plsnning agencies in population projecti ns in industrial countries will be reviewed. Approaches used in developing countries, when such project.ons are made, tend to be similar.

A survey of approaches used by the statistical offices of the 12 member states of the European Community, which have some of the most complete and detailed vital statistics available, shows few advantages over the approaches of the U.N. or the World Bank (Eurostat 1988). Generallv, the period TFR is used as a measure to express future fertilitv rates. In most cases, fertility is assumed either to remain constant at the current level or to increase somewhat for the next decade or so and to remain constant thereafter. The Federal Republic of Germany and Luxembourg make different assumptions for fertility trends of two subgroups. citizens and foreigners. In some Eastern European countries, larger increases in fertility have been projected, reflecting a belief that pro-natalist population policies will be effective (Isupov 1981), despite the lack of confirmatory evidence (Monnier 1989). Most of the statistical offices prepare several, or even mnany, different projection variants.

Some of the most detailed projections are made by the U.S. Bureau of the Census. No fewer than 27 projection variants till 2080 are provided, representing all possible combinations of three different assumptions each for fertility, mortality, and migration, assumptions specific to Whites and Blacks separately (U.S. Bureau of the Census 1989). The fertility assumptions are cc npler.. Trends in agespecific fertility rates are projected, from which other fertility measures are derived. The middle set of fertility assumptions includes no changes in age-specific fertility rates, which means that at first TFR **will** actually increase somewhat, then drop slightly below its current level. High and low assumptions are based partly on birth expectations data from surveys, and are gradually phased in by birth cohort, not taking full effect until about 2015, after whicb they remain constant. The process appears more careful and elaborate than that of other dtatistical offices but does require considerably more data.

Proximate deterninants of fertility approach. Changc in aggregate fertility measures are caused by changes in individual attributes and behavior, namely fecundity, coia-I frequency, postpartum infecundability, contraceptive practice, and abortion. The effects of these proximate dctterminants can be wodeled following a strategy proposed by Bongaarts (1978, 1982), in which the attributes or *,ehrviors are expressed as indices of the prevalence of pathological sterility, the proportion married, the duration of breastfeeding and postpartum abstinence, contraceptive prevalence, and the prevalence of abortion. The model shows the contribution that each proximate determinant makes toward reducing actual fertility below the biological maximum, and is useful especially for explaining current levels and differentials and past trends in fertility (Freedman 1987). Because fertility can change only when one or more of the proximnate determinants changes, extrapolations for levels of these determinants could provide projections of fertility (Chidambaram 1984).

However, extrapolated trends in proximate determinants are as uncertain as, if not more uncertain h'n, directly extrapolated fertility trends. The most important factor in the fertility transition has been the use of contraception, but predicting the start of widespread use appears very difficult. Breastfeeding has been declining in many developing countries, but the fertility-increasing effect of this trend may be offset by declining sterility. Another problem is that the method is not very robust with regard to the initial estimate of total fecundity; consequently, the estimates of actual total fartility in the presence of proximate determinants are likely to be uncertain. Although models for incorporating proximate determinants into projections exist (Chidambaram 1984), we are not aware of any national projection that has made explicit use of this approach.

Socioeconomic determinants approach. Macroeconomic models with endogenous demographic variables might be used for fertility projection. Such economic-demographic models have been used most often for regional or small-area projections in the U.S. (National Academy of Sciences 1980; Murdock et al. 1984). However, in most econometric models, demographic variables receive limited attention because they are not the primary aim of the forecasts, and consequently are not modeled with much care (Pittinger 1977). Isserman (1986) discussed a model in which fertility for states in the 4