Short-term inflation projections: A Bayesian vector autoregressive approach

In this paper we construct a large Bayesian Vector Autoregressive model (BVAR) for the Euro area that captures the complex dynamic inter-relationships between the main components of the Harmonized Index of Consumer Prices (HICP) and their determinants. The model generates accurate conditional and unconditional forecasts in real-time. We find a significant pass-through effect of oil-price shocks on core inflation and a strong Phillips curve during the Great Recession.     

Average cost and marginal cost pricing in Marshall: Textual analysis and interpretation

Abstract

This paper proposes a textual analysis of Marshall's theory of firm pricing behavior under competitive conditions. Average cost and marginal cost pricing theories have very distinct origins as they are rooted, respectively, in the classical and marginalistic theory of competition. I analyze to what extent and under which circumstances the two theories joined in the work of Alfred Marshall; and I argue that, even though only partial evidence can be found to support the adoption of the notion of marginal cost pricing by Marshall, he developed some concepts, such as the distinction between short and long periods and the notion of quasi-rents, which turned out to be fundamental for the joint acceptance of marginal cost and average cost pricing principles by the Marshallian school.     

The Role of Stocks and Shocks Concepts in the Debate Over Price Versus Quantity

Recent literature showed that the choice between a price or quantity control depends, in part, on the dynamic structure of cost uncertainty. Temporary shocks to abatement cost favors the use of a price control, while permanent shocks favor a quantity control. Unfortunately, the importance of this assumption to the optimal choice has not yet received wide attention among economists. We analyze the regulatory sproblem in an alternative setting and reproduce these results. Our contribution is the simplicity of the model and the accessibility of the results, which reinforce the critical role played by the assumed structure of uncertainty.     

Influence of tourist sector structure on motivations of heritage tourists

Cultural tourism has traditionally been approached in terms of its appeal to visitors wishing to find out about or get involved in places or to extend their education or to enjoy historical buildings and heritage managed for tourism. This is tourism that has most encouraged activities to preserve the environment and historical/artistic heritage, getting away from mass tourist models, destination impact and seasonality. The aim of this study is to develop a model to identify the elements that help modify the cultural tourist's motivations: the structure of the tourism industry (enterprise infrastructure factors, city infrastructure factors, tourist mobility and tourist resources) and value for money. The use of partial least square method allows us to confirm the proposed correlations and to validate a model.     

Aircraft safety analysis using clustering algorithms

In recent years, there have been many cost-benefit studies on aviation safety, which deal mainly with economic issues, omitting some strictly technical aspects. This study compares aircraft accidents in relation to the characteristics of the aircraft, environmental conditions, route, and traffic type. The study was conducted using a database of over 1500 aircraft accidents worldwide, occurring between 1985 and 2010. The data were processed and then aggregated into groups, using cluster analysis based on an algorithm of partition binary ‘Hard c means.’ For each cluster, the ‘cluster representative’ accident was identified as the average of all the different characteristics of the accident. Moreover, a ‘hazard index’ was defined for each cluster (according to annual movements); using this index, it was possible to establish the dangerousness of each ‘cluster’ in terms of aviation accidents. Obtained results allowed the construction of an easy-to-use predictive model for accidents using multivariate analysis.     

Lundberg parameters for non standard risk processes

We consider risk processes with delayed claims in a Markovian environment, and we study the asymptotic behaviour of finite and infinite horizon ruin probabilities under the small claim assumption. We also consider multivariate risk processes of the same kind, and we give upper and lower bounds for the Lundberg parameters of the corresponding total reserve. Our results have strong analogies with those one in the paper by Juri (Super modular order and Lundberg exponents, 2002).     

Optimierte Integration der Elektromobilität in das Stromversorgungssystem bei hohen Anteilen erneuerbarer Energien

Electric mobility will play a key role for the transformation of the energy supply in Germany [the “Energiewende”]. A successful market development of plug-in hybrids and battery electric vehicles and a full fleet penetration in the long-term are the most efficient and effective measure for integrating large amounts of renewable energy into the transport sector and for reaching the efficiency targets. These new electricity consumers in the supply system will cause additional electricity loads strongly dependent on the mobility needs of the vehicle users. A controlled battery charging is able to avoid new peak demands and to increase the efficiency of the power generation system by using excess power. By scenario analysis, the German Aerospace Center (DLR) in cooperation with the Fraunhofer Institute for Solar Energy Systems (ISE) and the Institute for High Voltage Technology of the RWTH Aachen investigated a possible successful development path of electric mobility in Germany and its integration into and interaction with the future power supply system. From both perspectives—the one of the total supply system as well as the other of local distribution grids—the results show promising potentials but also limits.     

Throwing good money after bad

An “investment bubble” is a period of “excessive, and predictably unprofitable, investment” (DeMarzo et al. in J Financ Econ 85:737–754, 2007). Such bubbles most often accompany the arrival of some new technology, such as the tech stock boom and bust of the late 1990s and early 2000s. We provide a rational explanation for investment bubbles based on the dynamics of learning in highly uncertain environments. Objective information about the earnings potential of a new technology gives rise to a set of priors or a belief function. A generalised form of Bayes’ rule is used to update this set of priors using earnings data from the new economy. In each period, agents—who are heterogeneous in their tolerance for ambiguity—make optimal occupational choices, with wages in the new economy set to clear the labour market. A preponderance of bad news about the new technology may nevertheless give rise to increasing firm formation around this technology, at least initially. To a frequentist outside observer, the pattern of adoption appears as an investment bubble.