Liquidity spreads in the corporate bondmarket: Estimation using a semi-parametric model

This study utilizes the liquidity risk associated with Treasury bonds to directly determine the degree to which liquidity spreads account for corporate bond spreads. This enhances understanding of their relative contributions to the yield spreads of corporate bonds. To capture time variation on instantaneous spreads and volatility and to reduce modeling bias, semi-parametric techniques are applied to estimate the time-varying intensity process. Empirical results indicate that our semi-parametric model is good at capturing the time variation in default and liquidity intensity processes. The credit spreads are due to default risk and reflect the relative liquidity of the corporate bond market, indicating that liquidity risk plays an important role in corporate bond valuation.     

CEO Narcissism and Global Performance Variance in Multinational Enterprises: The Roles of Foreign Direct Investment Risk-Taking and Business Group Affiliation

This study examines key mechanisms through which CEO narcissism influences global performance variance in the context of Asian emerging market multinational enterprises. Building on the contextual reinforcement model of narcissism and the cushion hypothesis, we focus on the role of foreign direct investment (FDI) risk-taking and business group affiliation (BGA). We test our moderated mediation model on data from 149 South Korean multinational enterprises from 2006 to 2016. The results show that CEO narcissism is positively associated with FDI risk-taking. The effect of CEO narcissism on global performance variance is mediated by FDI risk-taking. Furthermore, BGA moderates the above-mentioned relationships. Our findings offer important contributions to the international business and CEO narcissism literatures.     

An Empirical Analysis on Determinants of Aid Allocation by South Korean Civil Society Organizations

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This paper examines whether three sets of factors—humanitarianism, the South Korean government’s official aid,...     

Interval Estimation for the Correlation Coefficient

ABSTRACT

The correlation coefficient (CC) is a standard measure of a possible linear association between two continuous random variables. The CC plays a significant role in many scientific disciplines. For a bivariate normal distribution, there are many types of confidence intervals for the CC, such as z-transformation and maximum likelihood-based intervals. However, when the underlying bivariate distribution is unknown, the construction of confidence intervals for the CC is not well-developed. In this paper, we discuss various interval estimation methods for the CC. We propose a generalized confidence interval for the CC when the underlying bivariate distribution is a normal distribution, and two empirical likelihood-based intervals for the CC when the underlying bivariate distribution is unknown. We also conduct extensive simulation studies to compare the new intervals with existing intervals in terms of coverage probability and interval length. Finally, two real examples are used to demonstrate the application of the proposed methods.     

A 6.55 factor primal-dual approximation algorithm for the connected facility location problem

In the connected facility location (ConFL) problem, we are given a graph G=(V,E) with nonnegative edge cost c _e on the edges, a set of facilities ??V, a set of demands (i.e., clients) $\mathcal{D}\subseteq VIn the connected facility location (ConFL) problem, we are given a graph G=(V,E) with nonnegative edge cost c _e on the edges, a set of facilities ℱ⊆V, a set of demands (i.e., clients) D í V\mathcal{D}\subseteq V , and a parameter M≥1. Each facility i has a nonnegative opening cost f _i and each client j has d _j units of demand. Our objective is to open some facilities, say F⊆ℱ, assign each demand j to some open facility i(j)∈F and connect all open facilities using a Steiner tree T such that the total cost, which is ?_{i ? F}f_i+?_{j ? D}d_jc_i(j)j+M?_{e ? T}c_e\sum_{i\in F}f_{i}+\sum_{j\in \mathcal{D}}d_{j}c_{i(j)j}+M\sum_{e\in T}c_{e} , is minimized. We present a primal-dual 6.55-approximation algorithm for the ConFL problem which improves the previous primal-dual 8.55-approximation algorithm given by Swamy and Kumar (Algorithmica 40:245–269, 2004).     

Bayesian inference and model selection in latent class logit models with parameter constraints: an application to market segmentation

Latent class models have recently drawn considerable attention among many researchers and practitioners as a class of useful tools for capturing heterogeneity across different segments in a target market or population. In this paper, we consider a latent class logit model with parameter constraints and deal with two important issues in the latent class models--parameter estimation and selection of an appropriate number of classes--within a Bayesian framework. A simple Gibbs sampling algorithm is proposed for sample generation from the posterior distribution of unknown parameters. Using the Gibbs output, we propose a method for determining an appropriate number of the latent classes. A real-world marketing example as an application for market segmentation is provided to illustrate the proposed method.     

A Diagnostic Method for Principal Components Tests

The local influence method is adapted to testing hypotheses about principal components for investigating the influence of observations on the test statistic. Simultaneous perturbations on all observations are considered. The main diagnostic is the direction vector of the maximum slope of the surface formed by the perturbed test statistic. A perturbation is constructed whose result is the same as that of the influence function method. An example is given for illustration.     

Public Discourses About International Students

A growing, English‐language literature analyzes the public discourse of international education and students. One large set of studies highlight the discursive marginalization of non‐western, international students in western, host societies. They draw on critical discourse analysis (CDA) and meta‐narratives of western, White, and elite dominance, which diminish the theoretical importance of discourse in non‐western and non‐elite settings. A second, smaller set of studies analyze the public discourse of international education in non‐western, specifically Asian, countries; they generally reference educational discourse in both Asian and western countries. Relatively few studies critically examine patterns of discursive domination in Asian discourse; but the ones that do so compare both Asian and Western countries. Even rarer are studies of social media discourse among international students. We find a few studies of social media discourse among Asian students who studied abroad, but none of foreign students studying in host, Asian countries. Attention to multiple discourses and theoretical narratives offers a fruitful, research agenda and underlines the complex, dynamic, global nature of contemporary public discourse on international education.     

Optimal Policy for a Stochastic Scheduling Problem with Applications to Surgical Scheduling

We consider the stochastic, single‐machine earliness/tardiness problem (SET), with the sequence of processing of the jobs and their due‐dates as decisions and the objective of minimizing the sum of the expected earliness and tardiness costs over all the jobs. In a recent paper, Baker ( 2014 ) shows the optimality of the Shortest‐Variance‐First (SVF) rule under the following two assumptions: (a) The processing duration of each job follows a normal distribution. (b) The earliness and tardiness cost parameters are the same for all the jobs. In this study, we consider problem SET under assumption (b). We generalize Baker's result by establishing the optimality of the SVF rule for more general distributions of the processing durations and a more general objective function. Specifically, we show that the SVF rule is optimal under the assumption of dilation ordering of the processing durations. Since convex ordering implies dilation ordering (under finite means), the SVF sequence is also optimal under convex ordering of the processing durations. We also study the effect of variability of the processing durations of the jobs on the optimal cost. An application of problem SET in surgical scheduling is discussed.     

Rates and correlates of recurrent psychiatric crisis episodes among children and adolescents in state custody

The purpose of this study was to determine the extent of and factors associated with recurrent psychiatric crisis episodes among children and adolescents in state custody. A total of 1362 children ages 3 to 16 years who were in custody of the child welfare agency and underwent a psychiatric crisis screening and services for the first time between 2001 and 2003 were followed for the same observation period of 24 months. Logistic regression was used to determine the clinical and non-clinical factors associated with a return to psychiatric crisis screening and services. Overall, 44.6% of the sample had another psychiatric crisis episode in the following two years. Nearly two thirds of those who returned did so within 6 months of their first crisis episode. A greater likelihood of recidivism was associated with severity of psychiatric illness, being female, white, in residential care placement, and having placement instability. Recurrent psychiatric crises appear to be predictable using readily available variables, which can inform interventions designed to reduce repeat episodes.