Efficient Estimation of Data Combination Models by the Method of Auxiliary-to-Study Tilting (AST)

We propose a locally efficient estimator for a class of semiparametric data combination problems. A leading estimand in this class is the average treatment effect on the treated (ATT). Data combination problems are related to, but distinct from, the class of missing data problems with data missing at random (of which the average treatment effect (ATE) estimand is a special case). Our estimator also possesses a double robustness property. Our procedure may be used to efficiently estimate, among other objects, the ATT, the two-sample instrumental variables model (TSIV), counterfactual distributions, poverty maps, and semiparametric difference-in-differences. In an empirical application, we use our procedure to characterize residual Black–White wage inequality after flexibly controlling for “premarket” differences in measured cognitive achievement. Supplementary materials for this article are available online.     

Self‐Destructive Symptomatic Frames in Clinical Adolescents: Is the Same Different?

This study examines individual and family predictors of different self‐destructive patterns—only suicidal ideation, only nonsuicidal self‐injury (NSSI), or suicide attempts (that may also include both suicide ideation (SI) and NSSI)—in a sample of outpatient adolescents (N = 42; 86% females) with mean age of 16 years (SD = 1.86). Results indicated that there are differences in youngsters with self‐destructive behaviors in their perception of paternal rejection and maternal control, when compared with youngsters reporting only SI. Adolescents from the groups with self‐destructive behaviors differ only in age. Together, these data highlight the relevance of adopting an ecosystemic perspective, which includes both the patients and their families, regarding treatment and prevention of self‐destructive symptomatic frames.     

Aftershocks of Chile's earthquake for an ongoing, large-scale experimental evaluation

Evaluation designs for social programs are developed assuming minimal or no disruption from external shocks, such as natural disasters. This is because extremely rare shocks may not make it worthwhile to account for them in the design. Among extreme shocks is the 2010 Chile earthquake. Un Buen Comienzo (UBC), an ongoing early childhood program in Chile, was directly affected by the earthquake. This article discusses (a) the factors the UBC team considered for deciding whether to put on hold or continue implementation and data collection for this experimental study; and (b) how the team reached consensus on those decisions. A lesson learned is that the use of an experimental design for UBC insured that the evaluation's internal validity was not compromised by the earthquake's consequences, although cohort comparisons were compromised. Other lessons can be transferred to other contexts where external shocks affect an ongoing experimental or quasi-experimental impact evaluation.     

Optimality conditions for a bilevel matroid problem

In bilevel programming there are two decision makers, the leader and the follower, who act in a hierarchy. In this paper we deal with a weighted matroid problem where each of the decision makers has a different set of weights. The independent set of the matroid that is chosen by the follower determines the payoff to both the leader and the follower according to their different weights. The leader can increase his payoff by changing the weights of the follower, thus influencing the follower’s decision, but he has to pay a penalty for this. We want to find an optimum strategy for the leader. This is a bilevel programming problem with continuous variables in the upper level and a parametric weighted matroid problem in the lower level. We analyze the structure of the lower level problem. We use this structure to develop local optimality criteria for the bilevel problem that can be verified in polynomial time.     

Spillover Patterns in Single-earner Couples: Work,Self-care,and the Marital Relationship

The relationship between work and marriage is well documented in dual-earner couples. Work-marital spillover patterns, however, have been understudied in single-earner couples. The current study extends the work-marital spillover literature by examining spillover patterns from individual experiences and self-care behaviors to the marital relationship over a period of 42 days in husband-earner and wife-earner couples. Results of pooled time-series regression analyses indicated individual experiences and self-care behaviors predicted marital processes for both employment groups. For self-care behaviors, however, different patterns emerged for employed and unemployed spouses. Results identify an important connection between energy depletion and marital processes, and highlight the role of a spouse’s own and the partner’s self-care behaviors, particularly for the employed spouse in single-earner couples.     

Interparental Relations,Maternal Employment,and Fathering in Mexican American Families

This study examined independent and interactive relations between the interparental relationship and maternal employment in predicting fathering within low‐income, Mexican American two‐parent families (N = 115). Interparental conflict was negatively related to quality fathering, and these relations were noted only for single‐earner families. The parenting alliance was positively related to quality fathering irrespective of maternal employment. Fathering was associated with lower levels of child depression and conduct problems. Results suggest that bolstering quality fathering is a useful avenue for improving child well‐being and that strengthening the interparental relationship can support quality fathering and child mental health within Mexican American families.     

Formation of land market institutions and their impacts on agricultural activity

The process of transformation of Bulgarian agriculture from a centrally controlled economy to a market-oriented economy is resulting in land reform, which will necessitate the immediate development and operation of land markets. On the one hand, the land reform is restoring land to those who owned it in the year 1947, or their heirs, who not only have very small and scattered holdings, but who often live in urban areas far from the claimed land and do not practice farming. On the other hand, farming is being changed by the liquidation of the former collective farms and the emergence of privately managed farms and new forms of co-operatives. These new operating units may or may not have their own land claims, but in most cases, do not have immediate access to sufficient land for adequately sized operations. Without land market institutions for information, contracting land use, and enforcement of contractual rights, the transaction costs of bringing the suppliers of land together with those demanding land will result in unused land and distorted agricultural activity. The paper explores both the formation of institutions and the evidence of transactions, as well as the possible impacts on farming.     

From Syllables to Syntax: Multilevel Statistical Learning by 12‐Month‐Old Infants

To successfully acquire language, infants must be able to track multiple levels of regularities in the input. In many cases, regularities only emerge after some learning has already occurred. For example, the grammatical relationships between words are only evident once the words have been segmented from continuous speech. To ask whether infants can engage in this type of learning process, 12‐month‐old infants in 2 experiments were familiarized with multiword utterances synthesized as continuous speech. The words in the utterances were ordered based on a simple finite‐state grammar. Following exposure, infants were tested on novel grammatical and ungrammatical sentences. The results indicate that the infants were able to perform 2 statistical learning tasks in sequence: first segmenting the words from continuous speech, and subsequently discovering the permissible orderings of the words. Given a single set of input, infants were able to acquire multiple levels of structure, suggesting that multiple levels of representation (initially syllable‐level combinations, subsequently word‐level combinations) can emerge during the course of learning.     

Cross-validation methods in principal component analysis: A comparison

In principal component analysis (PCA), it is crucial to know how many principal components (PCs) should be retained in order to account for most of the data variability. A class of “objective” rules for finding this quantity is the class of cross-validation (CV) methods. In this work we compare three CV techniques showing how the performance of these methods depends on the covariance matrix structure. Finally we propose a rule for the choice of the “best” CV method and give an application to real data.