Population Growth

Over the past 50 years, the developing countries (as conventionally defined by the United Nations) added 3.2 billion people to the world's population, which has now reached 6.0 billion. Over the next 50 years, if current moderate projections hold, this same group of countries will add another 3.1 billion people to the world's population. Substantial population growth does not seem to have gone away.

Fifty years is a long period for a projection. However, shorter projections show the same trends. From 1975 to 2000, developing-country populations will have grown by 1.9 billion people (reaching 4.9 billion). From 2000 to 2025, they will continue to grow by an additional 1.8 billion people. Figure 1 shows population growth by decade in the industrial and developing countries. The peak decade for population growth in developing countries is the 1990s. Even if, as projected, growth falls off a little, it will still be well over 700 million per decade over the next 20 years, and then will decline only gradually. Industrial countries, on the other hand, will contribute little to world population growth and could as a whole experience negative growth toward the middle of the next century.

Projections naturally involve some uncertainty but are not pure speculation. After all, of the population in the year 2025, more than half have already been born, and of the population a decade from now, at least 80 percent are already among us. Historical experience with patterns of childbearing can be applied to estimate the remaining proportions.¹

¹Such projections almost always assume that current attempts to reduce the rate of population growth will continue and will not be weakened. If, instead, fertility were to cease to decline, the developing-country population would grow by 2.4 billion, not 1.8 billion, in 2000 to 2025, and by 5.8 billion, not 3.1 billion, in 2000 to 2050.

Figure 1 - Population Increments by Decade in Industrial and Developing Countries (millions)

SOURCE: United Nations (1996) and projections using the World Bank (1997a) model.

The projections show continued substantial growth despite the fact that fertility has moderated in developing countries. In the 1950s total fertility was estimated at 6.0 children per woman. By the first half of the 1990s, it had fallen almost by half, to 3.3 children per woman. Annual population growth, about 2.1 percent a year in the 1950s, is below 1.8 percent and falling.

Despite these fertility declines and even assuming they will continue, the annual increments to developing-country populations will still be large. While fertility has fallen overall, very high fertility persists in many countries: Total fertility in Uganda, for instance, has been estimated recently at 6.9 children per woman, and it is only one of about two dozen countries with fertility at 6.0 or higher. About another two dozen countries have fertility between 5.0 and 5.9 (World Bank, 1997a). In addition, annual increments are large because developing-country populations are much bigger now and are predominantly young, with a median age of about 23. Young populations include many potential childbearers, whose children in turn will continue to swell the population. As a result, the number of babies born in developing countries should keep increasing for another two decades. The population growth rate will moderate during this period only because, as the population ages, the number of deaths will also go up.

If each couple were to have no more children than those necessary to replace themselves, developing-country populations would still continue to grow because of their young age structures. This is illustrated in Figure 2 with population pyramids, which show the distribution of population by age and sex. Each cohort (each group of people born in contiguous years) moves upward in the pyramid as it ages, and the upper levels of the pyramid therefore expand over time, as the contrast between 1995 and 2025 shows. Even if each cohort only reproduces itself (so that the lowest rung of the pyramid resembles the preceding ones), population will still grow, especially at older ages. This phenomenon, known as population momentum, will account for almost three-quarters of the population growth in developing countries over the next 25 years and for practically all the growth in East Asia. Momentum is largely absent, by contrast, in the pyramid for industrial countries (the last pyramid), which has a narrow base.²

²Momentum can also be compared to the long-term interest on the national debt, continuing almost indefinitely into the future. The debt exists because of a previous excess of government expenses over revenue. Momentum exists because of a previous societal "excess" of births over deaths. The quicker a balanced budget is reached, the smaller the long-term debt. Similarly, the quicker a balance of fertility and mortality is reached, the smaller the long-term population momentum. If a balanced budget cannot be reached this year, reducing the deficit will at least slow the growth in the national debt. Likewise, reducing fertility will at least slow the increase in population momentum. Even if the government achieves a balanced budget, and keeps it balanced indefinitely, interest charges will continue on the accumulated debt. Even if fertility stays at replacement level indefinitely, population will continue to grow because of the accumulated momentum. Finally, just as only applying a government budget surplus to the principal on the national debt will reduce future interest payments, only fertility below replacement will reduce future population momentum.

Figure 2 - Population Pyramids: Distribution of Population by Age and Sex (millions)

SOURCE: World Bank (1997a, 1997b) and projections using the model used there.

Continued substantial population growth can be expected in every developing-country region. Of the 1.8 billion additional people that can be expected in the next 25 years, East and Southeast Asia and the Pacific will contribute about 400 million (Figure 3). More will come from sub-Saharan Africa (almost 500 million) and South Asia (480 million). The increments will be smaller, but still substantial, in the Middle East crescent (260 million for this band of mostly Islamic countries stretching from Morocco to Kazakhstan) and in Latin America and the Caribbean (170 million). Although population growth will be most impressive in sub-Saharan Africa - leading to a population 75-percent larger by 2025 than it is today - other regions will also show impressive expansion. Latin America, for instance, will have 33 percent more people by 2025, and much of the increase will undoubtedly go to expand such already massive urban agglomerations as Mexico City.

Figure 3 - Population Increments by Decade in Developing-Country Regions (millions)

SOURCE: Estimated using the World Bank (1997a) projection model.

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Expanding megacities will be among the substantial changes that these large population increments will bring. Countrysides will probably be more densely settled, and infrastructure and human services will be either substantially more extensive or under greater stress. The half century of growth since World War II has, for example, seen the Philippines increase from 70 to 226 people per square kilometer of land, and Bangladesh from 290 to 821 people per square kilometer. (At the latter density, the United States would have 7.7 billion people, not 270 million.)

Contrasts between the rapidly expanding developing countries and the steadily growing industrial economies can be extreme. Figure 4, for instance, compares income levels (gross national product, or GNP, per capita), the labor force in agriculture, and infant mortality.³ Average income in developing countries is less than one-twentieth of that in industrial countries. The proportion of the labor force in agriculture is on average more than 10 times as large as in industrial countries. And babies in developing countries die at a rate more than eight times that of industrial countries, producing average life expectancies about a dozen years shorter.

³The groups compared, strictly speaking, are high-income economies versus low- and middle-income economies, as defined in World Bank (1997b). "Europe and Central Asia" includes only the low- and middle-income economies in that region.

Figure 4 - Indicators for High-Income Economies and Low-and Middle-Income Regions

NOTE: Regional averages are weighted by population (or by number of births, for infant mortality) and exclude high-income economies. Data from World Bank (1997b).

How much of the difference in development and human welfare is explained by rapid population growth? A number of previous studies have produced inconclusive and even conflicting results. Cross-national regression analyses with data from the 1970s suggested that population growth did not affect national income, but studies of the 1980s suggested a negative impact.⁴ Population growth, after all, provides not only more consumers of societal resources and services but also more workers and producers of goods, a greater pool of human resources for developing new products and technology. The relevance of expanded pools of consumers and producers may depend on economic and social policies that are often enacted with little attention to population. The net effect of population on development could therefore vary across countries and periods and could be difficult to assess.

⁴See Ahlburg (1996) for a recent review of this general area.

What is clear, however, is that different sources of population growth have different economic implications. A population growing through migration often puts the migrants to work, earning some return from their labor.⁵ A population growing because of substantially longer life expectancies could in principle keep older people working longer to prevent any increase in dependency, although societal preferences and practices may preclude this. But a population growing because of high fertility must accept that those added to the population will spend years as dependents, becoming socialized and educated, before they are productive.

⁵Smith and Edmonston (1997) conclude, for instance, that U.S. residents gain economically from the presence of immigrants because of the additional labor (generally remunerated at lower rates than the average) and the increased specialization.

Dependency and Savings

The South Korean experience can illustrate how high fertility contributes to large numbers of dependents. Total fertility was well above four children per woman until 1970, and for every 100 persons of working age (15-64) there were between 70 and 90 dependents (either younger or older). But fertility was declining rapidly, and the dependency ratio followed it down, so that now there are only 40 dependents per 100 persons of working age, fewer than the 50 per 100 typical in other industrial countries (Figure 5). The dependency ratio will rise again in the future as the population ages, but since the mid-1980s South Korea has enjoyed a relatively light dependency burden and will for several more decades.

A key argument in a landmark study 40 years ago was that a light dependency burden should be good for economic growth (Coale and Hoover, 1958). Among the effects of the dependency burden, the way it depresses savings has recently received renewed attention. Arguments about this have gone back and forth among economists, but improved models now confirm this effect cross-nationally (Kelley and Schmidt, 1996). An analysis of household income and expenditures in Great Britain, Taiwan, Thailand, and the United States concludes that "in all countries except Thailand, more children depress the saving rate" (Deaton and Paxson, 1997, p. 106).⁶ Careful analysis of the experience of East Asian countries suggests that their reductions in fertility in the past decades relieved not only dependency burdens but also dependence on foreign capital by contributing to high saving rates (Higgins and Williamson, 1997; Williamson and Higgins, 1997; Lee et al., 1997; Bloom and Williamson, 1997).

⁶However, Deaton and Paxson go on to try to estimate the aggregate effect of population growth on the saving rate and find it is trivial (and actually has the reverse sign). They achieve this contradictory result with a model that assumes a stable population (contrary to the typical situation in a developing country, in which life expectancies are rising and fertility is falling) and unchanging age profiles of income and saving (contrary to their own empirical findings). These unusual assumptions may be largely responsible for their perverse aggregate results: A stable population, for instance, will have a different distribution of age groups - and therefore different proportions of high-saving and low-saving households - than a population nearing the end of fertility transition.

Figure 5 - Total Fertility Rate and Dependency Ratio, South Korea, 1950-2050

SOURCE: United Nations (1996) and World Bank (1997a).

Saving rates are indeed exceptionally high in East Asia: 35 percent of gross domestic product (GDP) in Northeast Asia and 33 percent in Southeast Asia, in contrast to 21 percent in the countries of the Organization for Economic Cooperation and Development (OECD) and only 10 percent in South Asia.⁷ Relying less on government services, the multitude of households save substantial amounts as their members save to provide for retirement; possibly to fund bequests to the next generation; sometimes to hedge against financial setbacks; and occasionally to anticipate large expenditures, such as those for children's education. Over their lives, people ordinarily save most in their middle years when they are most productive, provided their child-rearing expenses have declined. And as life expectancies rise, Asian workers, increasingly less confident of being able to depend on children in old age and unprotected by elaborate social security schemes, have also been pressed to save more for retirement.

⁷For present purposes, Northeast Asia covers Japan, South Korea, Taiwan, Hong Kong, and Singapore; Southeast Asia covers Indonesia, Malaysia, the Philippines, and Thailand.

Figures 6 and 7 show trends in dependency ratios, savings, and investment in Northeast and Southeast Asia.⁸ As expected, savings and investment generally moved in the opposite direction from dependency, rising as lower fertility reduced the size of dependent cohorts. To determine whether this apparent link is causal requires investigating many possible complicating factors. For instance, strong economic growth itself can produce greater savings, as households find their incomes augmented by unexpected windfalls. When such relationships are accounted for, however, the results still suggest that dependency has a strong effect on savings.

⁸The graphs show unweighted averages across countries, leaving out Taiwan for dependency ratios. Savings and investment rates cover five-year periods centered around the given dates, except that the last point is for 1990-1992 (Williamson and Higgins, 1997). Dependency ratios are for the middle of each period (United Nations, 1996).

For Northeast Asia, the net effect of a dependency ratio above 60 percent in the early 1970s was to depress savings by 5.2 percentage points (as a share of GDP), whereas the net effect of a dependency ratio close to 40 percent in the early 1990s was to increase savings by 8.4 percentage points (Williamson and Higgins, 1997).⁹ These percentages are not trivial. For South Korea, for example, an 8.4-point increase was worth additional savings of close to US$25 billion a year in the early 1990s. This figure exceeds the total official development assistance received by all of East Asia and the Pacific in 1991 (US$17 billion) and is equal to more than half the assistance received by all developing countries combined (US$47 billion).

⁹That is, savings were depressed or increased by the amounts given relative to what they would have been if "population age shares" had been at the 1950-1992 means.

Net effects of dependency on investment were similar: A reduction of 3.7 percentage points in the early 1970s contrasts with an increase of 5.4 percentage points in the early 1990s. The dependency burden contributed to these countries' international debt from 1950 to 1980, but the lighter dependency burden has contributed to positive current account balances since then. A similar, but slightly more moderate, pattern of net effects on savings and investment has been demonstrated for Southeast Asia (Williamson and Higgins, 1997).

The net effect of dependency ratios was large enough to produce all the decline in foreign capital dependence after 1970 in both Northeast and Southeast Asia, by itself turning these regions from net debtors to net creditors on world capital markets. It also produced substantial capital deepening: From 1965 to 1990, capital per worker grew 2.7 percent annually in the United States, but 6.6 percent annually in Thailand, 7.6 percent in Japan, 8.6 percent in South Korea, and 8.7 percent in Taiwan (Summers et al., 1995). (Although the United States appears disadvantaged in this comparison, it actually benefited by using East Asian savings to finance its perennial trade deficit.) The substantial liquidity these savings created, plus the additional investment attracted from foreign sources, could have contributed to the financial excesses, given lack of effective bank regulation, that led to the Asian currency crisis in 1997.¹⁰ Clearly, a savings bonus from favorable demography can cut two ways: Failing to use it productively can be, eventually, as injurious as investing it well can be beneficial.

¹⁰Krugman (1998) provides an interpretation of the crisis that explains its untraditional character: Implicit government guarantees for banks and finance companies, coupled with poor regulation, led to distorted investment decisions and an eventual collapse in asset prices.

Figure 6 - Dependency, Savings, and Investment in Northeast Asia

SOURCE: Based on Williamson and Higgins (1997).

Figure 7 - Dependency, Savings, and Investment in Southeast Asia

SOURCE: Based on Williamson and Higgins (1997).

The large effects of reduced dependency on savings owed something to the fact that these economies were rapidly growing, and the impact of dependency changes could be magnified by other factors. But this issue aside, East Asia does not appear to be a special case. Modeling suggests that the effect of a given demographic shock on the current account balance has been no different in the rest of the world. However, in such regions as South Asia, where dependency reductions have so far been smaller, the impact has been correspondingly less positive (Williamson and Higgins, 1997; Bloom and Williamson, 1997).

Education and Health

Smaller birth cohorts should reduce the pressure on schools, allowing improvements in education. Across developing countries, expenditures per pupil rise as the proportion of the population that is of school age declines. But education spending in total does not necessarily increase, and enrollment rates do not always rise (Schultz, 1987). The "demographic bonus" from declining fertility, which could be spent to increase enrollment or improve the quality of education, is sometimes spent instead on ineffective educational systems or on other things besides education.

Where the "demographic bonus" does go to improve education, the results can be salutary. For instance, South Korea raised net secondary enrollment from 38 to 84 percent between 1970 and 1990 and more than tripled expenditure per secondary pupil (Ahlburg and Jensen, 1997).¹¹ Demographic factors were not the only ones at work, but for East Asia as a whole they are estimated to have contributed 3 - 4 percent of the rise in enrollment and 10-13 percent of the increased expenditure (Williamson and Higgins, 1997).

¹¹In the 1960-1985 period, high enrollment levels (especially at the primary level but also at the secondary level) accounted for more than twice as much economic growth in Korea as the level of investment (Page et al., 1993).

Lower fertility presumably is a boon not only for the educational system as a whole but also for individual parents in educating their children. With fewer children, parents should have more resources, time, and energy to spend on each child. Empirical studies generally confirm that fewer children means each gets more education, although the effect is neither universal nor necessarily sizable (see, for example, Rosenzweig and Wolpin, 1980; Knodel et al., 1990; Foster and Roy, 1993; Lloyd, 1994). One of the larger effects is for the Dominican Republic: In households that had avoided any unwanted births, 56 percent of children completed primary school, as opposed to only 39 percent of children in households with two or more unwanted births. This effect of "unwantedness" is similar, although weaker, in the Philippines but does not appear in Egypt or Kenya (Montgomery and Lloyd, 1996).¹² As with the demographic bonus at the societal level, the effect of fertility on education at the household level may depend on context. When parents see improved futures for their children with education, consider it an affordable priority, bear at least some costs of sending children to school, and have begun to plan their families with children's education in mind, lower fertility can contribute to more educated children (Lloyd, 1994).

¹²Montgomery et al. (forthcoming) confirm the effect of unwantedness in further analysis but suggest it may be smaller, less than a year of schooling completed on average in the countries where it appears.

Lower fertility also produces healthier children. Closely spaced children, large numbers of children in each family, and children born to younger mothers are all more common before fertility declines, and such children all face higher mortality risks. Even up to the age of five years, the risk of death is greater if the interval since the preceding birth is shorter. The risk of death in the first month of life (the neonatal period) is 35-60 percent higher after a birth interval under 2 years than after an interval of 2-4 years (as Figure 8 shows for three regions). On the other hand, if the interval is longer than four years, the risk of neonatal death is reduced by 10 percent. Deaths in the postneonatal period (one month to one year) and in early childhood (1-4 years) show even more striking effects (Figure 8). Some of these effects of child survival may reflect limits on household resources for nutrition or health care, but physiological factors are also at work.

Figure 8 - Percentage Change in Risk of Death When Preceding Birth Interval Is Shorter or Longer than 24-48 Months

NOTE: Medians for 12 sub-Saharan, 10 Latin America, and 6 Asian - North African countries, excluding cases where the preceding sibling died before the following child's second birthday (Sullivan et al., 1994).

Close spacing interferes with breastfeeding, which has an important role in child nutrition and in protecting the child from infection.

Child survival is also affected by birth order, although this is not evident in sub-Saharan Africa. In several countries in that region, the risk of mortality under age 5 is still as high as one in five, and the risk in the region as a whole is equally high for all children (Figure 9). But in other regions, first, second, and third children clearly benefit from lower mortality, while children beyond the sixth continue to bear substantially greater risk. The effect of the mother's age is similar: Children of older mothers (35 and older) do not seem to be at greater risk in sub-Saharan Africa because every child is at high risk, but elsewhere children of older mothers bear a 10-25 percent greater risk. Even in sub-Saharan Africa, however, children of mothers under 20 have a 20-30 percent higher risk of death than do children of older mothers.

Figure 9 - Under-Five Mortality (per thousand), by Birth Order

The mother's health also benefits from lower fertility. The clearest benefit is a reduced risk of maternal death. Death in childbirth is about 20 times as likely for each birth in developing countries as in industrial countries. Having many successive pregnancies puts a mother at even greater risk. At the total fertility rate for sub-Saharan Africa of 5.6 children, the average woman has a lifetime risk of dying in childbirth of about 1 in 18. If total fertility could be approximately halved, this lifetime risk would also be halved, to 1 in 35.¹³

¹³ Maternal mortality ratios are taken from Tsui et al. (1997, p. 115) and total fertility from World Bank (1997a), adjusted upward by 20 percent to allow for pregnancies terminated without a live birth. An important assumption is that the women whose fertility would fall to bring down average fertility bear the same underlying risk per birth as those whose fertility would not fall. If those women whose fertility would fall bear a lowerrisk per birth perhaps related to higher socioeconomic status, which could produce greater propensity to use contraception - the reduction in average life-time risk would be less. On the other hand, these women might bear higher risk per birth - perhaps because of a greater likelihood their pregnancies are unintended and could lead to potentially unsafe abortions - in which case the reduction in average lifetime risk would be greater.

The Built and Natural Environments

Although the effects of lower fertility on health may be visible fairly quickly, the effects on public investments may take longer to work themselves out. Pressures from high fertility can last for an extended period, as the housing situation in Thailand illustrates. In the early 1960s expenditures on housing were 90 percent of what was required to keep up with the growth in number of households (which grow proportionally more rapidly than the population). By around 1980, even though fertility had declined substantially, households were still increasing rapidly, and expenditures had fallen to 50-60 percent of what was needed to prevent a decline in previous standards. Merely to maintain housing growth comparable to the growth of households, Thailand would have had to put 40 percent of all investment into housing in the 1990-1995 period. With substantially lower fertility, this proportion will fall, by 2005-2010, to 31 percent of all investment, and by 2010-2015 to 25 percent. In 15 years the number of housing starts will have to be 18 percent more numerous to maintain housing quality. But if fertility had not fallen as much, the number of housing starts would have to be even greater. In 15 years in the Philippines (where fertility is now roughly twice as high as in Thailand), annual housing starts will have to be 53 percent more numerous (Mason, 1996).

Besides raising the need for housing, high fertility produces more mouths to be fed. The link from this to increased food production to the clearance of forests is probably the most carefully studied of the environmental threats from rapid population growth. Studies of Thailand's poorest and most populous region, the northeast, illustrate the problem. Given few job opportunities in the 1970s and 1980s and a population with little cash and no special skills, farming absorbed most of the labor. But with soil fertility low, forests had to be cleared to provide more land, and the fallow cycle became shorter and shorter. Econometric studies show that a 10-percent increase in population growth contributed to a 3.3-percent increase in deforestation (Panayotou, 1994, pp. 172-173). A broader metanalysis of quantitative studies by Palloni (1994) indicates that population growth, in association with other factors, does make a modest contribution to deforestation cross nationally.

Other aspects of the environment, from fish stocks to water supplies, may feel a similar pressure from rapid population growth. In each case, appropriate technology and institutions to control access to and use of common resources could limit environmental damage and preserve resources for the future. But lower fertility and slower population growth, it is argued, would also relieve some of the pressure on resources and allow time to develop and institute the necessary policies. Even where the contribution of population growth to an environmental problem is small - as it is, for instance, for air pollution from carbon dioxide emissions - reducing population growth may still be cost-effective, requiring proportionally less investment than various technological or other policy measures (Birdsall, 1994).¹⁴

¹⁴For broad overviews of environmental and political effects, see Population Action International (1996) and Mazur (1997).

Lower fertility therefore provides societies with opportunities, especially in the form of increased savings that could spur investment and economic growth, a "demographic bonus" that could be spent to improve education, and fewer high-risk births that could lead to healthier childhoods, if other health risks can be contained. Additional opportunities include reduced pressure on public expenditures and the grace period that lower fertility and slower population growth provide for dealing with pressures on the environment and for managing such typically limited resources as a society's water supplies. Seizing such opportunities could provide a political bonus to regimes that need to be increasingly concerned with the welfare of their populations and could eventually be part of the process that transforms a society into a stable and prosperous contributor to the international order. But none of this is automatic, even with substantial fertility decline. Each of the potential benefits of such a decline will only be realized with appropriate governmental policies - on investment, on education, on health, on environmental protection, and so on.

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These potential benefits, however substantial they could appear to government planners, may not be the most important argument for seeking lower fertility. More significant is the fact that millions of couples in developing countries actually want to have smaller families. Motivated not by macroeconomic considerations but by practical concerns about family finances, health and well-being, and the future of their offspring, millions around the world would prefer to have fewer children than they are actually having.

Figure 10 compares the number of children women wanted, on average, in the early 1990s with total fertility across 28 developing countries in the 1990-1995 period. These countries are arrayed from those with the highest to those with the lowest desired family size. Except where desired family size exceeds six children (a setting somewhat overrepresented in this figure because more than half the data are from sub-Saharan Africa), the actual number of children tends to exceed the number desired by about three-fourths of a child on average.¹⁵

¹⁵Looking at number wanted person by person, one can identify births that exceed each person's desired number. Such calculations indicate even more "unwanted" births than suggested by Figure 10 (Bankole and Westoff 1995:24-25).

Figure 10 - Number of Children Desired and Total Fertitlity in 28 Countries

NOTE: Where available, desired family size is for all women; otherwise, it is for women ever married (Bankole and Westoff, 1995).

These statistics refer to what women - mostly married women - want. But men tend to have fairly similar, only slightly higher, preferences, except in the highest-fertility settings. Again excepting countries where average desired family size exceeds six children, men's preferred family size is usually higher than women's by no more that 0.1 or 0.2 children (Ezeh et al., 1996, p. 29) and therefore is still most often below actual fertility.

Unmet Need

The gap between preferences and actual fertility springs from what demographers label the "unmet need for contraception." Through survey questions that identify women who would prefer to delay or terminate childbearing but who are not using contraception despite the risk of pregnancy,¹⁶ demographers estimate that unmet need affects 10 to 40 percent of married women of reproductive age in developing countries. Levels of unmet need (Table 1) are high in high-fertility countries, such as Malawi (36 percent), but are still substantial in relatively advanced regions, such as Latin America, where they range from 12 to 29 percent. For all developing countries, the total with unmet need is estimated at about 150 million women.¹⁷

¹⁶This excludes those assumed not to be at risk: (1) those protected by postpartum anovulation, the temporary infertility that follows a pregnancy, which can be extended by continued full breastfeeding; and (2) the infecund, identified by not having conceived in five years despite taking no preventive measures, by not having menstruated in six months, or by claiming they could not have a baby or were menopausal.

¹⁷According to unpublished tabulations of Demographic and Health Survey data by Shea Rutstein (1997, personal communication). Precise definitions and therefore estimates of unmet need do vary somewhat, but the total of the estimates in Table 1 - 75 million women with unmet need across only 44 developing countries - appears consistent with this.

Unmet need is essentially a conflict between what a woman wants and what she does about it: She wants lower fertility but fails to do what is needed to prevent pregnancy. The reasons couples want smaller families are numerous and generally well-founded, from the financial strain large numbers of children put on households to the strain of continual childbearing on a woman's health and energy. Preferences for small families inevitably increase as societies modernize: Financial pressures grow; the need to educate children becomes more apparent; and the desire for more creature comforts or at least for release from unremitting childbearing begins to seem possible as the media promote alternative lifestyles. At levels of fertility reported in some earlier national surveys (as in Kenya in the 1977-1978 period), women spent the equivalent of six continuous years of their lives pregnant and 23 years caring for children younger than six years old (World Bank, 1993a, p. 9). With the early childbearing typical in some countries, pregnancy can account for more than a quarter of female school dropouts, beginning as young as primary school.¹⁸ Controlling their fertility can give women options and a degree of freedom not previously available.

¹⁸ As in Cameroon, as reported by Eloundou-Enyegue (1997).

Table 1 Married Women of Reproductive Age with an Unmet Need for Contraception

Country		Survey Year	Percent	Number (1000s)
Africa
	Botswana	1988	27	27
	Burkina Faso	1992-1993	33	522
	Burundi	1987	25	201
	Cameroon	1991	22	347
	Ghana	1994	33	759
	Kenya	1993	36	1,101
	Liberia	1986	33	131
	Madagascar	1992	32	551
	Malawi	1992	36	498
	Mali	1987	23	435
	Namibia	1992	22	22
	Niger	1992	19	243
	Nigeria	1990	22	3,928
	Rwanda	1992	37	332
	Senegal	1992-1993	29	350
	Sudan	1989-1990	25	940
	Tanzania	1991-1992	27	1,065
	Uganda	1988-1989	27	707
	Zambia	1992	31	368
	Zimbabwe	1994	15	207
Asia
	Bangladesh	1994	18	3,852
	India	1992	20	31,005
	Indonesia	1991	14	4,427
	Nepal	1991	28	970
	Pakistan	1991-1992	32	5,738
	Philippines	1993	26	2,512
	Sri Lanka	1987	12	332
	Thailand	1987	11	999
Latin America and the Caribbean
	Bolivia	1994	24	235
	Brazil	1986	13	3,034
	Colombia	1990	12	545
	Dominican Rep.	1991	17	171
	Ecuador	1987	24	411
	El Salvador	1985	26	182
	Guatemala	1987	29	382
	Mexico	1987	24	3,133