Sourcing Decisions with Competitive Suppliers and Imperfect Information

Manufacturers often must choose between outsourcing and producing internally. This choice is complex and influenced by a variety of factors, including the costs and capabilities of the potential suppliers. In addition, if the manufacturer outsources, he must design the sourcing process. We study the manufacturer's outsourcing decision, with a focus on the impact of the sourcing process on that decision. We consider a setting in which the manufacturer has imperfect information regarding the suppliers' costs and capabilities, and we assume that the manufacturer uses a two‐stage sourcing process. The first stage is the qualification stage, in which the manufacturer seeks to reduce the uncertainty regarding the suppliers' capabilities. The second stage is the supplier selection stage, in which the manufacturer selects among the qualified suppliers on the basis of price. We first characterize the optimal design of the two‐stage process, and then consider the outsourcing decision. We demonstrate several trade‐offs. Vertical integration enables the manufacturer to reduce uncertainty and extract all of the profits of production. However, outsourcing enables the manufacturer to take advantage of the (potentially) lower costs and higher capabilities of the suppliers, particularly if competition between suppliers can be encouraged. We find that the manufacturer is more likely to vertically integrate when the warranty cost and the cost of exerting effort during qualification are large, and when there is significant uncertainty regarding the suppliers' capabilities. The manufacturer is more likely to outsource when the suppliers' costs (capabilities) are low (high), and when the number of suppliers is large.     

Sexual minority youth in romantic relationships: Associations with youth well-being

This study investigated differences in depressive symptoms, loneliness, and self-esteem for monosexual (lesbian, gay) and plurisexual (bisexual, pansexual, queer) sexual minority youth (SMY) by relationship status (single, partnered) and relationship configuration (same-gender partner, different-gender partner). Participants included 338 SMY (M_age = 19.10 years) who reported on their relationship status, partner's gender identity, well-being, and ability to confide in partner about LGBTQ issues. Results indicated that for plurisexual youth, single status was associated with greater loneliness; plurisexual youth with same-gender partners reported fewer depressive symptoms and marginally greater ability to confide in their partner about LGBTQ issues than those with different-gender partners. Findings reveal similarities across SMY while also highlighting some unique challenges among plurisexual youth with different-gender partners.     

Identification and Estimation of a Discrete Game of Complete Information

We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute all of the Nash equilibria to a game, we propose simulation‐based estimators for static, discrete games. We demonstrate that the model is identified under weak functional form assumptions using exclusion restrictions and an identification at infinity approach. Monte Carlo evidence demonstrates that the estimator can perform well in moderately sized samples. As an application, we study entry decisions by construction contractors to bid on highway projects in California. We find that an equilibrium is more likely to be observed if it maximizes joint profits, has a higher Nash product, uses mixed strategies, and is not Pareto dominated by another equilibrium.     

Ranked sparsity: a cogent regularization framework for selecting and estimating feature interactions and polynomials

AStA Advances in Statistical Analysis - We explore and illustrate the concept of ranked sparsity, a phenomenon that often occurs naturally in modeling applications when an expected disparity exists...     

Cognitive reappraisal and need to belong predict prosociality in Mexican-origin adolescents

This 2-year longitudinal study examined Mexican-origin adolescents’ need to belong and cognitive reappraisal as predictors of multiple forms of prosocial behavior (i.e., general, emotional, and public prosocial behaviors). Prosocial behaviors, which are actions intended to benefit others, are hallmarks of social proficiency in adolescence and are influenced by intrapersonal abilities and motivations that typically develop during adolescence. Yet, few studies of Mexican-origin or other U.S. Latinx youths have examined whether such individual difference characteristics, specifically social motivation and emotion regulation skills, support prosocial behavior. In a sample of 229 Mexican-origin youth (M_age = 17.18 years, SD = .42, 110 girls), need to belong, cognitive reappraisal, and general prosocial behaviors were assessed at ages 17 and 19. Emotional and public forms of prosociality also were assessed at age 19. Cognitive reappraisal was positively associated with concurrent general prosociality at age 17, whereas need to belong was positively associated with concurrent public prosociality at age 19. Moderation analyses revealed that general and emotional types of prosocial behaviors at age 19 were lowest for youth with both lower need to belong and less use of cognitive reappraisal at 19 years. Greater cognitive reappraisal skills and need to belong may reflect distinct motivations for engaging in varying forms of prosocial behavior in late adolescence.     

Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts

High levels of prenatal alcohol exposure (PAE) result in significant cognitive deficits in children, but the exact nature of the dose-response relationship is less well understood. To investigate this relationship, data were assembled from six longitudinal birth cohort studies examining the effects of PAE on cognitive outcomes from early school age through adolescence. Structural equation models (SEMs) are a natural approach to consider, because of the way they conceptualise multiple observed outcomes as relating to an underlying latent variable of interest, which can then be modelled as a function of exposure and other predictors of interest. However, conventional SEMs could not be fitted in this context because slightly different outcome measures were used in the six studies. In this paper we propose a multi-group Bayesian SEM that maps the unobserved cognition variable to a broad range of observed outcomes. The relation between these variables and PAE is then examined while controlling for potential confounders via propensity score adjustment. By examining different possible dose-response functions, the proposed framework is used to investigate whether there is a threshold PAE level that results in minimal cognitive deficit.