A general theoretical and empirical framework is developed for assessing the potential of a vertically integrated firm to foreclose downstream competitors. Using this framework a policymaker may also evaluate the empirical welfare effects from a vertically integrated firm raising rivals' costs....

This paper measures and analyzes the technical efficiency of Islamic banks in the Middle East and North Africa (MENA) region during the period 2007-2012. To do this, the bootstrap Data Envelopment Analysis (DEA) approach was employed in order to provide a robust estimation of the overall...

In this paper, benefits resulting from the interaction of electric vehicles and photovoltaic generation units are analyzed. In doing so, a bottom-up approach is developed to simulate the driving and charging behavior of electric vehicles. An economic analysis is then performed to determine key...

Bootstrapping non-parametric models is a fairly complicated exercise which is associated with implicit assumptions or requirements that are not always obvious to the non-expert user. Bootstrap DEA is a significant development of the past decade; however, some of its assumptions and properties are...

Since the introduction of bootstrap DEA there is a growing literature on applications which use this method, mainly for hypothesis testing. It is therefore important to establish the consistency and evaluate the performance of bootstrap DEA. The few Monte Carlo experiments in the literature...

In this paper is carry out an analysis of affinities in the perception on how to leave the crisis behind. For that we have considered the opinion of experts belonging to the politics, the economy, the company and the banking in order to gather those opinions and to look for likeness and...

We introduce an adaptive importance sampling method for the loss distribution of credit portfolios based on the Robbins-Monro stochastic approximation procedure. After presenting the subtle construction of the algorithm, we apply our adaptive scheme for calculating the risk figures of a typical...

In this paper we develop several regression algorithms for solving general stochastic optimal control problems via Monte Carlo. This type of algorithms is particularly useful for problems with a highdimensional state space and complex dependence structure of the underlying Markov process with...

This paper deals with a system where batch arrivals wait in a station until a server (a train) is available, at which moment it services all customers in waiting. This is an example of a bulk server, which has many applications in public transportation, telecommunications, computer resource...

This study develops an easy forecasting model using prefectural data in Japan. The Markov chain known as a stochastic model corresponds to the vector auto-regressive (VAR) model of the first order. If the transition probability matrix can be appropriately estimated, the forecasting model using...