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 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...

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...

This paper considers Bayesian estimation strategies for first-price auctions within the independent private value paradigm. We develop an ‘optimization’ error approach that allows for estimation of values assuming that observed bids differ from optimal bids. We further augment this approach...

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 paper introduces a new dynamic frontier model that is used to analyze the impact of both ownership and regulation on airport technical and allocative efficiencies. We differentiate between the short and long-term effects. Based on a large sample of international airports, we find in the...

Standard stochastic frontier models estimate log-linear specifications of production technology, represented mostly by production, cost, profit, revenue, and distance frontiers. We develop a methodology for stochastic frontier models of count data allowing for technological and inefficiency...

In this paper we propose new estimation techniques in connection with regression models whose errors have distributions which are members of the celebrated Pearson’s system. Efficient MCMC procedures are proposed in the context of likelihood—based inference. The new techniques are applied to...