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In the course of railway reforms at the end of the last century, European national governments, as well the EU Commission, decided to open markets and to separate railway networks from train operations. Vertically integrated railway companies argue that such a separation of infrastructure and operations would diminish the advantages of vertical integration and would therefore not be suitable to raise economic welfare. In this paper, we conduct a pan-European analysis to investigate the performance of European railways with a particular focus on economies of scope associated with vertical integration. We test the hypothesis that integrated railways realize economies of joint production and, thus, produce railway services on a higher level of e±ciency. To determine whether joint or separate production is more e±cient we apply an innovative Data Envelopment Analysis super-e±ciency bootstrapping model which relates the e±ciency for integrated production to a virtual reference set consisting of the separated production technology and which is applicable to other network industries as energy and telecommunication as well. Our ¯ndings are that for a majority of European Railway companies economies of scope exist.
Strong sustainability, according to the common definition, requires that different natural and economic capital stocks have to be maintained as physical quantities separately. Yet, in a world of uncertainty this cannot be guaranteed. To therefore define strong sustainability under uncertainty in an operational manner, we propose to use the concept of viability. Viability means that the different components and functions of a dynamic, stochastic system at any time remain in a domain where the future existence of these components and functions is guaranteed with sufficiently high probability. We develop a unifying and general ecological-economic concept of viability that encompasses the traditional ecological and economic notions of viability as special cases. It provides an operational criterion of strong sustainability under conditions of uncertainty. We illustrate this concept and demonstrate its usefulness by applying it to livestock grazing management in semi-arid rangelands.
The paper demonstrates how the E–stability principle introduced by Evans and Honkapohja can be applied to models with heterogeneous and private information in order to assess the stability of rational expectations equilibria under learning. The paper extends already known stability results for the Grossman and Stiglitz model to a more general case with many differentially informed agents and to the case where information is endogenously acquired by optimizing agents. In both cases it turns out that the rational expectations equilibrium of the model is inherently E-stable and thus locally stable under recursive least squares learning.