Taiwan has completed the demographic transition from high birth rates and death rates to low birth rates and death rates during the past four decades. The country now is at a turning point in its population policy, and its central concern is beginning to shift from fertility and family planning to aging issues.
Presently, with only minimal social security system, health care, and counseling for the old, the younger generation has to provide for the bulk of caretaking and financial support for their parents. Based on intergenerational population projection, this paper finds that financial burden to support the old would increase rapidly for their offspring. By 2030, it would be a prevailing phenomenon that each retired parent would be supported by no more than one employed offspring, as compared to the current 2 to 3 employed children. If fertility continues to decline, the financial burden to the offspring would be much worse than what we project here.
However, attempts to devise substitutes to replace the family as the basic social and economic institution for supporting the old may not be workable in Taiwan. Policy study on financial arrangements to encourage retired parents to live with their offspring should be ranked as top priorities. In the meantime, economic policy to facilitate individual savings for retirement needs and pension plans should be encouraged.

Given a distinction of endogenous and exogenous population cycles, this paper searches the ways of characterizing the ‘endogenous’ cycles with the dynamics of changing age composition. It is argued that while the size of parental cohort is related to the size of offspring cohort by the renewal process, fluctuations in size are correspondingly transmitted and averaged time after time. It is shown that as the population transition in Taiwan is approaching the final stage of completion, population cycles appear to becoming the principal component of the population change. Though the cycles tend to converge in the long-run, the compression in age pattern of maternity has nevertheless effected a trend to the contrary. A decomposition of the crude birth rate is introduced to capture the cycle component of population renewal.

In Taiwan the total fertility rate decreased from 2.83 per woman in 1975 to 2.05 in 1984. The decline appeared accelerated during the recent years. Promotion of family planning programs has been implemented since 1964. IUD, oral pill, condom and sterilization are the methods provided by the program. Induced abortion has only been legalized based on specified grounds in July 1984. To establish the base line data and to evaluate the impacts of induced abortion of fertility before and after promulgation of the Law, an induced abortion prevalence survey was conducted by the Taiwan Provincial Institute of Family Planning in 1985 and sponsored by the Department of Health, the Executive Yuan. 10,516 samples of married women age 15-49 were covered in the survey. The sizable sample is significant to represent Taiwan area. Bongaarts’ model of proximate determinants of fertility is applied on the survey data to analyze the relationships among total fertility rate, total fecundity, and the indices of the proximate determinants on non-marriage, contraception, induced abortion, and lactation.
Using the Bongaarts’ model, the estimated total fertility rate is 1.96 which is slightly lower than that of 2.03 of the observed value and the total fecundity of 15.3 which is estimated by Bongaarts’ & Potter’s. The formulated proximate determinants of total fertility rate, total fecundity, and indices of proximate determinants of non-marriage, contraception, induced abortion, and lactation are shown as follows: TFR(total fertility rate)＝TF(total fecundity)×Cm(index of non-marriage)×Cc(index of contraception)×Ca(index of induced abortion)×Ci(index of lactational infecundability) 1.96＝15.3×0.43×0.38×0.80×0.98
By the logarithm method to portion the difference between total fecundity and total fertility rate among the four proximate determinants, the index of contraception (0.38) appears to have the greatest (47%) effect on the decline of TFR; followed by proportion of married which counted for 41%. As to the other two indices, induced abortion and lactational infecundability had slight effect, of 11% and 1% on the decline of TFR, respectively.
As regards to the different urbanization areas, the estimated value of TFR of large cities is 2.01 per woman, 1.96 for urban township, and 2.07 for rural areas. Compared with the observed value of 1.77, 2.02, and 2.31, the differences are small. The effect of four indices among the different urbanization areas, contraception has also the greatest effect on fertility decline. The effect of 45% for large cities, 46% for urbantownship, 50% for rural areas. The reason for higher effect in the rural areas than the large cities, is due to the fact that the woman in these areas use more effective method than the woman in other areas.
As regards to the effects of the proportion of married on the fertility of three different urbanization areas, they are 45%, 40%, and 40%, respectively. As of induced abortion, the effect is 13% in urban township and 11% in large cities. This fact may be due to underreporting in large cities. Other studies indicated that residents in large cities have more induced abortions. Lactation infecundability had no effect on decline of fertility in large cities but it had a very small impact of 1% in urban township and rural areas.

This paper deals with the problems of measuring and explaining local mortality variation, based on a case study of the Hamilton region in the Province of Ontario, Canada. Due to lack of detailed official data, the local mortality pattern is established after we have spent much time in recording information directly from individual death registrations and in matching the number of deaths by age and sex with the relevant at-risk population for each of the 96 census tracts in the Hamilton region. To explain local mortality variation by socioeconomic variables, we use the logit model and the maximum quasi-likelihood estimation method.
We find that local mortality variation is substantial in our study area; that median family income can explain nearly half of the mortality variation among the census tracts; and that other socioeconomic variables (e.g. widowhood and divorcehood), which appear to be significant variables of mortality variation in bivariate and non-spatial analyses, turn out to be insignificant in our multivariate analysis using the logit model.
Our results are by no means definitive. To help promote further research on local mortality variation, we conclude our paper by providing what we hope to be helpful and practical suggestions.

This paper presents new estimates of infant mortality levels, patterns, and differentials from Papua New Guinea through the application of direct and indirect techniques. The estimates are derived for data collected between November, 1979 and March, 1980 on fertility, mortality (infant and child), and contraception. The results indicate that infant mortality has declined in all parts of the country in the past 15 years. The results also reveal a slightly lower mortality for female infants than male infants. Furthermore, we observed the existence of moderate rural-urban infant mortality differential and substantial regional differences in the infant mortality levels.

This study examined mortality differentials by marital status in 11 low-mortality countries. The results show that, in general, unmarried populations have a higher mortality rate than that of married population. A more detailed analysis indicates that each country has its distinctive marital mortality features which are associated with cultural regions (East and West) but are not related to developmental factors. When marital mortality patterns of the East and the West are compared, it demonstrates that mortality rates of never-married Asian women are strikingly higher than that of their Western counterparts. This phenomenon has persisted during the last two decades. Two possible cultural interpretations are suggested: differential family support theses versus differential marital selection.

This study focuses on the determinants of migrant-nonmigrant fertility differentials in Taiwan with particular attention to rural-to-urban migrants. A socioeconomic model is developed in which the fertility determinants are classified into four broad categories: age characteristics, migration status, background characteristics, and current characteristics. The model is evaluated by analyzing data from a large and representative sample of Taiwanese wives of childbearing age in 1980 through the use of multiple regression and multiple classification analysis. The fertility of migrants moving from rural to urban area lie in between that of nonmigrants at the place of origin and destination. After adjustment for age or marriage duration and education, the differentials become smaller but still exist. However, the differentials are negligible after further adjustment for current socioeconomic characteristics. The statistical evidence has shown that migration is weakening extended families and urban environmental influences seem to produce anti-natal values regarding greater involvement in outside activities, greater exposure to mass media, lower son preference, and greater aspirations for children’s education for the migrants. These factors explain the fertility differential between urban in-migrants and rural natives of similar demographic and educational backgrounds. Perceptions of relative costs of goods and children might also be relevant, but no data on these were written in the survey. The fertility of city in-migrants of rural origin and that of urban natives ends up about the same, because anti-natal effect of lower male preference and less common importance of a male heir among migrants offset the anti-natal effect of greater exposure to mass media among urban natives on fertility.

The distribution pattern of South Africa’s heterogeneous population has historically been shaped not only by socio-economic forces but very markedly by political ones. Where members of the different population groups live － mainly Asians, Blacks, Coloureds and Whites － has, for many years to greater or lesser extent been determined by laws promulgated by consecutive White governments. Despite the effect of these restrictive measures on macro- and micro-spatial patterns, economic and political realities have recently brought adaptive changes in government policy with concomitant migration responses. Though these changes attract greater attention, significant evolutionary migratory movements are simultaneously taking place. In this paper a largely descriptive model of adaptive migration in South African society is presented. In explaining the model and to draw tentative conclusions the paper addresses three recent movements, the first two stemming from policy changes and the other evolutionary in nature.
The first movement, containing macro- and micro-elements pertains to Blacks. It follows in the wake of the acknowledgement that restrictive policies have failed to curb Black urbanization in “White” areas despite the establishment since 1960 of some 100 new towns in the homelands. As Blacks are still the least urbanized group in South Africa, have numerical superiority, as well as the highest rate of population growth of the four groups, their potential for urbanization is the greatest. These realities have caused the government to abolish influx control. Free movement is now possible but the already overpopulated Black townships adjacent to “White” cities cannot accommodate large numbers of in-coming people. Furthermore the Group Areas Act, which determines the place where population groups may reside is still in force, effectively closing “White” urban centres to Blacks－however the first signs of a breakdown of this act are noticeable. Normative policies facilitating societal change are obviously required.
The second movement, also of a macro-nature and relating to Indians, is very recent. Until the beginning of 1987 Indians, the major Asian group, were barred from residing in the Orange Free State. Since the scrapping of these restrictive measures they have been quick to respond and, though numbers are still small, Indians have moved into this province necessitating land allocation to them albeit subject to the Group Act.
The third movement pertains to elderly Whites in Pretoria. It is illustrative of evolutionary micro-migration in urban areas and as such reflects changes in life-cycle in relation to socio-economic status. It is used as an indicator of possible intra-urban movements in a normalised future South African society.