Saving face and group identity

Are people willing to sacrifice resources to save one’s and others’ face? In a laboratory experiment, we study whether individuals forego resources to avoid the public exposure of the least performer in their group. We show that a majority of individuals are willing to pay to preserve not only their self- but also other group members’ image, even when group identity is minimal. When group identity is made more salient, individuals help regardless of whether the least performer is an in-group or an out-group. In contrast, people are less likely to sacrifice for individual strangers, showing a major role for group identity and reputation concerns within groups relative to an interpretation in terms of moral norms.     

Cheating,emotions, and rationality: an experiment on tax evasion

The economics-of-crime approach usually ignores the emotional cost and benefit of cheating. In this paper, we investigate the relationships between emotions, deception, and rational decision-making by means of an experiment on tax evasion. Emotions are measured by skin conductance responses and self-reports. We show that the intensity of anticipated and anticipatory emotions before reporting income positively correlates with both the decision to cheat and the proportion of evaded income. The experienced emotional arousal after an audit increases with the monetary sanctions and the arousal is even stronger when the evader’s picture is publicly displayed. We also find that the risk of a public exposure of deception deters evasion whereas the amount of fines encourages evasion. These results suggest that an audit policy that strengthens the emotional dimension of cheating favors compliance.     

How Can Internet Comparison Sites Work Optimally for Consumers?

In today's information society, there is such a large amount of available information about any given good or service that consumers are unable to make an informed choice. Internet comparison sites (ICSs) could provide a solution to this problem by comparing markets for consumers and making a comprehensive recommendation. However, currently, they are not fully effective for consumers. Consumers do not trust ICSs because of concerns about commission biases and lack of full market coverage. To be fully effective, ICSs also ought to cover non-price dimensions such as product quality and after-sales service. Changing the economic model from the current two-sided platform to a one-sided platform could solve these problems. In order for this to occur, changes or clarifications to existing EU consumer laws might need to be made.     

New technology based firms and the emergence of new industries: some employment implications

This article challenges conventional theories on the role of NTBFs in the growth of new industries. Its'community dynamics'approach is an alternative to the SPRU model of'dynamic complementaries'and argues that while NTBFs are crucial, their capacity for employment generation is low.     

Taxation,redistribution, and observability in social dilemmas

In the presence of social dilemmas, cooperation is more difficult to achieve when populations are heterogeneous because of conflicting interests within groups. We examine cooperation in the context of a nonlinear common pool resource game, in which individuals have unequal extraction capacities and have to decide on their extraction of resources from the common pool. We introduce monetary and nonmonetary mechanisms in this environment. The two monetary mechanisms are tax extraction and redistribution of the tax revenue. These include a Pigovian per‐unit tax mechanism and an increasing block tax that only taxes units extracted above the social optimum. Another mechanism varies the observability of individual decisions. We find that the two tax and redistribution mechanisms reduce extraction, increase efficiency, and decrease inequality within groups. In contrast, observability impacts only the baseline condition by encouraging free‐riding instead of creating moral pressure to cooperate.     

Post-earnings announcement drift and parameter uncertainty: evidence from industry and market news

Review of Quantitative Finance and Accounting - Post-earnings announcement drift (PEAD), one of the most prominent and robust return anomalies, is often attributed to investor naiveté or...     

On the Market Timing of Hedging: Evidence from U.S. Oil and Gas Producers

Review of Quantitative Finance and Accounting - Using a hand-collected data, we provide evidence of extensive use of commodity derivative in hedging among U.S. oil and gas producers. We find large...     

Robust risk aggregation with neural networks

We consider settings in which the distribution of a multivariate random variable is partly ambiguous. We assume the ambiguity lies on the level of the dependence structure, and that the marginal distributions are known. Furthermore, a current best guess for the distribution, called reference measure, is available. We work with the set of distributions that are both close to the given reference measure in a transportation distance (e.g., the Wasserstein distance), and additionally have the correct marginal structure. The goal is to find upper and lower bounds for integrals of interest with respect to distributions in this set. The described problem appears naturally in the context of risk aggregation. When aggregating different risks, the marginal distributions of these risks are known and the task is to quantify their joint effect on a given system. This is typically done by applying a meaningful risk measure to the sum of the individual risks. For this purpose, the stochastic interdependencies between the risks need to be specified. In practice, the models of this dependence structure are however subject to relatively high model ambiguity. The contribution of this paper is twofold: First, we derive a dual representation of the considered problem and prove that strong duality holds. Second, we propose a generally applicable and computationally feasible method, which relies on neural networks, in order to numerically solve the derived dual problem. The latter method is tested on a number of toy examples, before it is finally applied to perform robust risk aggregation in a real‐world instance.     

How frequent a BEER? Assessing the impact of data frequency on real exchange rate misalignment estimation

This article explores the robustness of Behavioural Equilibrium Exchange Rate models, employed to estimate real effective exchange rate misalignments, to the frequency of the underlying data. It compares misalignments stemming from an annual model, estimated since 1980, and a comparable quarterly model, estimated since 1999. The two sets of estimates are similar. Moreover, the in-sample power of quarterly REER misalignments in explaining subsequent REER developments is higher than that of the annual estimates. This article therefore suggests that the “optimal” frequency of a BEER model depends on whether its resulting estimates are employed for research purposes or for policy-making activities.