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

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

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

Productivity Convergence in Europe

The paper examines the convergence properties of productivity in fifteen European countries over the period 1960-1997. Empirical tests are performed for the "Maastricht proposition," according to which nominal convergence in rates of inflation is a prerequisite for real convergence. Modern econometric techniques for non-stationary time series, organized Around and cointegration analysis are used to examine within-group and between-group convergence. The number of common, long-run stochastic trends in productivity series is also examined. The results suggest strong evidence against unconditional or conditional convergence. However, European productivity time series can be described by a relatively small number of common long-run trends.Convergence; Productivity

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

Multivariate stochastic volatility with large and moderate shocks

The paper proposes a multivariate stochastic volatility model where shifts in volatility are endogenously driven by large return shocks. The model proposed generalizes the univariate stochastic volatility model of Dendramis and colleagues to a multivariate context. Allowing for multivariate dependence permits the volatility of common return factors to affect individual stock returns volatility jointly. The model is further extended to allow for endogenous thresholds that depend on covariates. Model selection priors are introduced and the new techniques are applied by using data from the FTSE100‐index

An internally consistent approach to the estimation of market power and cost efficiency with an application to U.S. banking

We develop a novel unified econometric methodology for the formal examination of the market power – cost efficiency nexus. Our approach can meaningfully accommodate a mutually dependent relationship between the firm’s cost efficiency and marker power (as measured by the Lerner index) by explicitly modeling the simultaneous determination of the two in a system of nonlinear equations consisting of the firm’s cost frontier and the revenue-to-cost ratio equation derived from its stochastic revenue function. Our framework places no a priori restrictions on the sign of the dependence between the firm’s market power and efficiency as well as allows for different hierarchical orderings between the two, enabling us to discriminate between competing quiet life and efficient structure hypotheses. Among other benefits, our approach completely obviates the need for second-stage regressions of the cost efficiency estimates on the constructed market power measures which, while widely prevalent in the literature, suffer from multiple econometric problems as well as lack internal consistency/validity. We showcase our methodology by applying it to a panel of U.S. commercial banks in 1984–2007 using Bayesian MCMC methods

Debt dynamics in Europe: a network general equilibrium GVAR approach

In this work, we investigate the dynamic interdependencies among the EU12 economies using a competitive general equilibrium network system representation. Additionally, using Bayesian techniques, we estimate the autoregressive scheme that characterizes the equilibrium price system of the network, while characterizing each economy/node in the universe of our network in terms of its degree of pervasiveness. In this context, we unveil the dominant(s) unit(s) in our model and estimate the dynamic linkages between the economies/nodes. Lastly, in terms of robustness analysis, we compare the findings of the degree pervasiveness of each economy against other popular quantitative methods in the literature. According to our findings, the economy of Germany acts as weakly dominant entity in the EU12 economy. Meanwhile, all shocks die out in the short run, without any long lasting effect