Consumer welfare and unobserved heterogeneity in discrete choice models : the value of alpine road tunnels

We investigate the sensitivity of consumer surplus estimates to parametric assumptions on individual preference heterogeneity in a discrete choice framework. We compare results from a parametric random coefficients logit model and a recently proposed nonparametric sieve estimator. In particular, we provide an assessment of the direct economic value of crossing the Alps for the European road freight sector. Using revealed preference data from a detailed survey on transalpine road freight traffic, we estimate the yearly cost of closing the Mont-Blanc Tunnel, which was closed for 3 years following a large accident in early 1999. Ultimately, our results permit the economic evaluation of security and transport policy measures affecting transalpine traffic. Our findings suggest that the way we model unobserved heterogeneity significantly affects our welfare results

Forecasting Transitions in Digital Society: From Social Norms to AI Applications

The use of AI and digitalization in many areas of everyday life holds great potential but also introduces significant societal transitions. This paper takes a closer look at three exemplary areas of central social and psychological relevance that might serve as a basis for forecasting transitions in the digital society: (1) social norms in the context of digital systems; (2) surveillance and social scoring; and (3) artificial intelligence as a decision-making aid or decision-making authority. For each of these areas, we highlight current trends and developments and then present future scenarios that illustrate possible societal transitions, related questions to be answered, and how such predictions might inform responsible technology design

Model-based parallelization of discrete traffic simulation models

To re-establish regular operations in a tram traffic network after a large disturbance, e.g. resulting from vehicle breakdown or station closure, the viability of several rescheduling and rerouting strategies has to be evaluated prior to their implementation. Here, a multi-modal traffic simulation system can help to enhance the decision quality. Such a system obviously faces tight time constraints, so simulation data has to be acquired fast. In this paper we propose a method for the parallel execution of discrete traffic simulation models, which would accelerate data generation in comparison to a sequential model. To assess this method's dynamic behavior in real-world applications, some experiments conducted on a software system modeling schedule based tram traffic are presented. After giving an introduction to the scope and aim, we show some background on the parallelization of discrete simulation models. The main part of the paper begins with the proposal of a method to parallelize the execution of simulation models with problem specific properties. Some estimations of the method's efficiency are shared, followed by several experiments to highlight its dynamic behavior in real-world applications. The paper ends with a short summary and some thoughts on further research

A robust schedule for Montpellier's Tramway network

The city of Montpellier in the Languedoc-Roussillon region of France features a fast growing tram network as a central part of its public service infrastructure. Here, as in many other tram networks, resources like tracks and stations are shared between different lines. Because of the resulting dependencies, small inevitable delays can spread through the network and affect its global performance. Abstract This article examines whether a robust tram schedule may help to raise punctuality in Montpellier's tram network. To accomplish this, we apply a tool set designed to generate schedules optimized for robustness, which also satisfy given sets of planning requirements. These tools allow to compare time tables with respect to their punctuality and other key indicators. Abstract After an introduction to the goals of this paper, we continue with a description of the tool set focusing on optimization and simulation modules. These software utilities are then employed to generate and simulate robust and non-robust schedules for Montpellier's tram network, which are subsequently compared for the resulting delays

Reduzieren robuste Fahrpläne Verspätungen in Stadtbahnnetzen? - Es kommt drauf an!

Nicht in jedem Stadtbahnnetz ist Robustheit als Optimierungskriterium für Fahrpläne gleich-sam geeignet. Im Rahmen dieses Beitrags werden deshalb Faktoren für die Netzstruktur bestimmt, die die Wirksamkeit von Robustheit als verspätungsmindernden Faktor beeinflus-sen. Anhand von Optimierungs- und Simulationsexperimenten auf Basis von Modellen der Stadtbahnnetze von Köln und Montpellier werden die definierten Einflussfaktoren getestet

Kritische Diskursanalyse : Darstellung anhand der Analyse der Nahostberichterstattung linker Medien

Zuerst erschienen im Dietz-Verlag: Bartel, Daniel; Ullrich, Peter; Ehrlich, Kornelia: Kritische Diskursanalyse : Darstellung anhand der Analyse der Nahostberichterstattung linker Medien. - In: Freikamp, Ulrike [u.a.] (Hrsg.): Kritik mit Methode? : Forschungsmethoden und Gesellschaftskritik. - Berlin: Dietz, 2008. - (Texte / Rosa-Luxemburg-Stiftung; 42). - ISBN: 978-3-320-02136-8. - S. 53–72

Considerations on partially identified regression models

Motivated by Manski and Tamer (2002) and especially their partial identification analysis of the regression model where one covariate is only interval-measured, we offer several contributions. Manski and Tamer (2002) propose two estimation approaches in this context, focussing on general results. The modified minimum distance (MMD) estimates the true identified set and the modified method of moments (MMM) a superset. Our first contribution is to characterize the true identified set and the superset. Second, we complete and extend the Monte Carlo study of Manski and Tamer (2002). We present benchmark results using the exact functional form for the expectation of the dependent variable conditional on observables to compare with results using its nonparametric estimates, and illustrate the superiority of MMD over MMM. For MMD, we propose a simple shortcut for estimation