Thesis (M. Sc.)--University of Hong Kong, 1972. / Mimeographed.

Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 49-51).

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Abstract of thesis (Ph. D.)--University of Pennsylvania, 1915. / "Reprint from Publication of American statistical association, June, 1914." Also available in digital form on the Internet Archive Web site.

In order to maintain itself into the future, the People’s Republic of China undertook in the 1970s a legendary demographic endeavor dealing with the artificial constraint of population growth. The “later, longer, fewer” policy and the more rigid one-child policy were efforts to expedite the demographic transition in the country. The ultimate goal was the stabilization and eventual decline of the population, via fertility at below-replacement levels for an extended period of time. According to the 2000 census, the total fertility rate (TFR) for China was 1.22—well below 2.1, the replacement level of fertility. However, the country’s TFR fluctuated spatially with rates of .86, 1.08, and 1.43, for cities, towns, and rural areas, respectively. Undoubtedly, China’s family planning policy is largely responsible for the nation’s current low fertility, as well as the geographical variation in fertility just mentioned. Research has shown, however, that other factors have played a part in this fertility transition and the subsequent variation at the regional, provincial, and county levels. In keeping with the expectations of demographic transition theory (DTT), quantitative studies conducted over the last twenty years have linked an assortment of socioeconomic factors with China’s fertility decline and nationwide inconsistencies (Birdsall and Jamison 1983; Tien 1984; Poston and Gu 1987; Freedman et al. 1988; Peng 1989; Poston and Jia 1990; Poston 2000). My thesis built on and extended the above work, using the newly available demographic data provided by Census 2000. I tested the efficiency of demographic transition variables in explaining the variation in the TFR among the counties of China by estimating twelve Ordinary Least Squares (OLS) regression equations. Specifically, I examined the ways in which variables such as ethnicity, agricultural detachment, urbanization, economic conditions, cultural norms and gender differences were related to Chinese fertility in a nationwide analysis and in two region-specific analyses. My results showed rather definitively that demographic transition theory is applicable for predicting and understanding fertility among the counties of China. Irrespective of the nation’s extensive family planning policy, it is apparent that other factors contribute to the varying fertility rates across the country.

Prior research has focused on studying female fertility, but male fertility remains overlooked. Using data from the 2001 Demographic Yearbook, the 1964 to 2002 Taiwan-Fukien Demographic Yearbooks, the 2004 National Statistics Reports and the 2002 National Survey of Family Growth (NSFG) Cycle 6, this dissertation examines male and female fertility at the aggregate and individual levels by studying men’s and women’s fertility differentials in rates and in determinants. Based on examining the age-specific fertility rates (ASFRs) and the total fertility rates (TFRs) for men and women during the 1990 to 1998 period in 43 countries and places, results show that male and female age-specific fertility mainly differs in the older age groups. In those age groups, male fertility largely outnumbers female fertility. And this pattern is especially apparent in low fertility countries (TFR<2,200). With regard to total fertility, male and female TFRs tend to be similar in countries with TFR values lower than 2,200 where female fertility tends to be higher than male fertility. The opposite pattern is true for countries with male and female TFRs higher than 2,200. In the analysis of Taiwan fertility, results reveal that male and female TFRs for most years during 1975 to 2004 are far from identical. The ASFRs for men and women also differed over time and varied by educational attainment. Although fertility determinants at the aggregate level impact men’s and women’s fertility similarly, models combining these factors are more powerful when explaining female than male fertility. The individual level analyses of the U.S. samples also show significant fertility differentials by gender. Age, marriage, and Hispanic origin increase men’s fertility to a greater extent compared to women’s fertility. Family income increases men’s fertility but decreases women’s fertility. Participating in the labor force shows a much stronger positive effect on male than on female childbearing. Cohabitation experience, however, has a significantly stronger impact increasing women’s than men’s fertility. And an increased number of sexual partners is more likely to reduce men’s children compared to women. These findings reported draw research attention to male fertility and contribute to understanding the dynamics of male fertility.

In this dissertation I investigate whether or not a series of social, demographic, and cultural factors affect fertility differently, in either direction or magnitude, for men and women. This work situates the study of male fertility within the existing demographic literature, models and compares male and female fertility through the use of a variety of dependent and independent variables, discovers which of those variables reveal a difference between the determinants of male and female fertility, and extends understanding of how male fertility should be studied in addition to and alongside female fertility. Although there is a significant literature on the biological and anatomic components of male fertility, there is little work published on the social and cultural factors that affect male fertility. Comparisons of male and female fertility are also lacking within the discipline of demography. The National Survey of Family Growth (Cycle 7) provides survey data on both men and women on a number of social, cultural, and demographic variables used either on their own, or as components in the construction of indicator variables. I present the results of models utilizing both direct and indirect measures of fertility. Three models are direct measures of fertility, and three other indirect models examine behaviors as a measure of exposure to the risk of fertility. Only four of these models were significant under the initial analysis. Within each of the models, the respondent’s age, poverty level, age at first intercourse, and whether the respondent ever married or cohabited presented the most frequent differences, in either direction, magnitude, or both, between males and females. I discuss the implications of the findings presented in the dissertation, as well as the potential for future research using other data or methods.