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Telemonitoring devices can be used to screen consumer characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. Nevertheless, some consumers value their privacy and dislike sharing private information with insurers. In a secondbest efficient Miyazaki-Wilson-Spence (MWS) framework, we allow consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as social welfare. We find that information disclosure can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare. Yet, if all consumers are offered cross-subsidizing contracts, the introduction of a screening contract decreases or even eliminates cross-subsidies. Given the prior existence of a cross-subsidizing MWS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis informs the discussion on consumer protection in the context of digitalization. It shows that new technologies challenge cross-subsidization in insurance markets, and it stresses the negative externalities that digitalization has on consumers who are unwilling to take part in this
development
We prove the existence of an equilibrium in competitive markets with adverse selection in the sense of Miyazaki (1977), Wilson (1977), and Spence (1978) when the distribution of unobservable risk types is continuous. Our proof leverages the finite-type proof in Spence (1978) and a limiting argument akin to Hellwig (2007)’s study of optimal taxation.
Through the lens of market participants' objective to minimize counterparty risk, we provide an explanation for the reluctance to clear derivative trades in the absence of a central clearing obligation. We develop a comprehensive understanding of the benefits and potential pitfalls with respect to a single market participant's counterparty risk exposure when moving from a bilateral to a clearing architecture for derivative markets. Previous studies suggest that central clearing is beneficial for single market participants in the presence of a sufficiently large number of clearing members. We show that three elements can render central clearing harmful for a market participant's counterparty risk exposure regardless of the number of its counterparties: 1) correlation across and within derivative classes (i.e., systematic risk), 2) collateralization of derivative claims, and 3) loss sharing among clearing members. Our results have substantial implications for the design of derivatives markets, and highlight that recent central clearing reforms might not incentivize market participants to clear derivatives.
The Eastern Steppe of Mongolia is one of the world's largest mostly intact grassland ecosystems and is characterised by a close coupling of societal and natural processes. In this ecosystem, mobility is one of the key characteristics of wildlife and human societies alike. The current economic development of Mongolia is accompanied by extensive societal transformation and changes in nomadic lifestyles, which potentially affects the unique steppe ecosystem and its biodiversity. The changing lifestyles are mainly characterised by rural-urban migration, resulting in reduced mobility of herders and their livestock, and presumably affecting wildlife. The question is how mobility can be fostered under these transformation processes. Time is pressing as a new generation is born which is growing up in urban environments and with new skill sets but a potential loss of the tight connection to nature and the nomadic lifestyle.
In these volumes, we are very pleased to present a collection of papers based on talks and posters at Sinn und Bedeutung 22, which took place in Berlin and Potsdam on September 7-10, 2017, jointly organized by the Leibniz-Centre for General Linguistics (ZAS) and the University of Potsdam.
SuB22 received 183 submitted abstracts. Out of these, the organizing committee selected 39 oral presentations in the main session, 4 oral presentations in the special session ‘Semantics and Natural Logic’, and 24 poster presentations. There were an additional 6 invited talks. In total, 58 of these contributions appear in paper form in the present volumes.
In these volumes, we are very pleased to present a collection of papers based on talks and posters at Sinn und Bedeutung 22, which took place in Berlin and Potsdam on September 7-10, 2017, jointly organized by the Leibniz-Centre for General Linguistics (ZAS) and the University of Potsdam.
SuB22 received 183 submitted abstracts. Out of these, the organizing committee selected 39 oral presentations in the main session, 4 oral presentations in the special session ‘Semantics and Natural Logic’, and 24 poster presentations. There were an additional 6 invited talks. In total, 58 of these contributions appear in paper form in the present volumes.
Our recently developed LRSX Tool implements a technique to automatically prove the correctness of program transformations in higher-order program calculi which may permit recursive let-bindings as they occur in functional programming languages. A program transformation is correct if it preserves the observational semantics of programs- In our tool the so-called diagram method is automated by combining unification, matching, and reasoning on alpha-renamings on the higher-order metalanguage, and automating induction proofs via an encoding into termination problems of term rewrite systems. We explain the techniques, we illustrate the usage of the tool, and we report on experiments.
We explore space improvements in LRP, a polymorphically typed call-by-need functional core language. A relaxed space measure is chosen for the maximal size usage during an evaluation. It Abstracts from the details of the implementation via abstract machines, but it takes garbage collection into account and thus can be seen as a realistic approximation of space usage. The results are: a context lemma for space improving translations and for space equivalences; all but one reduction rule of the calculus are shown to be space improvements, and the exceptional one, the copy-rule, is shown to increase space only moderately.
Several further program transformations are shown to be space improvements or space equivalences, in particular the translation into machine expressions is a space equivalence. These results are a step Forward in making predictions about the change in runtime space behavior of optimizing transformations in callbyneed functional languages.
Exploiting the natural experiment of the German reunification, we examine how consumers adapt to a new environment in their macroeconomic forecasting. We document that East Germans expect higher in inflation and make larger forecast errors than West
Germans even decades after reunification. Differences in consumption baskets, financial literacy, risk aversion or trust in the central bank cannot fully account for these patterns. We find most support for the explanation that East Germans, who were used to a strong norm of zero inflation, persistently overadjusted the level of their expectations in the face of the initial inflation shock in reunified Germany. Our findings suggest that large changes in the economic environment can permanently impede people's ability to form accurate macroeconomic expectations, with an important role for the interaction of old norms and new experiences around the event.
Policymakers attach an important role to the macroeconomic outlook of households. Using a representative online panel form the U.S., the authors examine how individuals' macroeconomic expectations causally affect their personal economic prospects and their behavior and provide them with different professional forecasts about the likelihood of a recession. The authors find that groups with the largest exposure to aggregate risk, such as individuals working in cyclical industries, are most likely to respond to an improved macroeconomic outlook, while a large fraction of the population is unlikely to react.