Governments across the world have implemented restrictive policies to slow the spread of COVID-19. Recommended face mask use has been a controversially discussed policy, among others, due to potential adverse effects on physical distancing. Using a randomized field experiment (N = 300), we show that individuals kept a significantly larger distance from someone wearing a face mask than from an unmasked person during the early days of the pandemic. According to an additional survey experiment (N = 456) conducted at the time, masked individuals were not perceived as being more infectious than unmasked ones, but they were believed to prefer more distancing. This result suggests that wearing a mask served as a social signal that led others to increase the distance they kept. Our findings provide evidence against the claim that mask use creates a false sense of security that would negatively affect physical distancing. Furthermore, our results suggest that behavior has informational content that may be affected by policies.

This study employs bilateral data on external assets to examine the impact of climate policies on the reallocation of international capital. We find that the stringency of climate policy in the destination country is significantly and positively associated with an increase in the allocation of portfolio equity and banking investment to that country. However, it does not show significant effects on the allocation of foreign direct investment and portfolio debt. Our findings are not driven by valuation effects, and we present evidence that suggests diversification, suasion, and uncertainty mitigation as possible underlying mechanisms.

The economy is a complex system because market participants do not act independently but adjust their behavior to other agents and to the outcome which emerges from their joint actions (Arthur, 2014). Dependencies among participants can impede policy makers capabilities to influence or steer the course of the economy. Kambhu et al. (2007) argue that to influence developments in financial markets, for instance to prevent crises from spreading, there are only “coarse or indirect options” available for policy makers. Similar to crises which propagate through a complex system, interventions might result in unintended side effects which can also disseminate through the system. Thus, in a complex system, unintended consequences of policy efforts may well be the rule. Policy makers try to ward off or mitigate negative consequences for the economy and society during periods of crisis. For instance, during the Covid crisis large scale support programs for firms in Western economies were set up to avoid bankruptcies. Similarly, during the sovereign debt crisis in the Eurozone, the European Central Bank (ECB) set up large scale asset purchase programs as well as additionally longer-term refinancing operations (LTRO) which provided immediate support to financial market participants’ liquidity positions and thereby prevented a melt-down of the financial system. During these periods, immediate and abundant liquidity supply is of utmost importance. Meanwhile, crisis measures, due to their massive scale and non-specific target group, may entail unknown or unintended side effects for instance on competition among market participants, firms’ investment behavior, or changes in lending strategies and risk taking behavior of banks. Likewise, new regulatory frameworks such as the introduction of new markets can have consequences previously not thought of. For policy makers it is important to know direct effects of policy interventions but also to be aware of the possibility and impact of indirect or unexpected side effects in order to evaluate measures taken and to learn for future design of regulation or intervention.

Understanding human behavior in its entire complexity is an ambitious if not impossible challenge. It is however possible to study particular aspects of human behavior through experiments that allow us to isolate specific facets in the decision-making process, ultimately leading to a better understanding of human behavior as a whole. This thesis covers three experimental articles on unethical economic behavior and sheds light on the motives and circumstances that lead individuals to engage in these activities. Clearly, unethical behavior in all its different manifestations can pose great risk to society – both at the large (e.g. corporate tax evasion) and small (e.g. shoplifting) scale – making it a relevant topic to be studied in economic research. Trying to understand unethical behavior through the lenses of traditional economic theory is problematic.

Es handelt sich um eine kumulative Schrift, die aus Artikeln und einer vorangestellten Einleitung besteht

The recent advances in automation technology, robotics in particular, have sparked a heated debate over the future of labor and human society at large. The ongoing process of robotization may engender profound impacts on various segments of the labor market. Given the far-reaching implications of robots, it is thus very important to understand the scale and scope of robot use and characteristics of robot users. However, the main challenge is the limited availability of robot data at the microeconomic level (Raj and Seamans, 2018). Due to the data constraint, the bulk of the existing literature relies on cross-country industry-level data from the International Federation of Robotics (IFR). The lack of micro-level robot data makes it difficult to paint a comprehensive picture of robotization in industrial settings, and perhaps more importantly, to assess how within-industry firm level heterogeneity manifests itself in robot use and adoption.