Introduction

1. Age of entry into sexual union (this used to be “average age at marriage”)

2. Fecundity or infecundity (involuntary biological cause)

3. Use or nonuse of contraception

4. Fetal Mortality from voluntary cause (abortion)

The 1960s were a decade of great social upheaval. Many associate the 1960s with “Sex, Drugs, and Rock and Roll.” The development and public availability of the birth control pill undoubtedly contributed to the “sexual revolution” or “sexual liberation” of the 1960s. The pill allowed women to separate sex from procreation and avoid many of the myriad dangers and vulnerabilities associated with unwanted pregnancy. A core concept of the sexual revolution was the radical idea that women enjoyed sex and had sexual needs just like men. However, throughout history, women suffered the consequences of pregnancy in ways that men did not. There is a saying: “
If men got pregnant abortion would be a sacrament.” Nonetheless, the sexual revolution was not welcomed with open arms by all. Loretta Lynn’s famous 1975 song “The Pill” was banned by 60 country music radio stations and denounced from many a church pulpit. Nonetheless “The Pill” was an incredibly popular song and symbolizes a great deal about the sexual revolution and its relationship with women’s empowerment (Video 4.2). The birth control pill is one of the many “hows” of fertility control. The next section explores the “whys.” Public policy related to demographic issues must account for both the “hows” and the “whys” to be effective. The COVID pandemic certainly made that clear when we consider the fact that we had effective vaccines (“hows” for preventing illness and death) but failed in many respects to motivate (“whys”) a significant fraction of the public to use the vaccines. The fertility transition results from a combination of social and/or individual desire for reduced fertility in addition to the availability of effective contraceptives.

 

4.4.5 Personal, Social, Political, and Cultural Drivers of Fertility Change

The drivers of changes to fertility rates operate at individual, family, social, and national scales.
What causes people to desire more children or fewer children? Historically, there have been many reasons that people wanted high fertility levels, which we have already discussed. When and how did humans figure out that sex makes babies? This is not an easy question to answer but it is a precondition for effective fertility control. It is not particularly obvious because sex does not always result in babies and there is a long lead time between the act and the consequences. There is no solid answer to the question; however, Lowder’s exploration of the question (Lowder, 2013) suggests we have known for at least 50,000 years if not up to 200,000 years. Contemporary social mores suggest that choices about family planning take place primarily at the individual and family levels.
What cognitive and situational requirements are necessary for fertility decline?

The European Fertility Project led by Ansley Coale (Coale & Cotts, 1986) attempted to determine how an individual would need to perceive the world in order to consciously limit the number of children they would have. Coale argues there were essentially three preconditions for fertility decline: (1) decisions about childbearing are a real choice that women or couples can make; (2) there are advantages to having fewer children; (3) knowledge and capability of using effective birth control methods. These conditions were sometimes shortened to the “Ready, Willing, and Able” model (Weeks, 2016). The first condition of being “Ready” to change has a lot to do with beliefs and traditions that can change very slowly. If having or not having children is “God’s will,” then it is very difficult to establish this first precondition. Improved status of women, secularization, and science have all contributed to a growing fraction of the world’s population meeting this first criteria of being “Ready” for fertility control (which is usually fertility decline). The second condition is “Willing” or a desire to have fewer children. As the processes of urbanization and economic development (described in the next chapter) take place, people see increasing advantages to having fewer and fewer children. As men and women end up in the workplace childcare becomes increasingly expensive with higher fertility, as do the costs of sending kids to college. Knowledge, availability, and capability to use birth control constitute the third precondition of “Able.”

For most of the world’s population, there are many forms of birth control available at relatively low cost (Kudos to Planned Parenthood, the Guttmacher Institute, and other Women’s health organizations). However, “most” is not “all” and the difference is roughly 218 million women who have an unmet need for modern contraception (Sully et al., 2019). Roughly half the pregnancies in the lower and middle-income countries are unintended (111 million pregnancies resulting in roughly 80 million births). Note that if this birth control were available, it would prevent roughly 30 million abortions. It would cost only $8 billion annually to provide a package of care to meet all women’s needs for modern contraception, pregnancy-related and newborn care, as well as treatment for the major curable sexually transmitted infections. In a cost comparison, that is less than the $10 billion Americans will spend this year on Halloween costumes, candy, and lawn decorations. The amount we spend on Halloween is roughly three times the entire annual budget for the United States National Park Service ($3.5 Billion). Imagine that. For less than what we spend on Halloween in the United States alone we could reach ZPG for the entire world without coercing anyone to reduce their fertility.

While there are many women in the world who do not have access to family planning services, there is nonetheless significant geographic variation in the types of birth control used by women who are married or in committed relationships (Figure 4.15). Female sterilization (aka tubal ligation) is the leading form of contraception in the United States (and this choice increases in likelihood as women have their children and age). Europe, in contrast, has the highest prevalence of male sterilization (aka vasectomy).

[figure number=Figure 4.15 caption=Contraceptive Prevalence Among Married Women Aged 15–49 by Method and Region (2015) filename=Fig_4.15.jpg]

The types of birth control used also vary as a function of education. The percentage of women who use the pill increases significantly with level of education, while women choosing female sterilization decreases significantly with level of education. The use of condoms or long-acting reversible contraceptives does not vary significantly with education (Figure 4.16).

[figure number=Figure 4.16 caption=Type of Contraceptive Use Versus Level of Education for Women Aged 22–49 (2015–2017). From “Current Contraceptive Status Among Women Aged 15–49: United States 2015–2017” filename=Fig_4.16.jpg]

Ultimately, fertility decisions take place locally. Nonetheless, exogenous forces can influence individual decisions. Mother-in-laws can push for grandchildren. Governments can have pronatal population policies (e.g., Australian Federal Treasurer, Peter Costello, urging Australians “
You should have one for the father, one for the mother, and one for the country”), or antinatal population policies (e.g., China’s “One-Child” policy). These policies can be explicit or implicit (e.g., tax deductions for children, maternity leave for mothers). Some of these policies are effective (e.g., China’s One-Child Policy) and some fail miserably (e.g., India’s aggressive sterilization campaigns of the 1970s). Nationalistic population policies can manifest when there are differential fertility rates between ethnic or religious groups. In Israel, this has resulted in Jews being encouraged to “outbreed” the Palestinians because they were afraid of being outnumbered by the higher Palestinian birthrates (De Preneuf, 2001). Population policy is a very controversial issue which is likely why it is often not the favorite topic of politicians.

4.4.6 Geographic Patterns of Fertility

Fertility rates exhibit both spatial and temporal variation. In the early 1970s, fertility rates were high throughout Africa, the Middle East, India, China, and most of Latin America. Fertility rates of the countries of the world for the year 2019 show a roughly similar pattern (Figure 4.17).

[figure number=Figure 4.17 caption=Fertility Rate filename=Fig_4.17.jpg]

Fertility rates have dropped throughout the world most notably in China, India, and Brazil with some countries experiencing significantly below replacement fertility rates (e.g., Russia, Japan, Thailand, Italy, Spain, Portugal, South Korea, Germany, Switzerland, and much of Eastern Europe; Figure 4.17). The map of Figure 4.17 is aggregated to national levels. These maps can obscure significant
intranational variation in fertility rates taking place in the 2010–2016 time frame (Figure 4.18).

[figure number=Figure 4.18 caption=Fertility Rates of Subnational Areas in 70 Countries 2010–2016. From “Geographical Distribution of Fertility Rates in 70 Low-income Lower-middle-income and Upper-middle-income Countries 2010–16: A Subnational Analysis of Cross-sectional Surveys” filename=Fig_4.18.jpg]

The big picture with respect to fertility decline globally is that fertility is going down everywhere (Figure 4.19). Some countries have fertility rates dropping relatively slowly (e.g., Niger (7.2 [c. 1950] to 6.74 [c. 2020]), whereas many Latin American countries have exhibited rapid rates of fertility decline (e.g., Guatemala 7.15 [c.1950] to 2.78 [c.2020])

[figure number=Figure 4.19 caption=Changes to Fertility Rates 1950–2020 filename=Fig_4.19.jpg]

Another process associated with fertility and the demographic transition is migration. Consider Mexico and the United States. Mexico had a higher fertility rate than the United States for many years but they have become much closer over the years. Migration has contributed to this closing of the fertility gap between the countries. The predominant migration stream has been from Mexico to the United States. Migrants tend to be younger people who have not yet had children. Mexico has lost some of its childbearing population, while the United States has gained a childbearing population. Migration is a fundamentally geographic phenomenon that has implications for fertility patterns and the unfolding of the demographic transition.

[Insert Quick Check 4.3]

4.5 Migration

Many people maintain that religion and politics are topics that should never enter polite, civilized conversation. People often feel strongly about these topics and things can become heated very quickly. It could be argued that the topic of “immigration” should be added to that list along with sex and money. Immigration is a hot-button political issue in the United States and many other parts of the world. It is also a fundamental component of population geography and demography. Persons moving to a country are called immigrants and people leaving a country are called emigrants. If the migration in question is internal to a country, then the analogous terms are out-migrant and in-migrant. Recall the basic demographic equation:

Population

(t+1)

= Population

(t)

+ Natural Increase

(t)

+ Net Migration

(t)

Natural increase is essentially fertility minus mortality. Net migration is simply immigration minus emigration. The United States population would not be growing if not for the fact that immigration exceeds emigration. Examples of strong feelings about immigration are abundant: Southern Blacks fear getting pushed back in line by Hispanic immigrants (Wilkinson & Bingam, 2016), Europeans fear more refugees will mean more terrorism (Wike et al., 2016), In Modi’s India, anti-Bangladeshi-immigrant rhetoric is used to justify changes in citizenship laws (Rezwan, 2020), Almost half of Australians believe immigration should be reduced (Davidson, 2019). Currently, there are over 230 million people who now live outside of the country they were born in. This number is growing faster than the global population. In March 2022, over 3 million people fled the Ukraine because of the Russian invasion. War, poverty, environmental disasters, and climate change will all interact to increase the magnitude of immigration in the coming years. Immigration cannot be politely ignored because it is a profound and important aspect of world history and contemporary world affairs.

4.5.1 Defining and Conceptualizing the Migration Process

Migration is defined as a “permanent change of residence.” Migration is inherently a spatial or geographic phenomenon. Mobility is to be distinguished from migration. Seasonal workers, Sojourners (international migrants seeking temporary employment in other countries), tourists, international exchange students, etc. are not migrants. Movers also need to be distinguished from migrants. When a head of household gets a new job and the family moves across town without changing their county of residence they are referred to as movers. Some of these movers can be called migrants if they move to a different county. All migrants are movers but not all movers are migrants. Some persons fall into categories that are more challenging to categorize. Transients (hobos and other wandering souls) often do not have an official address to change. Nomads (e.g., pastoralists moving livestock) can also be difficult to categorize. People whose residence is always changing are difficult to characterize from a migration perspective. Demographers typically ignore them based on the argument that they represent a small fraction of the population.

The distinction between internal and international migration is also of great importance. Internal migration is often well documented by most national censuses and is used for a variety of public policy and business applications. Fortunately, in most countries of the world internal migration is relatively straightforward and does not involve the legal and cultural issues associated with international migration. It is much more difficult to cross international borders than most forms of internal migration. Because of this, international migrants are often much more motivated to succeed in their efforts to relocate. They are also facing the many challenges associated with new cultures, languages, and economic situations. The United Nations regards anyone who crosses a political boundary and stays for more than a year as a “Long-Term Immigrant.”

International migrants can be broadly categorized into four types: Legal immigrants, illegal immigrants (aka undocumented immigrants), refugees, and asylees. A legal immigrant is someone who moves to a new country of residence with the consent and authorization of that country’s government. Legal immigrants in the United States can have U.S. citizenship or can be legal residents (i.e., have a “Green Card”). Illegal immigrants are residents of a country who are not citizens and are not authorized by that country to live there legally. Refugees are defined by the United Nations as “owing to well-founded fear of being persecuted for reasons of race, religion, nationality, membership of a particular social group or political opinion, is outside the country of his nationality and is unable or, owing to such fear, is unwilling to avail himself of the protection of that country; or who, not having a nationality and being outside the country of his former habitual residence, is unable or, owing to such fear, is unwilling to return to it.” An “Asylee” or asylum seeker is a geographic twist on refugees. An asylee is a refugee who is already in the country to which they are applying for admission, whereas a refugee is outside of the country they are trying to get into at the time of application.

These definitions do matter which is why many migrants to the United States and other places claim “political asylum.” Once in the country, they are entitled to due process, which can take so long that they establish themselves in flow of life of the country they claim asylum in. Migration is an activity carried out by people under often challenging legal and sociopolitical circumstances. If we have these challenges associated with defining various types of migration, you can imagine how difficult it is to measure migration.

Measuring migration is not easy. Even with perfect data (which we rarely have), there are issues that must be decided with respect to spatial and temporal resolution that inevitably involve compromises. There is no biological component to migration. Births and deaths are vital statistics that governments make to great effort to measure carefully. Privacy concerns and other issues make measuring change of residence data a little more problematic. The temporal scale presents a problem. Over what period of time should migration be measured? Every year? Every 5 years? In 5 years, some individuals and/or households could have moved more than once? What does “permanent” mean in the phrase “permanent change of residence”? There are spatial scale problems also. Should intercounty be the spatial scale at which internal migration is measured? These are the kinds of decisions that can and do get made. Most information about migration in the United States, Mexico, and Canada comes from a question like” “
Where were you living ‘N’ years ago?.” If that location is in a different county or country then this move will be counted as a “migration.” In the year 2000 (according to the U.S. Current Population Survey) 16% of the population that was 1 year or older lived in a different house than the year before, 6% of the population were classified as migrants (crossed county lines), and 0.6% were immigrants from another country. The American Community Survey (
https://www.census.gov/programs-surveys/acs) makes these kinds of measurements as does the American Housing Survey (
https://www.census.gov/programs-surveys/ahs.html).

There are many institutional and methodological difficulties with measuring migration. The Immigration and Customs Enforcement agency (aka ICE and formerly known by the somewhat friendlier acronym INS or Immigration and Naturalization Service) tracks legal immigrants. ICE does not track emigrants. The situation is pretty much the same in Canada. This contrasts with most European countries that have a population register. Population registers are accounts of residents within a country. They are typically maintained because nationals and foreigners residing in that country must register with the local authorities. Many countries lack the capacity to maintain good population register data; consequently, migration data is often quite poor and numbers you may see are derived from surveys.

The one-child policy in China created some “artificial” migration data (Rosenthan, 2000). Political leaders of smaller rural administrative regions that experienced population growth from fertility rates that violated policy would often claim internal migration to their province to explain their population numbers. This produced an incoherent picture of internal migration in China and likely an undercount of the total population. Internal migration data can be challenging to obtain and curate and it can be a formidable thing to comprehend.

Consider the 50 states of the United States. Each state sends some number of people to each of the other 49 states (some of these numbers can be zero). Each state receives some number of people from each of the other 49 states (some of these numbers can be zero also). At a minimum it would require a 50 × 50 matrix of numbers to describe interstate migration in the United States for a single period of time. That is 2,500 numbers. Digital cartography has made visualizing these large matrices of spatially referenced numbers much more accessible. An interactive map of only the 64 counties of Colorado to the 3,243 counties and county equivalents in the United States might help one to visualize these large datasets. Visualizations of all intercounty migrations of all the counties of the United States would be over 10 million numbers and a map with all those lines would be a mess. Animated maps are perhaps the best way to achieve some sort of understanding of these large datasets.

The big picture of contemporary global migration patterns has two broad themes, one of rural to urban migration and another of migration from the developing world to the developed world. There are two broad categories of migration:
Internal migration (in the United States this is defined as changing county of residence) and
international migration (changing country of residence). There are many recent migrations that are significant including Latin Americans to the United States, Algerians to France, Moroccans to Spain, and Syrians to Europe. International migration flows can be mapped and animated (Figure 4.20 and Video 3.14). Figure 4.20 shows international migration that took place between 2010 and 2015. The United States receives more immigrants than any other country in the world. Other major receivers of immigrants are Canada, Australia, Turkey, and the United Kingdom. This time period includes the tragic civil war in Syria that resulted in over 5 million Syrian migrants leaving the country of Syria. India, China, Pakistan, and the Phillipines also provided many of the world’s emigrants in this time frame.

[figure number=Figure 4.20 caption=Global Migration Patterns filename=Fig_4.20.jpg]

4.5.2 Migration Measurements

There are many ways to measure migration. Typically, data from population registers, censuses, and a variety of surveys are used to produce a variety of migration statistics. The U.S. population in 2022 had 44.9 million immigrants (foreign-born individuals). This is roughly 14% of the total population. It is estimated that roughly 10.5 million of these foreign-born individuals are unauthorized illegal immigrants. The proportion of foreign-born individuals in any country changes from year to year because the flow rates of immigration change from year to year. Immigration undoubtedly interacts with the process of urbanization (Figure 4.21) and there is an interrelated and complex set of feedbacks between migration, fertility, and mortality (Figure 4.22). Despite these complexities, there are several measures used to capture a variety of the attributes of the nature of immigration.

[figure number=Figure 4.21 caption=Interaction Between Urbanization and Migration filename=Fig_4.21.jpg]

[figure number=Figure 4.22 caption=Interrelated Nature of Migration, Fertility, and Mortality filename=Fig_4.22.jpg]

There are seven commonly used migration statistics used to describe these changing flows of people: Gross Rate of Outmigration, Gross Rate of Inmigration, Crude Net Migration Rate (CNMR), Total Migration Rate, Migration Turnover Rate, Migration Effectiveness Rate, and Migration Ratio.

The gross rate of out-migration a crude measure of how many people are leaving (Figure 4.23). It is not a “net” number so a country can be growing from migration even with a high gross rate of out-migration.

[figure number=Figure 4.23 caption=Gross Rate of Out-Migration filename=Fig_4.23.jpg]

The gross rate of in-migration is a crude measure of the influx of people (Figure 4.24). Like the crude rate of out-migration, a country or region can have a high rate of in-migration and still be depopulating if the crude rate of out-migration is higher.

[figure number=Figure 4.24 caption=Gross Rate of In-Migration filename=Fig_4.24.jpg]

The CNMR is the way to measure the population change of a country or region due to migration (Figure 4.25). However, it does not take into account the magnitude of migration. For example, given country X with a population of 1 million. A total of 100,000 out-migrants and 120,000 in-migrants will have the same CNMR as 5,000 out-migrants and 25,000 in migrants. For the United States in 2022 the CNMR was 2.784.

[figure number=Figure 4.25 caption=Crude Net Migration Rate filename=Fig_4.25.jpg]

The total migration rate is a measure of the fraction of the population that is migrating (Figure 4.26). It does not tell you whether the population is growing or shrinking from migration. In the United States from 1985 to 1990 the average migration turnover rate for the U.S. counties was 35.5%. Kalawao County, Hawaii had the lowest rate (12.31%), while Summit County, Colorado had the highest rate (65.46%).

[figure number=Figure 4.26 caption=Total Migration Rate filename=Fig_4.26.jpg]

The migration turnover rate (Figure 4.27) is similar to an employee turnover rate in that it measures the turnover through in-migration and out-migration of the population of an area during a given period of time. The gross rate of in-migration is a crude measure of the influx of people. Like the crude rate of out-migration, a country or region can have a high rate of in-migration and still be depopulating if the crude rate of out-migration is higher. If you do the algebra this is simply:

(In + out / In − out) It results in a number describing the ratio of total migrants to the net result or impact on the population of the region in question.

[figure number=Figure 4.27 caption=Migration Turnover Rate filename=Fig_4.27.jpg]

Migration effectiveness (Figure 4.28) is simply the inverse of the migration turnover rate. This number is essentially a percentage impact of migration on the total population of a country or region.

[figure number=Figure 4.28 caption=Migration Effectiveness filename=Fig_4.28.jpg]

The migration ratio is a way of measuring the contribution that migration makes to population growth (Figure 4.29). In the United States in 2019–2020 there was a net increase of 677,000 from births minus deaths. In the same year 1,031,765 foreign nationals were admitted to the United States as naturalized citizens, lawful permanent residents asylees, or refugees. Thus, the migration ratio of the United States for 2019 is calculated as 1,000 × (1,031,765/677,000) or 1.524. This suggests that immigration contributes 1.524 times as much to U.S. population increases as does natural increase. In fact, the U.S. population would be declining if not for immigration because immigrants have higher fertility rates than the native population.

[figure number=Figure 4.29 caption=Migration Ratio filename=Fig_4.29.jpg]

The Fourteenth Amendment to the U.S. Constitution guarantees citizenship to anyone born within and subject to the jurisdiction of the United States. This fact creates confusing and controversial arguments with respect to immigration and population measurements for some people. Consider the case of a man and woman migrating to the United States from Mexico. They subsequently have three children in the United States. Is their impact on the United States population +5 from immigration or +2 from immigration and +3 from natural increase? Careful reading of this textbook should make it clear that this is the latter: +2 from immigration and +3 from natural increase. Some feel that it is disingenuous to suggest that the children born of immigrants (particularly if they are undocumented) should not be counted as population increase due to immigration. Again, definitions matter and it is important to be aware of them when interpreting demographic statistics provided by the government, media, and others.

The decadal census of the United States is one fundamental way we estimate the magnitude of immigration to the United States. For example, on April 1, 1990, the census counted 248,709,873 residents. Between April 1, 1990 and April 1, 2000, there were 39,865,670 births and 22,715,464 deaths. The natural increase of the United States in those 10 years was simply: 39,865,670 − 248,709,873 = 14,150,206. Using this information an estimate of the year 2000 population of the United States could be 248,709,873 + 14,150,206 = 265,860,079. However, the census 2000 actually counted 281,421,906. The difference 281,421,906 − 265,860,079 = 15,561,827 is declared to be the result of immigration. This is an immigration ratio of roughly 1 suggesting that immigration was roughly equivalent natural increase in its contribution to increases in the U.S. population. The United States had essentially completed the demographic transition; however, without immigration, the United States would have a declining population characteristic of Stage V of the demographic transition. The following section explores a theory of how migration influences the demographic transition.

4.5.3 The Migration Transition

Immigration contributes to the demographic transition. Wilbur Zelinsky hypothesized a “Migration Transition” that operated on the demographic transition (Zelinsky, 1971). The migration transition is related to the process of urbanization and economic development. Zelinsky hypothesized a sequence of five stages (I: Premodern traditional society, II: Early transitional society, III: Late transitional society, IV: Advanced Society, and V: Future super-advanced society). Stage I is characterized by little migration prior to urbanization despite high levels of mobility associated with nomadism. Stage II is rural-to-urban migration driven by nascent urbanization. Stage III is when urban-to-urban migration surpasses rural-to-urban migration. Stage IV is characterized by a dominance of urban-to-urban and urban-to-suburban migration. Stage V is characterized solely by urban-to-urban and intraurban migration. These ideas are interrelated to ideas of urbanization and the urban transition (Figure 4.21). There is an interdependence of migration, fertility, and mortality (Figure 4.22). Past migration from high-fertility Mexico to lower fertility United States has contributed to the reduction of Mexico’s TFR while increasing the U.S. population and its TFR. This is an example of migration and fertility interaction. Migration of retirees from New York to Florida increases Florida’s mortality rate while reducing New York’s. Relatively high fertility rates in the state of Utah change the age structure of Utah’s population resulting in lower mortality rates. These interactions can be complex; however, migration often has more of a local impact on a place than fertility or mortality. These local effects can be significant for both sending and receiving areas.

4.5.4 Why do People Choose to Migrate?

There are many explanations for human migration (Figure 4.30). Most of them have some element of truth to them, while none of them capture the complete essence of human propensity to migrate. Dramatic population growth during Stage II of the demographic transition has been posited as a fundamental cause of migration. Stage II population growth strains resources and causes out-migration (e.g., exodus from Europe in the 18th century). There is also a theory of demographic change and response that suggests that people move to where the resources are. The “Urban Transition” (discussed more in Chapter 5) explains migration from rural to urban areas as agriculture becomes increasingly mechanized and better jobs are available in the cities. Some of the most significant migrations in modern times are associated with exodus from war-torn areas (e.g., Syrian migration and Ukrainian migration). The following is a short list of several theoretical frameworks explaining migration.

[figure number=Figure 4.30 caption=Ravenstein’s Laws of Migration filename=Fig_4.30.jpg]

Ravenstien’s Laws of Migration: An early statement of the “Law of Migration” was developed by E.G. Ravenstein in the late 1800s (Ravenstein, 1885). Ravenstein proposed 11 laws of migration based on three basic attributes: Why migrants move, the distance migrants move, and the characteristics of the migrants (Figure 4.31). While these laws were developed in the late 19th century, they remain broadly true today. A key point is that the major motivation for migration is economic.

The “Push–Pull” theory of migration: Some people migrate because they are “pushed” or driven out of their home location (e.g., climate refugees from sea level rise or war refugees from Ukraine). Other people migrate because they are “pulled” or drawn to the location they migrate to (e.g., Latin Americans seeking economic opportunity in the United States).

The “cost–benefit” theory of migration: This explanation sees the decision to migrate as a cost–benefit analysis. Perhaps this is teleological. In any case, in the “Push–Pull” context, no matter how bad circumstances may be where people are (push) they are not motivated to move unless they see a better opportunity someplace else (pull). The “costs” of moving (e.g., intervening obstacles such as distance, cost to travel, personal health, etc.) come into the cost–benefit calculation of the potential migrant. Economic variables dominate most explanations of why people migrate which is consistent with Ravenstein’s last law. This theory is supported by the fact that the number one reason U.S. citizens migrate is to travel to a new job.

Migration Potential: A little thought about the potential to migrate suggests that there will be differential inclinations to migrate as a function of age, family status, geographic circumstances, and educational and employment opportunities. A study of growing and shrinking cities in France demonstrates several facets of migration potential (Rudolph, 2017). Out‑migration and in‑migration rates tend to be highest for individuals aged 20–30 (Figure 4.31). Between these ages, the probability of migration is the greatest both in growing and shrinking cities alike. However, there is a slight shift between the two rates: While mass in‑migration flows occur in urban areas around the age of 20, owing to residential mobility linked to higher education or employment strategies, the highest out‑migration rates are observed around age 30, as families grow. Growing cities show that in‑migration rates of young adults (aged 20–25) heavily exceed out‑migration rates and make up for the departures of 30-year-olds. Out‑migration rates in shrinking cities are constantly higher than in‑migration rates, even at age 20. Inhabitants who leave shrinking cities are mostly aged 20–40, creating population deficits for this age group that contributes to the faster aging process observed in these cities. The patterns described above are typical globally. Migration potential peaks in our 20s as many complete formal education and move out of the house for a job. Many marry at this age and men tend to be the older partner in marriages, which means women have a slightly earlier peak in migration potential. Thus, migration selectivity does vary in relatively predictable ways with age, life-cycle events (e.g., taking first job, getting married), and sex. Unmarried people (single, divorced, separated, and widowed) have much higher migration rates. Migration propensity is higher for people with smaller and younger families; however, once children are in school migration propensity drops significantly. Fertility is lower before migration events and higher after migration events.

[figure number=Figure 4.31 caption=In-migration and Out-migration by Age from Growing and Shrinking Cities in France filename=Fig_4.31.jpg]

Differences in migration potential by sex: Differences in migration potential between men and women often are a window into the nature and strength of male dominance in a society. The lower the status of women in a country or region, the greater the differential in migration propensity between men and women with men’s propensity being stronger. Countries where the wife joins a husband from “out of county” may have higher migration rates for women. When families move, the women usually have reduced employment relative to where they came from. Globally, the rates of female migration are increasing but they have yet to catch up with the rates of male migration.

4.5.5 Theories of International Migration

Migration is driven by people seeking a better life; however, the ability to migrate varies for many reasons including as a function of age, income, education, and geography. There are a variety of strategies for migration two of which are briefly described here: Step Migration and Chain Migration. Step migration is where migrants reduce the risk of the migration decision by “inching” their way from home. If things do not work out the cost of return is lower. Step migration is often the only choice of the particularly impoverished. Chain migration is where migrants follow the path of “pioneers” who have scoped out a particular place, sent information back, and made it easier to stay once they get there. There are many examples of this. Most Cubans in the United States live in the Miami area and Chicago has more Polish people than any other place outside of Warsaw, Poland. Chain migration is an established geographic concept (Burnley, 2009); however, it has been co-opted by anti-immigration activists in the United States and for some has become synonymous with “Family Reunification” mechanisms for legal migration to the United States. Both of these strategies are among the many used by people seeking to migrate to another country. A variety of theories of international migration are presented below.

The Neo-Classical Economic Approach: This approach regards migration as a “free market” adjustment of labor supply to the geographic differences in the supply and demand of labor. The idea is that countries with booming economies and labor shortages have higher wages. Thus, individual people (acting as solo
Homo economicus) will move from low wage to high wage areas. Migration will continue until the gap in wages is reduced to the sum of the monetary and psychosocial costs of migrating. This theory naively assumes that the free flow of labor from one country to another is not particularly mitigated by national sovereignty and border patrols. Contemporary empirical evidence seems to suggest that the jobs are moving to the cheap labor rather than the labor moving to the higher-paying jobs. Nonetheless, there is indeed some truth to this idea that migrants seek higher paying jobs and living circumstances.

The New Household Economics: This theory is similar to the neoclassical approach with a significant difference. The neoclassical theory posits that
individuals make the decision to migrate, whereas the New Home Economics sees the “household” as a whole as the decision-making entity (Stark & Bloom, 1985). Households can pool resources to send individuals based on both risk-minimizing and opportunity-maximizing perceptions of the planned migration. The reality of “remittances” strongly supports New Home Economics versus Neoclassical theory.

Dual Labor Market Theory: This theory argues that developed countries have a primary and a secondary sector of the economy (Bee & Barringer, 1975). The primary sector is characterized by good wages, benefits, status, and job security. The secondary sector is characterized by low wages, minimal benefits, instability, and low chances for advancement. Historically, women, minorities, and teenagers filled these jobs “in the country.” Lower birth rates reduced the supply of teenagers, and greater social equity produced better opportunities for women and minorities. This resulted in immigrants from developing countries filling these secondary labor positions. An interesting twist on these theories of the labor market is provided by Graeber (2017). Graeber suggests a growing fraction of the world’s jobs are “Bullshit Jobs” that are meaningless, unfulfilling, and unnecessary and that this is a significant societal problem with profound consequences.

World Systems Theory: World Systems theory is a post-Marxist multidisciplinary approach to world history and social change arguing that the world system rather than nation-states is the best lens for understanding society, the economy, and politics. The seminal work of world systems theory is
The Politics of the World-Economy: The States, the Movements and the Civilizations (Studies in Modern Capitalism; Wallterstein, 1984). Although it is a widely adopted perspective and warrants a broader discussion than can be provided here. With respect to migration theory, this curt summary of the theory is as follows: The global economy since the 16th century has developed into “core” and “periphery” nations. “Core” nations are the developed world of Europe, the United States, Japan, and Australia. “Periphery” is just about everyone else—the developing countries of the world. Migration is a natural outcome of “Core” nations exploiting “Periphery” nations in the process of capitalist development and natural resource extraction. As land, labor, and raw materials come under the influence and control of global markets migration flows are inevitably generated.

Network Theory: Migrants establish interpersonal ties that connect migrants, former migrants, and nonmigrants in origin and destination areas through ties of kinship, friendship, and shared community origin. This increases the likelihood of international movement because they lower the costs and risks of movement and increase the expected net returns of migration. In many respects, this is a generalization of the ideas of chain migration. Also, it is more of an explanation of sustaining existing migration than initiating new migrations.

Cumulative Causation Theory: This theory suggests that each act of immigration influences the potential for subsequent acts of migration. If receiving country “welcomes” immigrants that increases likelihood of even more immigration. If immigrants send money back home (remittances) that tells people back home that migrating to that country might not be so bad. Cumulative causation is similar to path dependence analysis whereby history matters; what has occurred in the past persists because of resistance to change.

Institutional Theory: Institutional theory is also an explanation for sustaining established migration streams. Once migration streams are established that either the donor or receiver or both find beneficial, institutions will develop that will sustain migration. These organizations may provide a range of services from humanitarian protection, smuggling people across borders, providing counterfeit documents, and arranging for lodging and or credit in the receiving country. These institutions can perpetuate migration in the face of government attempts to limit the flow of migrants.

There is no best theoretical explanation for these theories of international migration. None of these theories are entirely refuted by empirical observations. None of these theories really explain everything associated with migration either. Migration is a complex phenomenon with dramatic social and individual impacts. A poignant example of this is Tyson Foods.

On December 19, Tyson Foods was accused in a 36-count indictment of helping smuggle illegal aliens into the United States and employing them at various chicken-processing plants across the Southeast. The indictment capped a 2-½ year undercover investigation by the INS into the company. The indictment says that Tyson managers would contact local smugglers and contract out for shipments of workers. The managers would get fake documents for the illegal aliens; as part of getting fake Social Security cards they would submit stolen Social Security numbers to the INS’s Basic Pilot Program for verification of employability to see which ones were rejected. The managers would also arrange payment via corporate checks given to the illegal aliens who would turn the money over to the smuggler. As part of the investigation, undercover federal agents pretending to be smugglers contracted for a load of over 200 illegal aliens, negotiating with Tyson executives in several different states. The investigation marked a strategy shift for INS interior enforcement, the latest move to refine the agency’s efforts to stop illegal alien smuggling. The investigation involved wiretaps, paid informers, and undercover agents in an effort to uncover evidence of systematic illegal activity by Tyson. The INS has largely abandoned so-called “worksite enforcement” operations involving arresting and deporting illegal workers; INS statistics indicate worksite raids and arrests plummeted over 90% from the early 1990s. Experts estimate that a high percentage of the roughly 400,000 meatpacking workers in the United States are here illegally. Despite its own estimation that one quarter of those workers are illegal, the INS has engaged in limited efforts to stop illegal hiring prior to the December indictment. The agency has fined Tyson five times previously during the 1990s for illegal hiring, and other meatpackers have had to fire some workers under the now-abandoned Operation Vanguard. The chief reason for INS reticence appears political; each prior enforcement effort would bring attacks from immigrant advocates, unions, and meatpacking industry representatives. Residents of towns where Tyson has chicken plants say they were not surprised by the indictments. “
It was kind of an open secret that Tyson was helping ship these guys in. How else would they get from the middle of Mexico to the middle of nowhere?” asked one city employee in Ashland, Alabama. In Noel, Missouri, the city marshal said he had been reporting illegal aliens involved in crimes to the INS and expected some action.

4.5.6 Consequences of Migration

For the individual migrant migrating is usually pretty stressful. Often migrants deal with xenophobia, racism, language difficulties, and financial hardship. One coping strategy is seeking an enclave (a place within a larger community in which people of a particular subgroup tend to concentrate). Examples of enclaves are “Chinatowns,” Little Italy, etc. Enclaves have both advantages and disadvantages. They can provide access to working capital (e.g., financial resources to help new immigrants get established), protected markets, and pools of labor. Enclaves can also slow the process of adaptation, acculturation, and assimilation. Immigrants tend to go through these three processes of increasing integration with the culture of the country they migrate to. Acculturation is accelerated if they have children in school. Assimilation is often accelerated by marrying a native of the receiving country. There are different models for immigrants. With “Assimilation” the immigrants become virtually indistinguishable from the native population (note: persistent racism in the receiving country may make this impossible for immigrants with visibly distinct ethnic features). Ideally, the model of “Integration” is the case where immigrants maintain their own cultural identity but are accepted as equals (the “accepted as equals” happening to varying degrees). Exclusion is the situation in which immigrants are segregated in enclaves or ghettos and are not treated as equals.

Children of immigrants often find their circumstances to be stressful. They have immigrant parents yet are raised in a foreign place. The 1-12-year-olds who moved with their parents are often called the 1.5 generation and have a more mixed cultural upbringing. In the United States, there are many children in this category who may have arrived in the United States illegally as children and were under threat of deportation. President Obama pushed for DACA (Deferred Action for Childhood Arrivals) policy to allow these children a path to citizenship. Children born in the host country usually adopt the language and the culture of the host country to a greater extent than the country of their parents because they go to school in the host country. Consequently, these children are usually better speakers of English than the potentially different languages of their parents. Despite the lamentations of “English Only” fanatics (who are usually anti-immigrant), the United States is a graveyard for all languages other than English for this very reason. Some children go through a process of segmented assimilation that happens when children of immigrants either adopt the host country language and behavior but are limited because they are still perceived as a minority or assimilate economically but retain ethnic identity.

Migration has significant societal consequences for both the donor and host countries. Both are impacted demographically and economically. The age function that influences the propensity to migrate consequently increases the fertility rate of the host country and causes a loss of working age population in the donor country. Actual “costs” and “benefits” are very difficult to measure. In the United States, for example, it is pretty clear that immigrants reduce the cost of groceries, hotel rooms, and restaurant food; however, there are increases in health care, car insurance, and education costs. Most studies attempting to define the cost versus benefits of immigration are based on impacts on GDP. GDP is proportional to population growth and consequently, these studies usually find that immigration is a net benefit to the receiving country. In fact, immigration to the United States is often touted as way to help alleviate world poverty. A poignant counterpoint to that argument is provided by Roy Beck (Video 4.5).

4.5.7 History and Geography of Major Migrations

Historically, there has been massive migration to “New Worlds” in the 18th, 19th, and 20th centuries. Flows of immigrants ebbed worldwide in the early 20th century due to WWI, WWII, and the global depression. Post-WWII unleashed major migrations in Europe and Asia with boundary realignments and people leaving war-torn areas. In 1947, the partition of India into India and Pakistan prompted a mass migration of Hindus and Muslims. In 1948, the fiat creation of the state of Israel created an exodus of Palestinians from their homeland and an influx of Jews from many parts of the world. There is a general pattern of south-to-north migration in which people in the developing countries of the south migrate to the wealthier developed countries of the north. There is also a migration from really poor countries to the emerging economies in south and Southeast Asia (e.g., Korea). Oil-rich countries are often so wealthy that they can hire immigrants to engage in secondary sector jobs (e.g., in the oil fields). This results in a significant migration from oil-poor to oil-rich countries. In the aggregate, this manifests globally as roughly 5% of the population of the developed countries are foreign born, whereas less than 2% of the population of the developing world are foreign born. The 10 largest donor and host countries to immigrants in the world today share only two countries (Russia and the United Kingdom) that are large donors and hosts (Figure 4.32)

[figure number=Figure 4.32 caption=Top 25 Donor and Receiver Countries for International Migration 2015 filename=Fig_4.32.jpg]

The United States is the country that receives the most immigrants in the world today. This has been true for decades (Figure 4.33). The regions of the world that dominate migrants to the United States have changed over the years. In the early 19th century, the source was dominated by northern and western Europeans (Figure 4.33). From 1880 to WWI, it was dominated by southern and eastern Europe. The interwar period is characterized by lower levels of immigration to the United States and is nonetheless dominated by western Europe. Since roughly 1970 Latin America and increasingly Asia have been the major source of immigrants to the United States. The highest levels of immigration to the United States were during the Immigration Reform and Control Act that was enacted during the administration of President Ronald Reagan. Emigration
out of the United States is not insignificant; however, immigration is five times larger than emigration. Most emigrants are foreign born who stayed in the United States for some period of time and returned to their home country. The social security administration sends about 5 million social security checks to people living outside the United States every month.

[figure number=Figure 4.33 caption=U.S. Immigration Has Occurred in Waves, with Peaks Followed by Troughs filename=Fig_4.33.jpg]

Internal migration in the United States is also interesting. The “
center of mass of the population of the U.S.” has moved westward since the pilgrims arrived in 1620 (Figure 4.34). This shift in population center is contributed to by migration; however, most of the shift is caused by a natural increase in the west exceeding natural increase in the east. Capturing the complexity of the contemporary population movement in the United States is interesting. There are several hypothesized trends including: (1) Uneven urban renewal, (2) regional racial division, (3) increasing levels of inequality of income which manifest geographically, (4) baby boom and elderly geographic realignments, and (5) suburban dominance and city isolation. Uneven urban renewal is explored by many including Richard Florida in his book titled The Creative Class and Bill Bishop’s book The Big Sort. Both of these books describe different characteristics of cities and regions of the United States that result in distinct socioeconomic outcomes. Regional racial divisions are developed because some regions of the country (e.g., Texas, New York, and California) receive a disproportionate share of immigrants which gives them unique and distinct characteristics. It remains to be seen how the aging of the U.S. population (particularly the Baby Boom generation) will influence internal migration. There is a growing body of evidence that many baby boomers will retire in place and not move. The relative appeal of suburbs versus city centers and major cities versus smaller cities is experiencing changes due to the COVID pandemic and the ability of so many people to work from home via Zoom and other web-based meeting technologies. This aspect of the COVID pandemic has facilitated and enabled unprecedented changes in the way we may work in the future.

[figure number=Figure 4.34 filename=Fig_4.34.jpg]

Changing Center of Population in the United States

4.5.8 Forced Migration and the Contemporary Refugee Crisis

Theories about why people migrate are all well and good. In too many cases people move because they are driven out of their homeland by war, poverty, and changing environments. The Syrian refugee crisis is the humanitarian emergency that resulted from the Syrian civil war that began on March 15, 2011. The Syrian refugee crisis is the largest refugee and displacement crisis in the 21 century. Roughly 13.5 million Syrians have been forcibly displaced, which constitutes more than half of the country’s population. Of note, 6.8 million of these displaced persons have left the country and are seeking asylum in many countries around the world including most of Europe. Most of the refugees ended up in Turkey. The other 6.7 million are internally displaced within Syria. This crisis has been ongoing for over a decade. European countries were not uniformly welcoming these refugees. Angela Merkel, chancellor of Germany, suffered political penalties for welcoming large numbers of refugees. Other countries, like Hungary, placed refugees in so-called “reception centers” (
Link to Image; Figure 4.36). It is difficult to appreciate pain and suffering when reading about it on an iPad in the comfort of your own living room. Joseph Stalin is famous for saying:
“A single death is a tragedy; a million deaths are a statistic.” This photograph of a drowned toddler was perhaps the one death that allowed the world to recognize the tragedy of the Syrian migration crisis and the broader crisis of refugees in the world today (
Link to image). This drowned child (presumed to be Syrian) washed up on the beach in one of Turkey’s prime tourist resorts after eleven people drowned trying to reach the Greek island of Kos. People are increasingly desperate to migrate and will take extreme risks to do so (
Link to image). Increasing inequality of wealth and income intensifies these attempts to migrate. This juxtaposition is brilliantly captured in this photograph taken from tiny enclaves on Morocco’s Mediterranean coast, Cueta, and Melilla (
Link to image). These enclaves create a magnetic attraction for people trying to reach Europe. Here the continent is just a razor wire fence away.

The United Nations Refugee Agency (United Nations High Commission on Refugees UNHCR) estimates that 82.4 million people in the world are in a state of having been forcibly displaced from their homes. This includes 20.7 million refugees under the U.N. mandate, 5.7 million Palestinian refugees, 48 million people internally displaced within their own country, 4.1 million asylum seekers, and 3.9 million Venezuelans displaced abroad. Over two-thirds of these people come from just five countries (Syria, Venezuela, Afghanistan, South Sudan, and Myanmar). Some of these displacements are so profound that they can be seen in nighttime satellite imagery (Figure 4.35). Neighboring countries host the majority of these refugees (~73%)

[figure number=Figure 4.35 caption=Nighttime Satellite Imagery of Syria Before and After the Civil War filename=Fig_4.35.jpg]

and most of these countries are developing countries that can ill afford to host massive numbers of refugees. Over 86% of the world’s refugees are hosted in developing countries. Satellite imagery and cell phones with GPS are used to map refugee settlements that often exceed populations of 100,000 (Figure 4.36 and Video 4.6). The reality of the Zaatari refugee camp is perhaps better captured in the oblique air photo (Figure 4.37).

[figure number=Figure 4.36 caption=Zaatari Refugee Camp: Camp Infrastructure and Facilities—May 2019 filename=Fig_4.36.jpg]

[figure number=Figure 4.37 caption=An Aerial View of the Zaatari Refugee Camp filename=Fig_4.37.jpg]

It is sobering to think that the number of the world’s displaced people is comparable to the entire population of Germany. An infographic of the origin countries of the world’s roughly 30 million refugees outside of their home country is interesting in that it is a temporally structured geovisualization of this complex phenomena (Figure 4.39).

[Insert Quick Check 4.4]

4.6 Aging and Population Forecasting

The “age transition” is yet another element of the demographic transition. As a population goes through the demographic transition, it shifts from a very young population in which there are more males than females to an older population with more females than males. Along the way, there can be events that make subtle and not-so-subtle changes to the age and sex structure of the population. These represent powerful forces of social, economic, and political change. The interaction of fertility, mortality, and migration produce the age and sex structure of a population. This produces a record of past demographic history and provides clues as to how the future may unfold. Age stratification is the idea that societies have separate sets of norms and expected roles and obligations for people of different ages. The idea of a cohort or cohort flow embodies the notion that each generation will be influenced by the historical events and circumstances unique to that generation. For example, the depression of the 1930s resulted in across the board reduced fertility. The teenagers of the depression (sometimes referred to as “The Great Generation” share that experience of not only the depression itself but WWII in early adulthood and so on. These experiences can shape worldviews in profound ways that are unique to cohorts rather than age stratification attributes that are fairly common from one generation to the next (e.g., children aged 5–15 are expected to be in school).

Social pressures related to age stratification are much stronger than most of us realize. The age stratification theory begins with the proposition that age is a basis of social differentiation in a manner analogous with social class. The term stratification implies a set of inequalities or differences, and in this case, if refers to the fact that societies distribute resources unequally by age. These resources include not only economic goods but also such crucial intangibles as social approval, acceptance, and respect. This theory is not a mere description of status; however, it introduces a dynamic element by recognizing that aging is a process of social mobility. As an individual ages, they move within a social hierarchy. We move from one set of age-related social roles and expectations to another and at each level receive greater or lesser rewards than before. Consider the following social and economic phenomena that vary with age: Being sick and having restricted activities of daily living, dying, being sexually active, having a baby, moving or migrating, getting married or divorced, being involved in religious organizations, being involved in political organizations, school enrollment, level of educational achievement, being involved in criminal behavior, being in the labor force, current income, net worth. All these attributes are influenced by age. There is significant variability about many of them, but we do not expect 70-year-olds to be enrolled in primary school or to be having a baby.

The global population is aging and this represents an unprecedented challenge. Our economic system is predicated on perpetual growth. Our economic system is currently driving the unsustainable situation we find ourselves in now. We must learn to address aging and the population stabilization that comes with it. Japan and a few other countries are leading the way and hopefully, we can learn from their successes and failures with respect to dealing with stabilizing and declining populations. What is happening in Japan (declining population) is not a tragedy—it is inevitable. A larger fraction of older people in a population is a new reality.

Older people are less alike than people at younger ages. Stereotype them as your own risk but know this: Their numbers and proportion of the population are growing faster than any other age group of the population. This is the uncharted end of the demographic transition. There is a saying that “50 is new 40” and others like it. It raises the question: “What is Old?” (Figure 4.38).

[figure number=Figure 4.38 caption=What is Old? filename=Fig_4.38.jpg]

Currently, there are roughly 700 million people in the world over the age of 65. This number is expected to double to 1.5 billion by the year 2050 (United Nations, 2019). People aged over 65 will soon represent 10% of the global population. This is unprecedented. The rate of population growth of the elderly is greater than the global population growth rate. The spatial distribution of the elderly is not uniform. While 15% of the world’s elderly population lives in developing countries, over 41% of the world’s elderly population lives in developed countries. Increasing life expectancy and declining fertility act in combination to dramatically increase the size and proportion of the elderly in the population. In terms of sheer numbers, China and India have the largest over 65 populations. On a percentage basis, the following countries lead the list: Japan (29%), Monaco (26%), and Italy (24%; Figure 4.39).

[figure number=Figure 4.39 caption=Countries with the Highest Percent of Population Over 65 Years Old filename=Fig_4.39.jpg]

4.6.1 Age Cohorts and Generations

Many societies invest significant resources into providing public education for children. Most provide maternity leave, and some even provide free day care and preschool. Most developed countries also have some form of social security to ensure that the elderly have a minimal income in their retirement years. These age-specific benefits are typically paid for by the working adult population. Maintaining appropriate and sustainable ratios of children, working adults, and nonworking elderly is an important societal goal to ensure that the vulnerable (young and old) are adequately supported. Aging is distinct from other forms of social mobility in that it is inevitable, universal, and unidirectional. It is interesting to note that income (and power) increases with age. In that light how might a very young population in an African country differ from an older population in Mexico or the United States?

A few hundred years ago, European society had essentially three age strata: Infancy, Adulthood, and Old Age. Power was concentrated with the Old Age strata. In modern western societies there seem to be at least seven age strata: Infancy, childhood, adolescence, young adulthood, middle age, young-old, and old-old. Power is concentrated in the middle age and the young-old. This raises some interesting questions about how western cultures may be evolving into a culture of youth with power. However, the financial challenges faced by millennials and Generation Z with respect to income, student loans, and rising housing prices as a percentage of average income suggest that this evolution has not continued. The different experiences of millennials and Generation Z provide an example of how age stratification can vary with the experience of cohorts.

When my dad said to me: “
Son, when I was your age … ” I would interrupt him and say: “
Dad, you were never my age..” I grew up in a different cohort than my father. I was born at the tail end of the baby boom. Consequently, I enjoyed really good new schools that were built for the baby boomers because the Soviet Union put up the first satellite (Sputnik). Unfortunately, when I completed my education, I ran into high levels of unemployment because all the baby boomers that preceded me had taken up most of the jobs. I graduated from college with a BS in chemistry in 1983. Unemployment in 1983 was over 10%. My cohort had a harder time getting jobs, starting a family, and buying homes. The millennial and Generation Z cohorts seem to be experiencing something even worse than I did because student loans have grown in size due to reduced governmental funding for higher education. All of these phenomena are characteristic of cohort flow issues.

Every cohort starts out with a given size which, save for additions from immigration, is the maximum size it will ever attain. Over the life course of the cohort, some portion of its members survive, while others move away or die until the entire cohort dies off. Each cohort starts out with a given composition; it consists of members born with certain characteristics and dispositions. Over the life course of the individual, some of these characteristics are relatively stable (a person’s sex, color, genetic makeup, country of birth). When successive cohorts are compared, they resemble each other in certain respects but differ markedly in other respects: In initial size and composition, in age-specific patterns of survival (or longevity), and in the period of history covered by their respective life span. The life experiences of cohorts born in 1900, 1920, and 1940 vary dramatically. As they move through time, the characteristics of cohorts may change in response to changing social and economic conditions that will influence the formation of new cohorts. This continual feedback between the dynamics of successive cohorts and the dynamics of other changes in society produces a constant shifting in the status and meaning attached to each age stratum, providing an evolutionary link between the age structure and the social structure. These shifting trends are often difficult to anticipate which makes population projection and forecasting more difficult.

Common names for cohorts (aka generations) are “The great generation” (WWII adults), “The Baby Boomers” (born 1946–1964), “Generation X,” “Millenials,” and Generation Z. There are no standard definitions or names for when a generation begins or ends. However, there is general agreement on these generations for the American population (Table 4.5). What do the age structure and cohort dynamics suggest about the “baby boom” generation? One hypothesis is Richard Easterlin’s “Relative Cohort Size Hypothesis” (Easterlin et al., 1990), which posited that the larger cohort would increase the supply of labor relative to demand and thus depress wages and leave boomers less well off than their parents. Did this happen? Not exactly. Baby boomers adjusted in the following ways: (1) Delaying marriage, (2) postponing children in marriage, and (3) sending women to work. Were there downsides to these adaptations? Perhaps. Baby boomers have higher suicide rates than their predecessors and have not planned for retirement as well.

Table 4.5 Names of Generational Cohorts and Their Eras
Generation name	Births	Births	Youngest	Oldest age
	Start	End	Age today*	Today*
The Lost Generation	1890	1915	107	132
The Interbellum Generation	1901	1913	109	121
The Greatest Generation	1910	1924	98	112
The Silent Generation	1925	1945	77	97
Baby Boomer Generation	1946	1964	58	76
Generation X (Baby Bust)	1965	1979	43	57
Xennials	1975	1985	37	47
Millennials	1980	1994	28	42
Generation Y/ Gen Next/iGen / Gen Z	1995	2012	10	27
Gen Alpha	2013	2025	1	9

4.6.2 Aging, Wealth, and Income

The status of the elderly changes as countries change. Generally, as a country modernizes the elderly lose status; however, the trend can reverse as the elderly regain status because many of the processes that reduced that status disappear. The peak age for wealth (aka “net worth”) is 55–64 years of age. Many of America’s wealthiest citizens are over the age of 65 (~40%). It is estimated that roughly 40% of wealth is inherited (Kopczuk & Lupton, 2005). In the United States, the status of the elderly fell and is now rising. As each new generation enters their “golden years,” their character is markedly different from one another. People aged 65 years and older today are more likely to be registered to vote and more likely to actually vote. This is a common “Age Effect.” From 1960 to the present people over 65 have been even more likely to vote, whereas people aged 18–24 have become even less likely to vote. The younger generation can say “OK boomer” all they want but actually engaging in the voting process might affect more change. Income and education are also correlated to a great extent. In the year 2000, only 65% of those over 75 had a high school education, whereas 85% of those aged 25–29 had a high school diploma. In 1960 only 19% of those over 75 had a college degree, whereas in 1960 28% of those aged 25–29 had a college degree. The percentage of the American population achieving a college degree has steadily increased and currently stands at 42% of the current cohort.

The increasing income of countries in the later stages of the demographic transition has created new “age stratifications.” The idea of retiring at some age (often 65) and enjoying life is a very recent one. In the first half of the 20th century, most of the elderly were 65–74 and most worked until they were no longer physically able to work. “Third Agers” are those who are still healthy enough to engage in all normal activity but no longer have to work (some are very young “trust fund babies”). A major motivation for the establishment of Social Security in the United States was to entice older people out of the workforce to make room for young people seeking work. Life expectancy in the United States was very close to 65, which is what we now regard as retirement age. The increase in life expectancy since the establishment of Social Security is one of the challenges for keeping it solvent.

It may not surprise you to hear that most people who retire experience reduced incomes. The minimum social security benefit is below the poverty level. Although SSI (Supplemental Security Income) was established in 1974 to guarantee poverty-level income for really poor elderly, it is worth noting that poverty rates of people over 65 went from 35% to 10% from 1959–1998. In 1999 median income of over 65 households was $22,812 per year. For those less than 65, it was $46,805. Currently (2019) the median retirement income for Americans over 65 is $47,357. The average annual social security benefit is currently $19,370. Just over 90% of all households with someone over 65 in them collect social security. Most people get by combining Social Security with SSI, or a pension, or rent, or investment. The average age at which our net worth peaks is 65–74. There is a strong relationship between education and net worth with those who have gone to college having a net worth of $1.5 million relative to those with no high school diploma of $138,000 (Figure 4.40). Also, note how different average net worth and median net worth are. Clearly, net worth has a much skewed distribution with some very high values that make the average much higher than the median.

[figure number=Figure 4.40 caption=Net Worth by Education filename=Fig_4.40.jpg]

Improved living standards in some parts of the world are resulting in a “Fourth Age” or “Old-Old” population. People over 85 are a reasonable approximation of the “Old-Old.” Some people in their 60s have the attributes of the “Old-Old,” while some in their 90s are skiing and bungee jumping. In any case, roughly 5% of the population over 65 is in a nursing home. Most of these people are over 85 years old. About two-thirds of people over 85 report that they are healthy. A growing fraction of the population in the developed world will become centenarians (people who make it to age 100). In the United Kingdom, these people receive a letter from the Queen. A baby born in the United States today has roughly a 1 in 3 chance of making it to the age of 100. This is definitely a sign of progress. Of course, the odds are better for girl babies than for boy babies.

4.6.3 Sex Ratios

It is a common assumption that there are the same number of males and females at each age. This is rarely the case. Migration, mortality, and fertility operate differently on each sex at different ages to create inequalities in the ratio of males to females (the sex ratio; Figure 4.41).

[figure number=Figure 4.41 caption=The Sex Ratio filename=Fig_4.41.jpg]

At birth, the sex ratio is 104 to 110 in all human societies. More baby boys are born than baby girls. United States rates are a little lower, while Asian rates are a little higher. We do not know why. Data on miscarriages and fetal deaths suggests that more males are conceived than females. Males have higher death rates from conception onward. The higher at-birth sex ratio may be a cause or a result of this fact. The main conclusion is that men outnumber women in the early years of a cohort and women eventually outnumber men as the cohort ages. The story of mortality with respect to the sex ratio is fairly straightforward. Men have higher death rates than women at every age throughout the life cycle. As a cohort ages the sex ratio inevitably drops. The cultural meme of women in their 30s not being able to find a male partner is no joke. In the United States women start to outnumber men in the 25–29 age bracket and many people have formed committed relationships by that age and are having families. In Canada, the sex ratio is high because migrants to Canada are predominantly men. In Mexico, the sex ratio is low because emigrants from Mexico are predominantly men.

4.6.4 Characterizing Age Structure

The global average age has increased from 21.5 years in 1970 to over 30 years in 2020. A global population breakdown by age shows that roughly 25% of the world’s population are younger than 14 years old, 8% are older than 65, while half the world’s population is of working age (25 to 65). A population is “Young” if 35% or more of its population is under 15 years of age. A population is “old” if 12% or more of its population is over 65 years of age. A population is “aging” if the proportion of people over 65 is increasing. Populations can have different characteristics as they evolve. A stable population is one in which the age-specific birth and death rates do not change. This means that the proportionality of the pyramid does not change. A stable population could be growing shrinking or not changing. A stationary population is one in which it is both stable and at ZPG.

Key figures of merit for characterizing age structure are average age, dependency ratio, and age-specific growth rates. The average age reported is usually actually the median age. The dependency ratio is the number of old people (over 65) plus the number of young people (under 15) divided by the working-age population (aged 15–65). The age dependency ratios are particularly high for countries in Africa primarily due to very young populations (Figure 4.42). The dependency ratio does not capture the relative number of old and young. Mexico and the United States could have the same dependency ratio, but Mexico’s challenge would be more focused on caring for the young, while the U.S. challenge may be more oriented toward issues of aging and caring for the old.

[figure number=Figure 4.42 caption=Age Dependency Ratios Around the World filename=Fig_4.42.jpg]

Max Roser at “Our World in Data” has come through again with a beautiful infographic that shows how the global population pyramid has evolved over time (Figure 4.43). I quote his interpretation of the figure here:

Population pyramids visualize the demographic structure of a population. The width represents the size of the population of a given age; women on the right and men to the left. The bottom layer represents the number of newborns and above it you find the numbers of older cohorts. Represented in this way the population structure of societies with high mortality rates resembled a pyramid—this is how this famous type of visualization got its name.

In the darkest blue you see the pyramid that represents the structure of the world population in 1950. Two factors are responsible for the pyramid shape in 1950: An increasing number of births broadened the base layer of the population pyramid and a continuously high risk of death throughout life is evident by the pyramid narrowing towards the top. There were many newborns relative to the number of people at older ages. The narrowing of the pyramid just above the base is testimony to the fact that more than 1-in-5 children born in 1950 died before they reached the age of five.

Through shades of blue and green the same visualization shows the population structure over the last decades up to 2018. You see that in each subsequent decade the population pyramid was fatter than before—in each decade more people of all ages were added to the world population. If you look at the green pyramid for 2018 you see that the narrowing above the base is much less strong than back in 1950; the child mortality rate fell from 1-in-5 in 1950 to fewer than 1-in-20 today. In comparing 1950 and 2018 we see that the number of children born has increased—97 million in 1950 to 143 million today—and that the mortality of children decreased at the same time.

If you now compare the base of the pyramid in 2018 with the projection for 2100 you see that the coming decades will not resemble the past: According to the projections there will be fewer children born at the end of this century than today. The base of the future population structure is narrower.

We are at a turning point in global population history. Between 1950 and today, it was a widening of the entire pyramid—an increase of the number of children—that was responsible for the increase of the world population. From now on is not a widening of the base, but a “fill up” of the population above the base: the number of children will barely increase and then start to decline, but the number of people of working age and old age will increase very substantially. As global health is improving and mortality is falling, the people alive today are expected to live longer than any generation before us.

[figure number=Figure 4.43 caption=Global Population Pyramid Through Time filename=Fig_4.43.jpg]

There are nonetheless profound geographic differences in the nature of dependency ratios. The age structure of Japan has evolved (and is evolving) quite differently than the age structure of Nigeria (Figure 4.44). Japan is experiencing population decline (Stage V of the demographic transition), while Nigeria is experiencing the rapid population growth characteristic of Stage II.

[figure number=Figure 4.44 caption=Contrasting Evolution of the Age Structures of the Populations of Japan and Nigeria filename=Fig_4.44.jpg]

The kinds of differences shown between Japan and Nigeria (Figure 4.44) manifest as striking differences in Youth Dependency ratios and Old-age dependency ratios mapped globally (figures 4.45 and 4.46).

[figure number=Figure 4.45 caption=Youth Dependency Ratios Around the World in 2020 filename=Fig_4.45.jpg]

[figure number=Figure 4.46 caption=Old-age Dependency Ratios Around the World in 2020 filename=Fig_4.46.jpg]

4.6.5 Population Projections and Forecasts

A population projection is the calculation of the number of persons we expect to be alive at a future date given the number now alive and using reasonable assumptions about ASMRs and ASFRs. A population projection simply suggests a future value for the population if the set of underlying assumptions occur. Population forecasts speculate future values for the population with a certain level of confidence, based on current and past values as an expectation (prediction) of what will happen. The global human population reached the first billion milestone somewhere around 1800. In 222 short years, we reached 8 billion. The annual percentage growth rate has varied from values very close to zero, peaked at a little over 2% in the 1960s, and is currently at roughly 1%. It is expected to continue to drop and reach ZPG again. A population forecast involves predicting how several demographic variables will change over time. Key variables to know are life expectancy, fertility rates, and the age structure of the population. Current forecasts of the global population suggest we will reach almost 11 billion by the year 2100 (Figure 4.47). This forecast has the global annual population growth rate dropping to 0.1% by the year 2100.

[figure number=Figure 4.47 caption=Population Forecast for the World filename=Fig_4.47.jpg]

The United States and other agencies that have engaged in population projections and forecasts have avoided using the term “prediction” because many of their previous forecasts have been very different from reality. U.N. forecasts made in 1973 of the global population in the year 2000 were overestimated by over 400 million (Keilman, 2019). It turned out that global fertility rates dropped faster than the U.N. demographers anticipated. Population projections of the United States in 1968 suggested that the U.S. population would not reach 300 million and begin declining around 2040. Similar projections made in 1996 were much closer to what has occurred and have the United States approaching 400 million by 2050. The demographic theory has not been sophisticated enough to accurately predict shifts in demographic processes, especially fertility and migration. Forecasts of the weather in just a few hours or days are difficult enough, forecasts of employment over the next year are difficult too. Population forecasts, where one tries to predict years or decades into the future, are even more difficult. Nonetheless, we engage in population forecasting because it is the prudent thing for governments and businesses to do in order to engage in rational planning. These forecasts are much more accurate for short periods of time than they are for decades and centuries and that in and of itself can be incredibly useful.

There are many population projection and forecasting methods. We will discuss four commonly used methods: (1) Extrapolation, (2) Components of Growth, (3) Cohort Component Method, and (4) Backward or Inverse Projection. We will also explore a population modeling exercise that makes a forecast of the population based on changes to ecosystem services like the Limits to Growth models of the early 1970s.

Extrapolation: typically, extrapolation as a forecast method works by plotting known populations as a function of time. A mathematical curve is “fit” to the existing data points. This is the method that has historically described global human population growth as “exponential,” which is increasingly inaccurate as global fertility rates drop and the annual percentage growth rate of the population declines. The mathematical functions typically used are linear or exponential depending on the time frame of interest. The mathematical function is usually in some form like Pop(t) = some mathematical function of “t.” To calculate a future population at time “t,” one simply plugs that value of “t” into the formula. This is not a very sophisticated way of forecasting the population and not surprisingly does not work very well.

Components of Growth: the components of growth method uses the very fundamental population equation:

Population (t2) = Population (t1) + Births—Deaths + immigration—emigration 

This is a perfectly accurate way to forecast the population. Unfortunately, it depends on data that is often not available or if available is not necessarily accurate. This equation is often used to “solve” for one of the variables in it. For example, we have a year 2000 census and a year 2010 census and we know how many people were born, died, and emigrated in the intervening years. Thus, we can estimate immigration (legal and illegal) using this equation if the census was successful in capturing all the relevant people that it hoped to count.

Cohort Component Method: this is the most sophisticated method of projecting population. A significant amount of information is needed to do this properly including: (1) A complete age–sex structure profile of the population at a given time (all the info needed to make a population pyramid), and (2) age and sex-specific mortality and migration rates, and ASFRs. It can be “tweaked” by making assumptions about how mortality, fertility, and migration rates will change as the future unfolds. A cohort component model can use historical data and information as to how the fertility, mortality, and migration data of the past has changed to predict how they will change in the future. This is shown for Viet Nam from 1950 to 2100 (Video 4.5).

Backward or Inverse Projection: inverse projections can be done via any method (i.e., extrapolation, components of growth, or cohort component). The best methods use reverse cohort component in which a good age and sex structure is obtained with best estimates of age and sex-specific mortality and migration rates and ASFRs. This sort of “backcasting” method can be used to build a demographic history of a region or country. Wrigley and Schofield (1981) used a backward estimate from an 1871 census of England and Wales to prepare a demographic history of England. Another controversial question that can be interrogated using backward projection methods is the question of how many Native Americans were living in the western hemisphere prior to Columbus and European colonization? Whitmore (1996) used inverse projection to determine that 90% of the population of the basin of Mexico died in the first 100 years of European contact.

Population projection and forecasting is an essential tool of good governance. The age and sex structure of a population drives all demographic changes, which are translated into demographic realities that have profound impacts on governing. A high birth rate does not simply mean more people, it means that a few years from now there will be more kids entering school than before; it means that 18 years from now there will be more new job hopefuls and college freshmen than before. An influx of young adult immigrants this year means a larger than-average number of older people 30 or 40 years from now. This influx may also mean an immediate sudden rise in the number of births with all the immediate and subsequent consequences.

Countries and regions with very young populations have a momentum for population growth built into them. The large fraction of people under 15 years old will probably survive and have children. Even if they reduce fertility to a replacement level of 2.1 the population will continue to grow for a period of time. One way to measure this “population momentum” is to answer the question: If a population were to immediately reduce its fertility to replacement levels how big would it grow to before it became stationary? In Africa and some parts of Asia, this could be 1.5 times larger than the current population, whereas in the United States it is only 1.1 times as large. Population momentum is the dominant force driving population growth in the world today. Global fertility rates have dropped substantially. Only in Sub-Saharan Africa is the impact of high fertility greater than population momentum as a contributor to population growth.

One truth about the future of the global human population is increasingly being recognized—it will peak and drop to a much lower level (
New York Times, Sept 2023; Spears et al., 2023). Since the majority of demographers typically project only until 2100, there remains uncertainty regarding the pace of population decline beyond that point. Over the last century, the world population surged from 2 billion to 8 billion. Assuming current trends persist, characterized by a widespread preference for smaller family sizes, the decline in the 22nd or 23rd century will likely mirror the steep ascent experienced in the past.

[Insert Quick Check 4.5]

Chapter Summary/Key Takeaways

This chapter provided a description of the empirical observations that have come to be known as the demographic transition. The DTM has been developed to explain these observations. The basic observations are that populations begin with high birth and death rates with very small changes to total population size (Stage I). Historically this proceeds, in some parts of the world, to dropping death rates accompanied by high rates of population growth (Stage II). The third stage of the demographic transition involves dropping fertility rates. Numerous theories exist as to what causes fertility decline including improved status of women, industrialization, economic development, and increasing secularization. Stage III of the demographic transition is characterized by slowing rates of population growth. In Stage IV of the transition, the falling birth rates equilibrate with the death rates and total population size stabilizes. This chapter describes how fertility, mortality, migration, and aging are measured and explored some of the prevailing ideas as to the causes of these changes.

In the next chapter, we will take a closer look at the processes of urbanization and economic development. Both of these processes are believed to have significant impacts on the demographic processes of fertility, mortality, migration, and aging. Increasingly urbanization and economic growth are having impacts on our environment and its ability to support large human populations. These topics lead to the “Problematics” addressed in Part III of this book.

Comprehensive Questions

• What are the empirical observations that constitute the demographic transition?
• How does the demographic transition model explain those observations?
• How do we measure fertility, mortality, and migration?
• What are the proximate controls (e.g., “hows”) of fertility?
• What are the “whys” of fertility control (e.g., personal, social, and cultural)?
• What are the major migration streams in the world today?
• What are the major causes of death in the world today and in the past?
• What social challenges manifest as a population ages?
• What is the difference between a refugee and an asylum seeker?
• What is the state of the world’s refugees today?
• Explain Wilber Zelinsky’s Migration Transition Theory. Is it still relevant today?

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