Signaling to Partially Informed Investors in the Newsvendor Model

We analyze a signaling game between the manager of a firm and an investor in the firm. The manager has private information about the firm's demand and cares about the short‐term stock price assigned by the investor. Previous research has shown that under continuous decision choices and the Intuitive Criterion refinement, the least‐cost separating equilibrium will result, in which a low‐quality firm chooses its optimal capacity and a high‐quality firm over‐invests in order to signal its quality to investors. We build on this research by showing the existence of pooling outcomes in which low‐quality firms over‐invest and high‐quality firms under‐invest so as to provide identical signals to investors. The pooling equilibrium is practically appealing because it yields a Pareto improvement compared to the least‐cost separating equilibrium. Distinguishing features of our analysis are that: (i) we allow the capacity decision to have either discrete or continuous support, and (ii) we allow beliefs to be refined based on either the Undefeated refinement or the Intuitive Criterion refinement. We find that the newsvendor model parameters impact the likelihood of a pooling outcome, and this impact changes in both sign and magnitude depending on which refinement is used.     

Constant factor approximation for the weighted partial degree bounded edge packing problem

In the partial degree bounded edge packing problem (PDBEP), the input is an undirected graph \(G=(V,E)\) with capacity \(c_v\in {\mathbb {N}}\) on each vertex v. The objective is to find a feasible subgraph \(G'=(V,E')\) maximizing \(|E'|\), where \(G'\) is said to be feasible if for each \(e=\{u,v\}\in E'\), \(\deg _{G'}(u)\le c_u\) or \(\deg _{G'}(v)\le c_v\). In the weighted version of the problem, additionally each edge \(e\in E\) has a weight w(e) and we want to find a feasible subgraph \(G'=(V,E')\) maximizing \(\sum _{e\in E'} w(e)\). The problem is already NP-hard if \(c_v = 1\) for all \(v\in V\) (Zhang in: Proceedings of the joint international conference on frontiers in algorithmics and algorithmic aspects in information and management, FAW-AAIM 2012, Beijing, China, May 14–16, pp 359–367, 2012). In this paper, we introduce a generalization of the PDBEP problem. We let the edges have weights as well as demands, and we present the first constant-factor approximation algorithms for this problem. Our results imply the first constant-factor approximation algorithm for the weighted PDBEP problem, improving the result of Aurora et al. (FAW-AAIM 2013) who presented an \(O(\log n)\)-approximation for the weighted case. We also study the weighted PDBEP problem on hypergraphs and present a constant factor approximation if the maximum degree of the hypergraph is bounded above by a constant. We study a generalization of the weighted PDBEP problem with demands where each edge additionally specifies whether it requires at least one, or both its end-points to not exceed the capacity. The objective is to pick a maximum weight subset of edges. We give a constant factor approximation for this problem. We also present a PTAS for the weighted PDBEP problem with demands on H-minor free graphs, if the demands on the edges are bounded by polynomial. We show that the PDBEP problem is APX-hard even for bipartite graphs with \(c_v = 1, \; \forall v\in V\) and having degree at most 3.     

LBI tests for the detection of compound normal distribution in control and treatment populations

Independent samples are drawn from control and treatment populations with normal and compound normal distributions respectively. We derive the locally best invariant (LBI) tests through Wijsman’s representation for the detection of mixture departures from the normal distribution. These tests may be viewed as tests for the equality of control and treatment populations. Further, they are optimally robust for the model considered by Durairajan and Raman (1994).     

Career Issues and Workplace Considerations for the Transsexual Community: Bridging a Gap of Knowledge for Career Counselors and Mental Heath Care Providers

The field of career counseling has addressed the needs of several minority groups; however, the transsexual community has consistently been overlooked. Transsexual individuals may face many personal and professional obstacles due to the complex psychological aspects and expensive medical procedures inherent in transitioning (the complex and multidimensional process of changing genders). Maintaining employment and a steady income are vital when engaging in this costly transition experience. In this article, the authors bridge a gap of knowledge for career counselors and mental health care providers by identifying possible workplace issues and propose 4 primary competency components. A critique of the current literature, recommendations for counselors, and directions for future research are discussed.     

Toward Rigor and Relevance in US Social Work Education

Abstract

After reviewing the major changes taking place in American higher education, the present paper discusses a select number of challenges confronting US social work education. These challenges are broadly characterized as those of rigor and relevance. The paper presents the author's reflections on the best ways to meet these challenges and stresses the promotion of research and social innovations as important foci for social work education.     

An asymptotic distribution-free selection procedure for a two-way layout problem

This paper deals with an asymptotic distribution-free subset selection procedure for a two-way layout problem. The treatment effect with the largest unknown value is of interest to us. The block effect is a nuisance parameter in this problem. The proposed procedure is based on the Hodges-Lehmann estimators of location parameters. The asymptotic relative efficiency of the proposed procedure with the normal means procedure is evaluated. It is shown that the proposed procedure has a high efficiency.     

Estimation of the location and scale parameters of the extreme value distmbution based on multiply type-II censored samples

In this paper, we consider the problem of estimating the location and scale parameters of an extreme value distribution based on multiply Type-II censored samples. We first describe the best linear unbiased estimators and the maximum likelihood estimators of these parameters. After observing that the best linear unbiased estimators need the construction of some tables for its coefficients and that the maximum likelihood estimators do not exist in an explicit algebraic form and hence need to be found by numerical methods, we develop approximate maximum likelihood estimators by appropriately approximating the likelihood equations. In addition to being simple explicit estimators, these estimators turn out to be nearly as efficient as the best linear unbiased estimators and the maximum likelihood estimators. Next, we derive the asymptotic variances and covariance of these estimators in terms of the first two single moments and the product moments of order statistics from the standard extreme value distribution. Finally, we present an example in order to illustrate all the methods of estimation of parameters discussed in this paper.