A multivariate stochastic volatility model with dynamic equicorrelation and cross leverage effect is proposed and estimated. Using a Bayesian approach, an ecient Markov chain Monte Carlo algorithm is described where we use the multi-move sampler, which generates multiple latent...

A multivariate stochastic volatility model with dynamic equicorrelation and cross leverage effect is proposed and estimated. Using a Bayesian approach, an ecient Markov chain Monte Carlo algorithm is described where we use the multi-move sampler, which generates multiple latent variables...

　　 We formulate strategic aspects of speculative arbitrageurs in a stock market as a generalization of timing game with behavioral types explored by Matsushima (2013b). A company raises huge funds during the bubble driven by positive feedback traders' euphoria by issuing shares in...

The paper concerns small-area estimation in the heteroscedastic nested error regression (HNER) model which assumes that the within-area variances are different among areas. Although HNER is useful for analyzing data where the within-area variation changes from area to area, it is difficult to...

This paper is concerned with the prediction of the conditional mean which involves the fixed and random effects based on the natural exponential family with a quadratic variance function. The best predictor is interpreted as the Bayes estimator in the Bayesian context, and the empirical Bayes...

A multivariate stochastic volatility model with the dynamic correlation and the cross leverage effect is described and its efficient estimation method using Markov chain Monte Carlo is proposed. The time-varying covariance matrices are guaranteed to be positive definite by using a matrix...

　　 This study analyzes incentives and supplier-induced demand of care man- agers, middlemen between consumers and service providers in the Japanese social insurance program for long-term care. Care managers can be considered as pure gatekeepers in that their function is limited to...

A multivariate stochastic volatility model with the dynamic correlation and the cross leverage effect is described and its efficient estimation method using Markov chain Monte Carlo is proposed. The time-varying covariance matrices are guaranteed to be positive definite by using a matrix...

The problem of estimating a covariance matrix in multivariate linear regression models is addressed in a decision-theoretic framework. Although a standard loss function is the Stein loss, it is not available in the case of a high dimension. In this paper, a new type of a quadratic loss function,...

　　 This paper addresses the problem of estimating the normal mean matrix with an unknown covariance matrix. Motivated by an empirical Bayes method, we suggest a unied form of the Efron-Morris type estimators based on the Moore-Penrose inverse. This form not only can be dened for...