Poor Economics
Page 14
To find out whether it was the case, Donna Gibbons, Mark Pitt, and Mark Rosenzweig painstakingly matched the data on the number of family-planning clinics available at three points in time (1976, 1980, and 1986) in each of several thousand Indonesian subdistricts to village-level survey data on fertility.21 Unsurprisingly, they found that regions that had more clinics had lower fertility. However, they also found that the decline in fertility over time was unrelated to the increase in the number of clinics. They concluded that family-planning facilities were provided where people wanted them, but that they had no direct effect on fertility. Demand wallahs, 1; supply wallahs, 0.
The Matlab program has long been the poster child for the supply wallahs. Here at least, they argue, there is incontrovertible evidence that the availability of contraceptives makes a difference. As we saw, women age thirty to fifty-five in 1996 had on average 1.2 fewer children in treatment areas than those in control areas. But the program in Matlab was doing much more than just making contraceptives available. One of its key components was the biweekly visit by a female health worker to households where women were in purdah and therefore limited in their mobility, bringing the discussion of contraception to places where it used to be taboo. (This also made the program expensive—Lant Pritchett, then a World Bank economist, estimated that the Matlab program cost thirty-five times more per fertile woman and per year than the typical family-planning program in Asia.)22 Thus, it is plausible that the program directly altered the households’ desired number of children, rather than just giving them some tools they could use to control their fertility. Moreover, since about 1991, fertility has stopped falling in the program areas, and the difference between program areas and other control areas has started to narrow. In 1998, the last year for which we have data, the total fertility rate was 3.0 in the program areas, 3.6 in the control areas, and 3.3 in the rest of Bangladesh.23 The Matlab program may have simply accelerated a trend toward fertility reduction that was happening in the rest of the country. So at best, this one seems to be a draw.
The study of the Colombian Profamilia program also concludes that the program had very little effect on overall fertility. Access to Profamilia led women to have only about 5 percent fewer children in their lifetimes, which is less than one-tenth of the total fertility decline since the 1960s. Demand wallahs, 2; supply wallahs, 0.
Thus, the data seem to squarely hand victory to the demand wallahs: Contraceptive access may make people happy by giving them a much more convenient way to control their fertility than the available alternative. But it appears to do, in itself, little to reduce fertility.
Sex, School Uniforms, and Sugar Daddies
What better access to contraceptives can do, however, is help teenagers postpone pregnancies. The Profamilia program did that in Colombia and helped women get better jobs down the line. Unfortunately, in many countries, teenagers are barred from accessing the family-planning services unless their parents give official consent. Teenagers may be the most likely to have an unmet need for contraception, mainly because many countries do not recognize the legitimacy of their sexual desires or assume that they have so little control that they would not be able to use contraception properly. The result is that teenage pregnancy rates are extremely high in many developing countries, particularly in sub-Saharan Africa and in Latin America. According to WHO, the rate of teen pregnancy is above 10 percent in Côte d’Ivoire, Congo, and Zambia; and Mexico, Panama, Bolivia, and Guatemala have rates between 8.2 and 9.2 births per 100 adolescent women (in the United States, which has one of the highest teen pregnancy rates in the developed world, there are 4.5 births per 100 adolescent women).24 Further, the little that seems to be done about this issue or the related issue of the spread of sexually transmitted diseases (including HIV/AIDs) tends to completely miss the mark.
Esther found a clear example of the consequences of this kind of misguided effort in Kenya. With Pascaline Dupas and Michael Kremer, she followed schoolgirls—initially ages twelve to fourteen, who had never been pregnant.25 One, three, and five years down the road, average pregnancy rates among them were 5 percent, 14 percent, and 30 percent, respectively. Early pregnancies are not only undesirable in and of themselves, but they are also a marker for risky sex, which in Kenya means a higher risk of contracting HIV/AIDS. The official strategy to address this problem in Kenya, the result of a delicate balancing act negotiated among civic groups, various churches, international organizations, and the government, mostly emphasizes that sexual abstinence is the only foolproof solution. The standard message spells out a clear hierarchy of strategies: Abstain, Be faithful, use a Condom . . . or you Die (or in other words, ABCD). In schools, children are taught to avoid sex until marriage, and condoms are not discussed. For many years, this trend was encouraged by the U.S. government, which focused its AIDS prevention money on abstinence-only programs.26
This strategy presumes that adolescents are not responsible or smart enough to weigh the costs and benefits of sexual activity and condom use. If this were indeed the case, scaring them away from sex altogether (or at least from sex outside marriage) would be the only way to protect them. But several simultaneous experiments that Esther, Pascaline Dupas, and Michael Kremer conducted in Kenya suggest that, quite to the contrary, adolescents make carefully calculated, if not fully informed, choices about whom to have sex with and under what conditions.
In the first study, the ABCD strategy was evaluated by arranging for teachers in 170 randomly chosen schools to be trained in teaching the ABCD curriculum. Not surprisingly, this training increased the time spent on AIDS education in schools, but there were no changes in reported sexual behavior or even in knowledge about AIDS. In addition, when measured one, three, and five years after the intervention, pregnancy rates among adolescents were the same in schools where teachers were trained and where they were not, suggesting no change in the extent of risky sex.
The effects of the two other strategies that were tried in the same schools could not be more different. The second strategy just involved telling the girls something they did not know: the fact that older men are more likely to be infected with HIV than younger ones. A striking feature of HIV is that women from the ages of fifteen to nineteen are five times more likely to be infected than young men in the same cohort. This seems to be because young women have sex with older men, who have comparably high infection rates. The “sugar daddies” program simply informed students about what kind of people are more likely to be infected. Its effect was to sharply cut down sex with older men (the “sugar daddies”) but, also interestingly, to promote protected sex with boys their own age. After a year, the pregnancy rates were 5.5 percent in schools that had not received the program and 3.7 percent in schools that had received it. This reduction was mainly attributable to a reduction by two-thirds in pregnancies where an older male partner was involved.27
The third program just made it easier for girls to remain in school by paying for a school uniform. Teenage pregnancy rates in the schools where uniforms were offered fell from 14 percent to 11 percent after a year. To put it slightly differently, for every three girls who stayed in school because of the free uniform, two delayed their first pregnancy. Intriguingly, this effect was entirely concentrated in the schools where the teachers had not been trained in the new sex-education curriculum. In schools that had both the HIV/AIDS and the uniforms programs, girls were no less likely to become pregnant than those in the schools that had nothing. The HIV/AIDS education curriculum, instead of reducing sexual activity among adolescents, actually undid the positive effect of the uniform distribution.
Putting these different results together, a coherent story starts to emerge. Girls in Kenya know perfectly well that unprotected sex leads to pregnancy. But if they think that the prospective father will feel obliged to take care of them once they give birth to his child, getting pregnant may not be such a bad thing after all. In fact, for the girls who cannot afford a school uniform and therefore cannot stay in s
chool, having a child and starting a family of her own may be a relatively attractive option, compared to just staying at home and becoming the general “Hey, you” for the whole family, the usual outcome for unmarried out-of-school teenage girls. This makes older men more attractive partners than young boys who cannot yet afford to get married (at least when the girls don’t know that they are more likely to have HIV). Uniforms reduce fertility by giving girls the ability to stay in school, and thus a reason not to be pregnant. But the sex-education program, because it discourages extramarital sex and promotes marriage, focuses the girls on finding a husband (who more or less has to be a sugar daddy), undoing the effect of the uniforms.
One thing is relatively clear: For the most part, poor people, even adolescent girls, make conscious choices about their own fertility and sexuality and find ways—though perhaps not pleasant ways—to control it. If young women get pregnant even though it is extremely costly for them, it must reflect someone’s active decision.
Whose Choice?
One issue that immediately arises when we think about fertility choice, however, is whose choice? Fertility decisions are made by a couple, but women end up paying most of the physical costs of bearing children. Not surprisingly, their preferences for fertility end up being quite different from those of men. In surveys on desired family size in which men and women are separately interviewed, men usually report a larger ideal family size and consistently a lower demand for contraception than their wives. Given the potential for disagreement, how much say a woman has within the household will clearly matter. It is plausible, for example, that a woman who is much younger than her husband or much less educated (both consequences of early marriage) will find it harder to stand up to her husband. But it also depends on whether she can find a job, her freedom to divorce, and her survival options in the case of divorce. These contingencies, in turn, depend on the legal, social, political, and economic environment she and her husband inhabit, which can be affected by public policy. In Peru, for example, when former squatters were handed out property rights, fertility declined in households that got a title (compared to those that got nothing), but only if the woman’s name was included on the title along with that of the man.28 One likely explanation is that with her name on a property title, the woman acquired more bargaining power in the family and was therefore able to weigh more heavily in the decision on family size.
The conflict between husbands and wives also implies that whereas the availability of contraceptives per se may not do very much to reduce fertility, small changes in the way in which they are made available can potentially have larger effects. Nava Ashraf and Erica Field provided 836 married women in Lusaka, Zambia, with a voucher guaranteeing free and immediate access to a range of modern contraceptives through a private appointment with a family-planning nurse. Some women received the voucher in private. Some received the voucher in the presence of their husbands. Ashraf and Field found that this made a huge difference: Compared to cases where husbands were involved, women who were seen alone were 23 percent more likely to visit a family-planning nurse, 38 percent more likely to ask for a relatively concealable form of contraception (injectable contraceptives or contraceptive implants), and 57 percent less likely to report an unwanted birth nine to fourteen months later.29 One of the reasons the Matlab program changed fertility choices more than other family-planning programs is probably also that by visiting the women in their houses, presumably when the husbands were away, the female health worker may have enabled some of them to adopt family planning without his knowledge. In contrast, women whose mobility was restricted by the custom of purdah (which forbids a woman to leave the house without her husband) would have had to be accompanied by their husbands to go receive the services at a central location, and this might have changed their decision.
A possible explanation for the relatively large effects of the Matlab program, especially early on, is that it accelerated social change. One reason the fertility transition takes time is that people other than the wife and husband have a say about it. Fertility is in part a social and a religious norm, and deviations from it do get punished (by ostracism, ridicule, or religious sanctions). Therefore, it matters what the community deems to be appropriate behavior. In the treatment areas in Matlab, this change was faster than elsewhere—the community health workers, who tended to be relatively well-educated and assertive women, were both the embodiment of the new norm and the carrier of news about the shifting norms in the rest of the world.
Kaivan Munshi studied the role of social norms in the contraception decisions in Matlab. He cites a young woman who described how her peer group discussed “how many children we would have, what method would be suitable for us . . . whether we should adopt family planning or not, all these topics. . . . We used to know from people that they used (contraceptives). If a couple takes any such method, the news somehow spreads.”30
Munshi found that in Matlab villages where there was a community health worker, women were more likely to adopt contraceptives if village members of their own religious group had had higher contraceptive use over the previous six months. Even though both Hindus and Muslims within the village had access to the same health worker and had exactly the same access to contraceptives, Hindus adopted contraceptive use when other Hindus were doing so and Muslims adopted contraceptives when other Muslims did. The contraceptive adoption by Hindus had no effect on the adoption by their Muslim neighbors, and vice versa. This pattern, Munshi concludes, must mean that the women were progressively learning about what was acceptable behavior within their communities.
Negotiating shifts in the social norm within traditional societies can be a very complex business. It is not easy, for example, to ask certain questions (Is contraception against religion? Will it make me permanently barren? Where can I find it?) because the act of asking itself reveals your inclinations. As a result, people often pick up things from the most unlikely sources. In Brazil, a Catholic country, the state has carefully stayed away from encouraging family planning. However, television is very popular, in particular the telenovelas (soap operas) that air on prime time on one of the main channels, Rede Globo. From the 1970s through the 1990s, access to the Rede Globo channel expanded dramatically, and with it the viewership of the telenovelas. At the telenovelas’ peak popularity in the 1980s, the characters in the soaps tended to be very different from the average Brazilian in terms of both class and social attitudes: Whereas the average Brazilian woman had almost six children in 1970, in the soap operas most female characters under the age of fifty had none, and the rest had one. Right after soaps became available in an area, the number of births would drop sharply; moreover, women who had children in those areas named their children after the main characters in the soap.31 The novelas ended up projecting a very different vision of the good life than the one that Brazilians were used to, with historic consequences. This was not entirely accidental—in Brazil’s straitlaced society, the soap opera ended up being the outlet of choice for many creative and progressive artists.
At the risk of sounding, perhaps one time too many, like the “two-handed economists” that irritated Harry Truman, the answer to the question “Do the poor control their family decisions?” thus seems to proceed in two steps. At the most obvious level, they do: Their fertility decisions are the product of a choice, and even the lack of availability of contraception does not seem to be a big constraint. At the same time, what leads them to make these choices may be in part factors that are outside their immediate control: Women, in particular, may be pressured by their husbands, their mothers-in-law, or social norms to bear more children than they would like. This suggests a very different set of policies than those adopted by Sanjay Gandhi, or by the well-intentioned international organizations today: Making contraception available will not be sufficient. Affecting social norms may be more difficult, although the example of TV in Brazil shows it can be done. But the social norms may also reflect economic interests in a society.
To what extent do the poor want many children simply because it is a sound economic investment?
CHILDREN AS FINANCIAL INSTRUMENTS
For many parents, children are their economic futures: an insurance policy, a savings product, and some lottery tickets, all rolled into a convenient pint-size package.
Pak Sudarno, the scrap collector from the Cica Das slum in Indonesia, who was sending his youngest child to secondary school because that seemed to him to be a worthwhile gamble, had nine children and a large number of grandchildren. When we asked him whether he was happy that he had had so many children, he said “absolutely.” He explained that with nine children, he could be sure that at least a couple of them would turn out fine and take care of him when he was old. Clearly, having more children also increases the risk that something will go wrong with at least one of them. In fact, one of Pak Sudarno’s nine children suffered from severe depression and had disappeared three years before. He was sad about that, but at least he had the other eight to console him.
Many parents in rich countries don’t need to think in quite these terms because they have other ways to deal with their waning years—there is Social Security, there are mutual funds and retirement plans, and there is health insurance, public or private. We will discuss at some length why many of these options are not really available to someone like Pak Sudarno in the coming chapters. For the time being, we will just observe that for most of the world’s poor, the idea that children (and family beyond children—siblings, cousins, and so forth) will take care of parents in old age and during times of need is the most natural thing. In China, for example, more than half the elderly lived with their children in 2008, and that fraction increases to 70 percent for those who had seven or eight children (this was before family planning, when having many children was actually politically favored).32 Elderly parents also received regular financial help from their children, particularly boys.