By examining the impact of capital regulation on bank risk-taking using a local estimation technique, this paper attempts to quantify for the first time the heterogeneous response of banks towards this type of regulation in banking sectors of western-type economies. Subsequently, using this...

Christopoulos D. K. and Tsionas E. G. (2007) Are regional incomes in the USA converging? A non-linear perspective, Regional Studies 41, 525-530. This article deviates from the current practice of regional convergence by allowing output convergence to follow a non-linear process. In this scenario...

In this paper we consider marginal cost estimation in Greek railways over the period 2000-2004. Marginal cost estimation has been recently an active area of research when disaggregated data by line of operation are available but factor price data are not available. We propose panel data...

Productivity and efficiency analyses have been indispensable tools for evaluating firms’ performance in the banking sector. In this context, the use of Artificial Neural Networks (ANNs) has been recently proposed in order to obtain a globally flexible functional form which is capable of...

The purpose of this paper is to provide an introduction to stochastic frontier models as seen from the point of view of Bayesian analysis. Stochastic frontier models are central in efficiency measurement, and recent advances in Bayesian computation allow us to explore significant extensions of...

In the debate concerning a country’s structural weaknesses there is an obvious neglect of space issues, an important component of which is regional imbalances. Yet, the persistence of such imbalances within countries has dictated the continuous investigation of their causes and of the required...

Standard equilibrium models are unable to replicate the average return on equity and the risk-free rate during 1889-1978, the well-known asset returns puzzle. The present paper, motivated by the excess of outliers in the data, proposes a normal-scale mixture stochastic process for output that is...

The paper is concerned with several kinds of stochastic frontier models whose likelihood function is not available in closed form. First, with output-oriented stochastic frontier models whose one-sided errors have a distribution other than the standard ones (exponential or half-normal). The...

A convenient and simple GMM procedure for estimating stochastic frontier models in the presence of endogenous regressors is proposed. Monte Carlo simulations show that the proposed estimator works very well in finite samples. We apply the proposed method to panel data of Norwegian dairy farms to...

The purpose of this paper is to propose a simple stochastic frontier model with a non-parametric specification for covariates affecting the mean of technical inefficiency. We derive a simple two-step semiparametric estimation procedure to estimate the frontier parameters as well as the mean of...