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Shallow meritocracy
(2023)
Meritocracies aspire to reward hard work and promise not to judge individuals by the circumstances into which they were born. However, circumstances often shape the choice to work hard. I show that people's merit judgments are "shallow" and insensitive to this effect. They hold others responsible for their choices, even if these choices have been shaped by unequal circumstances. In an experiment, US participants judge how much money workers deserve for the effort they exert. Unequal circumstances disadvantage some workers and discourage them from working hard. Nonetheless, participants reward the effort of disadvantaged and advantaged workers identically, regardless of the circumstances under which choices are made. For some participants, this reflects their fundamental view regarding fair rewards. For others, the neglect results from the uncertain counterfactual. They understand that circumstances shape choices but do not correct for this because the counterfactual—what would have happened under equal circumstances—remains uncertain.
We analyze the repercussions of different kinds of uncertainty on cash demand, including uncertainty of the digital infrastructures, confidence crises of the financial system, natural disasters, political uncertainties, and inflationary crises. Based on a comprehensive literature survey, theoretical considerations and complemented by case studies, we derive a classification scheme how cash holdings typically evolve in each of these types of uncertainty by separating between demand for domestic and international cash as well as between transaction and store of value balances. Hereby, we focus on the stabilizing macroeconomic properties of cash and recommend guidelines for cash supply by central banks and the banking system. Finally, we exemplify our analysis with five case studies from the developing world, namely Venezuela, Zimbabwe, Afghanistan, Iraq, and Libya.
This paper challenges widespread assumptions in trust research according to which trust and conflict are opposing terms or where trust is generally seen as a value. Rather, it argues that trust is only valuable if properly justified, and it places such justifications in contexts of social and political conflict. For these purposes, the paper suggests a distinction between a general concept and various conceptions of trust, and it defines the concept as a four-place one. With regard to the justification of trust, a distinction between internal and full justification is introduced, and the justification of trust is linked to relations of justification between trusters and trusted. Finally, trust in conflict(s) emerges were such relations exist among the parties of a conflict, often by way of institutional mediation.
A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autogressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of uncertainty shocks on economic activity. We prove by counterexample that this practice is invalid in general, whether the data generating process is a structural VAR model or a dynamic stochastic general equilibrium model.
Droughts are anticipated to intensify in many parts of the world due to climate change. However, the issue of drought definition, namely the diversity of drought indices, makes it difficult to compare drought assessments. This issue is widely known, but its relative importance has never been quantitatively evaluated in comparison to other sources of uncertainty. Here, encompassing three drought categories (meteorological, agricultural, and hydrological droughts) with four temporal scales of interest, we evaluated changes in the drought frequency using multi-model and multi-scenario simulations to identify areas where the definition issue could result in pronounced uncertainties and to what extent. We investigated the disagreement in the signs of changes between drought definitions and decomposed the variance into four main factors: drought definitions, greenhouse gas concentration scenarios, global climate models, and global water models, as well as their interactions. The results show that models were the primary sources of variance over 82% of the global land area. On the other hand, the drought definition was the dominant source of variance in the remaining 17%, especially in parts of northern high-latitudes. Our results highlight specific regions where differences in drought definitions result in a large spread among projections, including areas showing opposite signs of significant changes. At a global scale, 7% of the variance resulted independently from the definition issue, and that value increased to 44% when 1st and 2nd order interactions were considered. The quantitative results suggest that by clarifying hydrological processes or sectors of interest, one could avoid these uncertainties in drought assessments to obtain a clearer picture of future drought change.
We relate time-varying aggregate ambiguity (V-VSTOXX) to individual investor trading. We use the trading records of more than 100,000 individual investors from a large German online brokerage from March 2010 to December 2015. We find that an increase in ambiguity is associated with increased investor activity. It also leads to a reduction in risk-taking which does not reverse over the following days. When ambiguity is high, the effect of sentiment looms larger. Survey evidence reveals that ambiguity averse investors are more prone to ambiguity shocks. Our results are robust to alternative survey-, newspaper- or market-based ambiguity measures.
Uncertainty is a central theme in the illness experiences of older cancer patients throughout their illness trajectory. Mishel’s popular theory on uncertainty during illness approaches uncertainty as an outcome and is characterized by the patient’s inability to find meaning in illness events. This study used the concepts of liminality and subjunctivity to explore uncertainty throughout the illness trajectory of cancer patients. We interviewed 18 older (age range = 57–92 years) patients with breast cancer or gastro-intestinal cancer 3 to 4 years post diagnosis. Our analysis is based on the QUAGOL guide that draws on elements of grounded theory such as constant comparison. We found that liminality and subjunctivity provide a useful frame for understanding uncertainty with a specific focus on its productive potential and meaning making. Health care professionals should be open to acquiring a complete picture of patients’ diverse and dynamic experiences of uncertainty in the different stages of their illness trajectory.
This special issue explores how finance deploys time, structures the future, and interacts with actors and institutions that sometimes function according to very different temporal regimes. Finance capitalism’s logic of recurrence, repetitive cycles, and successive ruptures has long been with us, but the essays in this special issue are particularly interested in how recent decades of intensified financialization have restructured temporal experience. They interrogate the production and dissemination of agency in an age of acceleration, risk, and uncertainty, asking how the temporality inscribed in financial transactions emerges from and simultaneously shapes individual and social practice. Topics covered range from the logic of finance and foundational concepts of financial theory to the intersection between objective structures and social practice, the role of literature, and finally questions of social insecurity, political action, and the possibility of resistance within a context of competing temporalities. In this introduction, the editors delineate some fundamental concepts and questions for our financial times.
The Earth's future depends on how we manage the manifold risks of climate change (CC). It is state-of-the-art to assume that risk reduction requires participatory management involving a broad range of stakeholders and scientists. However, there is still little knowledge about the optimal design of participatory climate change risk management processes (PRMPs), in particular with respect to considering the multitude of substantial uncertainties that are relevant for PRMPs. To support the many local to regional PRMPs that are necessary for a successful global-scale reduction of CC risks, we present a roadmap for designing such transdisciplinary knowledge integration processes. The roadmap suggests ways in which uncertainties can be comprehensively addressed within a PRMP. We discuss the concept of CC risks and their management and propose an uncertainty framework that distinguishes epistemic, ontological, and linguistic uncertainty as well as ambiguity. Uncertainties relevant for CC risk management are identified. Communicative and modeling methods that support social learning as well as the development of risk management strategies are proposed for each of six phases of a PRMP. Finally, we recommend how to evaluate PRMPs as such evaluations and their publication are paramount for achieving a reduction of CC risks.
The archaeological data dealt with in our database solution Antike Fundmünzen in Europa (AFE), which records finds of ancient coins, is entered by humans. Based on the Linked Open Data (LOD) approach, we link our data to Nomisma.org concepts, as well as to other resources like Online Coins of the Roman Empire (OCRE). Since information such as denomination, material, etc. is recorded for each single coin, this information should be identical for coins of the same type. Unfortunately, this is not always the case, mostly due to human errors. Based on rules that we implemented, we were able to make use of this redundant information in order to detect possible errors within AFE, and were even able to correct errors in Nomimsa.org. However, the approach had the weakness that it was necessary to transform the data into an internal data model. In a second step, we therefore developed our rules within the Linked Open Data world. The rules can now be applied to datasets following the Nomisma. org modelling approach, as we demonstrated with data held by Corpus Nummorum Thracorum (CNT). We believe that the use of methods like this to increase the data quality of individual databases, as well as across different data sources and up to the higher levels of OCRE and Nomisma.org, is mandatory in order to increase trust in them.