EFFECTS OF EXPOSURE ON PREVALENCE AND CUMULATIVE RELATIVE RISK: DIRECT AND INDIRECT EFFECTS IN A RECURSIVE HAZARD MODEL

This paper outlines decomposition methods for assessing how exposure affects prevalence and cumulative relative risk. Let     x     denote a vector of exogenous covariates and suppose that a single dimension of time   t   governs two event processes     T ₁  and   T ₂.    If the occurrence of the event     T ₁    determines entry into the risk of the event     T ₂,    then subgroup variation in     T ₁    will affect the prevalence     T ₂,    even if subgroups in the population are otherwise identical. Although researchers often acknowledge this phenomenon, the literature has not provided procedures to assess the magnitude of an exposure effect of     T ₁    on the prevalence of     T ₂.    We derive decompositions that assess how variation in exposure generated by direct and indirect effects of the covariates     x     affect measures of absolute and relative prevalence of     T ₂.    We employ a parametric but highly flexible specification for baseline hazard for the     T ₁  and   T ₂    processes and use the resulting parametric proportional hazard model to illustrate the direct and indirect effects of family structure when     T ₁    is age at first sexual intercourse and     T ₂    is age at a premarital first birth for data on a cohort of non-hispanic white U.S. women.     

Analyzing the Homeland Security of the U.S.-Mexico Border

We develop a mathematical optimization model at the intersection of homeland security and immigration, that chooses various immigration enforcement decision variables to minimize the probability that a terrorist can successfully enter the United States across the U.S.-Mexico border. Included are a discrete choice model for the probability that a potential alien crosser will attempt to cross the U.S.-Mexico border in terms of the likelihood of success and the U.S. wage for illegal workers, a spatial model that calculates the apprehension probability as a function of the number of crossers, the number of border patrol agents, and the amount of surveillance technology on the border, a queueing model that determines the probability that an apprehended alien will be detained and removed as a function of the number of detention beds, and an equilibrium model for the illegal wage that balances the supply and demand for work and incorporates the impact of worksite enforcement. Our main result is that detention beds are the current system bottleneck (even after the large reduction in detention residence times recently achieved by expedited removal), and increases in border patrol staffing or surveillance technology would not provide any improvements without a large increase in detention capacity. Our model also predicts that surveillance technology is more cost effective than border patrol agents, which in turn are more cost effective than worksite inspectors, but these results are not robust due to the difficulty of predicting human behavior from existing data. Overall, the probability that a terrorist can successfully enter the United States is very high, and it would be extremely costly and difficult to significantly reduce it. We also investigate the alternative objective function of minimizing the flow of illegal aliens across the U.S.-Mexico border, and obtain qualitatively similar results.     

Sick building syndrome and perceived indoor environmental quality: A survey of apartment buildings in Hong Kong

The outbreak of a highly communicable disease, SARS, in Asia in 2003 has revealed the health risk of living in a high-density environment. To show the important connection between human health and environmental quality, this study surveys the prevalence of sick building syndrome (SBS) among apartment residents and their evaluation of indoor environmental quality (IEQ). Based on a sample of 748 households living in Hong Kong, two interesting findings are revealed: (1) nasal discomfort was the commonest home-related SBS symptom despite the absence of any central ventilation system in apartment buildings; (2) noise, rather than ventilation, was the major IEQ problem perceived by residents. Our statistical analysis further showed that residents with SBS symptoms were less satisfied with their IEQ than those without. That is, despite a positive evaluation of specific IEQ criteria with respect to the building residents lived in, if they reported feeling SBS related symptoms, the overall IEQ evaluation of their building could still be negative. This perception bias gives rise to a sample selection problem in measuring perceived IEQ, which has implications on housing management practices and the formulation of a healthy housing policy.     

Technology transfer concerns of college graduates with disabilities: Profiles in transition from higher education to competitive careers

The article describes the technology transfer concerns reported by a small sample (N=14) of recent college graduates with disabilities. In structured, in-depth interviews, researchers asked respondents to reflect on the extent to which they had utilized technology resources during their college years in preparation for the world of work. Results suggest that colleges and universities need to play a more active role in introducing students with disabilities to both generalized and assistive technology services.     

Sex offender notification and protective behavior

A primary purpose of sex offender community notification statutes is to give community members the opportunity to engage in precautionary behavior to prevent victimization. This exploratory study examines the effect of notification by comparing the behavior of 87 Hamilton County, Ohio, residents receiving sex offender notification to the behavior of 149 other residents who had not received notification. The findings indicate that notified respondents are significantly more likely to engage in behaviors to protect themselves and others from victimization, and to engage in community reporting behavior.     

Out-of-Home Placement of Children and Economic Factors: An Empirical Analysis

In this paper, we use data from the National Longitudinal Survey of Youth (NLSY) to estimate the effects of income, maternal employment, family structure, and public policies on several measures of childrens living arrangements. We use both linear probability models and discrete-time event history models to explore the effects of these factors on: (1) the probability that a child is living out-of-home in a given year; (2) the probability that a child is removed from home in a given year, conditional on the child living at home in the previous year; (3) the probability that a child is removed from home for the first time; (4) the probability that a child is reunified with his/her biological parent(s) given that the child was living out-of-home in the previous year. We also analyze whether these estimates differ by types of out-of-home placements. Our results suggest that children from lower-income, single-mother, and mother–partner families are considerably more likely both to be living out-of-home and to be removed from home. A change in family structure also tends to place a child at higher risk of an out-of-home living arrangement, unless this transition functions to bring a childs father back into the household. Maternal work appears to increase the probability that a child lives at home. Additionally, once a removal has taken place, we do not find a relationship between income and the probability of a family reunification, but we do find that single-mother and mother–partner families are less likely to reunify. Finally, our analyses provide some evidence that welfare benefit levels are negatively related to out-of-home placements.Funding for this project was provided the National Institute of Child Health and Human Development through grant number 5 F32 HD044 302-02. We are grateful to Shoshana Grossbard-Shechtman, Jennifer Hill, Sanders Korenman, Leonard Lopoo, Katherine Magnuson, and Christina Paxson for their excellent comments and advice.JEL Classification: D10, I30, J13     

Evaluating the impact of utility company billing plans on residential energy consumption

Many utility companies offer their customers the choice of participation in an average payment plan, which enables them to pay a fixed sum for their utility bill each month (with final settlement at the end of the billing year), instead of the conventional “pay as you go” billing procedure. Because customers on average payment plans are protected from paying large bills during peak energy-use seasons and because the information about monthly energy use and its cost is perhaps less salient to them, it was hypothesized that customers on the average payment plan would use more electricity than customers not on the plan. Using a nonequivalent control group design, the electricity consumption of a selection of customers of two utility companies (Ns = 475 and 74) was examined. The results showed that there was no evidence to support the hypothesis. Since the logic of hypothesis testing does not permit the ready acceptance of the null hypothesis, several procedural, methodological, and statistical points were made to buttress the conclusion that the average payment plans had no effect on electricity consumption.