The literature of productive efficiency analysis is divided into two main branches: the parametric Stochastic Frontier Analysis (SFA) and nonparametric Data Envelopment Analysis (DEA). This paper attempts to combine the virtues of both approaches in a unified framework. We follow the SFA...

All multinational firms face foreign exchange fluctuations, which can create unstable cash flows and even bankruptcy. Managers of these firms face critical questions over how to reduce the risk due to income and expenses in multiple currencies. Traditional financial risk controls include futures...

We present a methodology to estimate fixed cost parameters relevant to the decision to operate, mothballor retire an open-cycle gas turbine (OCGT) using a dynamic discrete choice model, based on fuel andelectricity prices, as well as technical data and the operational status of OCGTs in the PJM...

In presence of panel data, technical efficiency is used to compare the performances of Decision-Making Units (DMUs). The novelty of this paper is the consideration of the dependence between the two error terms in the case of panel data and the introduction of time effect models in the Stochastic...

Electricity distribution network is a prime example of a natural local monopoly. In many countries, electricity distribution is regulated by the government. In Finland, the regulator estimates the efficient cost frontier using the data envelopment analysis (DEA) and stochastic frontier analysis...

The field of production frontier estimation is divided between the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper explores an amalgam of DEA and SFA that melds a nonparametric frontier with a stochastic composite...

This study presents the results of an extensive Monte Carlo experiment to compare different methods of efficiency analysis. In addition to traditional parametric-stochastic and nonparametric-deterministic methods recently developed robust nonparametric-stochastic methods are considered. The...

If a given risky prospect is compared with multiple choice alternatives, then a joint test for optimality is more appropriate than a series of pairwise Stochastic Dominance tests. We develop and implement a bootstrap empirical likelihood ratio test for this hypothesis. The test statistic and...

This paper considers an alternative way of structuring stochastic variables in a dynamic programming framework where the model structure dictates that numerical methods of solution are necessary. Rather than estimating integrals within a Bellman equation using quadrature nodes, we use nodes...

Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...