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Hinde,+2002+_Human+Pop+Dynamics_

Hinde,+2002+_Human+Pop+Dynamics_ - This chapter describes a...

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Unformatted text preview: This chapter describes a formal demographic perspective on human population dynamics. It first attempts to summarise the way in which human population dynamics are treated in the more technical and theoretical demographic literature. The next section considers some demographic fundamentals, including population structure (especially the age and sex composition) and the three components of population change: fertility mortality and migration. The third part looks at some of the formal models which demographers have de- veloped to help understand population change. These models make E- several assumptions in order to simplify a complex reality. One ofthese is that migration is zero: populations with zero migration are said to be closed. An attraction of this is that, if migration can be ignored, simple relationships exist between fertility, rationality, the population :- growth rate and the age structure. t In the {Ourth section population dynamics in the short to medium term are considered. The age and sex structure of a population is itself a dynamic feature, containing a record of the population’s past fertility, mortality and migration. Moreover, the future age—sex struo ture is determined by past and current events. Discussion of these E aspects of population dynamics leads naturally in the fifth section to a consideration of population momentum, or what is sometimes, inaccurately, called the ‘demographic time bomb’. The origins of population momentum are explained. 2' Finally, in the sixth and seventh sections long—run population dy- namics are explored in the context of the demographic transitions in lo HELEN nacssrn AND PAUL COLLINSON E334" Hum” PJiUI “AM ‘0 ‘1 ‘U Mi g ‘- C P055 997361} 1’5",” i pensfiacaE-w: . ll Q2 mioé’eé 5...! Val (M45 References E 2 car-«(0P3 4&fi 06L): iv)- flW , 100.2. Clarke, ji. (1972). Geographical influences upon the size, distribution and E ' ' growth of human populations. In The Structure nguman Populations, ed. GHA E" DEWOgqu [126 p 67516. 6612.063 07?, [1315an Harrison and AJ. Boyce, pp. 17—31. Oxford: Oxford University Press. E; POPZJZCZZZOW, dynamics Harrison, GA. and Boyce, AJ. (ed) (1972). The Structure quumon Populations. ET Oxford: Oxford University Press. E Malthus, TR (1803). An Essay on the Princzjole of Population. {Volume 2 of The Works E" of Thomas Robert Malthas, ed. EA. Wrigley and D. Souden (1986). London: E. ANDREW HINDE William Pickering] E E5 . E: Introduction E. .=.- 17 1C5 ANDREW HINDE Europe and contemporary Africa. The relationships between fer— tiiity, mortality and population growth enable closed populations to be placed in fertility—mortality space’. Placing historical and con~ temporary populations in this space reinforces the idea that long—run population growth is naturally very slow. It also allows comparisons to be made of the demographic transition in different cultures. Some demographic fundamentals Demography is about analysing the growth (or decline} of human populations and changes in their structure. We cannot analyse pop- ulation growth without some straightforward and unambiguous way of enumerating the members of a population, and this can only ex: ist if we can work out who is, and who is not, to be included in the enumeration. To demographers, a population consists of any group of persons who can be delimited on the basis of some observable characteristic. The most common way is to define the population on the basis of resi— dence within a given geographical area. Thus we speak, for example, of the “population of England’ as being all those persons normally resident in England. However, residence is not the only criterion. We could delimit populations on the basis of tribal affiliation: the Luo population of Kenya, for example, using both geographical residence and membership of a particular tribe as criteria. Necessary features of characteristics used to delimit a population are that they be observ~ able and well defined, so that we can use them to say whether any individual person is or is not a member of the population at a given time. Notice that although these characteristics are used to distinguish separate populations, they themselves are inclusive: they are shared features which bind the members of a distinct population together. In order to be able to analyse population growth and change, it is essentiai to be able to identify the processes by which persons enter or leave populations. It is fortunate for demographers that popula“ tions only change in size because of a limited, countable, range of events. Consider, for example, the population of a particular country at some time, say ijanuary 2000, which we might call P2000. Then the Demographic perspectives i9 population of that country on ljanuary 2091, P2001, is equal to P2999 plus the number of births during the year 2000, minus the number of deaths, pins the number of people who migrate into the country during the year, minus the number of persons who migrate out. The difference between the number of births and the number of deaths is known as natural increase (or decrease if deaths exceed births) and the difference between the number of immigrants and the number of emigrants is known as net migration. Analysing changes in the size of human populations, therefore, in~ volves the analysis of the processes by which births, deaths and migra~ tion events come about. The process which produces births is known as fertility; the corresponding process which results in deaths is called mandolin. The three processes of fertility, mortality and migration are known as the components of population change. Demographers are interested particularly in the intensity with which these events occur in a particular population. Since a large population will tend to generate more events than a small popula tion, the absolute numbers of, say, births and deaths in a particular time period are of limited use as measures of this intensity. Therefore, demographers use what are called rates. A demographic rate is a ratio of events of a particular type, for example deaths, to the number of persons exposed to the risk of experiencing that type of event. Thus the crude death rate is equal to the number of deaths in a given period divided by the ‘average’ population during that period. it is normally important that the events and the population ‘exposed to risk’ cor— respond. That is, we need to make sure that the persons exposed to risk really are at risk of experiencing the event in question, and that we do not include events in the numerator which do not occur to persons in the denominator. There are some exceptions to this, one being the crude birth rate (number of births in a given period divided by the ‘average’ population during that period) in which men, who do not give birth, are included in the denominator. Because peopie are not all identical, all human popuiations have a structure, By population structure demographers mean the distribution of various characteristics across the members of a population. The char— acteristics most commonly considered by demographers are sex and age. Certainly, these will be the most important variables so far as this 20 ANDREW HINDE chapter is concerned. Other variables by which a population struc— ture may be defined include genetic make—up, socioeconomic class- ification, occupation, educational attainment, place of birth, ethnic afifiiiation, etc. A very important feature of populations is that the intensity of the components of population change varies according to people’s char— acteristics. Thus, different subgroups within a population will have different risks of experiencing births, deaths and migration. People aged over 60 years have a higher risk of dying than do teenagers, for example. For this reason, demographers tend to work with rates specific to particular subgroups. The most commonly used of these are age-specific rates, but in principle, rates can be calculated speci« fic to any subgroup of interest, for example, as defined by variables discussed above in regard to structure. Formal demographic models of population change If migration is ignored (that is, if we assume a closed popuiation), simple relationships exist between a population’s fertility, its mortal— ity and its rate of growth, and between these three variables and its age structure. These relationships can be described mathematically, and this permits the construction of elegant demographic models of human population dynamics. Two sets of relationships are of great interest in a closed population (Figure 2.2). The first is that linking fertility and mortality to the rate of growth. The second is that linking the rate of growth and mortality to the population’s age structure. Let us consider the first ofthese. A convenient way to understand how the relationship works is to imagine the population of a remote island. Suppose that on this island there are 100 men and ISO women, and suppose that each man is ‘married’ to one woman so that we have 100 couples. By ‘married’ we simply mean that the couple is in a more or less stable sexual relationship, whether this is iegally formalised or not. One plausibie measure of the rate of population growth is the total number of children that these 100 couples produce. Clearly, if this is greater than 200, then the next generation will be larger Demographic perspectives 21 5ertility Mortality Age structure Figure 2.1. Relationships in a closed population. than the present generation, and the population will grow. If it is less than 200, the population will decline. The total number of children produced by the iOO couples can be divided by 100 to give the average completed family size. It" the average completed family size exceeds 2, then the population will grow. Demographers often refer to the average completed family size as the totalferiiligz rate (TFR). If, then, on our remote island the TFR is 4:, each woman will produce four chiidren. Suppose that half of these are boys and half girls. The result will be that our 300 couples will have 400 children, 200 sons and 200 daughters. If the same TFR is maintained for subsequent generations, then 800 grandchildren will be born, i,600 great—grandchildren, and so on. The population will therefore double in size every generation. This, of course, is what Thomas Malthus meant when, in his Essay) on the Principle if Population (1 798), he described popuiations as increasing in a :geometrical ratio’. The TFR is, in fact, the sum of a set of agemspeczfic fertility rates (ASFRs). Recall the definition of a demographic rate in the previ- ous section. The ASFR is defined as the number of births to women of a given age in a given year divided by the number of women of that age, i.e. events divided by those exposed to risk. It measures the number of births that the ‘average’ woman can expect to have in a year while she is at that age. So, for example, the ASFR for a woman aged 20 years last birthday is a measure of the number of children the 4!. ANDREW HINDE average woman has in the year between her 20th and 21st birthdays. In practice, this will be less than i in almost all human populations, as most women in most populations will have no children at all between their 20th and Qist birthdays. If we sum the ASFRs at all ages from the youngest age at which women hear children to the oldest age, the result will be an estimate of the number of children which the average woman will produce during the whole of her childbearing period, or, in other words, the TFR. Population growth, therefore, depends on fertility. However, it mat~ ters whether the children are boys or girls. To see this, imagine the populations on three remote islands, A, B and C. Each of these islands contains a population of 100 couples. Suppose that on all these islands each couple has exactly four children, i.e. the "FF R is equal to 4. On island A equal numbers of boys and girls are born. However, on island B three boys are born for every girl, and on island C thred girls are born for every boy. Island A exhibits the doubling every generation that we have already described. On island B the original 100 couples produce 300 sons and 100 daughters, whereas the 100 couples on island C produce 100 sons and 300 daughters. Thus in the first generation, the population ofboth islands doubles. However, in the next generation things become more interesting. Assuming that the women continue to have four children each, then on island B only 400 children will be born in the third generation, whereas on island C, each of the 300 daughters of the first generation will produce four children, making a total of £200 grandchildren (300 grandsons and 900 granddaughters). Oi” course, achieving this would involve polygyny or monogamy with extra—marital childbearing. For the population of island B to match the growth of island C, each of the daughters of the first generation would have to produce i2 child- ren. Even supposing that polyandry were widespread, as there are, after all, three males for every female in the second generation, it is most unlikely that this will he achieved. Indeed, the highest reliably recorded fertility in a human population is around ten children per woman among the Canadian Hutterite population during the 1920s and 1930s. The key point to take away from this stylised example is that the rate of population growth depends on the number of girls born rather than on the number of boys. Demographic perspectives 2 3 In practice the sex ratio of births among human populations varies rather little; it averages 105 or 106 boys per 100 girls. This implies that a TFR ofi will lead-to a population not quite doubling itself every gen eration. It is likely that an awareness that, so far as population growth is concerned, it is daughters that matter, almost certainly iay behind the female infanticide practised by certain tribal populations in the past. This mention of sex—selective infanticide (see Rousham and Humphrey, Chapter 7) leads neatly into the final factor determining the rate of population growth in a closed population. This, of course, is mortality. And what matters here is the chance that a daughter will survive long enough to have children herself. Returning to the remote islands, let us suppose that on islands D and E the sex ratio of births is 105 boys per 100 girls. Suppose, however, that on island l) four in every live girls horn survive to reproductive age, but that on island E only one in every two girls does this. On island D, the l00 women in the original generation will bear ti00 children, of which 395 will be daughters (400 X 100/205). Only four—fifths of these (i 95 x 0.8 2 156) survive to reproductive age. These 156 daughters will hear 624: (156X4) children in total, of which 304 will be girls {524x 100/ 205). Of these, 80% will survive to reproductive age, resulting in a popu- lation of 243 granddaughters. The female infant and child mortality has reduced the rate of population growth substantially This is even more strikingly illustrated by island E, in which only half of those born survive to reproductive age. It can be shown that the population of island E will decline over the generations and eventually die out. For population growth, the mortality of females matters more than that of males, though male mortality is not completely irrelevant. Moreover, even for females, it is only mortality up to and during the childbearing years that is of interest. Thus, to analyse population growth, we need to measure age-specific female mortality up to about age 50 years. Age-5,0953% death rates (ASDRS) can be caiculated in a way similar to that of ASFRS, by dividing the deaths in a given year to persons of a specific age by the population of that age. A set ofASDRs provides a complete description of the mortality experience of a pop» ulation. In particular, ASDRs can be used to draw up a table of the probability that a person will survive to at least a given age. This table is known as a life table, and an example is shown in Table 2.1, using 24 ANDREW HINDE Table 2.1. Conditional prbbabz’lia'es qfdeatfz and prababiiz‘gr @‘suraiaal to dg'firerent ages,females in England and Miles, 1901—] 0 Conditional probability Probability of of death before next survival to at Age 9: specified age least age 2: 0 0.1 174 1.0000 1 0.0689 0.8826 5 0.0173 0.8218 10 0.0206 0.8076 15 0.0143 0.7990 20 0.0173 0.7876 25 0.0208 0.7740 30 0.0265 0.7579 35 0.0334 0.7378 40 0.0414 0.7131 45 0.0529 0.6836 50 0.0705 0.6475 55 0.1001 0.6018 60 0.1374- 0.5416 65 0.1942 0.4672 70 0.2983 0.3764 75 0.4116 0.2641 80 0.5436 0.1554 85 1.0000 0.0709 M The conditional probabiiity of dying before the next specified age is the chance that a woman will die prior to the next specified age given that she is still alive at age x. 80, for example, the chance that a woman aged exactly 40 years will die before her 45th birthday is 0.0414 (just over 4%). Clearly, this conditional probability for the oldest specified age x must be 1.0000, as everyone eventually dies. Source: Woods and Hinde (1987: 33). data which relate to the female population of England and Wales in the decade 1901—40. Under this mortality regime, for example, a woman had about an 80% chance (probability 0.7990) of surviving to her 15th birthday, and about a 65 % chance (probability 0.6475) Demographic perspectives 25 of surviving to her 50th birthday. Associated with the probabilities of survival to given ages are conditional probabilities of death within a particular age range. These conditional probabilities are expressions of the chance that someone Wili die within an age range given that they are alive at the start of that age range. An important special case is the infant mortality rate, which is the probability that a baby will die before his or her first birthday From Table 2.1, it can be seen that the infant mortality rate for girls in England and Wales in i901—10 was 0.1l74. in other words, almost 12% of girls born during this period did not survive until their first birthday. Although the mortality of males is not so important for understanding population growth, it is worth pointing out that in most human populations, the mortality of males exceeds that of females at all ages. Infant and child mortality is discussed further by Rousham and Humphrey (Chapter 7). The stylised example described in this section shows that popula— tion growth depends on three things: the average number of children born to women, the sex ratio of births and the chance of a female child surviving to reproductive age. One measure of population growth which incorporates all of these is the net reproduction rate (NRR). The NRR is approximately equal to the TFR muitiplied by the propor— tion of births that are girls multiplied by the probability of a woman surviving to the mean age at childbearing. The mean age at child« bearing varies a little between populations, but is between 27.5 and 30 years in most cases. Therefore, suppose that a population had a TFR of 4.0, that i05 boys were born for every 100 girls, and that the mortality of females was described by Table 2.1. The chance that a woman will still be alive at exact age 25 years is 0.7740, and at age 30 years it is 0.7579. So the probability of survival to the mean age at childbearing (27.5430 years) may be estimated at, say, 0.76. The NRR is, then, calculated as 4X(100/205)><0.76 = 1.48. The NRR measures the size of the next generation relative to the size of the present generation. 80 an NRR of 1.48 means that the next generation will be 48% larger than the current one. The second important relationship is that between the rate of growth, the mortality and the age structure of a population. The number of persons alive at any age x, at a particular time, in a closed population, is the product of two factors: the number born at years ago ZO ANDREW HINDE and the probability o...
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