884 research outputs found
Existence and monotonicity of optimal debt contracts in costly state verification models
This note gives a simple proof of the existence and monotonicity of optimal debt contracts in simple models of borrowing and lending with ex-post asymmetric information, risk-averse agents and heterogeneous beliefs. Our argument is based on the concept of nondecreasing rearrangement and on a supermodular version of Hardy-Littlewood inequality.
Debt Contracts with ex-ante and ex-post Asymmetric Information: An Example
We consider a simple model of lending and borrowing combining two informational problems: adverse selection and costly state verification. Our analysis highlights the interaction between these two informational problems. We notably show that the higher the monitoring cost, the less discriminating the optimal menu of contracts is.debt contracts, diversity of opinions, screening, costly monitoring, pooling
Debt contracts with ex-ante and ex-post asymmetric information: an example.
We consider a simple model of lending and borrowing combining two informational problems: adverse selection and costly state verification. Our analysis highlights the interaction between these two informational problems. We notably show that the higher the monitoring cost, the less discriminating the optimal menu of contracts is.Debt contracts; Diversity of opinions; Screening; Costly monitoring; Pooling;
Optimal debt contracts and diversity of opinions: an extreme case of bunching
This paper studies optimal menus of debt contracts such as secured debentures or bonds, in the presence of diversity of opinions between borrowers and lenders. We first characterize incentive compatible contracts, then prove the existence of optimal debt contracts. Finally, we are able to explicitly characterize such optimal menus within a specific case: we notably show that borrowers optimally offer at most two contracts, which is an extreme case of bunching.debt contracts, heterogeneity of beliefs, multidimensional screening, bunching
Bilateral Commitment
We consider non-cooperative environments in which two players have the power to commit but cannot sign binding agreements. We show that by committing to a set of actions rather than to a single action, players can implement a wide range of action profiles. We give a complete characterization of implementable profiles and provide a simple method to find them. Profiles implementable by bilateral commitments are shown to be generically inefficient. Surprisingly, allowing for gradualism (i.e., step by step commitment) does not change the set of implementable profiles.Commitment; self-enforcing; generic inefficiency; agreements; Pareto-improvement
More strategies, more Nash equilibria
This short paper isolates a non-trivial class of games for which there exists a monotone relation between the size of pure strategy spaces and the number of pure Nash equilibria (Theorem). This class is that of two- player nice games, i.e., games with compact real intervals as strategy spaces and continuous and strictly quasi-concave payoff functions, assumptions met by many economic models. We then show that the sufficient conditions for Theorem to hold are tight.Strategic-form games, strategy spaces, Nash equilibrium, two players
Bilateral Commitment
We consider non-cooperative environments in which two players have the power to commit but cannot sign binding agreements. We show that by committing to a set of actions rather than to a single action, players can implement a wide range of action profiles. We give a complete characterization of implementable profiles and provide a simple method to find them. Profiles implementable by bilateral commitments are shown to be generically inefficient. Surprisingly, allowing for gradualism (i.e., step by step commitment) does not change the set of implementable profiles.commitment, self-enforcing, treaties, inefficiency, agreements, Pareto-improvement
Fader Networks: Manipulating Images by Sliding Attributes
This paper introduces a new encoder-decoder architecture that is trained to
reconstruct images by disentangling the salient information of the image and
the values of attributes directly in the latent space. As a result, after
training, our model can generate different realistic versions of an input image
by varying the attribute values. By using continuous attribute values, we can
choose how much a specific attribute is perceivable in the generated image.
This property could allow for applications where users can modify an image
using sliding knobs, like faders on a mixing console, to change the facial
expression of a portrait, or to update the color of some objects. Compared to
the state-of-the-art which mostly relies on training adversarial networks in
pixel space by altering attribute values at train time, our approach results in
much simpler training schemes and nicely scales to multiple attributes. We
present evidence that our model can significantly change the perceived value of
the attributes while preserving the naturalness of images.Comment: NIPS 201
First reports of autochthonous eyeworm infection by Thelazia callipaeda (Spirurida, Thelaziidae) in dogs and cat from France
Thelazia callipaeda (Spirurida, Thelaziidae) is a small nematode living in the conjunctival sac of domestic and wild carnivores, rabbits and humans causing lacrimation, epiphora, conjunctivitis, keratitis and even corneal ulcers. The first autochthonous cases of thelaziosis affecting four dogs and one cat living in South Western France (Dordogne area) are reported and described. Nematodes recovered from the animals were morphologically identified as T. callipaeda and a partial region of the cytochrome oxidase c subunit 1 gene (cox1) was amplified by PCR from nematode specimens (from two dogs and the cat). In each case, this was shown to have an identical sequence to the haplotype 1 (h1) of T. callipaeda. So far, the arthropod acting as intermediate host of T. callipaeda eyeworms has not been identified in France although it might be Phortica variegata (Steganinae, Drosophilidae) as recently described in Italy
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