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A growing body of social science research investigates whether the economic payoff to a college education is heterogeneous — in particular, whether disadvantaged youth can benefit more from attending and completing college relative to their more advantaged peers. Scholars, however, have employed different analytical strategies and reported mixed findings. To shed light on this literature, I propose a causal mediation approach to conceptualizing, evaluating, and unpacking the causal effects of college on earnings. By decomposing the total effect of attending a four-year college into several direct and indirect components, this approach not only clarifies the mechanisms through which college attendance boosts earnings, but illuminates the ways in which the postsecondary system may be both an equalizer and a stratifier. The total effect of college attendance, its direct and indirect components, and their heterogeneity across different subpopulations are all identified under the assumption of sequential ignorability. I introduce a debiased machine learning (DML) method for estimating all quantities of interest, along with a set of bias formulas for sensitivity analysis. I illustrate the proposed framework and methodology using data from the National Longitudinal Survey of Youth, 1997 cohort.

Opinion surveys often employ multiple items to measure the respondent's underlying value, belief, or attitude. To analyze such types of data, researchers have often followed a two-step approach by first constructing a composite measure and then using it in subsequent analysis. This paper presents a class of hierarchical item response models that help integrate measurement and analysis. In this approach, individual responses to multiple items stem from a latent preference, of which both the mean and variance may depend on observed covariates. Compared with the two-step approach, the hierarchical approach reduces bias, increases efficiency, and facilitates direct comparison across surveys covering different sets of items. Moreover, it enables us to investigate not only how preferences differ among groups, vary across regions, and evolve over time, but also levels, patterns, and trends of attitude polarization and ideological constraint. An open-source R package, hIRT, is available for fitting the proposed models.

Statistical analysis of mobility tables has long played a pivotal role in comparative stratification research. This article proposes a shrinkage estimator of the log-odds ratio for comparing mobility tables. Building on an empirical Bayes framework, the shrinkage estimator improves estimation efficiency by "borrowing strength" across multiple tables while placing no restrictions on the pattern of association within tables. Numerical simulation shows that the shrinkage estimator outperforms the usual maximum likelihood estimator (MLE) in both the total squared error and the correlation with the true values. Moreover, the benefits of the shrinkage estimator relative to the MLE depend on both the variation in the true log-odds ratio and the variation in sample size among mobility regimes. To illustrate the effects of shrinkage, the author contrasts the shrinkage estimates with the usual estimates for the mobility data assembled by Hazelrigg and Garnier for 16 countries in the 1960s and 1970s. For mobility tables with more than two categories, the shrinkage estimates of log-odds ratios can also be used to calculate summary measures of association that are based on aggregations of log-odds ratios. Specifically, the author constructs an adjusted estimator of the Altham index and, with a set of calibrated simulations, demonstrates its usefulness in enhancing both the precision of individual estimates and the accuracy of cross-table comparisons. Finally, using two real data sets, the author shows that in gauging the overall degree of social fluidity, the adjusted estimator of the Altham index agrees more closely with results from the Unidiff model than does the direct estimator of the Altham index.

The author presents a nonparametric approach to measuring stratification that highlights the distinction between stratification and inequality. Using pairwise comparison of ranks, the author develops an index of stratification that gauges the overall degree to which population subgroups occupy distinct strata with respect to a hierarchical outcome. This new index possesses a number of desirable properties that are not satisfied by existing measures of stratification. The overall index can be decomposed as a weighted average of pair-specific indices of stratification, which capture the extent of separation between any two particular groups. Besides, this index can be easily extended to measure conditional stratification through control of a third variable. In addition, the author builds a parallel between stratification and inequality in their measurement by developing a general formula of which the index of stratification and the Gini index of inequality can be considered as two special cases. Finally, this new approach is applied to depict the temporal trends of wage stratification by gender, race, and educational attainment over the past three decades in the United States.

Despite the rapid growth of blogging in China, little is known about the communicative processes of blogs and their implications for China. This current study aims to bridge that gap by specifically looking at the political blogs posted on the NetEase, one of the largest portal websites in China, regarding the dismissal of Shanghai leader Chen Liangyu. Results from a content analysis indicate that bloggers, giving quick responses to the event, were actively engaged in discussions on politically sensitive topics, and expressed different opinions of the event and even criticism of the government.

Intro -- Contents -- List of Charts -- List of Tables -- Chapter 1: Introduction: Social Change and Education Reform -- 1.1 Historical Orientation: Education Reform Gets into Deep Water -- 1.1.1 The "Chinese Model" of Educational Development -- 1.1.2 Education Reform Gets into Deep-Water Area -- 1.2 Policy Trend: Build a Fair and Just Society through Education -- 1.2.1 Guiding Ideology: Develop Education to the Satisfaction of the People -- 1.2.2 Reform Goal: Quality and Equality -- 1.2.3 Path of Reform: Comprehensive Reform -- 1.2.4 Reform Focus: Elimination of "Four Harmful Trends" -- Part I: Social Change and Improvement of the Education System -- Chapter 2: Efforts to Develop Preschool Education -- 2.1 The Current Situation of the Development of Preschool Education in China -- 2.2 Analysis of Problems in the Development of Preschool Education in China -- 2.2.1 Relative Inadequacy of Financial and Economic Investment and Unbalanced Allocation of Resources -- 2.2.2 Administration: Authorities for the Approval of Preschool Education Are Not Concentrated and Their Personnel Quality Needs to Be Improved -- 2.2.3 Teachers: Insufficient Numbers, Poor Quality and Weak Career Identity -- 2.3 Preschool Education Development Direction -- 2.3.1 Increase Financial Investment and Reform the Financial System of Preschool Education -- 2.3.2 Reform the Administrative System and Change Government Functions -- 2.3.3 Improve Teachers' Professional Quality and Protect Their Rights and Interests -- 2.3.4 Change the Inappropriate Trend of Kindergarten Being Approached in the Same Way as Primary School -- Chapter 3: Balanced Development of Compulsory Education -- 3.1 Balanced Development: A New Goal for Compulsory Education -- 3.2 Basic Principles and System for the Balanced Development of Compulsory Education.

How does higher education shape the Black-White earnings gap? It may help close the gap if Black youth benefit more from attending and completing college than do White youth. On the other hand, Black college-goers are less likely to complete college relative to White students, and this disparity in degree completion helps reproduce racial inequality. In this study, we use a novel causal decomposition and a debiased machine learning method to isolate, quantify, and explain the equalizing and stratifying roles of college. Analyzing data from the NLSY97, we find that a bachelor's degree has a strong equalizing effect on earnings among men (albeit not among women); yet, at the population level, this equalizing effect is partly offset by unequal likelihoods of bachelor's completion between Black and White students. Moreover, a bachelor's degree narrows the male Black-White earnings gap not by reducing the influence of class background and pre-college academic ability, but by lessening the "unexplained" penalty of being Black in the labor market. To illuminate the policy implications of our findings, we estimate counterfactual earnings gaps under a series of stylized educational interventions. We find that interventions that both boost rates of college attendance and bachelor's completion and close racial disparities in these transitions can substantially reduce the Black-White earnings gap.

An essential feature common to all empirical social research is variability across units of analysis. Individuals differ not only in background characteristics but also in how they respond to a particular treatment, intervention, or stimulation. Moreover, individuals may self-select into treatment on the basis of anticipated treatment effects. To study heterogeneous treatment effects in the presence of self-selection, Heckman and Vytlacil developed a structural approach that builds on the marginal treatment effect (MTE). In this article, we extend the MTE-based approach through a redefinition of MTE. Specifically, we redefine MTE as the expected treatment effect conditional on the propensity score (rather than all observed covariates) as well as a latent variable representing unobserved resistance to treatment. As with the original MTE, the new MTE also can be used as a building block for evaluating standard causal estimands. However, the weights associated with the new MTE are simpler, more intuitive, and easier to compute. Moreover, the new MTE is a bivariate function and thus is easier to visualize than the original MTE. Finally, the redefined MTE immediately reveals treatment-effect heterogeneity among individuals who are at the margin of treatment. As a result, it can be used to evaluate a wide range of policy changes with little analytical twist and design policy interventions that optimize the marginal benefits of treatment. We illustrate the proposed method by estimating heterogeneous economic returns to college with National Longitudinal Study of Youth 1979 data.

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.

We document a rapid increase in income inequality in China's recent past, capitalizing on newly available survey data collected by several Chinese university survey organizations. By now, China's income inequality not only surpasses that of the United States by a large margin but also ranks among the highest in the world, especially in comparison with countries with comparable or higher standards of living. We argue that China's current high income inequality is significantly driven by structural factors attributable to the Chinese political system, the main structural determinants being the rural-urban divide and the regional variation in economic well-being.

This research examined news frames in coverage of SARS by newspapers in China and the United States. The assumption was that with the adoption of Western news values and practices, the Chinese press would exhibit news frames similar to those found in Western news. The results showed the presence of economic consequences, responsibility, conflict, leadership, and human-interest news frames in both the U.S. and Chinese newspapers. Depending on the newspaper's country of origin, however, the degree and manner of the frame uses varied.