Inference on Causal Effects in a Generalized Regression Kink Design

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. We characterize a broad class of models in which a sharp “Regression Kink Design” (RKD or RK Design) identifies a readily interpretable treatment‐on‐the‐treated parameter (Florens, Heckman, Meghir, and Vytlacil (2008)). We also introduce a “fuzzy regression kink design” generalization that allows for omitted variables in the assignment rule, noncompliance, and certain types of measurement errors in the observed values of the assignment variable and the policy variable. Our identifying assumptions give rise to testable restrictions on the distributions of the assignment variable and predetermined covariates around the kink point, similar to the restrictions delivered by Lee (2008) for the regression discontinuity design. Using a kink in the unemployment benefit formula, we apply a fuzzy RKD to empirically estimate the effect of benefit rates on unemployment durations in Austria.     

Consumption Dynamics During Recessions

Are there times when durable spending is less responsive to economic stimulus? We argue that aggregate durable expenditures respond more sluggishly to economic shocks during recessions because microeconomic frictions lead to declines in the frequency of households' durable adjustment. We show this by first using indirect inference to estimate a heterogeneous agent incomplete markets model with fixed costs of durable adjustment to match consumption dynamics in PSID microdata. We then show that aggregating this model delivers an extremely procyclical Impulse Response Function (IRF) of durable spending to aggregate shocks. For example, the response of durable spending to an income shock in 1999 is estimated to be almost twice as large as if it occurred in 2009. This procyclical IRF holds in response to standard business cycle shocks as well as in response to various policy shocks, and it is robust to general equilibrium. After estimating this robust theoretical implication of micro frictions, we provide additional direct empirical evidence for its importance using both cross‐sectional and time‐series data.     

POLITICAL SELECTION IN CHINA: THE COMPLEMENTARY ROLES OF CONNECTIONS AND PERFORMANCE

Who becomes a top politician in China? We focus on provincial leaders—a pool of candidates for top political office—and examine how their chances of promotion depend on their performance in office and connections with top politicians. Our empirical analysis, based on the curriculum vitae of Chinese politicians, shows that connections and performance are complements in the Chinese political selection process. This complementarity is stronger the younger provincial leaders are relative to their connected top leaders. To provide one plausible interpretation of these empirical findings, we propose a simple theory in which the complementarity arises because connections foster loyalty of junior officials to senior ones, thereby allowing incumbent top politicians to select competent provincial leaders without risking being ousted. Our findings shed some light on why a political system known for patronage can still select competent leaders.     

An Examination of How Supervisors Influence Their Subordinates to Engage in Environmental Behaviors

Employee engagement in environmental behaviors is an important topic in operations management. Drawing upon stakeholder, commitment, and organizational support theories, this study creates and tests an empirical model of how store managers (i.e., supervisors) influence their direct reports (i.e., subordinates) to become engaged in environmental behaviors. Based on a dataset derived from supervisors and their subordinates who are employed at the same grocery store location across a large retail grocery chain, we test our study's nomological model and find support for the linkages proposed. Key research and managerial implications are discussed.     

Inference for $$L_2$$L2 -Boosting

We propose a statistical inference framework for the component-wise functional gradient descent algorithm (CFGD) under normality assumption for model errors, also known as $$L_2$$-Boosting. The CFGD is one of the most versatile tools to analyze data, because it scales well to high-dimensional data sets, allows for a very flexible definition of additive regression models and incorporates inbuilt variable selection. Due to the variable selection, we build on recent proposals for post-selection inference. However, the iterative nature of component-wise boosting, which can repeatedly select the same component to update, necessitates adaptations and extensions to existing approaches. We propose tests and confidence intervals for linear, grouped and penalized additive model components selected by $$L_2$$-Boosting. Our concepts also transfer to slow-learning algorithms more generally, and to other selection techniques which restrict the response space to more complex sets than polyhedra. We apply our framework to an additive model for sales prices of residential apartments and investigate the properties of our concepts in simulation studies.     

Model averaging inconcentration–QT analyses

This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Association of sexual abstinence in adolescence with mental health in adulthood

We examined whether adolescent sexual abstinence predicts better adult mental health. 1,917 adolescents, recruited from middle schools at age 13, were surveyed at ages 13, 18, 23, and 29. In bivariate analyses, adolescent sexual abstinence was associated with better mental health at age 29 for females, but not males; three adolescent factors, educational prospects, family bonding, and unconventionality were investigated as explanatory variables of this relationship. The abstinence-mental health relationship was nonsignificant when educational prospects was included in multivariate models, and marginally significant when family bonding and unconventionality were included; all three explanatory factors accounted for significant proportions of the variance in adult mental health. Girls who are uninvolved in school, have weak family backgrounds, and exhibit unconventionality may have poor adult mental health, whether or not they abstain from sex in adolescence. Interventions that strengthen adolescents' connections to families and schools may reduce risk for long-term mental health problems.     

Effects of a single-lesson tobacco prevention curriculum on knowledge, skill identification and smoking intention

One in five students report experimenting with tobacco before the age of 13 and most prevention efforts take place in the school setting. This study measures the effect of a single-lesson tobacco prevention curriculum, conducted by a health education center, focusing on knowledge of tobacco, ability to identify refusal techniques, and intent not to smoke. Data were collected, via electronic keypads, from students visiting a non-school, health education center in Michigan (n = 704 intervention and 85 comparison). Contingency table Chi-squared tests and t-tests demonstrated that a single lesson can improve general knowledge and ability to identify appropriate refusal techniques. Improvement in intent not to smoke was not significant because both groups had very high intent prior to implementation. Similar to results from other programs, multivariate logistic regression of gender, general knowledge, and skill identification revealed that only the skill variable was associated with intent not to smoke at pretest. Recommendations are given for further research and for designing more effective curricula or programs.     

Response Order Effects in Dichotomous Categorical Questions Presented Orally: The Impact of Question and Respondent Attributes

Using data from 548 experiments in telephone surveys conductedby the Gallup Organization, we explored how attributes of questionsand respondents moderate response order effects in dichotomouscategorical questions. These effects were predominantly recencyeffects and occurred most in questions that were more difficultto comprehend (especially among respondents with the least education),with response choices that were more difficult to comprehend(because they were complete sentences instead of words or phrasesand because they were not mutually exclusive), and that wereasked after many prior questions. Recency effects were alsomore common in questions that explicitly or implicitly encouragedrespondents to wait until they had heard all the answer choicesbefore formulating a judgment than in questions that inducedrespondents to begin formulating a judgment before all the answerchoices had been read (especially among the least educated respondents).A study of interviewer behavior revealed patterns of pausingbetween and within sentences that help to explain why some typesof questions are especially prone to recency effects and othersare not.