In important conflicts, people typically rely on experts' judgments to predict the decisions that adversaries will make. We compared the accuracy of 106 expert and 169 novice forecasts for eight real conflicts. The forecasts of experts using unaided judgment were little better than those of...

In diesem Diskussionspapier werden die Ergebnisse einer im Mai/Juni 2007 durchgeführten Unternehmensbefragung im Raum Niedersachsen vorgestellt in Bezug auf die Fragestellung, ob sich Unternehmen, die In-novationsförderung erhalten, von nicht geförderten Unternehmen in Bezug auf generelle...

This short article provides an introduction to the concept of transparency, utilizing the tools of game theory, information theory, development theory, and political economy. It considers the role of transparency in international economic law and, in particular, in international economic...

This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors’ information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the...

Based on OECD evidence, equity/housing-price busts and credit crunches are followed by substantial increases in public consumption. These increases in unproductive public spending lead to increases in distortionary marginal taxes, a policy in sharp contrast with presumably optimal Keynesian...

This paper uses the example of an exam to model multi-dimensional search under a deadline. When the dimension is two, an order-invariance property allows simple characterization of the optimal search policy. Behavior is shown to be highly sensitive to changes in the deadline, and a wide variety...

The goal programming (GP) is a well-known approach applied to multi-criteria decision making (M-DM). It has been used in many domains and the literature offers diverse extensions of this procedure. On the other hand, so far, some evident analogies between M-DM under certainty and scenario-based...

This paper studies sequential information acquisition by an ambiguity-averse decision maker (DM), who decides how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and updates prior by prior. We show that the consideration of...

We study the effect of ambiguity on timing decisions. An agent faces a stopping problem with an uncertain stopping payoff and a stochastic time limit. The agent is unsure about the correct model quantifying the uncertainty and seeks to maximize her payoff guarantee over a set of plausible...

This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors' information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the...