We propose a novel approach to the modelling of bidding behavior in pay-your-bid auctions that builds on the presumption that bidders are mostly concerned with losing an auction if they happen to have the highest signal. Our models assume risk neutrality, no profit maximization and the assumption that bidders do not bid above their respective values. The models may entail overbidding or Symmetric Bayes-Nash Equilibrium bidding and we discuss conditions for the revenue equivalence of standard pay-your-bid auctions to hold. We fit the models to the data of first-price auction experiments and find that they do at least as well as the Bayes-Nash equilibrium benchmark model in organizing the observed behavior. Assuming probability misperception or impulse weighting (when relevant) improves their goodness-of-fit and leads to very similar revenue predictions. An analysis of individuals´ heterogeneous behavioral traits suggests that impulse weighting is a more consistent rationale for the observed behavior than a power form of probability misperception.

Using a series of laboratory experiments, this paper studies the effect of tax misperceptions on retirement savings and whether information interventions and changing the form of the tax subsidy promote tax-efficient savings behavior. We find that deferred pension taxation results in after-tax pensions that are about 25% lower compared to an economically equivalent immediate pension tax system. This indicates substantial tax misperceptions. We demonstrate that neither recurrent information on the tax refund alone nor recurrent information about the pension tax alone mitigate this distortion. Only, if we present subjects with recurrent numerical information on tax refunds together with numerical information on future pension taxes, tax distortions disappear. Moreover, we find that replacing the tax deductibility of retirement savings with matching contributions increases tax-efficiency without the necessity to provide additional information.

Der Vortrag beschäftigt sich mit der Frage, ob aus Sicht der Informationsfunktion der Rechnungslegung ein variabler oder ein fester Zins besser für die Bilanzierung von Pensionsverpflichtungen geeignet ist. Die Informationsfunktion wird konsequent im Sinne der Messperspektive dahingehend interpretiert, dass Daten der Rechnungslegung für Bewertungszwecke eingesetzt werden. Die Eignung eines festen bzw. variablen Zinssatzes wird also danach beurteilt, ob diese geeignet sind, einen Bewertungsvorgang zu verbessern. Im Ergebnis kann festgestellt werden, dass für Bewertungszwecke ein fester Zinssatz geeigneter ist als ein variabler. Dies liegt daran, dass ein fester Zinssatz eine weniger volatile Erfolgsgröße generiert, die sich deshalb besser für Prognosezwecke eignet. Die Verwendung eines festen Zinssatzes zieht allerdings einen Bewertungsfehler nach sich, dessen Höhe vom Bewerter approximiert werden kann.

There are many aspects that make production planning and inventory control a challenging field for practice and science. A specific one is the fact that in many industries the production output can randomly deviate from what is intended when input decisions are made. This is an effect of unexpected scrap losses and uncertain production yields. Based on three recent publications, it will be shown how yield randomness can affect very different problem areas in operations management and inspire respective research. Particularly, it will be demonstrated that it is highly critical for effective decision making to identify the correct yield type and model it appropriately.

Despite a rather skeptical attitude of the economists toward state intervention in the housing markets, policy makers and the general public typically support it. As a result, since World War I, in many countries the state has been actively intervening in the housing market. It has employed a wide range of both restrictive (rent and eviction controls, and housing rationing) and stimulating (social housing construction and provision of housing allowances) tools, which have become an important element of economic and social policies. Nevertheless, the macroeconomic effects of such regulations are largely unknown. In this study, based on a thorough analysis of the legal acts issued between 1914 and 2017 in many countries across the world, regulation indices are constructed, which measure the intensity of governmental regulations with respect to the rental housing market. Then, the effects of these regulations on real house prices, price-to-rent and price-to-income ratios, real rents, as well as new housing construction are evaluated for the case of Germany between 1950 and 2015. This choice is dictated by the data availability. An immediate follow-up of this analysis is going to be a multi-country econometric estimation of the macroeconomic effects of restrictive regulations upon the housing market.

Decision making in real-world routing applications is generally conducted under incomplete information. The information is only revealed successively during the execution of the routing. Technological advances allow dispatchers to adapt their plans dynamically to new information. Nevertheless, current decisions influence later outcomes. Dispatchers have to anticipate future events in current decision making. The aim of this talk is to give guidance on how to model dynamic vehicle routing problems and how to achieve anticipation. For modeling dynamic vehicle routing problems, we propose the use of a Markov decision process (MDP). For the integration of stochasticity in dynamic decision making, we present novel methods of approximate dynamic programming (ADP). These methods are extensions and combinations of general ADP-methods and are tailored to match the characteristics of DVRPs. A comparison with conventional state-of-the-art benchmark heuristics for a DVRP with stochastic customer requests proves the ADP-methods to be highly advantageous.

Directive 2014/104/EU aims to facilitate compensation for victims of EU competition law infringements. The literature suggests that private damages actions may undermine leniency programs. This paper demonstrates that damages actions may, instead, also reinforce deterrence of antitrust enforcement. The paper presents a dynamic model, considering both the firms’ decision to collude and to report the cartel. Two novelties are that we consider partial compensation of victims, and consider that damages increase as the cartel lasts longer. As a result of the increasing liability for damages, the decision to collude and to apply for leniency is different for each subsequent period. The model elicits two possible effects of introducing partial compensation for victims. First, it may reduce incentives to apply for leniency. Alternatively, liability for damages may lead firms to refrain from colluding, meaning that partial compensation may also reinforce deterrence of antitrust enforcement.