Social Norms and a New Fertility Decline

Social Norms and a New Fertility Decline10

According to the 1994 revision of the official United Nations world population estimates and projections, a fertility transition is underway in several sub-Saharan African and South-Central Asian countries. Fertility levels have traditionally been very high in these countries.

Total fertility rates have declined in Madagascar (from 6.6 in 1980–85 to 6.1 in 1994), Rwanda (from 8.1 to 6.5), United Republic of Tanzania (from 6.7 to 5.9), Namibia (from 5.8 to 5.3), South Africa (from 4.8 to 4.1), and Mauritania (from 6.1 to 5.4). Fertility declines are also evident in Zambia, Zimbabwe, and Gambia. If we add to this list Kenya and Botswana, where evidence of a fertility decline already exists, we see the beginnings of an overall fertility decline in sub-Saharan Africa.

South-Central Asia shows continued fertility decline: fertility has fallen in Iran (6.8 to 5.0) and continues its downward course in Bangladesh (6.2 to 4.4), India (from 4.5 to 3.7), and Nepal (from 6.3 to 5.4).

As discussed in the text, a widespread change in social norms may be playing a central role. Fertility declines everywhere appear to be accompanied by a significant increase in contraceptive use. We must be careful here to not infer any sort of causal link, but the increased recourse to contraception is indicative of an accompanying social transformation. Huge jumps in contraceptive use have been seen in Kenya (up from 7% of couples in 1977–78 to 33% in 1993), Rwanda (from 10% in 1983 to 21% in 1992), Bangladesh (from 19% in 1981 to 40% in 1991), and Iran (from 36% in 1977 to 65% in 1992).




Norms regarding the age of marriage must play a role as well. In Tanzania, for example, the incidence of contraception is low (10% in 1991–92), but the average age of a woman at marriage has gone up from 19 years in 1978 to 21 years in 1988. This is also the case in countries where contraception has significantly increased.

To be sure, fertility declines are not universal in this region and do remain high in the large countries of Nigeria, Zaire, Ethiopia, and Pakistan, but going by the broader picture, change is on the way.

9.4. From population growth to economic development Just as economic development has implications for the pace of population growth, so the latter has implications for the rate of economic development. In large part, this relationship is thought to be negative. A large population means that there is less to go around per person, so that per capita income is depressed. However, this argument is somewhat more subtle than might appear at first glance. More people not only consume more, they produce more as well. The net effect must depend on whether the gain in production is outweighed by the increase in consumption. In the next two subsections, we clarify how the negative argument works and then follow this argument with some qualifications that suggest possible gains from population growth.

9.4.1. Some negative effects

The Malthusian view Beginning with Thomas Malthus, a standard view on population growth is that its effects on per capita welfare are negative. Malthus was particularly gloomy on this score. According to him, whenever wages rise above subsistence, they are eaten away in an orgy of procreation: people marry earlier and have more children, which depresses the wage to its biological minimum. Thus in the long run, the endogeneity of population keeps per capita income at some stagnant subsistence level.

This is not a completely bizarre view of human progress. It probably fit the fourteenth to the eighteenth centuries pretty well. Blips in productivity, such as those in agriculture, increased the carrying capacity of the planet, but population did rise to fill the gap. It is difficult to evaluate this scenario from a normative standpoint. Over time, it was possible to sustain human life on a larger scale, even though on a per capita scale, the Malthusian view predicted unchanged minimum subsistence. Evaluation of this prediction depends on how we compare the prospect of not being born to the prospect of living at minimum subsistence. As I already stated, we sidestep this issue to some extent and concentrate on per capita welfare alone. By this yardstick, the Malthusian view is neutral in its long-run view of population growth.

A central ingredient of the Malthusian argument deserves critical scrutiny. Do human beings react to economic progress by spontaneously having more children? Modern experience suggests just the opposite. Individuals do understand that having children is costly, and it is perhaps true that the costs increase with economic development, while the (economic) benefits decline. For instance, we argued in previous sections that economic development is associated with greater provision of organized old-age social security. We have seen that such institutions probably are more effective than any other in bringing down rates of fertility in developing countries. People have children for a reason, not just because it is feasible to have them.

Likewise, economic progress may shift societies from an extended family system to a nuclear family system. As labor force participation increases, it becomes progressively more unlikely that individuals in an extended family all find jobs in the same locality. At the same time, the insurance motives that underlie the joint family setup probably decline. With nuclear families, the costs of child rearing are internalized to a greater degree, which brings down fertility.

There are other aspects that we have discussed as well, such as an increase in female wages or reductions in infant mortality with development. All these have a moderating impact on fertility. Thus it is absurd to entertain the notion that people react to any surplus in their incomes by automatically having more children. It is true that the Malthusian theory doesn’t do a bad job for fourteenth century Europe, but in poor societies it is very difficult to separate the various determinants of fertility: fertility may have been high enough (for other reasons) relative to per capita income so that the Malthusian checks and balances applied better.

So as a first pass, it may not be a bad idea to think of population growth as an exogenous variable that is driven by features other than per capita income. At any rate, in societies that are not overwhelmingly poor, it is probably the case that if population growth is endogenous, it is a decreasing function of per capita income,11 and not increasing as Malthus suggested. Data such as those presented in Table 9.1 certainly support this hypothesis better




than the alternative.

Using growth models The growth models of Chapter 3 represent a good starting point in this respect. Recall the ingredients of the standard growth model: people make consumption and savings decisions. Savings are translated into investment, and the capital stock of the economy grows over time. Meanwhile, the population of the economy is growing too.

We know already how to figure out the net effect of all this. The rate of savings determines, via investment, the growth rate of the capital stock. The latter determines, via the capital-output ratio, the growth rate of national income. Does all this growth translate into an increase per person? Not necessarily. Population is growing too, and this increase surely eats away (so far as per capita growth is concerned) at some of the increase in national output. In Chapter 3, we did the simple algebra that puts these features together. Our first pass at this brought us to equation (3.6), which is reproduced here:

where s is the rate of savings, n is the rate o o ulation growth, is the rate o de reciation o the ca ital stoc , and g* is the rate of growth of per capita income. This is the Harrod–Domar model, and the implications are crystal clear. According to this model, population growth has an unambiguously negative effect on the rate of growth. To see this, simply stare at (9.2) and note that if all parameters remain constant while the rate of population growth n increases, the per capita growth rate g* must fall.

Nonetheless, we can criticize this prediction. The Harrod-Domar model, on which (9.2) is based, treats the capital–output ratio as exogenous, and therefore makes no allowance for the fact that an increased population raises output. After all, if the capital-output ratio is assumed to be constant, this is tantamount to assuming that an increased population has no effect on output at all. Would it not be the case that a higher rate of population growth would bring down the amount of capital needed to produce each unit of output, now that there is more labor as an input in production?

We have walked this road before; it leads us to the Solow model. In Solow’s world, a production function relates capital and labor to the production of output. In addition, there is technical change at some constant rate. We obtained the remarkable answer in that model that once the change in the capital-output ratio is taken into account, the steady-state rate of growth is independent of the rate of savings and the rate of population growth (see our analysis in Chapter 3). All that matters for long-run growth is the rate of technological progress!

This is odd, because the Solow model now seems to tilt us to the other extreme. It suggests that population growth has no effect at all! However, this is not true: what we have shown so far is that population growth has no effect on the long-run rate of per capita income growth. There is a level effect, however. We briefly recall the discussion from Chapter 3.

Recall why population growth rates have no growth effect. In the Harrod-Domar model, there is an implicit assumption that labor and capital are not substitutable in production. Thus added population growth exerts a drag on per capita growth, while contributing nothing of substance via the production process. In the Solow model, on the other hand, population growth, while continuing to have the first effect, contributes to productive potential as the extra labor force is absorbed into productive activity through a change in the capital–labor ratio. Indeed, implicit in the Solow model is the assumption that capital and labor can be substituted for each other indefinitely, although the process of substitution may become more and more costly.12 Because of this, population growth has no ultimate effect on the rate of growth in the Solow model.

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