Social stratification and mobility comprises an important field of social demography and population studies. Understanding social stratification and mobility hinges on knowledge of early lifecourse (ages 0-18) development—its patterns and causes.Unfortunately, demographic research in China has only made limited efforts to examine early life-course development from the perspective of social stratification and mobility as of yet, partly due to lacking a comprehensive conceptual framework for guidance. To address this issue, we propose a two-level and multi-factor theoretical framework based on the existing literature. Two-level refers to the macro level and the micro level. Multi-factor refers to the numerous influential factors affecting early-life development, which broadly fall into two categories: social and economic. This study contributes to population research by providing a comprehensive roadmap and guidance for future research on early-life development in China.

Reflecting collective norms towards childbearing at the societal level, the ideal number of children helps us project a society’s long  term fertility trend. Comparing China and other selected countries, our study shows that the average ideal number of children among women aged 18 to 49 is much lower in China than in other countries. We also observe relatively high one child and low 3 or more children ideals in China. Capitalizing on data from China Family Panel Studies, prefectural yearbooks, and digital map, we examine the effects of contextual factors on the ideal number of children in China. Results show that higher economic development level, higher income inequality level, lower total fertility rate, and higher educational competition level all lead to smaller ideal number of children. A mediation analysis reveals that contextual fertility level and educational pressure are important in shaping Chinese people’s ideal number of children. Our study suggests that fertility attitudes should be understood by taking historical and cultural contexts into account.

Chinese family has experienced dramatic changes in recent decades, especially in terms of union formation and dissolution. Using data from Census, miniCensus, and China Family Panel Studies, we provide estimates of marriage and divorce in China. We further compare marriage and divorce trends of China with those in the United States, Japan, South Korea, Russia, British, France, German, Italy, and Spain. Our results show a delayed first marriage age and increased singlehood rate in China, yet marriage is still earlier and more universal in China than in other developed countries. We expect increases in both marriage age and singlehood rate as Chinas economy further develops. Despite a high crude divorce rate in recent China, our results based on age and cohort analysis reveal that divorce is much less prevalent in China than in other countries. With the persistent childcentered family culture, we argue that marriage in China will remain relatively stable in the short term.

In the past two decades, the Second Demographic Transition (SDT) has become a major theoretical framework in explaining changes in family behaviors in many countries in the world. Using data from Census, miniCensus, and China Family Panel Studies, we present an overall evaluation of the indicators of the SDT in mainland China, including marriage timing, cohabitation rate, divorce rate, and fertility behavior. Our results suggest that different aspects of the SDT have had varying trajectories in China, in comparison to the West. A rapid change has been observed among more individualized family behavior like marriage and cohabitation: both men and women postpone the timing of transition to first marriage; cohabitation increases rapidly. In terms of childbearing, the extramarital childbirth rate and childless rate among married women are still rare. Divorce rate experienced a slow increase across cohorts, yet our prediction implies that it will remain relatively low in the near future. This study suggests that we should integrate local social, historical and cultural backgrounds in understanding family changes in China.

Using data from China Family Panel Study in 2014，we examine the prevalence and so- cial determinants of cohabitation in China. Descriptive results show that，although only about 10 percent of Chinese adults born before 1980 cohabited before first marriage，cohabitation has grown sharply among recent birth cohorts. Based on the“developmental idealism”perspective and Chinese social contexts，we propose that ideological changes and institution changes are the major driving forces of the emergence of cohabitation. Multivariate analysis shows that birth cohort，educational attainment，living in urban areas，migration，party membership，and regional development have significant effect on premarital cohabitation. Taken as a whole，our study of cohabitation helps advance our understanding of family changes in China.

The inverse association between sibship size and education is well established in social research. The resource dilution model posits that under the assumption of finite education resources, additional children could dilute the quantity of educational resources any one child would receive, and thus exert negative impacts on children’s educational outcomes. In China, relevant researches are all based upon adult samples. As most of adults have ended their educational career, research with adult samples cannot examine the role that various educational resources play in explaining the negative link between sibship size and educational outcomes. In this paper, based on a children sample from 2010 China Family Panel Studies, we divide educational resources that might be influential for children’s education into three types: financial investment resources, parental involvement resources, and family environment resources. Our results reconfirm that children with bigger sibship sizes are more disadvantaged both in obtaining all these educational resources and in academic achievement. Moreover, we find these educational resources could help explain substantively the negative effect of sibship size on academic achievement, whereas the three types of educational resources contribute differently to explaining the effect of sibship size on word verbal skills and the effect of sibship size on math skills.

Using 1993 － 2006 China Health and Nutrition Survey data，we test the motherhood penalty hypothesis with fixed-effects models. We find that fertility has a significant negative influence on women's wage and that each additional child lowers hourly wages by about 7 percent. In addition，the negative effect becomes larger as the number of children increases. The hypothesis holds true even if the women's human capital，job characteristics and family constraints are taken into account. We further explore whether the motherhood penalty varies by social group. The results show that the negative effect of having children is especially pronounced among women with high levels of education，women holding professional and managerial jobs，and women working in the state sector. The study shows that family factors play an important role in contributing to gender disparities in earnings and perhaps other labor market outcomes in contemporary China.

The paper introduces the basic ideas of design for longitudinal survey data and its advantages and shortcomings,and discusses the rationales for collecting longitudinal data from the statistical perspectives.Longitudinal data are informative because they enable identification of population heterogeneity,study of intervening causal mechanisms,study of causal effects,and study of state transitions.Special considerations in longitudinal settings are addressed,as well as the importance of hypotheses,illustrated with examples of study designs using longitudinal data.Longitudinal data are not perfect,because the most serious shortcomings come from the intrinsic variability of humans and human behaviors.Given such severe limitations,what researchers of social phenomena can do is to develop better understanding,better conceptualization,and better data analysis,aided by longitudinal data.