Income improvements and fertility

Income improvements and fertility.

Consider, first, the total potential income of the couple if they were to have no children at all. Income may be wage labor or some other form of income, such as land rent. If it is the former, potential income includes all income earned by each spouse, under the scenario that they have no children to look after. This amount is represented by the height of the point A in Figure 9.1.

Now it should be clear that as the number of children begins to rise, the income left for “other goods” will begin to fall. It will fall for two reasons. First, there are the direct expenses of the children. Next, earned income falls as well, because one or both parents spend some time at home to look after the child. This trade-off traces out the “budget line” AB. With very large numbers of children, residual income available to the parents may drop to zero: this is the point B at which the budget line cuts the horizontal axis. Panel (a) of the figure incorporates this description.

The slope of the budget line (see the indicated angle in Figure 9.1) is a measure of the unit cost of having children. If income is earned, it will be the wage rate multiplied by hours foregone per child. In addition, there are the direct costs per child.

The exercise that we now conduct has to do with an increase in family income. To fix ideas, suppose first that the source of income increase is not wage income. For instance, the individual in question may be a landowner who receives all income from leasing land to tenants. Rents have gone up. In this case, the budget line will undergo a parallel shift, moving to the position CD [see panel (a)]. What effect does this have on fertility? Well, if children are “normal goods,” the income effect must raise the demand for children, so that fertility rates go up as a result of

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the income increase. Contrast this change with a change in wage income. In this case, the budget line will not only shift outward, it

will swivel as well. This is because the opportunity cost of children has gone up. In Figure 9.1(b), we show this by shifting the budget line out and rotating around the point B at the same time, so that we have the new budget line EB. Potential income has gone up, but at the same time the opportunity cost of children has gone up as well. This creates a substitution effect away from children as well as an income effect. The substitution effect lowers fertility; the income effect raises it. The net effect is ambiguous.

Despite the ambiguity, one thing is clear from Figure 9.1: fertility certainly does not rise by as much as in the case where the income increase can be traced to “nonearned” sources. The intuition is straightforward. Wage income imposes an opportunity cost of having an extra child, whereas rental income does not. Thus wage income increases have a stronger impact on fertility reductions than rental income. This illustrates the usefulness of the cost–benefit approach, at least up to a certain point.

We can easily extend this argument to the case of gender bias. Suppose that only women look after children. Then an increase in rental income has the same effect as an increase in male wages: both lead to a parallel shift of the budget line, as in the move from AB to CD. Male wages impose no opportunity cost on childbearing if men play no part in raising children. In contrast, the swiveling of the budget line is characteristic of an increase in female wages. The opportunity cost of having children will go up. It follows that a society with gender bias is more likely to exhibit a reduction in fertility when female wages go up, as opposed to the case in which male wages rise. This argument was examined in a paper by Galor and Weil [1996] and by many others (see also the following box).

Women’s Wages and Fertility Decline: A Study of Sweden

Over the last century or more, there has been an increase in the wages of women relative to men. This is certainly the case in currently developed countries. Along with this increase, we see a concurrent reduction of fertility. Is this clear evidence of a causal relationship between women’s wages and fertility? It may not be. It is conceivable, for instance, that a reduction in fertility occurred for some other reason, and this reduction was associated with larger investments by women in education, which raised their wages. In this hypothetical situation, fertility and female wages are correlated, but no evidence of causality is established. What we need is separate evidence, quite apart from actions that may have been taken by women themselves “on the supply side,” that female employment is more in demand. Then we can relate this piece of evidence to the fertility decline.

Schultz [1985] raised precisely this question and addressed it in an interesting way using Sweden as an example. In the second half of the nineteenth century, the world grain market went through a declining phase of major proportions. The exports of Swedish grain collapsed. Faced with this decline in grain demand, there was a substantial reallocation of resources in agriculture. Animal husbandry was the benefactor. Swedish exports of butter soared.

Now, dairying and the processing of milk employed a larger fraction of women than did grain farming. As a result of this reallocation, the demand for female labor went up significantly and so did the wages paid to women.

The usefulness of focusing on the butter boom is that it effectively captures a pure demand effect on female wages, rather than an effect that could have been created by supply decisions. Did fertility drop in response to the butter boom?

It did. Schultz shows that in regions where the price of butter relative to rye (the basic food grain in Sweden) is high, the ratio of female to male wages was high as well and fertility rates were lower. Indeed, following up on the link between butter prices and female wages, Schultz estimated that about a quarter of the decline in the Swedish total fertility rate from 1860 to 1910 can be explained by the rise in relative female wages. The conclusion is that “the appreciating value of women’s time relative to men’s played an important role in the Swedish fertility transition.”

9.3.4. Is fertility too high? So far we have tried to provide an account of why fertility rates may be high in the face of falling death rates,

but “high” does not necessarily mean “suboptimal”: if a family chooses to have a large number of children, then why should social considerations dictate anything different? There are three answers to this question.5

Information and uncertainty The first answer relies on the incompleteness of information, which is an issue that we have already discussed. People simply may not internalize the general observation that death rates have undergone a decline, as in the example of the Rampur policeman Umed Singh (see box). In such a case, the number of children that couples have may not be socially optimal. Faced with fresh information regarding the environment that influences their fertility choices, the couple would typically revise their fertility decisions.

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The second answer relies on the distinction between decisions that are made ex ante and their ex post consequences. Consider the family that wants one child, but has five, in the hope of increasing the chances of old- age support. As we have already seen, such decisions are based both on the probability of a child dying and on the degree of aversion to risk of the family. Thus it is not unlikely (and this will be true especially for poor families that are highly risk-averse) that, in fact, a large percentage of the children do survive ex post. Such families will have too many children and they will suffer because these children will have to be looked after and fed. The evaluation of optimality becomes problematic in this case. If a family with a large number of children is asked if they are happy with this situation, they may reply that they are not, but if asked whether they would have made exactly those fertility choices all over again (in the face of the uncertainty that shrouded survival), they may well say that they would have. There is no contradiction between these seemingly contradictory answers.6

Externalities The third and most important answer is based on the existence of externalities. That is, the fertility decisions made by an individual or a couple may have implications for other members of a family or indeed for other families. To the extent that such effects are not internalized by the decision maker(s), fertility choices that are privately optimal may not be socially optimal.

As the following cases suggest, fertility-related externalities are typically negative (though this need not always be the case). Thus private fertility choices generally lead to overly large numbers of children.

Let us begin by studying some effects across families. These externalities are particularly pervasive in situations where infrastructure is provided by the government at little or no cost to users. In such cases, it is not possible for individual families to value these resources at their true social cost, because that is not the cost they (or their children) pay. This is not to say that such services should always be provided at market prices (often they represent the only way to redistribute income in an unequal society), but they do enlarge the number of situations in which an externality may be present.

Consider, for instance, the provision of free public education in an urban area. If a benevolent social planner could dictate the number of children that all families should have in that area, she would take the marginal social cost of providing educational resources into account. However, if education is provided free of charge, the private cost to the family typically is lower than the social cost, which therefore will not be properly internalized. It follows that the number of children that people choose to have will exceed the social optimum.

The same is true of other publicly provided services that are not valued at their true marginal cost, such as subsidized housing or health services. As I have already mentioned, these may often be the only feasible way to target the poor in a society where direct information on economic characteristics is hard to get hold of. These services have the same effect as the provision of education: they reduce private marginal costs below the social marginal costs and push fertility beyond the social optimum.

A similar set of observations applies to resources that are not properly priced, such as the environment. Such resources can be depleted even if they are renewable: they include fisheries, groundwater, forests, soil quality, and of course the ozone layer. The main characteristic of such resources is that they are generally underpriced, so that financial incentives bias their use in the direction of overexploitation. To the extent that such underpricing reduces the cost of child rearing, fertility is biased upward.

All of these effects can be summarized in one very general framework. In Figure 9.2, we show the costs and benefits of having children (say, for a single family). For simplicity, we take the cost curve to be a straight line (so that each new child costs the same additional amount), even though there are diminishing returns to having more children. This means that the benefit function has the familiar concave shape.

Focus now on the costs. The thick straight line shows the private costs of an additional child and the thinner line shows the social costs of an additional child. The preceding discussion indicated that in many situations, the private costs may be less than the social costs. Diagrammatically, this is captured by the fact that the “social cost” line is steeper than the “private cost” line. The socially optimum number of children is found by maximizing the vertical distance between the benefit line and the social cost line. This point is found by setting marginal benefit equal to marginal social cost, which occurs at the point A and yields a number of children n*. In contrast, the privately optimal number of children is found by maximizing the vertical distance between the benefit line and the private cost line. This occurs at the point B with associated number n**. Note that n** > n*.


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