The China Family Panel Studies (CFPS ), launched by Peking University, is a nearly nationwide, comprehensive, longitudinal social survey that is intended to serve research needs on a large variety of social phenomena in contemporary China. This article describes the background and characteristics of the CFPS, which was designed with the help of methods learned from the most influential survey projects in the world and their experiences. Extensive information is collected through computer-assisted person-to-person interviews of all family members. The questionnaires not only cover a wide range of topics but also consist of intergraded modules for rural and urban interviews, gathering information on family structure and family members, migrant mobility, event history (e.g., history of marriage, education, and employment), cognitive ability, and child development. The CFPS promises to provide the academic community with the most comprehensive and highest-quality survey data on contemporary China.
Since the seminal introduction of the propensity score (PS) by Rosenbaum and Rubin, PS-based methods have been widely used for drawing causal inferences in the behavioral and social sciences. However, the PS approach depends on the ignorability assumption: there are no unobserved confounders once observed covariates are taken into account. For situations where this assumption may be violated, Heckman and his associates have recently developed a novel approach based on marginal treatment effects (MTEs). In this article, we (1) explicate the consequences for PS-based methods when aspects of the ignorability assumption are violated, (2) compare PS-based methods and MTE-based methods by making a close examination of their identification assumptions and estimation performances, (3) apply these two approaches in estimating the economic return to college using data from the National Longitudinal Survey of Youth (NLSY) of 1979 and discuss their discrepancies in results. When there is a sorting gain but no systematic baseline difference between treated and untreated units given observed covariates, PS-based methods can identify the treatment effect of the treated (TT). The MTE approach performs best when there is a valid and strong instrumental variable (IV). In addition, this article introduces the “smoothing-difference PS-based method,” which enables us to uncover heterogeneity across people of different PSs in both counterfactual outcomes and treatment effects.
The localistic enclave is a special kind of enclave in urban China, which is characterised by a high concentration of rural migrants from the same place of origin. Prior research has documented that rural migrants work in these localistic enclaves, but the significance of participation in them for labour market outcomes among migrant workers has yet to be determined. In this article, it is argued that localistic economic enclaves may improve the labour force outcomes of rural-to-urban migrants. Results are reported from a study of the social determinants and consequences of working in localistic enclaves, based on data from a 2010 survey of migrant workers in the Pearl River and the Yangzi River deltas. The results provide limited support for the hypothesis: localistic enclaves enable migrant workers to earn higher earnings overall, but the earnings returns to human capital in an enclave are limited.
This article is motivated by the idea that development and developmental hierarchies have been constructed and embraced for centuries by scholars and policy makers and have been disseminated among ordinary people. Recent research shows that most people have constructions of development hierarchies that are similar across countries. In this article, we extend this research by examining how basic social factors influence ordinary people’s beliefs about development and developmental hierarchies in six countries: Argentina, China, Egypt, Iran, Nepal, and the United States. Results show that the understanding and perception of developmental hierarchies vary by gender and education. These results are important because they show how distinct groups of people have differential access to information or ideas.
Social contexts exert structural effects on individuals’ social relationships, including interracial friendships. In this study, we posit that, net of group composition, total context size has a distinct effect on interracial friendship. Under the assumptions of (i) maximization of preference in choosing a friend, (ii) multidimensionality of preference, and (iii) preference for same-race friends, we conducted analyses using microsimulation that yielded three main findings. First, increased context size decreases the likelihood of forming an interracial friendship. Second, the size effect increases with the number of preference dimensions. Third, the size effect is diluted by noise, i.e., the random component affecting friendship formation. Analysis of actual friendship data among 4,745 American high school students yielded results consistent with the main conclusion that increased context size promotes racial segregation and discourages interracial friendship.
We investigate the dynamic relationship between residential choices of individuals and resulting long-term aggregate segregation patterns, allowing for feedback effects of macrolevel neighborhood conditions on residential choices.We reinterpret past survey data on whites’ attitudes about desired neighborhoods as revealing large heterogeneity in whites’ tolerance of black neighbors. Through agent-based modeling, we improve on a previous model of residential racial segregation by introducing individual-level heterogeneity in racial tolerance. Our model predicts, in the long run, a lower level of residential racial segregation than would be true with homogeneous racial tolerance. Further analysis shows that whites’ tolerance of black neighbors is closely associated with their overall racial attitudes toward blacks.