While China successfully leveraged a favorable age structure to fuel decades of economic growth, this age-based demographic dividend is now weakening due to rapid population aging and sustained low fertility. Policy responses have largely focused on reversing fertility decline through pro-natalist measures, yet existing evidence suggests that such interventions have only limited effects (Gauthier & Gietel-Basten, 2025).

This raises a broader question: if the contribution of the age structure to economic growth is diminishing, what factors can sustain future development? To address this, it is useful to distinguish between two dimensions of the workforce. The first is captured by the age support ratio (ASR), which reflects the balance between the working-age population and dependents. The second is related to the skills embodied in the workforce. To measure this second dimension, we introduce the task-based skill ratio (TSR), an index that captures the composition of jobs in terms of the tasks they require, ranging from low- to high-skill activities.

The key challenge, therefore, is to understand how these two dimensions interact. Can improvements in the skill composition of the labor force compensate for the decline in the age-based demographic dividend? And to what extent can skill upgrading sustain economic growth in the context of continued demographic aging?

China provides a particularly relevant case to examine these questions. Its rapid transition from a labor-abundant economy to an aging society, combined with significant investments in education and structural economic transformation, offers a unique opportunity to observe how the sources of economic growth evolve. Insights from this transition are not only important for China, but also for other countries at different stages of the demographic transition.

A skill-based perspective

In a recent study (Gu et al., 2026), we constructed the TSR using an approach comparable in spirit to the ASR, but focused on skills rather than age. Building on the framework of the United States Occupational Information Network, occupations were decomposed into detailed work activities, which were then assigned skill intensities. These task-based scores were aggregated to the city level to produce a consistent measure of local skill composition. This makes the TSR directly comparable to the ASR: both are aggregate indicators defined at city level, both vary over time, and both can be linked empirically to economic outcomes such as per capita GDP. However, they capture different dimensions of the labor force: quantity versus quality. Empirically, we found that the ASR in China reached a turning point around 2010 and has since declined, reflecting demographic aging. In contrast, the TSR has continued to rise, particularly in eastern megacities, indicating sustained improvements in the skill composition of the workforce. 

We then estimated both the independent and joint effects of the ASR and TSR on economic performance, and projected the levels of TSR required to offset future declines in the ASR under different demographic scenarios from 2025 to 2100.

Synergy between age and skills

Both the ASR and the TSR have a positive effect on per capita GDP, but since around 2010, the TSR has become the stronger and more consistent driver of economic performance. Our results also show that expanding the working-age population alone is not sufficient to generate growth. In cities with low skill levels, a larger labor force yields limited economic benefits. By contrast, improvements in skill composition can sustain growth even as the advantage based on age structure declines. This complementarity weakens with population aging. As the workforce ages, the overall contribution of the ASR declines, and the adaptability of the labor force becomes more constrained. Older workers, on average, face greater challenges in adjusting to changing task requirements, which reinforces the shift from a quantity-based to a skill-based driver of economic growth.

Three phases of the demographic-skill transition

The demographic foundations of economic growth in China have undergone a clear transition across three distinct phases (Fig. 1). First, the age-based dividend phase (2000 to 2005) was characterized by rapid growth driven primarily by the expansion of the working-age population. Market reforms and the relaxation of household registration constraints facilitated large-scale labor reallocation from agriculture to industry, allowing China to fully exploit its demographic advantage.

Second, the transition phase (2005 to 2010) marked a turning point. During this period, the contribution of the ASR declined substantially, while the influence of the TSR increased. Third, the skill-based dividend phase (after 2010) saw a fundamental shift in the drivers of economic growth. As labor supply growth slowed and population aging intensified, the marginal effect of the ASR continued to weaken. At the same time, industrial upgrading and rising human capital led the TSR to become the dominant source of growth. Overall, Fig. 1 illustrates that the demographic dividend has not disappeared. Rather, its underlying mechanism has evolved from an extensive model based on labor supply to an intensive model driven by skill accumulation and productivity gains.

Projections and policy implications

To quantify the TSR enhancement required to counteract aging pressure, we constructed a dynamic projection based on the United Nations low fertility variant for the period between 2025 and 2100 (Fig. 2). We selected this low variant because recent fertility trends in China fall below medium-level projections, which makes it a realistic reflection of population dynamics. We then established three adjustment scenarios to evaluate future policy options:

1) Redefining the working-age population: We extended the upper boundary of the working-age population to 69 years and 74 years to simulate delayed retirement policies.

2) Age-dynamic scenario, assuming that the marginal contribution coefficient of the ASR (1) grows at an annual rate of 1% (i.e. becomes stronger over time).

3) Skill-dynamic scenario, assuming that the marginal contribution coefficient of the TSR (2) grows at an annual rate of 1%.

Projections of the compensatory TSR required up to the year 2100 indicate that delayed retirement can partially alleviate the effects of the declining age support ratio. Extending the upper boundary of the working age to 69 or 74 years dilutes the negative impact of age-structure changes by expanding the labor supply, which creates a substantial window for adjustment in the medium term. However, adjusting the labor supply provides only a temporary buffer and cannot reverse the long-term upward trend of ageing. 

The projections highlight that the evolution of economic parameters exerts a decisive influence on future outcomes and, not surprisingly, that combining the enhancement of the TSR with a moderate extension of working life offers the most viable path to navigate the challenges of advanced aging. Economic development relies less on favorable age structures and increasingly depends on the skill composition of the workforce, making skill upgrading a central policy priority.

References

Gauthier A. H. & Gietel-Basten S. (2025). Family policies in low fertility countries: Evidence and reflections, Population and Development Review, 51(1), 125-161. https://doi.org/10.1111/padr.12691

Gu H., Wu Y., Marois G., Lutz W. & Niu T. (2026). China’s demographic dividend has moved from age-based labor supply to skill-based productivity, Proceedings of the National Academy of Sciences, 123 (15) e2532906123. https://doi.org/10.1073/pnas.2532906123

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Introduction

How fertility changes over time in urban versus rural areas matters for demographic dynamics in an increasingly urbanized world. Trends in urban fertility determine endogenous population growth in cities, whereas trends in rural areas inform about demographic pressure for rural-to-urban migration. The urban-to-rural diffusion of the small family ideal also has implications for the pace of completion of the global fertility transition.

International comparisons of the fertility gradient by residence (in a given period) found a higher excess of rural over urban fertility in countries situated in the middle of their demographic transition (i.e. the shift from high to low birth and death rates), when compared to those in early or advanced transitional stages (Shapiro and Tambashe 2000, United Nations 1987), suggesting that the evolution of rural excess fertility follows an inverted U-shaped curve. However, this pattern has not been confirmed by analyses of trends within countries over time (Montgomery et al. 2003). We aim to re-assess this question (see also Lerch 2018).

The present analysis covers a larger geographical and temporal spectrum of fertility change than previous research. We use 295 World Fertility Surveys (WFS), Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and International Public Use Samples of Population Censuses (IPUMS) to estimate cohort fertility of women born between 1896 and 1982, covering 60 countries across the global South. This study also adds to the existing knowledge by controlling for three potential biases in the international comparison of fertility trends. First, we measure trends in the rural-urban fertility gradient over the course of the national fertility transition, rather than over calendar years, in order to account for international differences in demographic context. Second, the heterogeneity in the urbanization context (such as the definitions of urban areas) is controlled for by estimating an average within-country trend across the global South (see Lerch 2018 for details about methods). Third, we focus on the average number of children ever born to successive birth cohorts (rather than on fertility in calendar years) in order to avoid the disturbing effect of large-scale rural-to-urban migration on the measurement of urban fertility trends. Last, we dissect the trend in rural excess fertility through an analysis of the underlying dynamics in the rural and urban transitions.

Does the excess of rural over urban fertility follow an inverted U-shaped curve?

The results support the hypothesis of an inverted U-shaped trend in rural excess fertility over the course of the national fertility transition (Figure 1). The average rural-urban fertility ratio rises from 1.06 to 1.16 before the national transition onset, increases sharply to 40 percent in the first 20 transition cohorts, stabilizes at this level in the subsequent 10 cohorts, and finally drops monotonically down to 1.23 in the 55th transition cohort.

What explains this curvilinear trend in the excess of rural over urban fertility?

Changes in the rural-urban fertility ratio are determined by three underlying dynamics:

(a) the pace of the earlier fertility decline in urban areas,

(b) the time lag in fertility transition onset in rural areas, and

(c) the rural-urban difference in the trajectories of fertility change following the sector-specific transition onsets.

How do these dynamics interact to produce the above non-linear trend in rural excess fertility?

The average decline in urban fertility was continuous (from 5.9 at the national transition onset to 2.6 in the cohort born 55 years later). This explains the early rise in the rural-urban fertility ratio. The median lag between the onsets of fertility decline in urban and rural areas was 16 years, which accounts for the stabilization of the rural excess fertility at its peak level.

Interestingly, the average urban and rural trajectories of fertility decline after their respective onsets followed a similar U-shaped curve: starting from an initial annual drop of about -0.075 children per woman and cohort, the pace accelerated to about -0.093 in the mid-transitional stages, and then decelerated (to -0.030 in urban areas). Therefore, once rural fertility finally started to drop, the pace of decline was much faster in rural than in urban areas (given the substantial time difference between the sector-specific transition onsets). This explains the bulk of the decrease in the rural-urban fertility ratio from its peak level.

At more advanced transitional stages, the decline in the rural-urban fertility ratio was exacerbated by a more pronounced slowing of the urban fertility transition with respect to the rural transition. This can be attributed to the positive indirect demographic effect on urban fertility of rural-to-urban migrants. They had a higher level of childbearing compared to non-migrant women socialized in cities.

Discussion

Our analysis of within-country trends in the rural-urban fertility gradient confirms an inverted U-shaped evolution over the course of the national fertility transition—as suggested by previous inter-country comparisons of fertility levels in a given period. The earlier onset of the fertility transition in urban than in rural areas confirms the importance for fertility change of structural and ideational changes in society, which are intimately related to, and intensified by, population concentration (e.g. urbanization). The major role played by the rural lag in the transition onset for the evolution of rural excess fertility also highlights how the pace of national fertility transitions is dependent on the spread of societal transformations from cities to the periphery of a given country.

These lessons have implications for our understanding of future population trends and policies. First, we can recommend a strengthening of urban-rural interactions and family planning programs in rural areas in order to advance fertility transitions in high fertility regions (such as sub-Saharan Africa). Second, given the continuous fertility decline among long-term urban dwellers, the dominance of natural increase in the process of urban growth in developing countries may end soon. The role played by the direct and indirect demographic effects of migrants can be expected to increase in the future. Last but not least, this study underlines the need for improved collection of demographic data in urban and rural areas.

References

Lerch Mathias. 2018. “Fertility Decline in Urban and Rural Areas of Developing Countries.” Population and Development Review online first.

Montgomery Mark R., Stren Richard, Cohen Barney, Reed Holly E. 2003. Cities Transformed: Demographic Change and Its Implications in the Developing World. Edited by Panel on Urban Population Dynamics. Washington D.C.: The National Academies Press.

Shapiro David, Tambashe B. Oleko. 2000. “Fertility Transition in Urban and Rural Areas of Sub-Saharan Africa.” Working Papers from the Department of Economics Pennsylvania State University September:1-29.

United Nations. 1987. Fertility Behaviour in the Context of Development – Evidence from the World Fertility Survey. New York: United Nations Publications.

United Nations. 2017. World Population Prospects: The 2017 Revision, Key Findings and Advanced Tables: New York, United Nations, Department of Economic and Social Affairs, Population Division.

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Four population-driven threats to space

If from abstract principles and paradigms of my previous article (Malthus, forever?), we turn to the real, contemporary world, we may say that the rapidly expanding world population also has other consequences – beyond the reduction of “pristine” space – that may adversely affect the quality of the environment (space, in our paradigm) and bring about critical situations. Four of these consequences are strictly linked to sensitive environmental questions that will become critical as we proceed towards the end of the century, when world population growth, according to a rather optimistic consensus, is forecast to be close to zero. In the coming eight decades, the world is set to host an additional 3.4 billion people, a number equal to the increase accumulated in the preceding half a century.^[1]

These four consequences are:

(i) human intrusion into the great forests, and particularly the rainforests, whose integrity is a guarantee of the bio-natural equilibrium;

(ii) the intensification of human settlement in the most precarious habitats, in particular along coasts and on the shores of rivers and lakes;

(iii) the explosion of urbanization processes and

(iv) last but not least, global warming.

Each one of these four processes may be described as a population-driven threat to the environment, affecting the quality of space available to humankind.

Population-driven threats to the environment: 1) deforestation

Deforestation processes have accompanied demographic growth ever since the initial spread of agriculture. The great forests play a crucial role in maintaining environmental balances by moderating greenhouse gas emissions, and thus global warming; by maintaining the integrity of water reserves; and by protecting biodiversity. Unfortunately, trees give more (immediate) profit when they are cut down than when they are alive and growing, and pasture and arable land have more (immediate) value than virgin forests. There is ample historical evidence of the deforestation process that occurred in step with population growth across Europe up to the Industrial Revolution. In North America, population settlement and industrialization wiped out the original woodland cover from Canada to the Gulf of Mexico. In coastal Brazil, the Mata (forest) Atlántica was greatly reduced by demand for wood for the sugar cane plantations and the mining industry, and in nineteenth century India, vast areas were deforested to meet the needs of railway construction and the corresponding demand for fuel, as well as for the shipyards and navy. Perhaps, the single phenomenon that currently arouses the greatest concern and debate is the deforestation of the Amazon basin, which is estimated to have eaten away between 15 and 20% of the rainforest cover. This process, which accelerated after the 1940s, is attributable to multiple factors: the acquisition of land for livestock and crops driven by the demands of a rising population at both local and global levels, timber production, mining and oil prospecting, infrastructure development and immigration.

Similar processes have also taken place – or are taking place – in other parts of the world, such as the Congo Basin, Papua New Guinea and Indonesia. Figure 1 shows how, over the period 2000-2010, the development of land in the tropical regions for agricultural purposes has taken place at the expense of forested land. Fortunately, this process has been partially (but only partially) offset by the contrary trend in the te mperate regions, but the global balance has been negative for the planet’s health.

Population-driven threats to the environment: 2) fragile coastal regions

Population growth has been particularly rapid in coastal belts, which are advantageous not only in terms of their climate and landscape but also with regard to communications and the multiple economic opportunities they offer. History teaches us that the majority of the world’s great cities develop along the coast or on major watercourses. However, coastal cities are also the most vulnerable. Uncontrolled expansion of residential and industrial infrastructure in such contexts has negative effects in terms of water contamination, degradation of areas of environmental value, as well as exposure to natural risks (just think of the more than 200,000 deaths caused by the 2004 tsunami).^[2] These risks are destined to grow as a consequence of global warming. The environmental vulnerability of coastal areas has become obvious in recent years given the recurrence of natural disasters (typhoons and tidal flooding) in the river delta regions of South and South-East Asia, especially in Bangladesh.

Data on population distribution in coastal areas is scarce and unsatisfactory. First, there are no standardized (and therefore comparable) definitions of what ‘coastal areas’ actually are. Measures include estimating the population of a coastal belt of determinate width (10, 20… 100 kilometres from the sea), or, equally crudely, counting the population of administrative units that border the sea.

A study making use of satellite measurements has estimated the population living within 100 kilometres of the sea but in areas at less than 10 metres above sea level in each country.^[3] These are the most vulnerable territories, and they are placed at further risk by rising sea levels and the intensification of extraordinary atmospheric events. In 2000, 10% of the world population lived in low-altitude coastal regions, which constituted 2% of planet’s total land area. 60% of these 634 million people lived in urban areas. In general, populations in coastal regions tend to increase more quickly than those living inland, and thus the degree of concentration along the coastlines tends to increase (Figure 2). The same study from which we draw these aggregate data also highlighted the dynamics in two countries – China and Bangladesh – between 1990 and 2000, which are home to about one-third of all inhabitants of low-lying coastal areas worldwide.

In China the growth rate in these areas over that decade was 1.9%, versus 1% nationwide; in Bangladesh the growth rates were 2.1% and 1.1%, respectively.^[4]

Population-driven threats to the environment: 3) urbanization

According to United Nations estimates, the world’s urban population has now surpassed that living in the countryside: in 2018, town and city dwellers represent 55% of the total, and this proportion is destined to increase in the coming decades. In many developed countries, more than 80% of the total population is classified as ‘urban’.

A growing proportion of what is classified as the urban population today lives in big and sprawling conurbations with ill-defined boundaries. In 1950, there were 2 so-called ‘mega-cities’ or agglomerates of over 10 million inhabitants; by 1990, according to UN estimates, there were 10 of them, and 33 in 2018. Meanwhile large settlements of between 5 and 10 million inhabitants have more than doubled in number from 21 in 1990 to 48 in 2018, while the number of “small” settlements of 1 to 5 million people (i.e., “small” only in the terms of this international terminology) rose from 239 to 467.^[5] Demographic concentration in urban areas is not, as such, a negative phenomenon. Humans are essentially gregarious animals and tend to live in restricted spaces. But the modern mega-urbanization process has been compressed into a very short length of time, and has occurred in a disorderly and often anarchic manner. Its main negative consequences for the environment take the form of air pollution – with its well-known ill-effects for health – and water contamination, with effects spreading out into the ecosystem well beyond the mega-city’s own territory. Further consequences are the accumulation of waste, and the degradation of space. And since large conurbations are growing faster than the urban population – a gap that will likely intensify in the future – the negative effect on the ecosystem is destined to become further aggravated, unless robust corrective measures are taken.

Population-driven threats to the environment: 4) global warming

Diminishing pristine land and deterioration of space increase the cost of hosting each new human being. Other factors, such as increased greenhouse gas emissions, have a negative effect on the environment. Indeed, increased human presence on the planet is a powerful contributor to modern climate change, which entails global warming, rising sea levels, the tropicalization of the climate in temperate regions, desertification in some regions, and an increase in extreme climate events. This is a very intricate and technically complex subject, and here we will only touch on it fleetingly. It has now been proved that the increase in greenhouse gas emissions – due to the rise in population numbers and in human activities – is at the root of the global warming that has been underway over the last several decades. As we read in the IPCC’s (International Panel on Climate Change) Fifth Assessment Report: “Anthropogenic greenhouse gas emissions have increased since the pre-industrial era, driven largely by economic and population growth, and are now higher than ever”.^[6] Between 1970 and 2010 there was an 80% increase in the volume of greenhouse gas emissions (four-fifths of which are CO2). All kinds of human activity have contributed to this increase, from energy production to industry, agriculture, housing, trade and transport. Rising population alone may be held responsible for close to half this increase (figure 3).

The IPCC makes complex global simulations based on hypotheses regarding population increase, economic growth, and the rise in emissions. The most recent ones have confirmed that the tendency towards global warming (almost one degree higher in 2000-2010 than in 1850-1900) will continue across the next century. Depending on different hypotheses of emission increases, by the end of the century (2081-2100) the mean temperature on Earth will be between 1 and 4°C higher than it was in 1986-2005.^[7] Specialist publications explain the complex geophysical consequences of global warming, from the melting of the polar ice caps to rising sea levels, the desertification of vast regions and changes in ocean currents. All of these things are of great significance for human society.

Global warming is the consequence of population growth and increasing human activity. Indeed, it could be easily described with an adaptation of the well-known Ehrlich’s equation:

GW = P x A x T x B

where global warming GW is caused by combination of Population, Affluence, Technology and (missing in Ehrlich’s original formulation) Behaviour B, which might be seen as a function of knowledge, customs, social norms and individual tastes. Virtuous behaviours can probably reduce global warming, everything else equal, although the extent of their impact, and how this impact can be measured remain unanswered questions.

Malthus forever?

The notion that space is finite and that population cannot grow forever is probably obvious and intuitive for everyone. The difference with respect to a still recent past is that what once appeared as an immense, unmeasurable expanse of land at the disposal of humankind is now more clearly perceived as finite and increasingly limited. Population growth, dispersion of human settlements, development of technology, increasing wellbeing are the forces that reduce the available space in pristine conditions and endanger the quality of that space, either settled or under the impact of human activity. Space is, indeed, the ultimate resource and the final limit to growth. Malthus was right: nature “has been comparatively sparing in the room… necessary to rear …” us humans. This “room” is shrinking under our very eyes.

Footnote

[1] According to the estimates, and to the median variant projection of the United Nations, the world population was 4.381 billion in 1979, will be 7.795 billion in 2020, and will reach 11.184 billion in 2100. More precisely, given the probabilistic approach followed in the projection, a population of 11.184 billion in 2100 represents the median value of a distribution that, within 80% confidence limits, ranges from a minimum of 10.089 to a maximum of 12.436 billion. United Nations, World Population Prospects. The 2017 Revision.

[2] On September 28, 2018, an earthquake followed by a tsunami in the Indonesian island of Sulawesi killed about 2,000 people.

[3] Gordon McGranahan, Deborah Balk and Bridget Anderson, ‘The Rising Tide: Assessing the Risks of Climate Change and Human Settlements in Low Elevation Coastal Zones’, in Environment & Urbanization, 19, 1, 2007, pp. 17-37.

[4] It is worth adding that the concentration of people in urban areas is very high in these same low-altitude coastal areas.

[5] United Nations, The World’s Cities in 2018, New York, 2018,

[6] International Panel on Climate Change, 2014

[7] International Panel on Climate Change (IPCC), Climate Change 2014, Synthesis Report, Summary for Policymakers.

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Malthus and the limits to growth

Concise and clear, Malthus wrote in the first chapter of his Essay: “Through the animal and vegetable kingdoms, nature has scattered the seeds of life abroad with the most profuse and liberal hand. She has been comparatively sparing in the room and the nourishment necessary to rear them. The germs of existence contained in this spot of earth, with ample food, and ample room to expand in, would fill millions of worlds in the course of a few thousand years”.[1] Nothing new under the sun: in modern times, two centuries before Malthus, Botero had written similar words[2] and Ortes, the bizarre venetian clergyman-economist, acknowledged that geometrical growth is impossible, because it would lead mankind to “grow not only beyond the number of persons that could breathe on the earth, but to such a number as could not be contained on all its surface, from lowest valley to highest mountain, crowded and crammed together like dried dead herrings in their barrel”.[3] So, for both Ortes and Malthus, and for a score of other writers and, indeed, for everybody with a minimum of common sense, the ultimate limit to population growth is space (or land). Because cultivation depends on land, and so do pastures, cattle raising, hunting, and energy, and all material resources for manufacture, and – above all – subsistence.

Space is getting smaller

Centuries ago, the lack of space was a remote threat in a vast, largely unexplored and uninhabited world. But in our times, the limitations imposed by the finite space of our planet are becoming visible at the global scale. Let us suppose that mankind is subdivided into biologically and demographically sustainable groups (communities, clans, tribes, etc.), each one composed of 1,000 inhabitants. Let us call these abstract groups demoi, and let us imagine that 10,000 years ago, at the time of the “invention” of agriculture, 6 million people were evenly distributed across 6,000 demoi. Each demos would have had, on average, an endowment of land equivalent to the surface of Sardinia (22,333 sq.km). Plenty of land, by all means, for 1,000 humans. By the beginning of the Common Era (birth of Christ), the endowment of each of the 250,000 existing demoi would have shrunk to the size of Ibiza (536 sq.km), while at the start of the industrial revolution (around 1800), it would have been the size of Milos (151 sq.km), in the Aegean Sea, (blessed by the statue of Aphrodite which now welcomes visitors at the entrance of the Louvre), which measures only 15 km by 10 km. Three centuries later, in 2100, each demos’ land endowment will be about the size of minuscule Capri (10.4 sq.km), whose renown is incommensurably greater than its size.

Anthropization of the planet and the value of space

Population dispersion and growth have determined a gradual process of anthropization of the planet. A recent study^[4] makes use of the increasingly precise data that is now available thanks to high-definition satellite imaging. It estimates that agricultural and forest cultivation covers some 47% of the earth’s land area, with around 13% devoted to arable use and permanent cultivation; 26% covered by permanent pastureland and meadows; and around 8% more comprising areas subject to deforestation, or which have been artificially replanted. But to this 47% we must also add the other spaces in which human action is radically changing the face of the Earth: the 3% of land surface devoted to urban areas, another 3% to various types of economic activity, and a further percentage point to infrastructure (roads, ports, railways) and mining activities. The total area directly used or transformed by human activity thus accounts for more than half the Earth’s land area (54%). As for the remaining ‘natural’ areas, 28% of total land is covered by woods and forests, while 19% cannot be turned over to agriculture or other human uses because it is frozen, desertic or situated in high-altitude mountain areas. And even these areas are not totally natural, since they too may be affected by human activities through contamination or global warming.

In conclusion, three intertwined global processes are at work: (i), population growth and dispersion; (ii), occupation and anthropization of space; (iii), increasing unfitness of the remaining “pristine” or “semi-pristine” land for human settlement and activities. In the very long run, an additional human, occupying an additional unit of space, will settle in an increasingly inhospitable setting. In other words, the “quality” of that marginal unit of space is declining while the “cost” of occupying or settling it is increasing. It is true that the real world is subject to a plurality of forces, and that adaptation, human ingenuity and technology may sometimes do miracles, but the general (human, social, and economic) cost of settling additional and increasingly inhospitable spaces is tending to increase and represents the “real” limit to population growth.

Similar reasoning can be applied to marginal units of land exploited to produce subsistence or mineral resources and that yield diminishing returns.^[5] In Figure 1, where the population P increases following a logistic curve, while space in pristine conditions S declines in parallel (following an inverted logistic), a proxy for the value V of the marginal unit of land could be the ratio between the two.^[6] This value, in this abstract paradigm, is close to zero at the onset of agriculture, and grows exponentially as population increases and available space declines.

Note

[1] Thomas R. Malthus, An Essay on the Principle of Population, Penguin Books, Harmondsworth, 1970, pp. 71-72 (1st edition 1799). Author’s italics.

[2] Giovanni Botero, Delle cause della grandezza delle città, 1588.

[3] Giammaria Ortes, Riflessioni sulla Popolazione delle Nazioni per Rapporto all’Economia Nazionale, in Pietro Custodi, Raccolta degli scrittori italiani di Economia politica, vol. XXIV, Milan, 1804, Chapter 1.

[4] Roger LeB. Hooke, José F. Martín-Duque and Javier Pedraza, ‘Land Transformation by Humans: A Review’, GSA Today, December 2012.

[5] I am less certain about this last assumption, since modern extractive technology now extends to regions that were once beyond reach, like the Arctic and Antarctic zones.

[6] Or, more correctly, it is the pressure that the existing population exerts on the residual space.

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In recent years, the world has witnessed an intensification of population movements (IOM, 2017). Data from the United Nations High Commissioner for Refugees (UNHCR) shows that while the stock of international migrants increased from 69.3 million persons in 1960 to 247.6 million in 2015, the ratio of displaced persons to international migrants increased tenfold in that same period, from 2.5% to 25% (Figure 1). These figures are highly suggestive of two related processes: on the one hand, the increasing scale of international migration worldwide and, on the other, the growth of other forms of mobility over time. For instance, the number of displaced persons worldwide grew from 1.5 million in 1960 to 60.5 million in 2015, a forty-fold increase. There has also been a change in the composition of these flows, with refugees losing their dominance among the displaced: in 2006, Internally Displaced Persons (IDPs) due to conflicts already outnumbered refugees. This points to another interesting feature of the evolution of mobility in recent years, its growing complexity and the highly heterogeneous nature of the movement of individuals across space.

Increased complexity

Population movements have also become more complex in terms of their causes and consequences. The traditional idea of a migrant who opts for a well-defined migratory project has gradually been replaced by the figure of an agent whose aspirations, intentions, and opportunities for movement are shaped by a rapidly changing socio-political and economic context. Moreover, new events such as political conflicts and environmental disasters have created unprecedented challenges for understanding how and why individuals move, and what legal and humanitarian protection ought to be offered to them. While Afghanistan, Somalia and Sudan dominated the stock of refugees until the mid-2000s, the Syrian and South Sudanese conflicts have made their mark in recent years (Figure 2). The impact of the Syrian conflict on the mobility of its population has been dramatic since the very outset. Syria has dominated the yearly flows of refugees since 2011 and surpassed the historical dominance of Colombia as the country with the highest number of internally displaced persons (IDPs) in 2013. The scales of the yearly flows of IDPs for the other countries shown in Figure 2 mirror the outbreak of local conflicts.

These figures reveal that the world today is a lot more complex than in the years that followed the Second World War, when much of the displacement was concentrated in Europe. The world was also less interconnected, making distances seem longer and destinations more uncertain. It was in this context that the United Nations Convention Relating to the Status of Refugees was created in 1951. The Convention sought to guarantee protection to European citizens who, as a direct consequence of the War, had a well-founded fear of returning to their country of origin on account of their race, religion, nationality, social group, or political orientation. Some years later, the 1967 Protocol Relating to the Status of Refugees was an important step towards the ‘democratization’ of these protections, removing the temporal and geographical restrictions of the Convention by extending the right to seek protection (asylum) to any citizen, not only from Europe.

Since then, new dynamics and types of displacement have led to discussions on the need to retool these normative instruments, which constitute the central elements of the international refugee protection system. Some examples of the increasing complexity of these new movements are the growing numbers of people forced to leave their home because of their inability to guarantee their socioeconomic reproduction or who are escaping from conditions analogous to war. Displacement caused by environmental factors is another visible example of this complexity (IDMC, 2017). These new mobilities highlight the need to develop regulations that are more consistent with the principles contained in the 1948 Universal Declaration of Human Rights. They also raise questions about the impact of these movements on the economies of the countries of destination, as well as their potential for cultural and political conflicts.

The emergence and intensification of old and new conflicts and crises have affected a growing number of countries in the Global South such as Libya, Syria, Yemen, Venezuela, and the Northern Triangle of Central America. There has also been a significant increase in the numbers of people displaced by environmental disasters linked to climate change. It is estimated that in 2016 alone, 31.1 million people were (internally) displaced by conflict, violence, and disasters: one person is forced to flee every second. Of these, 6.9 million were displaced by conflict and violence, mainly in Sub-Saharan Africa and the Middle East, while 24.2 million were hit by climatic events such as typhoons in China and the Philippines, and floods in Indonesia and the Indian Subcontinent (IDMC, 2017).

Demographers between science and politics

Although the developing world hosts 85% of the world’s refugees (UNHCR, 2018a), the so-called “refugee/migrant crisis” has been accompanied by the politicization and increasing criminalization of population movements. The criminalization of migration, and mobility more generally, has been underpinned by the misuse and overestimation of migration data for political purposes, even though the stock of international migrants (including refugees) has remained constant since the 1960s, at around 3% of the world’s population (de Haas, 2017). The image of “invasion” propagated by the media has exacerbated the negative perception that surrounds these population movements, provoking the (re)emergence of often openly racist and xenophobic ultra-right-wing nationalist parties in the European Union. The corollary of this phenomenon has been the withdrawal of the United Kingdom from the European Union (Brexit) and, on the other side of the Atlantic, the election of Donald Trump to the US presidency.

In this context, population mobility has become one of the most important issues of the twenty-first century, a fact made clear by the increasing visibility of the UNHCR and the recent conversion of the International Organization for Migration – historically an advisory intergovernmental organization – into an official UN body. There has also been an intense promotion of migration management and control instruments, and of the migration-development nexus, in particular through the implementation of a series of political, social, and economic policies that seek to incorporate diasporas into the national policies of their sending-countries. These efforts were recently materialized in the Global Compact for Safe, Orderly and Regular Migration and the Global Compact on Refugees to be adopted by the UN General Assembly in December 2018. However, discussions at the international level have, for the most part, placed little emphasis on the main drivers of contemporary migration flows, namely, the intensification of economic globalization, the rise in socioeconomic inequalities within and between countries, and the pre-eminence of demographic factors, which influence the pattern and composition of contemporary flows (Livi-Bacci, 2012).

In this context, demographers and social scientists have a lot to contribute towards understanding the causes and consequences of contemporary population mobilities, especially by working across disciplinary boundaries to address the current conceptual and methodological gaps that are holding back the production of research-based evidence for public debate and policy formation at the national and international levels.

References

de Haas, H. (2017). Myths of Migration: Much of What We Think We Know Is Wrong. Spiegel Online. Hamburg, Der Spiegel.

IDMC (2017). Global Report on Internal Displacement (GRID). Geneva, Internal Displacement Monitoring Centre

IOM (2017). World Migration Report 2018. International Organization for Migration (IOM). Geneva.

Livi-Bacci, M. (2012). International Migration: a global force, ungoverned. População e desenvolvimento em debate: contribuições da Associação Brasileira de Estudos Populacionais C. Maldonado Turra and J. M. P. da Cunha. Belo Horizonte, ABEP.

UN-DESA (2018). Population Division: International Migration.

UNHCR (2018). Population Statistics.

UNHCR. (2018a). Global Trends: Forced Displacement in 2017. Geneva.

Sources figures

Source figure 1 –  UNHCR, 2018 • UN-DESA, 2018

Source figure 2 – UNHCR, 2018

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No disciplinary field develops in isolation from its political, social and cultural environment, and demography is no exception. The first advances in population studies were achieved thanks to the individual efforts of scholars from different backgrounds: political writers like Botero, merchants like Graunt, astronomers like Halley and Wargentin, clergymen like Süssmilch and Malthus. Later, in the 19^th century, with the development of statistics, Quetelet, Farr and Lexis – among others – shaped the contours of the discipline, which was enriched on a regular basis by the results of population censuses and the collection of vital statistics, as well as by closer and systematic contacts among scholars.

This growing body of knowledge attracted the interest of sociologists, economists, and scholars of other social sciences – even biomedical experts. In general, however, it remained at the periphery of these disciplines. The study of population needed specialists, the development of coherent analysis methods, the creation of an autonomous discipline, the formation of specialized institutions, with dedicated chairs, research centers and scientific associations.

This process was initiated in the 1920s and 1930s, and the IUSSP (initially named the “International Union for the Scientific Investigation of Population Problems” and referred to hereafter as “the Union”) was founded in 1928. The population conferences in London and Rome in 1931, in Berlin in 1935, and in Paris in 1937, attest to the scientific progress of the discipline, to the strengthening of the methodology, and to the depth and breadth of the participants’ interests. However, this process of growth – and the life of the newborn IUSSP as well – was marred by the interference of politics, by the influence of ideologies, by unhealthy scientific partisanship and, ultimately, by the catastrophe of the Second World War.[1]

A rebirth after the War

Before the war, the Union was a federation of national committees, not of individual scholars, and this was a major weakness: it increased the risk of political interference in the life of the association, and was a divisive factor among individual researchers. In 1947, the new Union was reestablished as an association of individual scholars who were free, in theory, from political manipulation and interference.

These pages are dedicated to the life of the Union during the half a century or so between its reconstitution in 1947 and 1994, when the United Nations organized the Cairo International Conference on Population and Development (ICPD).^[2] I will not cover the last quarter of a century because many of our readers are familiar with the most recent developments of international demography. Some of them have been important actors on the demographic scene and could talk about the Union better than me.[3]

In a first phase, between the 1947 and 1969, when the General Conference was held in London, the Union gradually built up its international profile and its administrative and organizational autonomy. International meetings were held every other year, but the first five of them (from 1949 to 1957) were special – although independently organized – sessions of the ISI Conferences (International Statistical Institute).[4] In 1959 and 1961, the meetings in Vienna and in New York were autonomous initiatives, while in 1963 the Ottawa Conference was again held under the ISI umbrella. The large conferences held in Rome (1954) and Belgrade (1965) were joint initiatives of the Union with the United Nations, which, despite its active involvement in population questions, preferred to remain in the background, leaving the debate in the hands of individual scholars and experts.

In the late 1960s, the Union reached full autonomy, having built a recognized international reputation. It established permanent independent headquarters in Liège, and functioned according to well-tested protocols, including constitutional rules governing the election of its members and officers. A General Conference was held every four years,[5] the Council established scientific Committees with well-defined mandates, and other less regular activities were carefully planned.

Main themes of interest

During this period, demography advanced under the impulse of several driving forces. The first was the full realization by the international community of the extent of the acceleration of world population growth and, therefore, of the need to better understand its causes, mechanisms and consequences. One important achievement was the organization of census rounds every ten years, with shared protocols that ensured the comparability of results.

The population explosion (or time-bomb, or boom, to use the militaristic vocabulary of population change) generated growing interest in the analysis of relations between population growth and social and economic development, and in the design of policies to control such growth, particularly in developing countries. There were also worries about the sustainability (although different words were used at that time) of population growth, and the possible exhaustion of basic resources, such as food, water, energy and minerals.

The role of demography as a discipline became central for the comprehension of such complex questions; it was necessary to improve analysis methods; to reinforce, expand and integrate data collection systems; and to extend the analysis to countries and regions that had remained at the periphery of research.

The Union and its functioning

The Union played an important role in responding to the new challenges. In 1954 and in 1965, the Conferences co-organized with the United Nations were important steps in building international awareness about the political, economic and social relevance of population issues, highlighting the urgent need for appropriate expertise to address these issues.

While the international meetings held before the war were essentially “Western” events in terms of their participants and the topics presented, scholars from the “Third World” – an expression coined by Alfred Sauvy[6] – were now making their voices heard; their number grew rapidly and so did the quality of their contributions. At the 1954 Rome conference, one in five participants were from Africa, Latin America or Asia, while in 1965 in Belgrade, the proportion was one in three.

Topics such as family planning, methods of analysis with defective or incomplete data, demographic aspects of savings, investment and technological development – and the strong focus on developing countries[7] – attest to the transition of demography from a peripheral and ancillary discipline to a well-defined field of study, offering a growing body of knowledge that was key to our understanding of society.

In the 1950s, scholars were essentially professors in the fields of economic, social and political sciences (including statistics) or specialists who worked in research centers dedicated to the same disciplines or belonged to government agencies dealing with planning, census-taking or vital statistics. There were no professorships in demography, and few would have described themselves as “demographers”. Things changed rapidly in the following decades. At the same time, the research focus of individual scholars, dedicated institutions, and international organizations shifted rapidly towards the developing world, whose rate of population growth peaked at the worrying pace of about 2.5 percent per year in the 1960s and 1970s.

The governance and the Union’s activities readily reflected, but also guided, the general shift in attention to developments in non-Western countries. Before 1969, the Presidents of the Union were illustrious European and American scholars (Hersch, Landry, Mortara, Lorimer, Sauvy, Glass, Vogelnik), but in 1969, Chidambara Chandrasekharan from India was elected President (with a four-year mandate), followed by Carmen Miró (Panama) in 1973, and Mercedes Concepción (Philippines) in 1981.[8] Each continental region was represented by an elected member on the Council of the Union (board of directors) where the major scientific and administrative decisions were taken.

The Union still had solid foundations in Europe, and from 1966, led by an Executive Secretary, [9] it moved into small but permanent headquarters in Liège (Belgium).[10] A Secretary General and Treasurer – a European for the sake of proximity to the headquarters[11] – was in charge of transforming the Council’s directives[12] into practical activities. Union members went through an election procedure based on their scientific and professional merits, and membership climbed almost tenfold from a little over 200 in 1951 to close to 2,000 in the early 1990s, with an increasing presence of scholars from less developed countries (LDCs), who nonetheless remained a minority.

During the 1969-1994 period, the Union’s activities were very intensive. They included the planning and organization of the General Conferences every four years,[13] costly events bringing together up to 1,000 experts; the organization of the Regional and of the Special Conferences[14], and of the many Seminars and Workshops organized by the Union’s Committees and Working Groups, established or renewed every four year by the Council (more on these below). Funds had to be raised; venues for the events had to be chosen in cooperation with the hosting country and institution; scientific programs had to be designed and participants invited: the quantity and quality of output was impressive.[15]

Protocols, finance, and politics

Not everything ran smoothly. The Union acts under a constitution that, notwithstanding adaptations, calls for relatively rigid procedures and protocols. This gave rise to competition between a somewhat rigid modus operandi (particularly for the General Conferences and other big events) and the need to incorporate the new cutting-edge research, to recruit the most qualified experts, and to cooperate with the best institutions. However, the Union’s priorities were also to disseminate knowledge, to promote the inclusion of left-behind countries and regions, to build bridges with other disciplines, and to ensure smooth collaboration with the growing number of national research centers and of international organizations whose main missions were not to produce original research.

Aside from a fair amount of diplomatic compromise, a way was found to reconcile these competing viewpoints through the activity of the scientific Committees and Working Groups, which had considerable autonomy and flexibility in planning their activities, recruiting members, organizing seminars and meetings that, in general, were co-sponsored and co-financed by research centers and institutions hosting the various events. For instance, in 1988 (admittedly a record year), there were as many as 10 seminars on the following topics: Event history analysis, Biomedical and demographic determinants of human reproduction, Fertility transition in Asia, Collection of demographic data in Latin America, Medicine and the decline of mortality, Mortality in south-east and east Asia, International migration systems, Family in aging societies, Nuptiality in Sub-Saharan Africa, Theories of family change (plus a large African Population Conference, and another conference on Women’s role and demographic changes).[16] In the following four-year period 1989-1993, 22 similar events were organized by the Union.

Another thorny problem was finance. Most international associations of scientists struggle with financial constraints. Autonomous revenues (membership dues, Conference registration fees, sales of publications) covered only a fraction of the Union’s general budget. Non-earmarked grants from Governments and other institutions, highly appreciated for the flexibility they allowed in spending, were unfortunately rare and small.

Some donors were generous (first and foremost the UNFPA, created in 1969) in supporting activities that coincided with their missions and priorities. There were no problems in financing activities on topics like population and development, high fertility, family planning, maternal and child health, AIDS/HIV, gender issues… But financing the committees on historical demography, anthropology and demography, or meetings on issues pertaining to the developed world, was much more difficult. Maintaining a certain balance between “fashionable” topics and themes that lay outside the remit of the various donors proved hard to manage. The temptation was, of course, to “follow the money”, but on the whole, the Union has succeeded in maintaining a reasonable and honorable balance.

I have touched upon the issue of expanding the membership of LDC scholars, and the (slow) progress achieved. But during the period under examination there were two major problems, concerning the USSR and its satellites on one hand, and China on the other.

In the socialist bloc, experts were few, and participants in Union-sponsored events were often bureaucrats under an official mandate. A personal recollection provides a good illustration of the situation: on two or three occasions, the Union invited a well-respected Polish scholar who declined to participate, giving unconvincing reasons for his refusal. These invitations were reiterated until we were warned (of course, unofficially) that insistence on our part (a letter was also sent to the president of the Academy of Science) was dangerous for the person in question since his (purely intellectual) ties with the West had aroused the suspicions of the authorities.

Another episode illustrates the attitude of China. Early in 1977, I had an interview in Paris with the Chinese Ambassador to UNESCO. I told him that the Council would be pleased to invite a delegation of Chinese scholars to the General Conference to be held in the same year in Mexico City. China, at the time, had begun sending students to doctoral programs in Western universities. The Ambassador listened to my words kindly and attentively, asking about several aspects of the Conference, and I thought that things were going well. But I realized I was wrong when he remarked abruptly “I have been informed that your association includes a few members from Taiwan and this fact makes it impossible for us to participate in the Union’s activities”. It proved fruitless for me to point out that the Union chose its members solely on their individual merits, and that Conference participants were individual scholars and not representatives of a nation. No Chinese scholars came to Mexico. Four years later, things had changed radically: at the General Conference in Manila there was a substantial Chinese delegation, and a special session was dedicated to the population of China, with papers presented by Chinese colleagues.

The basic principles of the Union: then and now

In 1989, addressing the General Assembly as the newly elected President of the Union, I summed up the principles that I intended to follow,[17] and I think those principles are still valid today, with the necessary adaptations to the new situation.

They were:

1. Defense of the Union as an association of individual scholars who must not be subjected to lobbying by pressure groups acting on behalf of organized interests.
2. Defense of the Union’s scientific prestige through the selection, planning and professional implementation of its scientific activities.
3. Importance of building bridges with other disciplines: fruitful collaboration has been established with historians, anthropologists and researchers in the biomedical fields. Less satisfactory, for complex reasons, is our record with economics.
4. More flexibility in the implementation of scientific programs.
5. Importance of improving relations and dialogue with donors, reaffirming the Union’s independence and autonomy in deciding our scientific priorities, while submitting their priorities to serious analysis.
6. Importance of responding to the request that the Union take some responsibility in the dissemination of knowledge.

“Being an association of scholars, we are not very good at dissemination. Our timid attempts have not been very successful. And yet it is an important area; we have many things to say, many interesting results to communicate not only to other scientists, but to administrators and policy makers. It is a difficult area that requires professional skills that we do not have”.

Have we made progress in the last quarter of a century? Have we kept our independence? Is our scientific prestige intact? Have we taken full advantage of the digital era? (Until the 70s, before the introduction of fax machines, communication about the international affairs of the Union was handled by the postal service, as in the 19^th century.) Have we improved the dissemination and communication of our research? Have we developed interactions with other disciplinary fields? Recounting the recent and less recent history of our association, and comparing the present with the past, is a healthy exercise.

Footnote

[1] On the history of the Union from 1928 to the end of the War, see the booklet prepared by IUSSP for the General Conference of Florence, in 1985, The IUSSP in History; see also L. MacKellar and B.W Hart (2014). “Captain George Henry Lane-Fox Pitt-Rivers and the Prehistory of the IUSSP”, Population and Development Review 40(4).

[2] Another reason for this choice of period is that in 1993, at the end of my mandate as President, I ceased to be directly involved with the IUSSP.

[3] Among them, past IUSSP Presidents (José Alberto Magno de Carvalho, Jacques Vallin, John Cleland, Peter McDonald, Anastasia Gage) or Secretary Generals (Allan Hill, Wolgfang Lutz, France Meslé, Nico van Nimwegen).

[4] Geneva 1949; Washington 1951; Rome 1953; Petropolis 1955; Stockholm 1957; Ottawa 1963.

[5] London 1969; Liège 1973; Mexico City 1977; Manila 1981; Florence 1985; New Delhi 1989; Montreal 1993; Beijing, 1997. Regional Conferences were also organized in cooperation with United Nations regional branches: Sydney, 1967 (with ESCAP); Mexico City in 1970 (with ECLA and CELADE).

[6] Alfred Sauvy was President of IUSSP between 1961 and 1963.

[7] “In each topical meeting, special attention was given to the problems of developing countries”, United Nations, World Population Conference, 1965, Vol. 1, Summary Reports, p. 1.

[8] Ansley Coale, USA, was elected President in 1977. William Brass (UK) and Jack Caldwell (Australia), who served as Presidents in 1985-89 and 1993-97 had devoted a large share of their scientific career to research on developing countries. I myself (1989-1993), on the other hand, had worked mainly on historical topics and on the demography of contemporary Europe.

[9] Bruno Remiche from Belgium was Executive Secretary from 1969 to 1995.

[10] In 1981 The Union acquired the building that housed the headquarters in Liège.

[11] Eugene Grebenik was Secretary General in 1965-1973; followed by me (1973-1981), Georges Tapinos (1981-89), and Allan Hill (1989-97).

[12] The General Assembly, convened only every four years, could also give general guidelines.

[13] In London in 1969, Liège in 1973, Mexico City in 1977, Manila in 1981, Florence in 1985, New Delhi in 1989, Montreal in 1993, Beijing in 1997.

[14] Regional Conferences in Sydney in 1967, in Mexico City in 1970, in Accra in 1971; Conference on Population and Economics in Helsinki in 1978, and Conference on The Peopling of America in Veracruz, 1992.

[15] I recommend that a directory of all the activities undertaken by the Union since its foundation be posted on the Union’s website. (A list of IUSSP activities – probably not complete – is available at: https://iussp.org/en/iussp-meetings-and-events). Besides, a special program could be launched in anticipation of the Union’s centenary to be celebrated in 2028, nine years from now. The three volumes of the Veracruz Conference of 1992 on the Peopling of the Americas, for instance, are already online, thanks to the effort of the Colegio de México (http://iussp.colmex.mx/descargar-volumenes).

[16] IUSSP, Newsletter n. 36, May-August 1989, pp. 5-6.

[17] IUSSP, Newsletter n. 37, September-December 1989, pp. 17-18.

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Norway and others: incapable of predicting life expectancy accurately?

In June 2018, Statistics Norway (2018) published its latest population forecast. The agency expects that the average length of life of men will increase to 87 years in 2050. This is six years more than the current value of 81 years. In a forecast published in 1993, the life expectancy prediction for 2050 was eight years lower than in today’s population forecast. For women, the life expectancy prediction for 2050 increased by “only” four and a half years – from 84.5 years in the 1993 forecast to 89 years now. Demographers and other social scientists, in Norway as well as in other developed countries, have systematically underestimated the rate of life expectancy increase. Governments should be concerned about stronger ageing than official forecasts suggest.

In the population forecasts published approximately every third year between 1990 and 2018, Statistics Norway predicted ever-higher life expectancy values ​​for men in 2010, 2030 and 2050 (and other years, not shown here). Figure 1 shows how much the agency adjusted men’s life expectancy forecasts for 2010, 2030 and 2050 each time they updated their calculations. Almost without exception, the forecasts were higher. For women, the picture is the same, but the adjustments were a bit smaller. There is no reason to assume that the situation is very different in other developed countries. Pison (2018), for instance, notes that official French forecasts of life expectancy at birth published by INSEE between 1970 and 1995 all underpredicted the actual values. This confirms earlier findings for many developed countries (Keilman and Pham 2004). Up-to-date information of the kind shown in Figure 1 is only available for Norway.

However, a re-analysis of data collected by Keilman and Pham (2004) reveals the same patterns for older forecasts for Austria, Denmark, Netherlands, Norway, Sweden, and the United Kingdom (Figure 2).

All life expectancy values in Figure 2 relate to assumed values for the year 2000, according to official population forecasts published by statistical agencies in six countries before 2000. The trend is clearly upwards, from 70-72 years in forecasts of the early 1970s to around 76 years in forecasts of the late 1990s. As in the case of Norway in Figure 1, the pattern for women in these six countries is similar, but the increase is slower.

Why is life expectancy increasing more rapidly than expected?

Why were demographers and other social scientists not more optimistic about people’s length of life? Pison (2018) suggests that French forecasters long underestimated the increase in life expectancy because they did not anticipate the sharp drop in adult mortality, old-age mortality in particular. There is no reason to assume that the situation was different in the six countries in Figure 2. The decline in cardiovascular mortality explains much of the drop in adult mortality during the past fifty years. Falling numbers of cancer deaths contribute also. Forecasters did not foresee this decline, and relied heavily upon observed trends. Longevity improved only slowly during the 1950s and early 1960s, in particular for men. In some countries, there was even a decline. Therefore, forecasters assumed that the life expectancy would increase very little in the immediate future, and that it would soon reach a maximum value (“ceiling”, or “limit”; see Oeppen and Vaupel, 2002). Indeed, five countries of Figure 2 used such a ceiling: Austria (until the 1990 forecast, in which mortality was kept constant after 2015), Denmark (forecast of 1997, constant after 2012), Norway (forecast of 1990, constant after 2010), Netherlands (forecast of 1995, constant after 2010), Sweden (forecast of 1994, constant after 2025). During the 1990s, however, the forecasters in these countries dropped the idea of a ceiling, and started to extrapolate a much more systematic increase in future life expectancy, although not steep enough. French forecasters used a life expectancy ceiling up to the forecast published in 1986, but gave up this idea starting with the forecast published in 1995 (Pison 2018).

Forty years ago, Ascher (1978) analysed fertility forecasts in developed countries and noted that forecasters tend to rely strongly on recently observed data; they give less weight to the long-term trend. This “assumption drag” holds for mortality, too.

Will mortality forecasters become less timid in their extrapolations when they inspect cohort life expectancies? The life expectancy from a period life table for a particular year is a hypothetical value. It gives a snapshot of mortality in an ever-changing society. In developed countries, in the past decades, this hypothetical value has increased by about 1-2 years of age for each ten-year period. However, Human Mortality Database data for cohort life tables of ten developed countries show that the real life expectancy of the birth cohorts born between 1880 and 1915 increased approximately twice as fast (Human Mortality Database 2017).¹

Another possibility is that forecasters will learn from the errors they make, although this is easier said than done. For instance, a (naïve) straight-line extrapolation of the green line in Figure 1 would lead to a life expectancy of Norwegian males in 2050 of 97 years. This appears to be a bit high although, probably, not by much. After all, there is no sign that the upward trend in the green line will flatten out soon. It is likely that the true value in 2050 will end up closer to 97 years than to the current, timid projection of 87 years.

A systematic bias, with potentially dire consequences

We have witnessed a huge increase in human average length of life – one of the greatest achievements of mankind in modern times. However, it also creates challenges for, among other things, public pensions and national health care systems. The challenges caused by ageing populations are larger than what official population forecasts suggest. Governments of developed countries should be concerned.

References

Ascher, W. (1978) Forecasting: An appraisal for policy makers and planes. Baltimore: Johns Hopkins University Press.

Keilman, N., Pham, D.Q. (2004) Empirical errors and predicted errors in fertility, mortality and migration forecasts in the European Economic Area. Discussion Paper no 2004/386. Oslo: Statistics Norway.

Human Mortality Database – HMD (2017). University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany). Available at www.mortality.org.

Oeppen, J. and Vaupel, J. (2001) Broken limits to life expectancy. Science 296(5570), 1029-1031.

Pison, G. (2018) 1968-2018: Four demographic surprises in France over the last 50 years. Population & Societies 553, 1-6.

Statistics Norway (2018) Norway’s 2018 population projections: Main results, methods and assumptions (by Astri Syse, Stefan Leknes, Sturla Løkken, and Marianne Tønnessen. Discussion Paper no 2018/22. Oslo: Statistics Norway.

Footnote

¹HMD data on cohort life tables for Denmark, England and Wales, Finland, France, Iceland, Italy, Netherlands, Norway, Sweden, and Switzerland.

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Questions about family change

Models of family change provide contrasting views on how the stability of cohabiting families should vary across countries. The second demographic transition theory predicts greater family diversity driven by powerful ideational shifts toward individual needs, nonconformity, and gender equality (van de Kaa 1987). Along the way, distinctions between cohabitation and marriage should fade, with cohabitation becoming a more stable arrangement in which having and raising children is commonplace (Kiernan 2000). An alternative view points to persistent differences in the experiences of marriage and cohabitation, drawing on U.S. accounts of the symbolic significance of marriage as a marker of prestige (Cherlin 2009) and a “pattern of disadvantage” evident in the link between cohabitation and economic instability (Perelli-Harris et al. 2010b). Rather than convergence, this pattern suggests growing disparities in family patterns and the resources associated with them (McLanahan 2004).

Our study

In a study recently, we examined how union instability among married and cohabiting couples with children differed across eight Western countries: United States, United Kingdom, Norway, Sweden, Austria, France, Italy, and Spain (Musick and Michelmore 2018). We examined whether factors commonly associated with union dissolution were more common in the United States than in the European countries, and whether these differences account for why couples in the United States are much more likely to separate than couples in much of Western Europe.

We used data from the Harmonized Histories (Perelli-Harris, Kreyenfeld, and Kubisch 2010a) on women of childbearing age (15-45) who had a birth with a cohabiting or marital partner within 10 years of the interview date. We followed couples over time, taking note of whether and when they married or separated from their partners, and we conducted a number of simulations to illustrate how much of the differences in separation rates across countries were due to differences in cohabitation, educational attainment, early childbearing, and prior childbearing.

Key findings

Overall, estimated probabilities of separation within five years of having a birth were about 2 to 4 times higher in the United States than elsewhere. We showed that this was not due to higher relative odds of separation among U.S. cohabiting versus married parents, which were similar in the European countries we analyzed, net of controls. U.S. marriages were about as stable as cohabitations in most of the countries we studied, and they were less stable than cohabitation in Norway and Sweden. On the other end of the continuum, Italy and Spain stood out in having low levels of union instability.

Across all study countries, we found that cohabiting parents who did not subsequently marry were much more likely to separate than married parents (see Figure 1). However, in most countries we also found that the odds of separation among cohabiting parents who subsequently married were statistically indistinguishable from those married at the time of a child’s birth, net of controls (Spain and Austria were exceptions). This is an important distinction that is not often emphasized in the literature.

In the United States and United Kingdom, we found stark differences in the characteristics of married and cohabiting couples: cohabiting couples in these countries were less educated, younger at birth, and more likely to have had a child with a previous partner, compared to married couples. In contrast, we found relatively few differences in the characteristics of cohabiting and married couples in the Nordic countries (where cohabitation has long been common), consistent with predictions of the second demographic transition theory that differences between cohabitation and marriage will fade as cohabitation becomes more prevalent.

Low education, prior childbearing, and early age at birth were associated with union instability fairly consistently across countries, but the prevalence of these characteristics varied substantially. The United States and Italy both stood out in levels of prior childbearing and early childbearing—the United States in its high levels, and Italy in its low levels. We ran simulation exercises to highlight how couple characteristics at these two extremes might play into union instability elsewhere. Simulations showed that couple’s characteristics played a role in explaining differences in separation rates across countries, but did not account for the whole story. For example, even when assigned Italy’s very low prior childbearing and high maternal age, simulated probabilities of separation in the U.S. remained substantially higher than elsewhere.

In addition to the high levels of prior childbearing and early childbearing, another distinguishing feature of U.S. instability is the clustering of these factors, i.e., the tendency of low education, early childbearing, and prior childbearing to go together. U.S. patterns provide the clearest illustration of diverging destinies, in which women at the bottom and top of the education distribution follow different paths of family change. The absolute gap in separation rates between the highly-educated and the less-educated was by far the largest in the U.S. (see Figure 2). Separation probabilities of U.S. college graduates (9%) were in line with their European counterparts, whereas less-educated couples in the U.S. had separation probabilities (35%) that ranged from 2 to 7 times higher than less-educated couples elsewhere. Less-educated U.S. couples are outliers in the cross-national context in their high levels of prior childbearing and young age at birth, but not their detachment from marriage. U.S. college graduates, on the other hand, look much similar to college graduates in comparison countries, with the exception of their low share of cohabiting at birth.

Conclusions

Parental separation is high in the U.S. relative to Europe—and the implications for children are potentially amplified by distinct features of the U.S. context. One feature is the tighter packaging of factors associated with union instability in the U.S. that may compound any resource loss associated with parental separation. The relatively weak U.S. social safety net is another feature potentially exacerbating the implications of parental separation for U.S. children. The U.S. social safety net has turned away from serving its most vulnerable since the 1980s (Moffitt 2015) and does little relative to other rich countries to pull single-parent families out of poverty (Maldonado and Nieuwenhuis 2015; Smeeding 2005). Diverging destinies appear to be a common feature of family life, evident across the countries examined here. But they are starker in the U.S. and are likely more consequential for the next generation.

References

Cherlin, A. J. (2009). The marriage-go-round: The state of marriage and the family in America today. New York, NY: Alfred A. Knopf.

Kiernan, K. (2000). European perspectives on union formation. In L. Waite, C. Bachrach, M. Hindin, E. Thomson, & A. Thornton (Eds.), Ties that bind: Perspectives on marriage and cohabitation (pp. 40–58). Hawthorne, NY: Aldine.

Maldonado, L. C., & Nieuwenhuis, R. (2015). Single-parent family poverty in 24 OECD countries: A focus on market and redistribution strategies (LIS Center Research Brief 2/2015). New York: Luxembourg Income Study Center, City University of New York Graduate Center.

McLanahan, S. (2004). Diverging destinies: How children fare under the second demographic transition. Demography, 41, 607–627.

Moffitt, R. (2015). The deserving poor, the family, and the U.S. welfare system. Demography, 52, 729–749.

Musick, K., Michelmore K. (2018). Cross-national comparisons of family complexity and stability. Demography, 55(4), 1389-1421. DOI:10.1007/s13524-018-0683-6

Perelli-Harris, B., Kreyenfeld, M., & Kubisch, K. (2010a). Harmonized Histories: Manual for the preparation of comparative fertility and union histories. (MPIDR Working paper WP-2010-011). Rostock, Germany: Max Planck Institute for Demographic Research.

Perelli-Harris, B., Sigle-Rushton, W., Kreyenfeld, M., Lappegård, T., Keizer, R., & Berghammer, C. (2010b). The educational gradient of childbearing within cohabitation in Europe. Population and Development Review, 36, 775–801.

Smeeding, T. (2005). Public policy, economic inequality, and poverty: The United States in comparative perspective. Social Science Quarterly, 86, 955–983.

van de Kaa, D. (1987). Europe’s second demographic transition. Population Bulletin, 42(1). Washington, DC: Population Reference Bureau.

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The demographics of the Brazilian sandwich generation

The increasing delay in fertility and the reduction in mortality have changed not only the population age structure (Castanheira and Kohler, 2017; França el al, 2017), but also family dynamics. Among other things, middle-aged women now face a much higher probability of having their elderly parents alive while still having to care for their young children. This so-called “sandwich generation”, with responsibilities towards both the younger and older generations, is a phenomenon that has attracted the attention of researchers and policy makers in recent years (Goldstein, Mason and Zagheni, 2011; Dukhovnov and Zagheni, 2015).

The operative definition of the sandwich generation may vary, depending on research objectives and data availability. It is usually defined as the middle-aged population, especially women, who have a dependent child (under 18 years old) and a living parent (aged over 65 who may need assistance). Both groups are generally assumed to be incapable of providing for their own needs, and therefore to compete for care and put the sandwich generation under pressure. Here, we adopt a slightly different definition, following Mason and Zagheni (2014): a woman is “sandwiched” if she has one or more children under the age of ten and one or more (old) parents who are less than five years away from the average age at death.

We discuss this phenomenon in Brazil, where both mortality and fertility have changed rapidly in the past few years. Fertility declined from 6.1 to 1.8 children per woman between 1950 and 2010 (when considerable postponement was also observed) whereas life expectancy increased from 50.8 years to 74.6. (Figure 1). In addition to this rapid demographic change, public transfers to the elderly are relatively high, but this has co-existed with a tradition of family support (Turra, Queiroz and Rios-Neto, 2011).

Different perspectives of the Brazilian sandwich generation

To get a glimpse of what has actually happened in Brazil in the past century or so we used Socsim, a social simulation demographic model, originally conceived by Gilbert and Hammel and further developed by Hammel, Wachter and Peter Laslett. We tried alternative scenarios of fertility and mortality (all compatible with Brazil’s history), but the differences between them turned out to be minor, so we will concentrate only on one of them, the most realistic, in our opinion (Lima, Tomás and Lanza Queiroz 2015).

Figure 2 shows some of our results: while the average age of mothers at childbirth has not changed much over time (from 25 years at the beginning of the century to 30 years today – but with a large decline in fertility), the age at becoming a grandparent increased rapidly from 1920 to 1940, and then stayed roughly constant.

Figure 3 shows the prevalence of the sandwich generation from the perspective of the child, by year. What emerges very clearly is that the average time women spend sandwiched between elderly parents and young children has declined in Brazil over the past 60 years, contrary to common perceptions and to what seems to happen in most developed countries.

A limitation of our analysis is that we use a definition of sandwich generation which is not fully comparable to that used by most of the literature in developed countries. However, we do not think that this invalidates our substantive findings: Mason and Zagheni (2014), for instance, who use the same definition as we do, observed a decline in sandwichness for most countries in the world, explained by the reduction in fertility levels and the increase in longevity.

References

Castanheira H.C., & Kohler H.P. (2017). Social determinants of low fertility in Brazil. Journal of Biosocial Science, 49(S1), S131-S155.

Dukhovnov D., & Zagheni E. (2015). Who takes care of whom in the United States? Time transfers by age and sex. Population and development review, 41(2), 183-206.

França E.B., et al (2017). Cause-specific mortality for 249 causes in Brazil and states during 1990–2015: a systematic analysis for the global burden of disease study 2015. Population Health Metrics, 15(1), 39.

Goldstein J., Mason C. and Zagheni E. (2011). Can grandma help with the kids? A demographic analysis of the sandwich generation. In Annual Meeting of the Population Association of America, Washington DC.

Lima E.E.C., Tomás M.C. and Lanza Queiroz B. (2015). The sandwich generation in Brazil: demographic determinants and implications. Revista Latinoamericana de Población, 9(16).

Mason C. and Zagheni E. (2014), “The sandwich generation: demographic determinants of global trends”, Annual Meeting of the Population Association, Boston. Mass.

Turra, C. M.; Queiroz, B L.; Rrios-Neto, E LG.. Idiosyncrasies of intergenerational transfers in Brazil. In: Lee, R. & Mason, A. (eds) Population Aging and the Generational Economy, p. 394, 2011.

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Death rates in summer and winter

Our recent research (Ho and Noymer, 2017) looks at the question of what life expectancy would be if it was always summertime – and the answer is that women in the United States would have about one year more life expectancy, and men, about two-thirds of a year. Easier living, indeed, although the difference is not overwhelming. Rather than the four seasons, we divided the year into two “pseudoseasons”, to keep it simple: pseudowinter (November through April) and pseudosummer (May through October). We split mortality data for the United States into these pseudoseasons and calculated life expectancy for these periods instead of for calendar years. Figure 1 shows our results, as pseudosummer and pseudowinter life expectancy over time.

Mortality rates are lower in the summertime, yielding longer life expectancy. In fact, our findings indicate that winter mortality rates are higher by about ten percent, especially at ages 45 and above, the ages at which most deaths in the United States occur. If winter mortality rates are that much higher, why does life expectancy not differ by around ten percent – or about seven years – between the seasons? The answer lies in the nature of mortality at older ages: mortality rates rise steeply with age. The one-year probability of dying for a 70 year-old is about double that of a 60 year old; that for an 80 year-old is a little more than double that of a 70 year-old, and so on. A ten-percent difference in mortality rates has a marginal impact on this overall steep ladder of increasing mortality by age. So, life expectancy at levels typical of the United States is not drastically changed by the seasons, even though the summertime enjoys more lenient mortality.

Another way to think about the ten-percent lower mortality rates in the summer is in terms of age shifts. For people at about age 45 and up, death rates increase by age, so living in the summertime with its kinder mortality is just like being younger. Imagine the seasonal change like an age difference. In 2010, in United States, we found that for women at age 50, their “summer” age (in terms of mortality rates, compared to winter) is 49.4; at age 60, 59.3; at age 70, 69.1; at age 80, 79.0, and at age 90, 88.9. For men, the relationships were similar: 49.5; 59.3; 69.1; 78.9, and 88.7, respectively. Conceived as age shifts, these data are very telling. Yes, mortality is ten-percent lower in the summertime, but because death rates rise steeply by age, this is like being only a little younger. Therefore, the overall difference in life expectancy, while noticeable, is not enormous.

If I move to Florida will I live longer?

As a practical matter, what does this mean? If their goal is to live longer, should people move to warmer places with milder winters? All else being equal, yes, but with two major caveats. First, these effects are small for an individual, small enough that a person should just live where she wants to live. Second, there is much more to mortality than just temperature (Kalkstein, 2013). While tropical Hawaii is the U.S. state with longest life expectancy, Florida — also known for its warmth — only comes in 20th, while Minnesota, known for its severe winters, holds second place. What is more, not all the summer-winter effects are temperature-related. While causes of death such as thrombosis show an association with cold, the reasons for the seasonality of influenza and other respiratory viruses are not fully understood, and may be driven by the timing of the school year.

Nonetheless, when aggregated over millions of people moving to places with milder winters, the differences add up. Deschênes and Moretti (2009) estimate that population movements from the colder U.S. Northeast to the warmer Southwest “account for 4% to 7% of the total gains in life expectancy experienced by the U.S. population over the past thirty years”.

What about climate change? Our findings, based on data from 1959–2014, are hard to extrapolate. Hotter summers can bring more heat-related deaths, winter extremes still occur, and influenza persists, so unfortunately we do not regard our findings as predictive of a mortality silver lining to global climate change.

Fish are jumpin’, and the life expectancy is high

Demographers have a longstanding interest in the seasonality of mortality (Rau, 2006). In the United States and other temperate regions, winters see higher mortality than summers. The reasons are complex and include cold and the circulation of viruses (“the flu season”). Cardiovascular causes increase in the winter, which for some sub-causes like thrombosis are cold-related, and, more broadly, may be influenza-related (this is still not fully understood). Cancer mortality is not seasonal. All in all, the living is, in fact, a little easier in the summer if we’re talking about lower death rates. Universal influenza vaccines — ones that would not need to be re-administered every fall — are often described as a public health innovation that is desperately needed. Our work shows that the best-case scenario of their impact on life expectancy is about one year.

References

Deschênes, Olivier and Enrico Moretti. 2009. “Extreme weather events, mortality, and migration.” Review of Economics and Statistics 91(4):659–681.

Ho, Tina and Andrew Noymer. 2017. “Summertime and the livin’ is easy: Winter and summer pseudoseasonal life expectancy in the United States.” Demographic Research 37(45):1445–1476.

Kalkstein, Adam J. 2013. “Regional similarities in seasonal mortality across the United States: An examination of 28 Metropolitan Statistical Areas.” PLoS One8(5):e63971.

Rau, Roland. 2006. Seasonality in human mortality: A demographic approach. No. 3 in Demographic Research Monographs, Springer, Berlin.

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