to focus on establishing similarity patterns and anomalous values of selected demographic variables in the cores and peripheral areas of Functional Urban Areas. At the background of this study lies an assumption that population development of FUA's is shaped by different factors connected with second demographic transition and migrations. To achieve the aims the following demographic characteristics were used: population growth rate, dependency ratio, rate of natural increase, the net migration rate, and the dynamic economic ageing index, Spatial methods play an increasingly important role in contemporary socio-demographic research. In order to identify spatial systems Global Moran Statistics and the Local Indicators of Spatial Association (LISA) including Local Moran statistics as well as Getis-Ord Gi* statistics were used.The research showed global and local autocorrelation of demographic processes in Functional Urban Areas in Poland, namely population growth, natural increase, net migration and population ageing. The use of local Moran's I statistic and the Getis-Ord Gi* method has led to identification of spatial clusters and dispersions representing different demographic variables. Spatial autocorrelation methods can be useful in an analysis of demographic variables including changes in time. The main contribution of this study to the research on demographic processes in urban areas was an application of spatial groupings techniques not only to find out similarity and dissimilarity patterns of demographic indicators but also to apply this findings for the needs of spatial planning.

This paper aims to examine the association of female education, under-five mortality, and poverty in fertility reduction in the districts of India. Data from the census of India and large-scale population-based surveys are used. Difference-in-difference panel models are used to account for both initial conditions and contemporaneous changes in fertility reduction. While one-third of the districts have reached below replacement level of fertility, under-five mortality and poverty level have reduced by half from the initial level and the female literacy level has almost doubled, suggesting a remarkable degree of convergence across all distal determinants but only limited evidence of convergence for fertility. The single largest predictor of fertility reductions in the districts of India was initial TFR, followed by increase in female literacy, the initial female literacy level and reduction in under-five mortality. The effect of initial level of poverty on fertility reduction was 0.13, while that of reduction in poverty was -0.05.

China's total fertility rate (TFR) has been below replacement level since the 1990s and below 1.5 since the 2000s. To address the issue of low fertility and rapid aging, the Chinese government replaced the strict one-child family planning policy with the selective two-child family planning policy in 2013 and then the comprehensive two-child family planning policy in 2015. However, a strong baby boom did not ensue, and births hit a record low in 2018. It is thus vital to understand fertility motivation among younger generations of women. Collecting qualitative data in a small city in the Yangtze Delta, we found that the high costs of current practices of child raising and education are prominent factors in women's mind-sets, and that bilateral family support, including but not limited to help with finances and care, is the cornerstone of this expensive, modern child raising model. A complex, bilateral family model has gradually grown out of the patriarchal system. Grandparents on both sides collaborate with the mother at different times of the day and in different stages of children's development. A familial relay race of child care reduces the mother's work-family conflicts. The sustainability of mosaic familism, the gendered intergenerational collaboration following bilateral family lines, is questionable, particularly when raising children comes into conflict with caring for the elderly. We suggest that future policies pay sufficient attention to the needs of women who are embedded in the bilateral extended family.