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.     

Frailty modelling approaches for semi-competing risks data

Lifetime Data Analysis - In the semi-competing risks situation where only a terminal event censors a non-terminal event, observed event times can be correlated. Recently, frailty models with an...     

Unveiling the Canvas Ceiling: A Multidisciplinary Literature Review of Refugee Employment and Workforce Integration

Increasing levels of displacement and the need to integrate refugees in the workforce pose new challenges to organizations and societies. Extant research on refugee employment and workforce integration currently resides across various disconnected disciplines, posing a significant challenge for management scholars to contribute to timely and relevant solutions. In this paper, we endeavour to address this challenge by reviewing and synthesizing multidisciplinary literature on refugee employment and workforce integration. Using a relational framework, we organize our findings around three levels of analysis – institutional, organizational and individual – to outline the complexity of factors affecting refugees’ employment outcomes. Based on our analysis, we introduce and elaborate on the phenomenon of the canvas ceiling ? a systemic, multilevel barrier to refugee workforce integration and professional advancement. The primary contributions of this paper are twofold. First, we map and integrate the multidisciplinary findings on the challenges of refugee workforce integration. Second, we provide management scholarship with a future research agenda to address the knowledge gap identified in this review and advance practical developments in this domain.     

Collective versus Individual Effects in Survival Analysis of Multiple Failures

In survival analysis, we sometimes encounter data with multiple censored outcomes. Under certain scenarios, partial or even all covariates have ‘similar’ relative risks on the multiple outcomes in the Cox regression analysis. The similarity in covariate effects can be quantified using the proportionality of regression coefficients. Identifying the proportionality structure, or equivalently whether covariates have individual or collective effects, may have important scientific implications. In addition, it can lead to a smaller set of unknown parameters, which in turn results in more accurate estimation. In this article, we develop a novel approach for identifying the proportionality structure. Simulation shows the satisfactory performance of the proposed approach and its advantage over estimation under no assumed structure. We analyse three datasets to demonstrate the practical application of the proposed approach.     

Dealing with the Initial Observation in the LM Unit Root Test

This article proposes a linearly weighted unit root test with a new weighting scheme which reflects the trade-off in power between the ADF and LM tests regarding the initial value of a time series. Simulation results indicate that the proposed test has better power performance and works better than other available tests in the literature for a range of initial conditions.     

Measuring Social Tension from Income Class Segregation

We develop an index that effectively measures the level of social tension generated by income class segregation. We adopt the basic concepts of between-group difference (or alienation) and within-group similarity (or identification) from the income [bi]polarization literature; but we allow for asymmetric degrees of between-group antagonism in the alienation function, and construct a more effective identification function using both the relative degree of within-group clustering and the group size. To facilitate statistical inference, we derive the asymptotic distribution of the proposed measure using results from U-statistics. As the new measure is general enough to include existing income polarization indices as well as the Gini index as special cases, the asymptotic result can be readily applied to these popular indices. Evidence from the Panel Study of Income Dynamics data suggests that, while the level of social tension shows an upward trend over the sample period of 1981 to 2005, government’s taxes and transfers have been effective in reducing the level of social tension significantly.     

Finie mixures of canonical fundamenal skew $$$$-disribuions

This paper introduces a finite mixture of canonical fundamental skew \(t\) (CFUST) distributions for a model-based approach to clustering where the clusters are asymmetric and possibly long-tailed (in: Lee and McLachlan, arXiv:1401.8182 [statME], 2014b). The family of CFUST distributions includes the restricted multivariate skew \(t\) and unrestricted multivariate skew \(t\) distributions as special cases. In recent years, a few versions of the multivariate skew \(t\) (MST) mixture model have been put forward, together with various EM-type algorithms for parameter estimation. These formulations adopted either a restricted or unrestricted characterization for their MST densities. In this paper, we examine a natural generalization of these developments, employing the CFUST distribution as the parametric family for the component distributions, and point out that the restricted and unrestricted characterizations can be unified under this general formulation. We show that an exact implementation of the EM algorithm can be achieved for the CFUST distribution and mixtures of this distribution, and present some new analytical results for a conditional expectation involved in the E-step.     

Stochastically optimal bootstrap sample size for shrinkage-type statistics

In nonregular problems where the conventional \(n\) out of \(n\) bootstrap is inconsistent, the \(m\) out of \(n\) bootstrap provides a useful remedy to restore consistency. Conventionally, optimal choice of the bootstrap sample size \(m\) is taken to be the minimiser of a frequentist error measure, estimation of which has posed a major difficulty hindering practical application of the \(m\) out of \(n\) bootstrap method. Relatively little attention has been paid to a stronger, stochastic, version of the optimal bootstrap sample size, defined as the minimiser of an error measure calculated directly from the observed sample. Motivated by this stronger notion of optimality, we develop procedures for calculating the stochastically optimal value of \(m\). Our procedures are shown to work under special forms of Edgeworth-type expansions which are typically satisfied by statistics of the shrinkage type. Theoretical and empirical properties of our methods are illustrated with three examples, namely the James–Stein estimator, the ridge regression estimator and the post-model-selection regression estimator.     

Sampling Telephone Numbers and Adults, Interview Length, and Weighting in The California Health Interview Survey Cell Phone Pilot Study

This article describes several features included in a CaliforniaHealth Interview Survey cell phone pilot study that differ fromearlier cell phone surveys conducted in the United States. Onedifference is that the study used a screening design and onlyadults living in cell-only households were interviewed. Mostof the previous studies used dual frame designs. Another differencewas the development and implementation of a within-householdadult sampling procedure to cover adults when cell phones wereshared in the household. The study was also intended to determineif conducting a cell phone interview of the same scope and lengthas a regular telephone interview was feasible. Most previoussurveys were focused on cell phone topics and were shorter thanthe comparable landline surveys. We then explore some interestingproblems that arise in weighting a cell phone survey using ascreening design. We conclude with a discussion of planninga new cell phone survey in 2007 that incorporates findings fromthis study.     

College and university compliance with a required meningococcal vaccination law

OBJECTIVE: Maryland became the first state to pass a vaccination law requiring college and university students living on campus to obtain a meningococcal vaccination or to sign a waiver refusing vaccination because college students are at increased risk for disease. The authors sought to identify how Maryland colleges addressed the law and determine whether schools were in full compliance. PARTICIPANTS: The authors surveyed 32 college/university administrators via a self-administered questionnaire. METHODS: The authors calculated vaccination and waiver rates and assessed compliance with the law overall and with specific law components. RESULTS: Among 28 participating schools, annual vaccination rates and waiver rates among students during 2000-2004 ranged from 66%-76% and 12%-17%, respectively. Two (7%) schools were compliant with all components of the law. CONCLUSIONS: Mandatory vaccination laws do not ensure compliance at the college and university level. Mandatory reporting, increased education, and collaboration between colleges and universities and public health agencies are needed.