Efficiency in European railways: Not as inefficient as one might think

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 represented using a generalized McFadden flexible functional form. Policy implications and guidelines for rational decision making in the railway sector, are discussed in detail.technical efficiency; symmetric generalized McFadden form; flexible functional forms; duality; input-specific technical efficiency; European railways

A spatial stochastic frontier model with spillovers:evidence for Italian regions

Efficiency measurement using stochastic frontier models is well established in applied econometrics. However, no published work seems to be available on efficiency analysis using spatial data dealing with possible spatial dependence between regions. This article considers a stochastic frontier model with decomposition of inefficiency into an idiosyncratic and a spatial, spillover component. Exact posterior distributions of parameters are derived, and computational schemes based on Gibbs sampling with data augmentation are proposed to conduct simulation-based inference and efficiency measurement. The new method is illustrated using production data for Italian regions (1970–1993). Clearly, further theoretical and empirical research on the subject would be of great interest

The good, the bad and the technology:endogeneity in environmental production models

In this paper we consider an environmental production process in which firms intend to produce outputs (which we label as desirable/good) but the production process is such that it automatically produces some other unintentional but inevitable undesirable (bad) outputs as by-products (emission of pollutants). Like stochastic production frontier, by-production technology specifies that there is a minimal amount of the by-product that is produced, given the quantities of inputs and desirable outputs. The presence of (environmental) inefficiency in by-production therefore means that more than this minimal amount of the undesirable output is produced. Similarly, the presence of technical inefficiency implies that, given inputs, less than the maximal possible amount of desirable outputs is produced. Alternatively, it means that more than the minimal amounts of inputs are used to produce a given level of desirable output. We use the “by-production technology” approach which is a composition of production technology of desirable outputs and the technology of by-products, and estimate both technical and environmental efficiency. Given that electricity, the good output in our application, is demand determined, we treat it as exogenous and address the endogeneity of inputs by using the first-order conditions of cost minimization. Some of our models automatically take endogeneity of bad outputs into account. We use an efficient Bayesian MCMC technique to estimate both good and bad output technologies and both types of inefficiency. We also compare results with some alternative models with and without endogeneity corrections

Returns to scale, productivity and efficiency in US banking (1989-2000): the neural distance function revisited

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 approximating any existing output distance function while enabling the a priori imposition of the theoretical properties dictated by production theory, globally. Previous work has proposed and estimated the so-called Neural Distance Function (NDF) which has numerous advantages when compared to widely adopted specifications. In this paper, we carefully refine some of the most critical characteristics of the NDF. First, we relax the simplistic assumption that each equation has the same number of nodes because it is not expected to approximate reality with any reasonable accuracy and different numbers of nodes are allowed for each equation of the system. Second, we use an activation function which is known to achieve faster convergence compared to the conventional NDF model. Third, we use a relevant approach for technical efficiency estimation based on the widely adopted literature. Fitting the model to a large panel data we illustrate our proposed approach and estimate the Returns to Scale, the Total Factor Productivity and the Technical Efficiency in US commercial banking (1989-2000). Our approach provides very satisfactory results compared to the conventional model, a fact which implies that the refined NDF model successfully expands and improves the conventional NDF approach.Output distance function; Neural networks; Technical efficiency; US banks

Technical and Allocative Efficiency in European Banking

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 address the issue known in the literature as the Greene problem. The results suggest that, on average, European banks exhibit constant returns to scale, that technical and allocative efficiency are close to 80% and 75% respectively, and that overall economic efficiency shows a clearly improving trend. We also show through the comparison of various estimators that models incorporating only technical efficiency tend to overestimate it.Technical and allocative efficiency; Translog cost function; Maximum likelihood; European banking

System estimation of GVAR with two dominants and network theory:evidence for BRICs

The dynamics of traditional economic structures changed dramatically in the US and globally after 2006. In this context, the need for modeling complex macroeconomic interactions, has led us to develop an upgraded compact global (macro) econometric GVAR model, which is capable of incorporating both the complex interdependencies that exist between the various economic entities and the fact that in the global economy more than one of these entities could have a predominant role, without neglecting the channels of trade and finance. Additionally, based on the trade weight matrix that lies in the core of the GVAR framework, we provide both an analytical procedure and an ex-post econometric criterion for the selection of dominant entities. We demonstrate the dynamics of our model by focusing on the impact of a potential slowdown in the BRICs on the US and EU17 economies. According to our findings, the dominant economies are those of the USA and EU17, while the results suggest that EU17 is more vulnerable than the USA to shocks from the BRICs, implying that a potential slowdown in the BRICs will primarily affect the EU17 economy. Clearly, the proposed model can be easily used for analyzing a number of transmission mechanisms, contagion effects and network interdependencies in various settings

Computational Discovery of Hydrogen Bond Design Rules for Electrochemical Ion Separation

Selective ion separation is a major challenge with far-ranging impact from water desalination to product separation in catalysis. Recently introduced ferrocene (Fc)/ferrocenium (Fc⁺) polymer electrode materials have been demonstrated experimentally and theoretically to selectively bind carboxylates over perchlorate through weak C–H···O hydrogen bond (HB) interactions that favor carboxylates, despite the comparable size and charge of the two species. However, practical application of this technology in aqueous environments requires further selectivity enhancement. Using a first-principles discovery approach, we investigate the effect of Fc/Fc⁺ functional groups (FGs) on the selectivity and reversibility of formate–Fc⁺ adsorption with respect to perchlorate in aqueous solution. Our wide design space of 44 FGs enables identification of FGs with higher selectivity and rationalization of trends through electronic energy decomposition analysis or geometric hydrogen bonding analysis. Overall, we observe weaker, longer HBs for perchlorate as compared to formate with Fc⁺. We further identify Fc⁺ functionalizations that simultaneously increase selectivity for formate in aqueous environments but permit rapid release from neutral Fc. We introduce the materiaphore, a 3D abstraction of these design rules, to help guide next-generation material optimization for selective ion sorption. This approach is expected to have broad relevance in computational discovery for molecular recognition, sensing, separations, and catalysis.National Science Foundation (U.S.) (ECCS-1449291