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.     

The Development of Peer Interaction in Infancy: Exploring the Dyadic Processes

Peer interaction is an important component of children's social repertoires that is associated with a variety of developmental outcomes and life skills. The present study provides an in‐depth study of early dyadic peer behaviors during the infancy period, during which social competence with peers is first being developed. Results from variable‐centered analyses highlight the effectiveness of behaviors, such as offering objects to peers, and point to the importance of the social context set by a peer's prior social behavior and processes for eliciting peer responses. Findings from person‐centered analyses reveal marked individual differences in the processes through which infants are successful in eliciting responses from their peers, illustrating the presence of multiple pathways to achieving social competence with peers.     

Are Female Executives Over‐represented in Precarious Leadership Positions?

We use a sample of CEO appointments at US corporations over the years 1992–2004 to test the 'glass cliff' hypothesis, which posits that females are appointed to leadership positions at firms that are in a precarious financial condition. Our analysis utilizes three measures of stock-price-based financial performance and two distinct control samples of appointments of males to the CEO position. We find that corporate performance preceding CEO appointments tends to favor females, implying that females (males) are appointed to the CEO position largely at times when the firm is in relatively better (worse) financial health. Disaggregating the data by appointments in up versus down markets, at high-risk versus low-risk firms, and by calendar time yield similar conclusions. There appears to be no glass cliff facing female CEOs at US firms. Our findings suggest a need for additional research to identify where and for what types of positions this phenomenon is prevalent.     

Transforming sub-Saharan Africa

This article provides an analysis of my personal experience and research on the need for sub-Saharan African economic transformation. It contains relevant references to econometric modeling which are consistent with this analysis. After presenting the causes of African failures, ranging from the alleged role of slavery and colonization, to trade composition and relative decline, to present day problems of governance, low level of foreign investment in Africa, and mass unemployment, the article concludes with an agenda for the transformation of sub-Saharan Africa.     

The complementarity of internal integration and product modularity: An empirical study of their interaction effect on competitive capabilities

Modular product design and internal integration are commonly adopted by manufacturers to improve operational performance. A number of studies argue that the adoption of product modularity significantly alters organization design, which affects the impact of internal integration on competitive capabilities. This paper thus aims to empirically explore the individual effects as well as interaction effects of product modularity and internal integration on competitive capabilities. The competitive capabilities studied in this paper include product innovativeness, low price, product quality, delivery, flexibility and customer services. After analysing the data from 251 Hong Kong manufacturers through moderated multiple regression analysis, the study found that better internal integration can significantly improve product innovativeness, product quality, delivery, flexibility and customer services, while a high level of product modularity enhances product innovativeness, flexibility and customer services. More importantly, the study shows that internal integration and product modularity can interact to improve product innovativeness and product quality. These results enhance our understanding of the interaction of product design and organizational coordination.     

Teacher–Child Relationships from Kindergarten to Sixth Grade: Early Childhood Predictors of Teacher-perceived Conflict and Closeness

This article examined general trends in teacher-reported conflict and closeness among 878 children from kindergarten through sixth grade, and examined early childhood characteristics that predict differences in initial levels and growth of conflict and closeness over time. Results indicated modest stability of teacher-perceived conflict and closeness through sixth grade, with relatively greater stability in perceptions of conflict. Levels of conflict at kindergarten were higher for children who were male, Black, had greater mean hours of childcare, had lower academic achievement scores, and had greater externalizing behavior. Children identified as Black and those with less sensitive mothers were at greater risk for increased conflict with teachers over time. Levels of teacher-reported closeness were lower when children were male, had lower quality home environments, and had lower academic achievement scores. The gap in closeness ratings between males and females increased in the middle elementary school years. Additional analyses were conduced to explore differences in teacher ratings of conflict between Black and White students.     

Alternative Methods for Computing the Sensitivity of Complex Surveillance Systems

Stochastic scenario trees are a new and popular method by which surveillance systems can be analyzed to demonstrate freedom from pests and disease. For multiple component systems—such as a combination of a serological survey and systematically collected observations—it can be difficult to represent the complete system in a tree because many branches are required to represent complex conditional relationships. Here we show that many of the branches of some scenario trees have identical outcomes and are therefore redundant. We demonstrate how to prune branches and derive compact representations of scenario trees using matrix algebra and Bayesian belief networks. The Bayesian network representation is particularly useful for calculation and exposition. It therefore provides a firm basis for arguing disease freedom in international forums.     

Adolescent girls’ race/ethnic status, identities, and drive for thinness

Using data from 7272 adolescent US girls, we explore how girls’ race/ethnic group status affects their bodyweight, perceptions of overweight, and weight control practices. We hypothesize that a girl’s race/ethnic status influences her basic identity which in turn prompts her to adopt or reject a “drive for thinness.” After controlling for family and peer support, school engagement, family SES, maturation, and family structure, we find that girls’ race/ethnic status influences their susceptibility to the thinness ideals of mainstream culture. African American girls weigh more than Asian, Hispanic, or White girls, but at any given weight they perceive themselves as overweight and attempt to control their weight less. Asian American and White girls invest most in thinness dynamics. Some evidence also suggests girls from lower SES families are less driven to be thin. Our results affirm the utility of viewing material bodies as “situations” that are experienced and interpreted in accord with identity group relations and dynamics.     

Expected Utility Consistent Extensions of Preferences

We consider the problem of extending a (complete) order over a set to its power set. The extension axioms we consider generate orderings over sets according to their expected utilities induced by some assignment of utilities over alternatives and probability distributions over sets. The model we propose gives a general and unified exposition of expected utility consistent extensions whilst it allows to emphasize various subtleties, the effects of which seem to be underestimated – particularly in the literature on strategy-proof social choice correspondences.      

The Collapsing Choice Theory: Dissociating Choice and Judgment in Decision Making

Decision making theory in general, and mental models in particular, associate judgment and choice. Decision choice follows probability estimates and errors in choice derive mainly from errors in judgment. In the studies reported here we use the Monty Hall dilemma to illustrate that judgment and choice do not always go together, and that such a dissociation can lead to better decision-making. Specifically, we demonstrate that in certain decision problems, exceeding working memory limitations can actually improve decision choice. We show across four experiments that increasing the number of choice alternatives forces people to collapse choices together, resulting in better decision-making. While choice performance improves, probability judgments do not change, thus demonstrating an important dissociation between choice and probability judgments. We propose the Collapsing Choice Theory (CCT) which explains how working memory capacity, probability estimation, choice alternatives, judgment, and regret all interact and effect decision quality.