Sequential Monte Carlo for rare event estimation

This paper discusses a novel strategy for simulating rare events and an associated Monte Carlo estimation of tail probabilities. Our method uses a system of interacting particles and exploits a Feynman-Kac representation of that system to analyze their fluctuations. Our precise analysis of the variance of a standard multilevel splitting algorithm reveals an opportunity for improvement. This leads to a novel method that relies on adaptive levels and produces, in the limit of an idealized version of the algorithm, estimates with optimal variance. The motivation for this theoretical work comes from problems occurring in watermarking and fingerprinting of digital contents, which represents a new field of applications of rare event simulation techniques. Some numerical results show performance close to the idealized version of our technique for these practical applications.     

Incarceration and Household Asset Ownership

A considerable literature documents the deleterious economic consequences of incarceration. However, little is known about the consequences of incarceration for household assets—a distinct indicator of economic well-being that may be especially valuable to the survival of low-income families—or about the spillover economic consequences of incarceration for families. In this article, we use longitudinal data from the Fragile Families and Child Wellbeing Study to examine how incarceration is associated with asset ownership among formerly incarcerated men and their romantic partners. Results, which pay careful attention to the social forces that select individuals into incarceration, show that incarceration is negatively associated with ownership of a bank account, vehicle, and home among men and that these consequences for asset ownership extend to the romantic partners of these men. These associations are concentrated among men who previously held assets. Results also show that post-incarceration changes in romantic relationships are an important pathway by which even short-term incarceration depletes assets.     

Survival and lifetime data analysis with a flexible class of distributions

We introduce a general class of continuous univariate distributions with positive support obtained by transforming the class of two-piece distributions. We show that this class of distributions is very flexible, easy to implement, and contains members that can capture different tail behaviours and shapes, producing also a variety of hazard functions. The proposed distributions represent a flexible alternative to the classical choices such as the log-normal, Gamma, and Weibull distributions. We investigate empirically the inferential properties of the proposed models through an extensive simulation study. We present some applications using real data in the contexts of time-to-event and accelerated failure time models. In the second kind of applications, we explore the use of these models in the estimation of the distribution of the individual remaining life.     

What Influences the Location of Nonprofit Organizations? A Spatial Analysis in Brazil

What are the local characteristics influencing where new nonprofits will be established? How important are community needs, available resources, or the existence of similar organizations for nonprofits’ location? This paper analyzes how the characteristics of 5562 Brazilian municipalities in the year 2000 help explain the location of nonprofits formed between 2001 and 2010. Based on geographically weighted regressions, results indicate that neither access to resources nor poor socioeconomic indicators are powerful influences on nonprofit location in Brazilian municipalities. The main predictor of nonprofit entry is a high pre-existing density of nonprofits in that area. These findings, however, vary across regions and nonprofit fields of activity. By mapping the effect of key explanatory variables, this paper helps understand nonprofit location. The methodology and findings on nonprofit location presented here are novel and may contribute to research in other countries.     

Bureaucratic Neglect and Oppression in Child Welfare: Historical Precedent and Implications for Current Practice

Historically, child maltreatment has been seen as an issue warranting the involvement of the American government. However, over time, the definition of child maltreatment has changed; typically, maltreatment is often understood as a violation of the parental right to care for and protect a child. Consequently, the government, through systems such as child protective services is expected to be the acceptable parental alternative. As illustrated by the numerous negative outcomes experienced, it is clear that the system is not meeting the needs of abused and neglected children. This bureaucratic neglect is allowed to occur because of population primarily served by the child welfare system, the poor and families of color. In this way, dynamics of power and privilege manifest in the differing expectations of appropriate care between biological parents and the foster care system.     

Coalitions of Actors and Managerial Innovations in the Healthcare and Social Healthcare Sector

This paper studies the behavior of a variety of stakeholders around the adoption of managerial innovations desired by operational managers of health services institutions. We show that if the operational manager may cause the managerial innovation, the tool prospective is subject to power games around coalitions of actors. The study of several management situations in health services institutions enables us, using the game theory, to highlight the “winning”, “losing” and “uncertain” coalitions that can achieve operational management within the establishment to settle a managerial innovation.     

Load-Oriented Order Release (LOOR) revisited: bringing it back to the state of the art

In the workload control literature, the Load-Oriented Order Release (LOOR) approach has been neglected since its robustness was questioned at the end of the 1990s. This paper revisits LOOR and evaluates whether its performance can be improved in two ways. First, an intermediate pull release mechanism is added to avoid starvation between periodic release events. This mechanism was recently shown to be effective at improving the performance of a state-of-the-art release method known as LUMS COR. Second, an integer linear programming model is used to manage the trade-off between the timing and load balancing functions of order release. The two refinements are assessed using simulations of different shop configurations, which allow us to evaluate robustness. Results demonstrate that the refinements contribute to improving the performance of LOOR such that it can even outperform LUMS COR. Perhaps counter-intuitively, putting more emphasis on load balancing than on the urgency of individual orders is shown to lead to a lower percentage of tardy orders. Overall, the improvements mean that concerns about LOOR’s robustness are no longer valid – it now appears suitable for a wide range of shops found in practice.