This paper specifies an empirical framework for estimating both technical and allocative efficiency, which is applied to a large panel of European banks over the years 1996 to 2003. Our methodology allows for self-consistent measurement of technical and allocative inefficiency, in an effort to...

This study examines the relationship between Corporate Social Responsibility (CSR) and corporate performance using a sample of listed shipping companies. Recognizing heterogeneous CSR behavior across shipping companies, we employ Markov Chain Monte Carlo techniques for Bayesian inference and...

We propose a generic latent variable approximation (GLVS) scheme for posterior inference in models with possibly high-dimensional spaces of latent variables. Direct sampling from the approximate posterior is possible. The new technique is applied to univariate and multivariate stochastic...

In this paper, we propose simulation based Bayesian inference procedures in a cost system that includes the cost function and the cost share equations augmented to accommodate technical and allocative inefficiency. Markov Chain Monte Carlo techniques are proposed and implemented for Bayesian...

The paper examines whether inflation systematically distorts the informational content of price signals. A shadow cost function is specified, and the deviation of shadow from actual prices is modeled as a function of the level of economy-wide inflation, as well as other conditioning variables...

The paper studies technical inefficiency in the railway systems of ten countries of the European Union. A new approach is used which permits the disaggregation of inefficiency by factor of production to result in estimates of input-specific technical inefficiency. The cost structure is...