Demographic transition

The existence of some kind of demographic transition is widely accepted in the social sciences because of the well-established historical correlation linking dropping fertility to social and economic development.[1] Scholars debate whether industrialization and higher incomes lead to lower population, or whether lower populations lead to industrialization and higher incomes. Scholars also debate to what extent various proposed and sometimes inter-related factors such as higher per capita income, higher female income, lower mortality, old-age security, and rise of demand for human capital are involved.[2]

Demographic transition overview, with below-replacement-fertility broken out into a "stage 5"

History of the theory

The theory is based on an interpretation of demographic history developed in 1929 by the American demographer Eric Lofstedt (1887–1973).[3] Adolphe Landry of France made similar observations on demographic patterns and population growth potential around 1934.[4] In the 1940s and 1950s Frank W. Notestein developed a more formal theory of demographic transition.[5] By 2009, the existence of a negative correlation between fertility and industrial development had become one of the most widely accepted findings in social science.[1]

Summary of the theory

Demographic change in Germany, Sweden, Chile, Mauritius, China from 1820 to 2010.
Pink line: crude death rate (CDR), green line: (crude) birth rate (CBR), yellow line: population.

The transition involves four stages, or possibly five.

  • In stage one, pre-industrial society, death rates and birth rates are high and roughly in balance. All human populations are believed to have had this balance until the late 18th century, when this balance ended in Western Europe.[6] In fact, growth rates were less than 0.05% at least since the Agricultural Revolution over 10,000 years ago.[6] Population growth is typically very slow in this stage, because the society is constrained by the available food supply; therefore, unless the society develops new technologies to increase food production (e.g. discovers new sources of food or achieves higher crop yields), any fluctuations in birth rates are soon matched by death rates.[6]
  • In stage two, that of a developing country, the death rates drop quickly due to improvements in food supply and sanitation, which increase life expectancies and reduce disease. The improvements specific to food supply typically include selective breeding and crop rotation and farming techniques.[6] Other improvements generally include baking and access to ovens. For example, numerous improvements in public health reduce mortality, especially childhood mortality.[6] Prior to the mid-20th century, these improvements in public health were primarily in the areas of food handling, water supply, sewage, and personal hygiene.[6] One of the variables often cited is the increase in female literacy combined with public health education programs which emerged in the late 19th and early 20th centuries.[6] In Europe, the death rate decline started in the late 18th century in northwestern Europe and spread to the south and east over approximately the next 100 years.[6] Without a corresponding fall in birth rates this produces an imbalance, and the countries in this stage experience a large increase in population.
  • In stage three, birth rates fall due to various fertility factors such as access to contraception, increases in wages, urbanization, a reduction in subsistence agriculture, an increase in the status and education of women, a reduction in the value of children's work, an increase in parental investment in the education of children and other social changes. Population growth begins to level off. The birth rate decline in developed countries started in the late 19th century in northern Europe.[6] While improvements in contraception do play a role in birth rate decline, it should be noted that contraceptives were not generally available nor widely used in the 19th century and as a result likely did not play a significant role in the decline then.[6] It is important to note that birth rate decline is caused also by a transition in values; not just because of the availability of contraceptives.[6]
  • During stage four there are both low birth rates and low death rates. Birth rates may drop to well below replacement level as has happened in countries like Germany, Italy, and Japan, leading to a shrinking population, a threat to many industries that rely on population growth. As the large group born during stage two ages, it creates an economic burden on the shrinking working population. Death rates may remain consistently low or increase slightly due to increases in lifestyle diseases due to low exercise levels and high obesity and an aging population in developed countries. By the late 20th century, birth rates and death rates in developed countries leveled off at lower rates.[7]
  • Some scholars break out, from stage four, a "stage five" of below-replacement fertility levels. Others hypothesize a different "stage five" involving an increase in fertility.[8]

As with all models, this is an idealized picture of population change in these countries. The model is a generalization that applies to these countries as a group and may not accurately describe all individual cases. The extent to which it applies to less-developed societies today remains to be seen. Many countries such as China, Brazil and Thailand have passed through the Demographic Transition Model (DTM) very quickly due to fast social and economic change. Some countries, particularly African countries, appear to be stalled in the second stage due to stagnant development and the effect of AIDS.

Stage one

In pre-industrial society, death rates and birth rates were both high, and fluctuated rapidly according to natural events, such as drought and disease, to produce a relatively constant and young population. Family planning and contraception were virtually nonexistent; therefore, birth rates were essentially only limited by the ability of women to bear children. Emigration depressed death rates in some special cases (for example, Europe and particularly the Eastern United States during the 19th century), but, overall, death rates tended to match birth rates, often exceeding 40 per 1000 per year. Children contributed to the economy of the household from an early age by carrying water, firewood, and messages, caring for younger siblings, sweeping, washing dishes, preparing food, and working in the fields.[9] Raising a child cost little more than feeding him or her; there were no education or entertainment expenses. Thus, the total cost of raising children barely exceeded their contribution to the household. In addition, as they became adults they become a major input to the family business, mainly farming, and were the primary form of insurance for adults in old age. In India, an adult son was all that prevented a widow from falling into destitution. While death rates remained high there was no question as to the need for children, even if the means to prevent them had existed.[10]

During this stage, the society evolves in accordance with Malthusian paradigm, with population essentially determined by the food supply. Any fluctuations in food supply (either positive, for example, due to technology improvements, or negative, due to droughts and pest invasions) tend to translate directly into population fluctuations. Famines resulting in significant mortality are frequent. Overall, population dynamics during stage one are comparable to those of animals living in the wild. According to Edward, Revocatus. (2016) This is the earlier stage of demographic transition in the world and also characterized by primary activities such as small fishing activities, farming practices, pastoralism and petty businesses.

Stage two

Population curve
World population 10,000 BC-2017 AD

This stage leads to a fall in death rates and an increase in population.[11] The changes leading to this stage in Europe were initiated in the Agricultural Revolution of the eighteenth century and were initially quite slow. In the twentieth century, the falls in death rates in developing countries tended to be substantially faster. Countries in this stage include Yemen, Afghanistan, the Palestinian territories and Iraq and much of Sub-Saharan Africa (but do not include South Africa, Zimbabwe, Botswana, Swaziland, Lesotho, Namibia, Kenya, Gabon and Ghana, which have begun to move into stage 3).[12]

The decline in the death rate is due initially to two factors:

  • First, improvements in the food supply brought about by higher yields in agricultural practices and better transportation reduce death due to starvation and lack of water. Agricultural improvements included crop rotation, selective breeding, and seed drill technology.
  • Second, significant improvements in public health reduce mortality, particularly in childhood. These are not so many medical breakthroughs (Europe passed through stage two before the advances of the mid-twentieth century, although there was significant medical progress in the nineteenth century, such as the development of vaccination) as they are improvements in water supply, sewerage, food handling, and general personal hygiene following from growing scientific knowledge of the causes of disease and the improved education and social status of mothers.

A consequence of the decline in mortality in Stage Two is an increasingly rapid growth in population growth (a.k.a. "population explosion") as the gap between deaths and births grows wider and wider. Note that this growth is not due to an increase in fertility (or birth rates) but to a decline in deaths. This change in population occurred in north-western Europe during the nineteenth century due to the Industrial Revolution. During the second half of the twentieth century less-developed countries entered Stage Two, creating the worldwide rapid growth of number of living people that has demographers concerned today. In this stage of DT, countries are vulnerable to become failed states in the absence of progressive governments.

Another characteristic of Stage Two of the demographic transition is a change in the age structure of the population. In Stage One, the majority of deaths are concentrated in the first 5–10 years of life. Therefore, more than anything else, the decline in death rates in Stage Two entails the increasing survival of children and a growing population. Hence, the age structure of the population becomes increasingly youthful and start to have big families and more of these children enter the reproductive cycle of their lives while maintaining the high fertility rates of their parents. The bottom of the "age pyramid" widens first where children, teenagers and infants are here, accelerating population growth rate. The age structure of such a population is illustrated by using an example from the Third World today.

Stage three

In Stage 3 of the Demographic Transition Model (DTM), death rates are low and birth rates diminish, as a rule accordingly of enhanced economic conditions, an expansion in women's status and education, and access to contraception. The decrease in birth rate fluctuates from nation to nation, as does the time span in which it is experienced.[13] Stage Three moves the population towards stability through a decline in the birth rate.[14] Several fertility factors contribute to this eventual decline, and are generally similar to those associated with sub-replacement fertility, although some are speculative:

  • In rural areas continued decline in childhood death means that at some point parents realize they need not require so many children to be born to ensure a comfortable old age. As childhood death continues to fall and incomes increase parents can become increasingly confident that fewer children will suffice to help in family business and care for them in old age.
  • Increasing urbanization changes the traditional values placed upon fertility and the value of children in rural society. Urban living also raises the cost of dependent children to a family. A recent theory suggests that urbanization also contributes to reducing the birth rate because it disrupts optimal mating patterns. A 2008 study in Iceland found that the most fecund marriages are between distant cousins. Genetic incompatibilities inherent in more distant outbreeding makes reproduction harder.[15]
  • In both rural and urban areas, the cost of children to parents is exacerbated by the introduction of compulsory education acts and the increased need to educate children so they can take up a respected position in society. Children are increasingly prohibited under law from working outside the household and make an increasingly limited contribution to the household, as school children are increasingly exempted from the expectation of making a significant contribution to domestic work. Even in equatorial Africa, children (age under 5) now required to have clothes and shoes, through the body, and may even require school uniforms. Parents begin to consider it a duty to buy children(s) books and toys, partly due to education and access to family planning, people begin to reassess their need for children and their ability to grow them.[10]
A major factor in reducing birth rates in stage 3 countries such as Malaysia is the availability of family planning facilities, like this one in Kuala Terengganu, Terengganu, Malaysia.
  • Increasing literacy and employment lowers the uncritical acceptance of childbearing and motherhood as measures of the status of women. Working women have less time to raise children; this is particularly an issue where fathers traditionally make little or no contribution to child-raising, such as southern Europe or Japan. Valuation of women beyond childbearing and motherhood becomes important.
  • Improvements in contraceptive technology are now a major factor. Fertility decline is caused as much by changes in values about children and gender as by the availability of contraceptives and knowledge of how to use them.

The resulting changes in the age structure of the population include a decline in the youth dependency ratio and eventually population aging. The population structure becomes less triangular and more like an elongated balloon. During the period between the decline in youth dependency and rise in old age dependency there is a demographic window of opportunity that can potentially produce economic growth through an increase in the ratio of working age to dependent population; the demographic dividend.

However, unless factors such as those listed above are allowed to work, a society's birth rates may not drop to a low level in due time, which means that the society cannot proceed to stage Three and is locked in what is called a demographic trap.

Countries that have witnessed a fertility decline of over 50% from their pre-transition levels include: Costa Rica, El Salvador, Panama, Jamaica, Mexico, Colombia, Ecuador, Guyana, Philippines, Indonesia, Malaysia, Sri Lanka, Turkey, Azerbaijan, Turkmenistan, Uzbekistan, Tunisia, Algeria, Morocco, Lebanon, South Africa, India, Saudi Arabia, and many Pacific islands.

Countries that have experienced a fertility decline of 25–50% include: Guatemala, Tajikistan, Egypt and Zimbabwe.

Countries that have experienced a fertility decline of less than 25% include: Sudan, Niger, Afghanistan.

Stage four

This occurs where birth and death rates are both low, leading to a total population stable. Death rates are low for a number of reasons, primarily lower rates of diseases and higher production of food. The birth rate is low because people have more opportunities to choose if they want children; this is made possible by improvements in contraception or women gaining more independence and work opportunities.[16] The DTM is only a suggestion about the future population levels of a country, not a prediction.

Countries that are at this stage (2 < Total Fertility Rate < 2.5 in 2015) include: Antigua and Barbuda, Argentina, Bahrain, Bangladesh, Bhutan, Cabo Verde, El Salvador, Faroe Islands, Grenada, Guam, India, Indonesia, Kosovo, Libya, Malaysia, Maldives, Mexico, Myanmar, Nepal, New Caledonia, Nicaragua, Palau, Peru, Seychelles, Sri Lanka, Suriname, Tunisia, Turkey and Venezuela.[17]

Stage five

World population (UN)
United Nation's population projections by location.
Note the vertical axis is logarithmic and represents millions of people.

The original Demographic Transition model has just four stages, but additional stages have been proposed. Both more-fertile and less-fertile futures have been claimed as a Stage Five.

Some countries have sub-replacement fertility (that is, below 2.1–2.2 children per woman). Replacement fertility is generally slightly higher than 2 (the level which replaces the two parents) both because boys are born more often than girls (about 1.05–1.1 to 1) and to compensate for deaths prior to full reproduction. Many European and East Asian countries now have higher death rates than birth rates. Population aging and population decline may eventually occur, assuming that the fertility rate does not change and sustained mass immigration does not occur.

In an article in the August 2009 issue of Nature, Myrskylä, Kohler and Francesco Billari argue that the previously negative relationship between "development", as measured by the Human Development Index (HDI), and birth rates has become J-shaped. The HDI is a composite of life expectancy, income, and level of education. Development promotes fertility decline at HDI levels below 0.9 but further advances in HDI cause a small rebound in birth rate.[18] In many countries with very high levels of development, fertility rates are now approaching two children per woman — although there are exceptions, notably Germany, Italy and Japan.[19]

From the point of view of evolutionary biology, wealthier people having fewer children is unexpected, as natural selection would be expected to favor individuals who are willing and able to convert plentiful resources into plentiful fertile descendants. This may be the result of a departure from the environment of evolutionary adaptedness.[8][20][21]

Most models posit that the birth rate will stabilize at a low level indefinitely. Some dissenting scholars note that the modern environment is exerting evolutionary pressure for higher fertility, and that eventually due to individual natural selection or due to cultural selection, birthrates may rise again. Part of the "cultural selection" hypothesis is that the variance in birthrate between cultures is significant; for example, some religious cultures have a higher birthrate that isn't accounted for by differences in income.[22][23][24]

Jane Falkingham of Southampton University has noted that "We've actually got population projections wrong consistently over the last 50 years... we've underestimated the improvements in mortality... but also we've not been very good at spotting the trends in fertility."[8] In 2004 a United Nations office published its guesses for global population in the year 2300; estimates ranged from a "low estimate" of 2.3 billion (tending to −0.32% per year) to a "high estimate" of 36.4 billion (tending to +0.54% per year), which were contrasted with a deliberately "unrealistic" illustrative "constant fertility" scenario of 134 trillion (obtained if 1995–2000 fertility rates stay constant into the far future).[8][25]

Effects on age structure

Dtm pyramids
One such visualization of this effect may be approximated by these hypothetical population pyramids.

The decline in death rate and birth rate that occurs during the demographic transition may transform the age structure. When the death rate declines during the second stage of the transition, the result is primarily an increase in the child population. The reason being that when the death rate is high (stage one), the infant mortality rate is very high, often above 200 deaths per 1000 children born. When the death rate falls or improves, this may include lower infant mortality rate and increased child survival. Over time, as individuals with increased survival rates age, there may also be an increase in the number of older children, teenagers, and young adults. This implies that there is an increase in the fertile population proportion which, with constant fertility rates, may lead to an increase in the number of children born. This will further increase the growth of the child population. The second stage of the demographic transition, therefore, implies a rise in child dependency and creates a youth bulge in the population structure.[26] As a population continues to move through the demographic transition into the third stage, fertility declines and the youth bulge prior to the decline ages out of child dependency into the working ages. This stage of the transition is often referred to as the golden age, and is typically when populations see the greatest advancements in living standards and economic development.[26] However, further declines in both mortality and fertility will eventually result in an aging population, and a rise in the aged dependency ratio. An increase of the aged dependency ratio often indicates that a population has reached below replacement levels of fertility, and as result does not have enough people in the working ages to support the economy, and the growing dependent population.[26]

Historical studies


Between 1750 and 1975 England experienced the transition from high levels of both mortality and fertility, to low levels. A major factor was the sharp decline in the death rate due to infectious diseases, which has fallen from about 11 per 1,000 to less than 1 per 1,000. By contrast, the death rate from other causes was 12 per 1,000 in 1850 and has not declined markedly. The agricultural revolution and the development of transport, initiated by the construction of canals, led to greater availability of food and coal, and enabled the Industrial Revolution to improve the standard of living. Scientific discoveries and medical breakthroughs did not, in general, contribute importantly to the early major decline in infectious disease mortality.


In the 1980s and early 1990s, the Irish demographic status converged to the European norm. Mortality rose above the European Community average, and in 1991 Irish fertility fell to replacement level. The peculiarities of Ireland's past demography and its recent rapid changes challenge established theory. The recent changes have mirrored inward changes in Irish society, with respect to family planning, women in the work force, the sharply declining power of the Catholic Church, and the emigration factor.[27]


France displays real divergences from the standard model of Western demographic evolution. The uniqueness of the French case arises from its specific demographic history, its historic cultural values, and its internal regional dynamics. France's demographic transition was unusual in that the mortality and the natality decreased at the same time, thus there was no demographic boom in the 19th century.[28]

France's demographic profile is similar to its European neighbors and to developed countries in general, yet it seems to be staving off the population decline of Western countries. With 62.9 million inhabitants in 2006, it was the second most populous country in the European Union, and it displayed a certain demographic dynamism, with a growth rate of 2.4% between 2000 and 2005, above the European average. More than two-thirds of that growth can be ascribed to a natural increase resulting from high fertility and birthrates. In contrast, France is one of the developed nations whose migratory balance is rather weak, which is an original feature at the European level. Several interrelated reasons account for such singularities, in particular the impact of pro-family policies accompanied by greater unmarried households and out-of-wedlock births. These general demographic trends parallel equally important changes in regional demographics. Since 1982 the same significant tendencies have occurred throughout mainland France: demographic stagnation in the least-populated rural regions and industrial regions in the northeast, with strong growth in the southwest and along the Atlantic coast, plus dynamism in metropolitan areas. Shifts in population between regions account for most of the differences in growth. The varying demographic evolution regions can be analyzed though the filter of several parameters, including residential facilities, economic growth, and urban dynamism, which yield several distinct regional profiles. The distribution of the French population therefore seems increasingly defined not only by interregional mobility but also by the residential preferences of individual households. These challenges, linked to configurations of population and the dynamics of distribution, inevitably raise the issue of town and country planning. The most recent census figures show that an outpouring of the urban population means that fewer rural areas are continuing to register a negative migratory flow – two-thirds of rural communities have shown some since 2000. The spatial demographic expansion of large cities amplifies the process of peri-urbanization yet is also accompanied by movement of selective residential flow, social selection, and sociospatial segregation based on income.[29]


McNicoll (2006) examines the common features behind the striking changes in health and fertility in East and Southeast Asia in the 1960s–1990s, focusing on seven countries: Taiwan and South Korea ("tiger" economies), Thailand, Malaysia, and Indonesia ("second wave" countries), and China and Vietnam ("market-Leninist" economies). Demographic change can be seen as a byproduct of social and economic development together with, in some cases, strong governmental pressures. The transition sequence entailed the establishment of an effective, typically authoritarian, system of local administration, providing a framework for promotion and service delivery in health, education, and family planning. Subsequent economic liberalization offered new opportunities for upward mobility — and risks of backsliding —, accompanied by the erosion of social capital and the breakdown or privatization of service programs.


As of 2013, India is in the later half of the third stage of the demographic transition, with a population of 1.23 billion.[30] It is nearly 40 years behind in the demographic transition process compared to EU countries, Japan, etc. The present demographic transition stage of India along with its higher population base will yield a rich demographic dividend in future decades.[31]


Cha (2007) analyzes a panel data set to explore how industrial revolution, demographic transition, and human capital accumulation interacted in Korea from 1916–38. Income growth and public investment in health caused mortality to fall, which suppressed fertility and promoted education. Industrialization, skill premium, and closing gender wage gap further induced parents to opt for child quality. Expanding demand for education was accommodated by an active public school building program. The interwar agricultural depression aggravated traditional income inequality, raising fertility and impeding the spread of mass schooling. Landlordism collapsed in the wake of de-colonization, and the consequent reduction in inequality accelerated human and physical capital accumulation, hence leading to growth in South Korea.[32]


Campbell has studied the demography of 19th-century Madagascar in the light of demographic transition theory. Both supporters and critics of the theory hold to an intrinsic opposition between human and "natural" factors, such as climate, famine, and disease, influencing demography. They also suppose a sharp chronological divide between the precolonial and colonial eras, arguing that whereas "natural" demographic influences were of greater importance in the former period, human factors predominated thereafter. Campbell argues that in 19th-century Madagascar the human factor, in the form of the Merina state, was the predominant demographic influence. However, the impact of the state was felt through natural forces, and it varied over time. In the late 18th and early 19th centuries Merina state policies stimulated agricultural production, which helped to create a larger and healthier population and laid the foundation for Merina military and economic expansion within Madagascar. From 1820, the cost of such expansionism led the state to increase its exploitation of forced labor at the expense of agricultural production and thus transformed it into a negative demographic force. Infertility and infant mortality, which were probably more significant influences on overall population levels than the adult mortality rate, increased from 1820 due to disease, malnutrition, and stress, all of which stemmed from state forced labor policies. Available estimates indicate little if any population growth for Madagascar between 1820 and 1895. The demographic "crisis" in Africa, ascribed by critics of the demographic transition theory to the colonial era, stemmed in Madagascar from the policies of the imperial Merina regime, which in this sense formed a link to the French regime of the colonial era. Campbell thus questions the underlying assumptions governing the debate about historical demography in Africa and suggests that the demographic impact of political forces be reevaluated in terms of their changing interaction with "natural" demographic influences.[33]


Russian male and female life expectancy
Russian male and female life expectancy since 1950[34][35]

Russia entered stage two of the transition in the 18th century, simultaneously with the rest of Europe, though the effect of transition remained limited to a modest decline in death rates and steady population growth. The population of Russia nearly quadrupled during the 19th century, from 30 million to 133 million, and continued to grow until the First World War and the turmoil that followed.[36] Russia then quickly transitioned through stage three. Though fertility rates rebounded initially and almost reached 7 children/woman in the mid-1920s, they were depressed by the 1931–33 famine, crashed due to the Second World War in 1941, and only rebounded to a sustained level of 3 children/woman after the war. By 1970 Russia was firmly in stage four, with crude birth rates and crude death rates on the order of 15/1000 and 9/1000 respectively. Bizarrely however, the birth rate entered a state of constant flux, repeatedly surpassing the 20/1000 as well as falling below 12/1000.

In the 1980s and 1990s, Russia underwent a unique demographic transition; observers call it a "demographic catastrophe": the number of deaths exceeded the number of births, life expectancy fell sharply (especially for males) and the number of suicides increased.[37] From 1992 through 2011, the number of deaths exceeded the number of births, from 2011 onwards the opposite has been the case.

United States

Greenwood and Seshadri (2002) show that from 1800 to 1940 there was a demographic shift from a mostly rural US population with high fertility, with an average of seven children born per white woman, to a minority (43%) rural population with low fertility, with an average of two births per white woman. This shift resulted from technological progress. A sixfold increase in real wages made children more expensive in terms of forgone opportunities to work and increases in agricultural productivity reduced rural demand for labor, a substantial portion of which traditionally had been performed by children in farm families.[38]

A simplification of the DTM theory proposes an initial decline in mortality followed by a later drop in fertility. The changing demographics of the U.S. in the last two centuries did not parallel this model. Beginning around 1800, there was a sharp fertility decline; at this time, an average woman usually produced seven births per lifetime, but by 1900 this number had dropped to nearly four. A mortality decline was not observed in the U.S. until almost 1900—a hundred years following the drop in fertility.

However, this late decline occurred from a very low initial level. During the 17th and 18th centuries, crude death rates in much of colonial North America ranged from 15 to 25 deaths per 1000 residents per year[39][40] (levels of up to 40 per 1000 being typical during stages one and two). Life expectancy at birth was on the order of 40 and, in some places, reached 50, and a resident of 18th century Philadelphia who reached age 20 could have expected, on average, additional 40 years of life.

This phenomenon is explained by the pattern of colonization of the United States. Sparsely populated interior of the country allowed ample room to accommodate all the "excess" people, counteracting mechanisms (spread of communicable diseases due to overcrowding, low real wages and insufficient calories per capita due to the limited amount of available agricultural land) which led to high mortality in the Old World. With low mortality but stage 1 birth rates, the United States necessarily experienced exponential population growth (from less than 4 million people in 1790, to 23 million in 1850, to 76 million in 1900.)

The only area where this pattern did not hold was the American South. High prevalence of deadly endemic diseases such as malaria kept mortality as high as 45–50 per 1000 residents per year in 18th century North Carolina. In New Orleans, mortality remained so high (mainly due to yellow fever) that the city was characterized as the "death capital of the United States" – at the level of 50 per 1000 population or higher – well into the second half of the 19th century.[41]

Today, the U.S. is recognized as having both low fertility and mortality rates. Specifically, birth rates stand at 14 per 1000 per year and death rates at 8 per 1000 per year.[42]

Critical evaluation

Countries with lower economic development have much faster demographic transition than high-income countries.

It must be remembered that the DTM is only a model and cannot necessarily predict the future. It does however give an indication of what the future birth and death rates may be for an underdeveloped country, together with the total population size. Most particularly, of course, the DTM makes no comment on change in population due to migration. It is not applicable for high levels of development, as it has been shown that after a HDI of 0.9 the fertility increases again.[1]

DTM does not account for recent phenomena such as AIDS; in these areas HIV has become the leading source of mortality. Some trends in waterborne bacterial infant mortality are also disturbing in countries like Malawi, Sudan and Nigeria; for example, progress in the DTM clearly arrested and reversed between 1975 and 2005.[43]

DTM assumes that population changes are induced by industrial changes and increased wealth, without taking into account the role of social change in determining birth rates, e.g., the education of women. In recent decades more work has been done on developing the social mechanisms behind it.[44]

DTM assumes that the birth rate is independent of the death rate. Nevertheless, demographers maintain that there is no historical evidence for society-wide fertility rates rising significantly after high mortality events. Notably, some historic populations have taken many years to replace lives after events such as the Black Death.

Some have claimed that DTM does not explain the early fertility declines in much of Asia in the second half of the 20th century or the delays in fertility decline in parts of the Middle East. Nevertheless, the demographer John C Caldwell has suggested that the reason for the rapid decline in fertility in some developing countries compared to Western Europe, the United States, Canada, Australia and New Zealand is mainly due to government programs and a massive investment in education both by governments and parents.[12]

Second demographic transition

The Second Demographic Transition (SDT) is a conceptual framework first formulated in 1986 by Ron Lesthaeghe and Dirk van de Kaa in a short article that was published in the Dutch sociology journal Mens en Maatschappij.[45]:181[46][47][45] SDT addressed the changes in the patterns of sexual and reproductive behavior which occurred in North America and Western Europe in the period from about 1963, when the birth control pill and other cheap effective contraceptive methods such as the IUD were adopted by the general population, to the present. Combined with the sexual revolution and the increased role of women in society and the workforce the resulting changes have profoundly affected the demographics of industrialized countries resulting in a sub-replacement fertility level.[48]

The changes, increased numbers of women choosing to not marry or have children, increased cohabitation outside marriage, increased childbearing by single mothers, increased participation by women in higher education and professional careers, and other changes are associated with increased individualism and autonomy, particularly of women. Motivations have changed from traditional and economic ones to those of self-realization.[49]

In 2015, Nicholas Eberstadt, political economist at the American Enterprise Institute in Washington, described the Second Demographic Transition as one in which "long, stable marriages are out, and divorce or separation are in, along with serial cohabitation and increasingly contingent liaisons."[50]

See also


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  2. ^ Galor, Oded (17 February 2011). "The demographic transition: causes and consequences". Cliometrica. 6 (1): 1–28. doi:10.1007/s11698-011-0062-7. PMC 4116081. PMID 25089157.
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  5. ^ Woods, Robert (2000-10-05). The Demography of Victorian England and Wales. Cambridge University Press. p. 18. ISBN 978-0-521-78254-8.
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  9. ^ "Demographic Transition Model".
  10. ^ a b Caldwell (2006), Chapter 5
  11. ^ BBC bitesize Archived October 23, 2007, at the Wayback Machine
  12. ^ a b Caldwell (2006), Chapter 10
  13. ^ "Stage 3 of the Demographic Transition Model - Population Education". 16 October 2014.
  14. ^ "Demographic transition", Geography, Marathon, UWC.
  15. ^ "Kissing cousins, missing children", The Economist, 7 February 2008.
  16. ^ "Demographic", Main vision.
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  18. ^ Myrskyla, M; Kohler, H-P; Billari, F (6 August 2009), "Advances in development reverse fertility declines", Nature, 460 (7256): 741–43, Bibcode:2009Natur.460..741M, doi:10.1038/nature08230, PMID 19661915.
  19. ^ "The best of all possible worlds?", The Economist, 6 August 2009.
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Ansley J. Coale

Ansley Johnson Coale (November 14, 1917 – November 5, 2002), was one of America's foremost demographers. A native to Baltimore, Maryland, he earned his Bachelor of Arts in 1939, his Master of Arts in 1941, and (after a period of service in the Navy) his Ph.D. in 1947, all at Princeton University. A long-term director of the Office of Population Research at Princeton, Coale was especially influential for his work on the demographic transition and leadership of the European Fertility Project.

Demographic economics

Demographic economics or population economics is the application of economic analysis to demography, the study of human populations, including size, growth, density, distribution, and vital statistics.

Demographic momentum

Demographic momentum is the tendency for growing populations to continue growing after a fertility decline because of their young age distribution. This is important because once this happens a country moves to a different stage in the demographic transition model.

Demographic trap

According to the Encyclopedia of International Development, the term demographic trap is used by demographers "to describe the combination of high fertility (birth rates) and declining mortality (death rates) in developing countries, resulting in a period of high population growth rate (PGR)." High fertility combined with declining mortality happens when a developing country moves through the demographic transition of becoming developed.

During "stage 2" of the demographic transition, quality of health care improves and death rates fall, but birth rates still remain high, resulting in a period of high population growth. The term "demographic trap" is used by some demographers to describe a situation where stage 2 persists because "falling living standards reinforce the prevailing high fertility, which in turn reinforces the decline in living standards." This results in more poverty, where people rely on more children to provide them with economic security. Social scientist John Avery explains that this results because the high birth rates and low death rates "lead to population growth so rapid that the development that could have slowed population is impossible."

Demographics of Bolivia

The demographic characteristics of the population of Bolivia are known through censuses, with the first in 1826 and the most recent being in 2012. The National Institute of Statistics of Bolivia (INE) has performed this task since 1950. The population of Bolivia in 2012 had reached 10 million for the first time in history. The population density is 9.13 inhabitants per square kilometer, and the overall life expectancy in Bolivia at birth is 68.2 years. The population has steadily risen from the late 1800s to the present time. The natural growth rate of the population is positive, which has been a continuing trend since the 1950s; in 2012, Bolivia's birth rate continued to be higher than the death rate. Bolivia is in the third stage of demographic transition. In terms of age structure, the populations is dominated by the 15–64 segment. The median age of the population is 23.1, and the gender ratio of the total population is 0.99 males per female.

Bolivia is inhabited mostly by Quechua (45.6%) and Aymara (42.4%), while minorities include 37 indigenous groups (0.3% average per group). The Spanish, Quechua, Aymara, Guarani languages, as well as 34 other native languages are the official language of Bolivia. Spanish is the most-spoken language (60.7%) within the population. The main religions of Bolivia are Catholicism (81.8%), Evangelicalism (11.5%), and Protestantism (2.6%). Education is of poor quality, and has a 91.2% literacy rate. An estimated 7.6% of the country's gross domestic product (GDP) is spent on education. The average monthly household income was Bs.1,378 ($293) in 1994. In December 2013 the unemployment rate was 3.2% of the working population. Average urbanisation rate in Bolivia is 67%.

Demographics of the Gambia

The demographic characteristics of the population of The Gambia are known through national censuses, conducted in ten-year intervals and analyzed by The Gambian Bureau of Statistics (GBOS) since 1963. The latest census was conducted in 2013. The population of The Gambia at the 2013 census was 1.8 million. The population density is 176.1 per square kilometer, and the overall life expectancy in The Gambia is 64.1 years. Since the first census of 1963, the population of The Gambia has increased every ten years by an average of 43.2 percent. Since 1950s, the birth rate has constantly exceeded the death rate; the natural growth rate is positive. The Gambia is in the second stage of demographic transition. In terms of age structure, The Gambia is dominated by 15- to 64-year-old segment (57.6%). The median age of the population is 19.9 years, and the gender ratio of the total population is 0.98 males per female.

Dependency ratio

In economics, geography, demography and sociology, the dependency ratio is an age-population ratio of those typically not in the labor force (the dependent part ages 0 to 14 and 65+) and those typically in the labor force (the productive part ages 15 to 64). It is used to measure the pressure on the productive population.

Consideration of the dependency ratio is essential for governments, economists, bankers, business, industry, universities and all other major economic segments which can benefit from understanding the impacts of changes in population structure. A low dependency ratio means that there are sufficient people working who can support the dependent population. A lower ratio could allow for better pensions and better health care for citizens. A higher ratio indicates more financial stress on working people. While the strategies of increasing fertility and of allowing immigration especially of younger working age people have been formulas for lowering dependency ratios, future job reductions through automation may impact the effectiveness of those strategies.

Health in Lebanon

Lebanon is a small middle-income country on the Eastern Mediterranean shore with a population of around 4 million Lebanese citizens, 1.2 million Syrian refugees, and half a million Palestinian refugees. It is at the third stage of its demographic transition characterized by a decline in both fertility and mortality rates . Moreover, Lebanon, like many countries in the Middle East is experiencing an epidemiological transition with an increasingly ageing population suffering from chronic and non-communicable diseases . Mortality related to non-communicable diseases is 404.4 deaths per 100,000 individuals, with an estimate of 45% due to cardiovascular diseases, making them the leading cause of death in Lebanon . Lebanon has health indices that are close to those of more developed countries, with a reported life expectancy at birth of 80.1 years (81.4 years for women and 78.8 years for men) and an under-five mortality rate of 9.5 per 1,000 live births in 2016 . Since the end of the 15-year [[Lebanese Civil War

|civil war]] in 1990, Lebanon’s health indicators have significantly improved .

History of German women

History of German women covers gender roles, personalities and movements from medieval times to the present in German-speaking lands.

Neolithic Revolution

The Neolithic Revolution, Neolithic Demographic Transition, Agricultural Revolution, or First Agricultural Revolution was the wide-scale transition of many human cultures during the Neolithic period from a lifestyle of hunting and gathering to one of agriculture and settlement, making an increasingly larger population possible. These settled communities permitted humans to observe and experiment with plants to learn how they grew and developed. This new knowledge led to the domestication of plants.Archaeological data indicates that the domestication of various types of plants and animals happened in separate locations worldwide, starting in the geological epoch of the Holocene around 12,500 years ago. It was the world's first historically verifiable revolution in agriculture. The Neolithic Revolution greatly narrowed the diversity of foods available, resulting in a downturn in the quality of human nutrition.The Neolithic Revolution involved far more than the adoption of a limited set of food-producing techniques. During the next millennia it would transform the small and mobile groups of hunter-gatherers that had hitherto dominated human pre-history into sedentary (non-nomadic) societies based in built-up villages and towns. These societies radically modified their natural environment by means of specialized food-crop cultivation, with activities such as irrigation and deforestation which allowed the production of surplus food. Other developments found very widely are the domestication of animals, pottery, polished stone tools, and rectangular houses.

These developments, sometimes called the Neolithic package, provided the basis for centralized administrations and political structures, hierarchical ideologies, depersonalized systems of knowledge (e.g. writing), densely populated settlements, specialization and division of labour, more trade, the development of non-portable art and architecture, and property ownership. The earliest known civilization developed in Sumer in southern Mesopotamia (c.  6,500 BP); its emergence also heralded the beginning of the Bronze Age.The relationship of the above-mentioned Neolithic characteristics to the onset of agriculture, their sequence of emergence, and empirical relation to each other at various Neolithic sites remains the subject of academic debate, and varies from place to place, rather than being the outcome of universal laws of social evolution. The Levant saw the earliest developments of the Neolithic Revolution from around 10,000 BCE, followed by sites in the wider Fertile Crescent.

Parental investment

Parental investment, in evolutionary biology and evolutionary psychology, is any parental expenditure (e.g. time, energy, resources) that benefits offspring. Parental investment may be performed by both males and females (biparental care), females alone (exclusive maternal care) or males alone (exclusive paternal care). Care can be provided at any stage of the offspring's life, from pre-natal (e.g. egg guarding and incubation in birds, and placental nourishment in mammals) to post-natal (e.g. food provisioning and protection of offspring).

Parental investment theory, a term coined by Robert Trivers in 1972, predicts that the sex that invests more in its offspring will be more selective when choosing a mate, and the less-investing sex will have intra-sexual competition for access to mates. This theory has been influential in explaining sex differences in sexual selection and mate preferences, throughout the animal kingdom and in humans.

Population momentum

Population momentum is a consequence of the demographic transition. Population momentum explains why a population will continue to grow even if the fertility rate, the number of children per woman, declines. Population momentum occurs because it is not only the number of children per woman that determine population growth, but also the number of women in reproductive age. Eventually, when the fertility rate reaches the replacement rate and the population size of women in the reproductive age bracket stabilizes, the population achieves equilibrium and population momentum comes to an end. Population momentum is defined as the ratio of the size of the population at that new equilibrium level to the size of the initial population. Population momentum usually occurs in populations that are growing.

Population planning in Singapore

Population planning in Singapore spans two distinct phases: first to slow and reverse the boom in births that started after World War II; and second, from the 1980s onwards, to encourage parents to have more children because birth numbers had fallen below replacement levels.

The first phase was enforced, by Singapore Family Planning and Population Board (SFPPB) Act, in 1966 after Singapore faced “post war food and housing shortages". SFPPB targeted low-socioeconomic status individuals, particularly females, and worked to encourage contraceptive use, such as condoms and birth control. The SFPPB advocated for small families, establishing the "Stop-at-Two" programme, which pushed for small two-children families and promoted sterilisation in order to have population control. SFPPB also opened more clinics to better the health and welfare of families.The government program “Stop-at-Two” was very successful. The program could even be considered too successful. The policy that only allowed couples to have only two children started to cause a population decline and impact the population structure of Singapore in a negative manner. The government has made attempts to reverse the falling birth rates, initiating phase two.

Phase two has been very unsuccessful. A lot of policies set in place by the government during phase one made phase two difficult to take place. In phase one, civil workers were not paid for maternity leave after their second child, hospital fees were higher after the second child, top school choices were given to only children, and sterilization was benefited with seven days of paid leave. During phase two, several of these policies were still taking place and individuals remained having one child, or no children.The government eventually became pro-natalist, and officially announced its replacement "Have-Three-or-More (if you can afford it)" in 1987, in which the government continued its efforts to better the quality and quantity of the population while discouraging low-income families from having children. The Social Development Unit (SDU) was also established in 1984 to promote marriage and romance between educated individuals.

Population pyramid

A population pyramid, also called an "age-sex- pyramid", is a graphical illustration that shows the distribution of various age groups in a population (typically that of a country or region of the world), which forms the shape of a pyramid when the population is growing. Males are conventionally shown on the left and females on the right, and they may be measured by raw number or as a percentage of the total population. This tool can be used to visualize and age of a particular population. It is also used in ecology to determine the overall age distribution of a population; an indication of the reproductive capabilities and likelihood of the continuation of a species.

Rate of natural increase

In demography, the rate of natural increase (RNI) is a statistic calculated by subtracting the crude death rate from the crude birth rate of a given region.This rate gives demographers an idea of how a certain country's population is growing. RNI excludes in-migration and out-migration, giving an indication of population growth based only on births and deaths. RNI can indicate what stage of the Demographic Transition Model (DTM) a country is in. Trends in RNI can predict a country's economic stability, level of development, and other things.The DTM explains how countries move between being a developing nation to a developed nation. A country's RNI can help determine which stage of the DTM they are in. This in turn helps policy makers and non-profit organizations, like the United Nations, determine how to allocate aid and resources. Developing countries typically have higher RNI values as they have limited infrastructure and access to healthcare which limits them to unregulated fertility levels. These countries also have higher incidence of disease and poor health outcomes leading to more deaths on top of the already high fertility. Developing countries are therefore in the earlier stages of the DTM with high fertility levels. This leads to developing countries to have high rates of natural increase. Developed countries have lower RNI values because they are usually more technologically advanced and have the necessary steps put into place to limit fertility. They also have better access to healthcare and the resources necessary to combat disease. Developed countries are there in the later stages of the DTM with low fertility levels. This usually results in developed countries having lower RNI values.

Theory of population

Theory of population may refer to:

The theory of population published by Thomas Malthus (1766–1834) in his book An Essay on the Principle of Population

Neo-Malthusian theory of Paul R. Ehrlich (born 1932) and others

Theory of demographic transition by Warren Thompson (1887–1973)

Warren Thompson

Warren Thompson is the name of:

Warren A. Thompson (1802–1891), explorer and original citizen of Butler County, Alabama

Warren T. Thompson, American photographer

Warren Thompson (boxer) (born 1956), amateur boxing champion

Warren Thompson (rugby league) (born 1990), professional rugby league player

Warren Thompson (1887–1973), demographer, see demographic transition

Warren Thompson (fighter)

Warren E. Thompson, author of military history

Warren Thompson, the main character of Warren

Youth in Brazil

Youth in Brazil includes Brazilians aged 15 to 24 or 29, depending on the definition of youth. Youth account for 16.5% of the population in Brazil which is, 202,656,788 people. There are 16,993,708 male youth and 16,521,057 female youth in Brazil.The youth population in 2010 was 34.5 percent higher than it was in 1980. However, birthrates among Brazilians are dropping and youth as a percent of total population is decreasing. The fast fertility decline since the 1960s is the largest contributing factor to Brazil's slowing population growth rate, aging population, and fast-paced demographic transition. By 2050 the number of youth is projected to fall again by 33.1 percent in comparison to the 2010 youth population.

Zelinsky Model

The Zelinsky Model of Migration Transition, also known as the Migration Transition Model, claims that the type of migration that occurs within a country depends on how developed it is or what type of society it is. A connection is drawn from migration to the stages of within the Demographic Transition Model (DTM). It was developed by Wilbur Zelinsky (1921–2013), longtime professor of geography at the Pennsylvania State University.

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