The Effects of Social Trust and Institutional Trust on Formal Volunteering and Charitable Giving in Japan

This study is part of the growing literature on the effects on civic engagement of attitudinal predictors, such as trust, along with structural predictors. Drawing data from the 2005 Japanese General Social Survey, it examines the association between trust and the probabilities of formal volunteering and charitable giving. A bivariate probit analysis of the data suggests that trust, institutional trust in particular, matters more to predict giving than volunteering. Although the number of membership affiliations is positively and significantly associated with both types of civic engagement, the association between membership affiliations and formal volunteering is significantly greater. Implications of these and other findings are discussed for future studies linking trust to civic engagement in group-collectivist societies such as Japan.     

Progressively Type-II censored conditionally N-ordered statistics from a unified elliptically contoured copula

Progressively Type-II censored conditionally N-ordered statistics (PCCOS-N) arising from iid random vectors X_i = (X¹_i, X²_i, …, X_i^p), i = 1, 2…, n, were investigated by Bairamov (2006 Bairamov, I. (2006). Progressive Type II censored order statistics for multivariate observations. J. Mult. Anal. 97:797–809.[Crossref], [Web of Science ®] , [Google Scholar]), with respect to the magnitudes of N(X_i), i = 1, 2, …, n, where N( · ) is a p-variate measurable function defined on the support set of X₁ satisfying certain regularity conditions and N(X_i) denotes the lifetime of the random vector X_i, i = 1, …, n. Under the PCCOS-N sampling scheme, n independent units are placed on a life-test and after the ith failure, R_i (i = 1, …, m) of the surviving units are removed at random from the remaining observations. In this article, we consider PCCOS-N arising from a vector with identical as well as non identical dependent components, jointly distributed according to a unified elliptically contoured copula (PCCOSDUECC-N). Results established here contain the previous results as particular cases. Illustrative examples and simulation studies show that PCCOSDUECC-N enables us to analyze the lifetime of several systems, including repairable systems and systems with standby components, more efficiently than PCCOS-N.     

Neighborhood Association Participation and Formal Volunteering in Japan

We examine the effect of participation in neighborhood association (NHA) activities on volunteering using the 2010 Japanese General Social Survey data. We find that controlling for established predictors of formal volunteering such as demographic and socioeconomic variables, NHA association participation, either operationalized as a dichotomous or interval variable, positively predicts volunteering. Moreover, some of the established predictors of volunteering (e.g., marital status and associational membership) are useful in predicting NHA participation. Our results indicate a complementary relationship between volunteering and NHA participation. We discuss implications of our study for future research on community volunteering in Japan and elsewhere.     

CATEGORY WIDTH COGNITIVE STYLE AS A FACTOR IN ACCOUNTANTS' PERCEPTIONS OF ACCOUNTING INFORMATION

This paper reports the findings of a laboratory experiment designed to investigate the relationship of category width (CW) cognitive style with accountants' perceptions of accounting information. Subjects drawn from large accounting firms in Sydney, Brisbane, and Melbourne, Australia, were classified into broad, medium, and narrow categories following the test devised by Pettigrew [19]. Subjects were requested to state their level of confidence in decisions they had made after receiving (1) conventional accounting information or (2) conventional accounting information and human resources accounting (HRA) information using a one-group pretest-posttest design. The results indicated a significant relationship between CW cognitive style and the accountants' confidence in their decisions. Furthermore, CW cognitive style moderated the accounting-information/decision-making relationship.     

Robust finite mixture modeling of multivariate unrestricted skew-normal generalized hyperbolic distributions

In this paper, we introduce an unrestricted skew-normal generalized hyperbolic (SUNGH) distribution for use in finite mixture modeling or clustering problems. The SUNGH is a broad class of flexible distributions that includes various other well-known asymmetric and symmetric families such as the scale mixtures of skew-normal, the skew-normal generalized hyperbolic and its corresponding symmetric versions. The class of distributions provides a much needed unified framework where the choice of the best fitting distribution can proceed quite naturally through either parameter estimation or by placing constraints on specific parameters and assessing through model choice criteria. The class has several desirable properties, including an analytically tractable density and ease of computation for simulation and estimation of parameters. We illustrate the flexibility of the proposed class of distributions in a mixture modeling context using a Bayesian framework and assess the performance using simulated and real data.

     

The unequal impact of Covid-19 on the lives and rights of the children of modern slavery survivors,children in exploitation and children at risk of entering exploitation

This article discusses the unequal impact of Covid-19 on the lives of the children of survivors of modern slavery, child victims of exploitation and children at risk of exploitation in the UK. It draws on research that has analysed the risks and impacts of Covid-19 on victims and survivors of modern slavery. It explores how pandemic responses may have hindered these children's rights to education, food, safety, development and participation and representation in legal processes. It suggests that the pandemic should be used as an impetus to address inequalities that existed pre-Covid-19 and those that have been exacerbated by it.     

Bargaining and Reputation

The paper develops a reputation based theory of bargaining. The idea is to investigate and highlight the influence of bargaining ‘postures’ on bargaining outcomes. A complete information bargaining model a la Rubinstein is amended to accommodate ‘irrational types’ who are obstinate, and indeed for tractability assumed to be completely inflexible in their offers and demands. A strong ‘independence of procedures’ result is derived: after initial postures have been adopted, the bargaining outcome is independent of the fine details of the bargaining protocol so long as both players have the opportunity to make offers frequently. The latter analysis yields a unique continuous‐time limit with a war of attrition structure. In the continuous‐time game, equilibrium is unique, and entails delay, consequently inefficiency. The equilibrium outcome reflects the combined influence of the rates of time preference of the players and the ex ante probabilities of different irrational types. As the probability of irrationality goes to zero, delay and inefficiency disappear; furthermore, if there is a rich set of types for both agents, the limit equilibrium payoffs are inversely proportional to their rates of time preference.     

Testing the equality of two independent regression models

In some situations, for example in agriculture, biology, hydrology, and psychology, researchers wish to determine whether the relationship between response variable and predictor variables differs in two populations. In other words, we are interested in comparing two regression models for two independent datasets. In this work, we will use the parametric and nonparametric methods to establish hypothesis testing for the equality of two independent regression models. Then the simulation study is provided to investigate the performance of the proposed method.     

Bayesian spatial regression models with closed skew normal correlated errors and missing observations

This paper is concerned with Bayesian estimation of a spatial regression model with skew non-Gaussian errors. The regression parameters are estimated by using a closed skew normal (CSN) distribution, which is closed under conditioning and linear combination. The proposed model captures skewness in the response variable. Sometimes, we may encounter missing observations in the response variable, accordingly we model and predict the missing observations by a Bayesian approach using Gibbs sampling methods. Next, a simulation study is performed to asses our model validity. Also, the proposed model in this work is applied to CO data from Tehran, the capital city of Iran. Then, the accuracy of the CSN and Gaussian models is compared by cross validation criterion.