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Author: Xie, Yu
Resulting in 5 citations.
1. Brand, Jennie E.
Xie, Yu
Who Benefits Most from College? Evidence for Negative Selection in Heterogeneous Economic Returns to Higher Education
American Sociological Review 75,2 (April 2010): 273-302.
Also: http://asr.sagepub.com/content/75/2/273.abstract
Cohort(s): NLSY79
Publisher: American Sociological Association
Keyword(s): College Education; Earnings; Educational Returns; Gender Differences; Life Course; Propensity Scores; Wisconsin Longitudinal Study/H.S. Panel Study (WLS)

Permission to reprint the abstract has not been received from the publisher.

In this article, we consider how the economic return to a college education varies across members of the U.S. population. Based on principles of comparative advantage, scholars commonly presume that positive selection is at work, that is, individuals who are most likely to select into college also benefit most from college. Net of observed economic and noneconomic factors influencing college attendance, we conjecture that individuals who are least likely to obtain a college education benefit the most from college. We call this theory the negative selection hypothesis. To adjudicate between the two hypotheses, we study the effects of completing college on earnings by propensity score strata using an innovative hierarchical linear model with data from the National Longitudinal Survey of Youth 1979 and the Wisconsin Longitudinal Study. For both cohorts, for both men and women, and for every observed stage of the life course, we find evidence suggesting negative selection. Results from auxiliary analyses lend further support to the negative selection hypothesis.
Bibliography Citation
Brand, Jennie E. and Yu Xie. "Who Benefits Most from College? Evidence for Negative Selection in Heterogeneous Economic Returns to Higher Education." American Sociological Review 75,2 (April 2010): 273-302.
2. Brand, Jennie E.
Xie, Yu
Moore, Ravaris L.
Effects of Parental Divorce on Children's Psychosocial Skills
Presented: Boston MA, Population Association of America Annual Meeting, May 2014
Cohort(s): Children of the NLSY79, NLSY79, NLSY79 Young Adult
Publisher: Population Association of America
Keyword(s): Adolescent Behavior; Age at First Intercourse; Depression (see also CESD); Divorce; Educational Outcomes; Parental Influences; Parental Marital Status; Pearlin Mastery Scale; Social Emotional Development

Permission to reprint the abstract has not been received from the publisher.

A large literature suggests parental divorce leads to worse educational and socioeconomic outcomes among children. A recent study by Kim (2011) highlights the role of parental divorce in the development of children's cognitive and noncognitive skills. However, we contend that the development literature points to important asymmetry between these skills. While cognitive skills stabilize relatively early in childhood, psychosocial skills evolve and change through young childhood, thus allowing family environments to play a sizeable role in shaping psychosocial skills. Using data from the National Longitudinal Survey of Youth (NLSY) and the National Longitudinal Survey's Child-Mother file (NLSCM), we assess the effects of parental divorce on children's psychosocial skills. We also evaluate the degree to which psychosocial skills mediate the relationship between parental divorce and children's educational outcomes.
Bibliography Citation
Brand, Jennie E., Yu Xie and Ravaris L. Moore. "Effects of Parental Divorce on Children's Psychosocial Skills." Presented: Boston MA, Population Association of America Annual Meeting, May 2014.
3. Cheng, Siwei
Brand, Jennie E.
Zhou, Xiang
Xie, Yu
Who Benefits First? Whose Benefits Last? Economic Returns on College Over the Life Cycle
Presented: Denver CO, Population Association of America Annual Meeting, April 2018
Cohort(s): NLSY79
Publisher: Population Association of America
Keyword(s): College Degree; Earnings; Educational Returns; Life Cycle Research; Propensity Scores

Permission to reprint the abstract has not been received from the publisher.

Most prior research on the college premium focuses on earnings at a certain age or averaged across the lifetime. We believe, however, that there are three important reasons for considering these college returns as varying over the life cycle. First, the economic benefits of college may emerge slowly rather than instantaneously over the career, therefore, college may be associated with a higher initial earnings as well as faster earnings growth rate. Second, individuals with varying propensity of attending college may also reap the returns to college at different life stages, which leads to the heterogeneity in the college premium across the propensity spectrum. Third, the life cycle variations in college premium may further depend on family and personal characteristics. Applying propensity-score based methods to data from NLSY79, our preliminary findings show that these three arguments are supported by empirical evidence in the United States.
Bibliography Citation
Cheng, Siwei, Jennie E. Brand, Xiang Zhou and Yu Xie. "Who Benefits First? Whose Benefits Last? Economic Returns on College Over the Life Cycle." Presented: Denver CO, Population Association of America Annual Meeting, April 2018.
4. Xie, Yu
Brand, Jennie E.
Jann, Ben
Estimating Heterogeneous Treatment Effects with Observational Data
Sociological Methodology 42,1 (August 2012): 314-347.
Also: http://smx.sagepub.com/content/42/1/314.abstract
Cohort(s): NLSY79
Publisher: American Sociological Association
Keyword(s): College Enrollment; Fertility; Heterogeneity; Modeling; Propensity Scores

Permission to reprint the abstract has not been received from the publisher.

Individuals differ not only in their background characteristics but also in how they respond to a particular treatment, intervention, or stimulation. In particular, treatment effects may vary systematically by the propensity for treatment. In this paper, we discuss a practical approach to studying heterogeneous treatment effects as a function of the treatment propensity, under the same assumption commonly underlying regression analysis: ignorability. We describe one parametric method and two nonparametric methods for estimating interactions between treatment and the propensity for treatment. For the first method, we begin by estimating propensity scores for the probability of treatment given a set of observed covariates for each unit and construct balanced propensity score strata; we then estimate propensity score stratum-specific average treatment effects and evaluate a trend across them. For the second method, we match control units to treated units based on the propensity score and transform the data into treatment-control comparisons at the most elementary level at which such comparisons can be constructed; we then estimate treatment effects as a function of the propensity score by fitting a nonparametric model as a smoothing device. For the third method, we first estimate nonparametric regressions of the outcome variable as a function of the propensity score separately for treated units and for control units and then take the difference between the two nonparametric regressions. We illustrate the application of these methods with an empirical example of the effects of college attendance on women’s fertility.
Bibliography Citation
Xie, Yu, Jennie E. Brand and Ben Jann. "Estimating Heterogeneous Treatment Effects with Observational Data." Sociological Methodology 42,1 (August 2012): 314-347.
5. Zhou, Xiang
Xie, Yu
Propensity Score-based Methods Versus MTE-based Methods in Causal Inference: Identification, Estimation, and Application
Sociological Methods and Research 45,1 (February 2016): 3-40.
Also: http://smr.sagepub.com/content/45/1/3
Cohort(s): NLSY79
Publisher: Sage Publications
Keyword(s): College Education; Educational Returns; Modeling, Instrumental Variables; Propensity Scores

Permission to reprint the abstract has not been received from the publisher.

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.
Bibliography Citation
Zhou, Xiang and Yu Xie. "Propensity Score-based Methods Versus MTE-based Methods in Causal Inference: Identification, Estimation, and Application." Sociological Methods and Research 45,1 (February 2016): 3-40.