Options to liberalize Social Security disabled widow(er)s benefits

Each month, 200,000 widows and 6,000 widowers receive Social Security disabled widow(er)s benefits, each benefit averaging about $550. Among the most economically at-risk Social Security beneficiaries, their benefits are permanently reduced. This paper reviews the legislative history of the disabled widow(er)s benefit, identifying key decisions that gave shape to this benefit. Social Security program data and six years of Current Population Survey data (March Annual Demographic Files, 1995-2000) are used to profile the economic status of current and potential disabled widows. The analysis, including comparison with other widows, provides strong evidence of economic need among disabled widows with, for example, 44% of disabled widow beneficiaries, ages 50-59, having below-poverty incomes compared with 15% of like-aged non-disabled widows. We conclude that serious consideration should be given to extending eligibility to all widow(er)s disabled before the normal retirement age; to providing a benefit equal to 100% of the deceased spouse's private insurance amount (PIA); to eliminating the unnecessarily restrictive seven-year rule; and to protecting beneficiaries from losing their eligibility to Medicaid. Even in the context of today's heated Social Security debate, we suggest that a rare opportunity may exist to garner bipartisan support for meaningful, low-cost improvements, in a benefit that primarily targets women.     

Uniform Ergodicity of the Particle Gibbs Sampler

The particle Gibbs sampler is a systematic way of using a particle filter within Markov chain Monte Carlo. This results in an off‐the‐shelf Markov kernel on the space of state trajectories, which can be used to simulate from the full joint smoothing distribution for a state space model in a Markov chain Monte Carlo scheme. We show that the particle Gibbs Markov kernel is uniformly ergodic under rather general assumptions, which we will carefully review and discuss. In particular, we provide an explicit rate of convergence, which reveals that (i) for fixed number of data points, the convergence rate can be made arbitrarily good by increasing the number of particles and (ii) under general mixing assumptions, the convergence rate can be kept constant by increasing the number of particles superlinearly with the number of observations. We illustrate the applicability of our result by studying in detail a common stochastic volatility model with a non‐compact state space.     

Strategy Alternatives for Homeland Air and Cruise Missile Defense

Air and cruise missile defense of the U.S. homeland is characterized by a requirement to protect a large number of critical assets nonuniformly dispersed over a vast area with relatively few defensive systems. In this article, we explore strategy alternatives to make the best use of existing defense resources and suggest this approach as a means of reducing risk while mitigating the cost of developing and acquiring new systems. We frame the issue as an attacker‐defender problem with simultaneous moves. First, we outline and examine the relatively simple problem of defending comparatively few locations with two surveillance systems. Second, we present our analysis and findings for a more realistic scenario that includes a representative list of U.S. critical assets. Third, we investigate sensitivity to defensive strategic choices in the more realistic scenario. As part of this investigation, we describe two complementary computational methods that, under certain circumstances, allow one to reduce large computational problems to a more manageable size. Finally, we demonstrate that strategic choices can be an important supplement to material solutions and can, in some cases, be a more cost‐effective alternative.     

Keeping partners together: algorithmic results for the hospitals/residents problem with couples

The Hospitals/Residents problem with Couples (HRC) is a generalisation of the classical Hospitals/Residents problem (HR) that is important in practical applications because it models the case where couples submit joint preference lists over pairs of hospitals (h _i ,h _j ). We consider a natural restriction of HRC in which the members of a couple have individual preference lists over hospitals, and the joint preference list of the couple is consistent with these individual lists in a precise sense. We give an appropriate stability definition and show that, in this context, the problem of deciding whether a stable matching exists is NP-complete, even if each resident’s preference list has length at most 3 and each hospital has capacity at most 2. However, with respect to classical (Gale-Shapley) stability, we give a linear-time algorithm to find a stable matching or report that none exists, regardless of the preference list lengths or the hospital capacities. Finally, for an alternative formulation of our restriction of HRC, which we call the Hospitals/Residents problem with Sizes (HRS), we give a linear-time algorithm that always finds a stable matching for the case that hospital preference lists are of length at most 2, and where hospital capacities can be arbitrary.     

Adolescent Adjustment and Patterns of Parents' Behaviors in Early and Middle Adolescence

In this study, we identified unique clusters of parenting behaviors based on parents' school involvement, community involvement, rule‐setting, and cognitive stimulation with data from the Panel Study of Income Dynamics—Child Development Supplement. In early (n=668) and middle adolescence (n=634), parents who provided high cognitive stimulation (i.e., cognitive enrichment parents) or engaged in all parenting behaviors (i.e., engaged parents) had the highest family income, parent education, and percentage of European Americans. Adolescents of cognitive enrichment or engaged parents often evidenced the highest academic and social adjustment. Adolescents whose parents set a large number of rules (i.e., “Rule setters”) or were also heavily involved in the community (i.e., the “Managers” cluster) had the lowest adjustment.     

Diversity research—what do we currently know about how to manage diverse organizational units?

Diversity with respect to demographic variables such as gender, age, and cultural background, as well as directly job-related characteristics such as tenure, educational specialization, and functional background is both a challenge and an opportunity. We review the extant literature on how best to manage diverse organizational units. We discuss the definition and conceptualization of diversity, its direct effects on team performance and team member satisfaction, as well as the mediating variables that explain these effects and the moderating variables that determine when the positive effects of diversity are likely to prevail over the negative effects. We conclude by offering managerial suggestions on how to leverage diversity’s potential.