Impatience versus Incentives

This paper studies the dynamics of long‐term contracts in repeated principal–agent relationships with an impatient agent. Despite the absence of exogenous uncertainty, Pareto‐optimal dynamic contracts generically oscillate between favoring the principal and favoring the agent.     

Determinants of Interoutsourcing: An Analytical Approach

Interoutsourcing is a round‐way process in which the vendor is its customer's customer and the customer is its vendor's vendor. While interoutsourcing is emerging as a prominent outsourcing strategy in many industries, there are no rigorous analytical studies focusing on this mechanism. In this article, we analytically demonstrate the efficacy of interoutsourcing by comparing it with normal outsourcing. Our results show that, compared with normal outsourcing, interoutsourcing acts as a self‐enforcer of vendor firms' behaviors toward increasing outsourcing service value. However, in situations where there is a mismatch of outsourcing activities, a high degree of incentive that is based on outsourcing service value, and a high cost of capital, interoutsourcing is not preferred to normal outsourcing. We discuss these results in detail and provide managerial implications for firms involved in interoutsourcing decisions.     

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.     

Examining the Relationship between Domestic Violence and Depression among Koreans: The Role of Self‐esteem and Social Support as Mediators

Domestic violence is a prevalent social issue in Korea affecting a significant number of people every day. It is thus important to examine how the experience of domestic violence affects their mental health to better address their needs. Using stress‐coping theory as a theoretical framework, this study examines the domestic violence and depression relationship among Korean men and women. Two aspects of self‐esteem and informal and formal social support are examined as potential mediators of this relationship. The data was the first wave of Korean Welfare Panel Study data including 2477 individuals with experiences of abuse. Structural equation modeling procedures were used for analyses. Domestic violence was significantly associated with self‐worth, self‐deprecation, and depression. The experiences of violence eroded self‐worth while reinforcing self‐deprecation and those with more exposure to violence showed a higher level of depression. Self‐deprecation played a significant role in mediating the effect of domestic violence on depression. However, different findings were yielded for social support. While informal social support was significantly associated with domestic violence, formal social support was not associated with domestic violence. Findings suggest for mental health interventions targeting self‐esteem, particularly the diminution of self‐deprecation in working with the victims. Suggestions for future research and implications for social work are also discussed.     

A Bayesian estimate of the concordance correlation coefficient with skewed data

Concordance correlation coefficient (CCC) is one of the most popular scaled indices used to evaluate agreement. Most commonly, it is used under the assumption that data is normally distributed. This assumption, however, does not apply to skewed data sets. While methods for the estimation of the CCC of skewed data sets have been introduced and studied, the Bayesian approach and its comparison with the previous methods has been lacking. In this study, we propose a Bayesian method for the estimation of the CCC of skewed data sets and compare it with the best method previously investigated. The proposed method has certain advantages. It tends to outperform the best method studied before when the variation of the data is mainly from the random subject effect instead of error. Furthermore, it allows for greater flexibility in application by enabling incorporation of missing data, confounding covariates, and replications, which was not considered previously. The superiority of this new approach is demonstrated using simulation as well as real‐life biomarker data sets used in an electroencephalography clinical study. The implementation of the Bayesian method is accessible through the Comprehensive R Archive Network. Copyright © 2015 John Wiley & Sons, Ltd.     

Measures of Association and Visualization of Log Odds Ratio Structure for a Two Way Contingency Table

The odds ratio (OR) is a measure of association used for analysing an I × J contingency table. The total number of ORs to check grows with I and J. Several statistical methods have been developed for summarising them. These methods begin from two different starting points, the I × J contingency table and the two‐way table composed by the ORs. In this paper we focus our attention on the relationship between these methods and point out that, for an exhaustive analysis of association through log ORs, it is necessary to consider all the outcomes of these methods. We also introduce some new methodological and graphical features. In order to illustrate previously used methodologies, we consider a data table of the cross‐classification of the colour of eyes and hair of 5387 children from Scotland. We point out how, through the log OR analysis, it is possible to extract useful information about the association between variables.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

Confidence Intervals for Linear Combinations of Poisson Means

Parametric confidence intervals are given for linear combinations of the means of independent Poisson variables and for their continuous versions. The performance of the intervals is assessed using simulation. A real data set is used to compare the proposed intervals with known ones. The proposed intervals are shown to be superior to known ones and comparable to exact intervals.