Fertility exposure analysis: A new method for assessing the contribution of proximate determinants to fertility differentials

Summary Several recent papers have dealt with the problem of assessing the impact of the proximate determinants on fertility. All these approaches rely on combining a series of separately estimated aggregate level indicators. This paper proposes an approach which uses individual-level data and thus permits regression analyses as well as analyses for sub-groups. In the course of development it became clear that there are several deficiencies and inconsistencies in the measurement and formation of indices proposed elsewhere, which are overcome. We illustrate our approach with data from the Dominican Republic. The approach used involves attributing exposure to one or more of several states, including pregnancy, lactational and non-lactational components of post-partum amenorrhoea, absence of sexual relations and contraception. Key elements are efficacies of contraception and components of post-partum infecundity and the treatment of overlaps through an explicit hierarchy. We treat both unconditional (or additive) and conditional analyses. Intriguing findings on the age-specific pattern of fertility control emerge. Major advantages of regression analysis, such as simultaneous treatment of several variables and estimation of sampling variation are stressed.     

An analysis of the fertility of Chinese women]

The 1982 census provided detailed information on fertility in China. It recorded 20,689,704 births in 1981, producing a birth rate of 2.1%, a decrease, respectively, of 43% and more than 50% in comparison with 1952 and 1963. The birth rate has varied widely over the last 30 years, from 3.6% in the early 1950's, to 1.8% in 1961, after a planned birth program was begun, to a record high of 3.7% in 1962 following the economic recovery, to 3.3% in 1970, after a gradual decline through the 1960's. By 1981 the birth rate had declined to 2.1%, clearly resulting from the intense planned fertility promotion begun in the early 1970's. In the mid- and late 50's, urban birth rate was consistently higher than rural, with the mass move to the cities at the beginning of the People's Republic. General economic development after 1957 brought simultaneous declines of both urban and rural rates, both reaching a low point in 1961. Age structure of the population also has an influence, depending on the proportion of childbearing women in the population. In 1981, the fertility of China's childbearing women was 8.3%, lower than that of the developing countries, but higher than the developed countries. By age group, the fertility rates reached 14.7% and 23.9% respectively in women between 20-24 and 25-29 years of age; the legal marriage age is 20. The fertility rate in large cities is generally lower than that of provinces. Higher educational and socio-economic level also exert an inverse influence on fertility rates; in low socio-economic areas the rate reached 3.5%, and in more advanced areas it was held to 2.2%. In all professions with the exception of agriculture, fishing, and forestry, the percentage of families with 1 child was 81.8%. Since planned fertility was implemented, the overall fertility rate has dropped from 3% to 2%. China's fertility mode has changed to that of developed countries, with high intensity between 20 and 29 years of age. Appropriate measures should be taken to lower the fertility rate in different regions.     

An analysis of the fertility transition in developing countries]

Most developing countries are in the demographic stage of early mortality, high birth rates and high rates of natural population increase. A characteristic of developing countries is that after World War ii, particularly since the 1960s fertility rates are on the decline, even though they still remain high. The fertility rate of developed countries fell from a 1950 rate of 22.9/1000 to 15/1000 in 1982, a decrease of 34.5%, whereas the fertility rate of developing countries hovered around 43/1000 between 1930-1950, 40.6/1000 during the 1960s and 33/1000 in 1982. Between 1950 and 1982 there was a decrease of 24.8%. But the main reason for this decrease is the decline in the last 20 years of the fertility rates of China and India, whose rates fell 34.9% from 1960-1980. Changes in fertility rates are influenced by the age structure of a country, as seen in the changing age structure of developing countries from 1960-80. For example, an increase in fertility rates was 1 consequence of an increase in the number of fertile women aged 15-45 from 42.6% in 1960 to 44.4% in 1980. Nevertheless, there exists some sort of birth control, whether conscious or subconscious, because the number of births per fertile woman is 3-4 fewer than the 14-15 children a woman can theoretically bear. The reason for changes in fertility rates in developing countries can be traced to marriage and family customs, and even more important, to social and economic factors. For example, Asian, African and Latin American cultures tend to support early marriages. When the fertility rates of developed and developing countries are looked at for a comparable period, then the rate of decrease for developing countries is slower than developed countries. But, if the comparison is made for a transitional period (i.e., industrialization), then the rate of decrease for developing countries is faster than for developed countries. Currently there are 25 developing countries that have attained a fertility rate of 25/1000 or lower, and 52 developing countries with a rate of 35/1000.     

An inquiry into expected lifetime fertility]

Expected lifetime fertility rate, or completed fertility rate, refers specifically to the cumulative fertility rate of a cohort of women after the age of reproducibility; however, in China's case, "reproduccibility" virtually ends after a woman gives birth to a 2nd child (assuming both children live). Hypothetical situations specific to China's system of family planning are presented and analyzed; statistical formulas and lifetime fertility rates (including allowances for violations of the e child policy), are provided.     

Socioeconomic determinants of fertility in China

This paper reports the first set of estimates of the socioeconomic determinants of fertility in China using micro-data available from China's 1985 In-Depth Fertility Survey. Based on existing microeconomic theories of fertility, an econometric model was specified and estimated. The results indicate that even after age, marriage duration and child mortality are taken into account, education level of the woman, occupational status of the husband, the place of former and current residence, sex preference for boys, durable goods ownership, and family structure affect fertility. For the middle cohorts (aged 25–34 years in 1985), the relationship between fertility and education takes the form of a J-shaped curve.This paper is drawn from Essay II of my Ph. D. thesis submitted to McMaster University. I am grateful to Frank Denton and Byron Spencer for discussion in connection with the thesis and comments on earlier versions of this paper, to Ronald Lee, the external examiner of the thesis, for many insightful comments, and to Martin Dooley, Lonnie Magee and two anonymous referees for very helpful suggestions. I would also like to thank International Statistical Institute Research Center for supplying the data used in this study.     

Socioeconomic determinants of China's urban fertility

This paper examines socioeconomic forces other than population policies and family planning programs that have affected the fertility transition in urban China. The authors argue that before and since the intensification of population planning activities, the government influenced fertility directly and indirectly through socialization of the economy, the transformation of the Chinese family, and the provision of education, employment, health, medical, welfare, cultural, and related services in urban areas. The various social institutions and subsystems of society have greatly weakened the motivation for large families. The byproducts of the slow urbanization process in urban China including housing shortages, unemployment, rising living standards, changes in the cost of raising a child, and urban-rural downward mobility have affected the social and economic costs of childbearing, which in turn have affected the postponement of childbearing. Thus, our considerations of urban China's fertility transition must be broadened to include the issues of social development strategy in Chinese urban experience.     

A socio-psychological analysis of attitudes toward fertility]

This is an introduction to the study of attitudes toward fertility and the psychosocial factors that influence them. Both individual and group attitudes are included. The author also examines how such attitudes change over time.     

A socioeconomic analysis of the determinants of fertility: the case of Vietnam

This paper is an economics-based quantitative analysis of the determinants of individual fertility in Vietnam, measured as the number of children ever born. In addition to the conventional linear model, two limited dependent variable models, Poisson and ordered-logit, are estimated using data from the 1988 Vietnam Demographic and Health Survery. We find, among other things, that husbands‘ characteristics are almost as important as those of wives in determining fertility, perhaps a reflection of the still dominant role of husbands in Vietnamese families. Both paternal and maternal education have important impacts on fertility. Of special interest is the evidence that supports the attitudinal effect of education over the opportunity-cost effect. Received April 22, 1996 / Accepted January 13, 1997     

对我国未来“内生型”极低生育率水平的预警分析

本文通过对世界“内生型”极低生育率国家和地区的生育率主要影响因素分析,采用横截面替代方法得出了在极低生育率条件下生育率影响因素的替代系数,并对我国生育意愿达到“内生型”极低生育率的时间进行了估测,为我国调整生育政策避免进入“逆马尔萨斯”陷阱的人口危机做出了预警,并结合实际对我国生育政策微调提出了相关建议。     

The determinants of early fertility decline in Texas

This study examines the determinants of fertility control in a frontier population made up largely of German-Americans during the years from 1850 to 1910. The analysis employs a complex register of population constructed from census enumerations, civil and ecclesiastical vital registration, and tax assessment rolls. The article begins with a series of bivariate analyses with cohort of mother’s birth, religion, ethnicity, and husband’s occupation determining marital fertility. The second half of the paper presents a multivariate model of the determinants of fertility using these and other demographic characteristics as independent variables. The conclusions emphasize the importance of the overall trend toward fertility decline in the United States, as well as the role of religion and of occupational differences, in determining changes in fertility behavior in the population of Gillespie County, Texas.     

A quantitative study of the determinants of fertility behavior

Recent literature shows great interest in the quantitative study of the determinants of fertility. In a similar way, this study takes an across-country approach to specify independent variables, to separate economic from social and political variables, to make distinct comparisons of fertility responses in developed and underdeveloped countries, and to examine a wide range of hypotheses. The key is empirical analysis by separate regressions. This permits direct comparisons of countries at different levels of development, increases the probability of obtaining statistically significant regression coefficients, and standardizes the analysis for factors which vary with level of development.In this way, the authors determine positive and statistically significant relations between fertility and illiteracy, child mortality, proportion of agricultural population, proportion of nonfarm selfemployment, and overcrowded housing and show a negative significant relationship between fertility and communism. The study does not establish statistically significant relations, however, for population density, social mobility, substitutes for sexual intercourse, achievement motivation, protein in the diet, and religion.In general, the signs of the regression coefficients for the separate levels of development are the same as those for all countries combined. Any failure to attain statistical significance may be explained by small sample size and insufficient variation in the variables for separate levels of development.     

Urbanization and fertility: An event-history analysis of Coastal Ghana

In this article, we undertake an event-history analysis of fertility in Ghana. We exploit detailed life history calendar data to conduct a more refined and definitive analysis of the relationship among personal traits, urban residence, and fertility. Although urbanization is generally associated with lower fertility in developing countries, inferences in most studies have been hampered by a lack of information about the timing of residence in relationship to childbearing. We find that the effect of urbanization itself is strong, evident, and complex, and persists after we control for the effects of age, cohort, union status, and education. Our discrete-time event-history analysis shows that urban women exhibit fertility rates that are, on average, 11% lower than those of rural women, but the effects vary by parity. Differences in urban population traits would augment the effects of urban adaptation itself. Extensions of the analysis point to the operation of a selection effect in rural-to-urban mobility but provide limited evidence for disruption effects. The possibility of further selection of urbanward migrants on unmeasured traits remains. The analysis also demonstrates the utility of an annual life history calendar for collecting such data in the field.     

A tentative analysis of the effect of income on women's fertility]

The impact of income on women's fertility in China is analyzed using data from official and other published sources. The author notes that there is a clear link between lower fertility and higher income up to a certain point. This point seems to be when family income reaches a level of 300 yan in rural areas. Other factors affecting fertility are also considered, including the national family planning program, female educational level, and female labor force participation.     

Son targeting fertility behavior: Some consequences and determinants

This article draws out some implications of son targeting fertility behavior and studies its determinants. We demonstrate that such behavior has two notable implications at the aggregate level: (a) girls have a larger number of siblings (sibling effect), and (b) girls are born at relatively earlier parities within families (birth-order effect). Empirically testing for these effects, we find that both are present in many countries in South Asia, Southeast Asia, and North Africa but are absent in the countries of sub-Saharan Africa. Using maximum likelihood estimation, we study the effect of covariates on son targeting fertility behavior in India, a country that displays significant sibling and birth-order effects. We find that income and geographic location of families significantly affect son targeting behavior.     

The evolution in China's fertility and an analysis of population development]

There have been numerous projections on China's population at the end of century. Their differences are due to different estimations on the effects of fertility determinants. 2 simulation models have been developed, both from micro and macro levels, to estimate the population at the end of the century on the basis of 6 different fertility patterns. 3 possible options for fertility patterns are discussed. 1.) The 1 child per family option means that every couple has 1 child by the year 1989, the population of China will be 1.2 billion in the year 2000. Even if this is a ideal situation, it would not be a feasible policy, as the pressure from the rural population to have more than 1 child has been increasing in recent years. Nevertheless, it is still possible for urban couples to accept having only 1 child. Therefore, encouraging more people to have 1 child should be held as a basic policy. 2.) Under the option of 2 children per family with 2 or 3 years of spacing, the total population in the year 2000 would be 1.2 - 1.4 billion, which is unacceptable in terms of the development situation. 3.) Following a differential fertility policy towards urban, rural, and minority populations would mean that urban couples would have 1 child, rural couples whose first child is a girl or those who are in special circumstance would have 2 children. Minorities would have 2 or 3 children. AMong the above options, number 3 is more likely to be achieved in view of current socioeconomic, cultural, and demographic factors.     

Proximate determinants of Philippine fertility: 1983 levels and patterns

Data from the 1983 National Demographic Survey are used to analyze the proximate determinants of Philippine fertility in each of the 3 stages of family formation and to identify all of the direct and indirect factors affecting fertility levels and trends. 10,843 ever-married women and 12,771 children were included. The analysis pertains first to the starting patterns of family formation, the age at first birth, and the proximate determinants (age at menarche, age at first marriage/union, conception before first birth, fetal wastage first birth, interval between first marriage and first birth). Further analysis examines birth spacing patterns including the postpartum nonsusceptible period, the exposure interval and stopping patterns. Almost all births occur within marriage, and childbearing begins late at 22.5 years. However, 15.4% of first births are conceived premaritally. The mean age at first birth increases from younger to older cohorts. Urban women were slightly older (23.0 years) at the birth of their first child. Those with education below the 4th grade had first births 3.5 years earlier. Contraceptive use was low at 1.8% before first birth. Younger cohorts were more likely to use birth control and urban wives were more likely to use it than rural wives. 6.4% reported a first pregnancy ending in nonlive births, which were primarily spontaneous abortions (5.2%), stillbirths (1.0%), and induced abortions (.2%). 5.8% report never having been pregnant and 1.1% never having given birth to a live-born child. 20.4% were childless between the ages of 15-24 years, and 4.6% between 25-34 years. Childlessness was slightly higher among urban women (7.1%) than rural women (6.7%). A decreasing age at menarche has appeared; i.e., 13.6 years for the cohort 15-24 years, and 14.0 for the oldest cohort. By age 15, 82.9% had begun menstruating. The mean age at marriage is early at 20.7 years, and older cohorts tended to marry later at 21.4 years. Urban women marry a year later (21.4 years) than rural women. Lower educated women marry 4 years earlier. The mean length between first marriage and first birth was 18.4 months. In the younger cohorts, spacing patterns are shorter. Postpartum susceptibility is short. Return to sexual relations after a birth occurred at 2.8 months. The exposure time required to conceive is fairly long at 16.6 months and is attributed to contraceptive use, since coital frequency is high and temporary separation is infrequent. The average age at last birth is late at 37.6 years.     

Comparative analysis of the index of our population life quality]

A comprehensive method of calculating and measuring a country's or an area's health and literacy levels is examined. The method, known as population quality life inference (PQLI), was used to determine which of China's provinces has the highest and the lowest degree of population quality. The PQLI indicates infant mortality, average life expectancy of 1 year olds, and literacy rates of those 15 years and older. Because developing countries traditionally have high rates of infant mortality and illiteracy and low life expectancy rates during their industrialization, measuring the degree of population quality of life improvement of such countries during this period was found to be significant. These factors (infant mortality, illiteracy, and life expectancy) will improve substantially as industrialization continues. In order to compare various areas, these 3 factors must be changed into "inferences" 0-100, "0" representing the lowest population quality and "100" the highest. These 3 inferences must then be averaged in order to calculate the PQLI. For example: life expectancy value 77 (highest in the world) minus 38 (lowest)/100 = .39. In order to measure the value of India's life expectancy: value of 1-year-old's life expectancy = 56 (1-year-old's life expectancy in India) minus 38/.39 = 46. The value of adult illiteracy does not need to be changed. Thus, the actual comparison will be based on the values of the 3 inferences. Using this method of calculation, it is concluded that the PQLI analysis indicated that Peking (93.04) is the highest in China and Yumnan Province (60.72) is the lowest.     

Child care arrangements and fertility: An analysis of two-earner households

The determinants of child care arrangements and relations between child care and fertility are examined using data on two-earner households from the 1976 National Survey of Family Growth. We find that the probability of relying on market arrangements is higher among families in which the husband's income, the wife's wage, and the level of the wife's labor supply are high; these households are likely to benefit the most from subsidies to the market forms of care that are small relative to the total cost of care (e.g. the present system of tax credits). In addition, parental education, family size, child's age, race, religion, and place of residence have important influences on the choice of child care mode. When other factors are held constant, reliance on a relative for child care is positively associated with intentions to have further children among couples with infants and preschoolers.     

Analysis of the determinants of fertility decline in the Czech Republic

In this paper, we analyze the decline in the total fertility rate (TFR) in the Czech Republic during the economic transition. To identify transition-specific features of this decline, we estimate a Heckman–Walker multistate model of the birth process using data from the 1998 Family and Fertility Survey. We find that the negative effect of transition on TFR is mostly driven by a sharply increased influence of higher education, limited ability to combine employment with childbearing and lack of adequate childcare facilities. We also detect a significant role of the increased use of contraception, motivated by both economic and demographic reasons.     

An analysis of marital status]

In the 1980 census, a special investigation was conducted in Wuxi City on the marital status of the local population above the age of fifteen. The investigation covered detailed information concerning those married, divorced, single, and widowed. Results from this investigation show that more men are single than women, and more men are also widowed. In part this is because the average age for husband is older than his wife and the death rate higher is for men than women. Data show that the popular marriage age is between 25 and 29, evidence of a general trend toward late marr iage. In the area of the divorce rate, the rate for women in the city is higher than that in the countryside. The divorce rate for men is higher in the countryside than in the city. In the rate of being single through a lifetime, the rate for men in the countryside is higher than that in the city. This situation shows that in the countryside, because of the poor geographical and economic condition, men suffer from their marriage status. Generally speaking, the divorce rate in China is still lower than that of Western countries and the marital status in China remains more stable. The marital status is influenced by many factors, such as the social and economic situation, customs and habits, religious beliefs, profession, and educational and cultural levels. The collection of information regarding the marital status is useful for analysis of the birthrate and population forecast.