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Vincent Vannetelbosch - One of the best experts on this subject based on the ideXlab platform.
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horizon k Farsightedness in criminal networks
Games, 2021Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We study the criminal networks that will emerge in the long run when criminals are neither myopic nor completely farsighted but have some limited degree of Farsightedness. We adopt the horizon-K farsighted set to answer this question. We find that in criminal networks with n criminals, the set consisting of the complete network is a horizon-K farsighted set whenever the degree of Farsightedness of the criminals is larger than or equal to (n−1). Moreover, the complete network is the unique horizon-(n−1) farsighted set. Hence, the predictions obtained in case of completely farsighted criminals still hold when criminals are much less farsighted.
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horizon k Farsightedness in criminal networks
Research Papers in Economics, 2021Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We study the criminal networks that will emerge in the long run when criminals are neither myopic nor completely farsighted but have some limited degree of Farsightedness. We adopt the horizon-K farsighted set of Herings, Mauleon and Vannetelbosch (2019) to answer this question. We Ond that in criminal networks with n criminals, the set consisting of the complete network is a horizon-K farsighted set whenever the degree of Farsightedness of the criminals is larger than or equal to (n 1). Moreover, the complete network is the unique horizon-(n 1) farsighted set. Hence, the predictions obtained in case of completely farsighted criminals still hold when criminals are much less farsighted.
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stability of networks under horizon k Farsightedness
Economic Theory, 2019Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We introduce the concept of a horizon-K farsighted set to study the influence of the degree of Farsightedness on network stability. The concept generalizes existing concepts where all players are either fully myopic or fully farsighted. A set of networks $$G_{K}$$ is a horizon-K farsighted set if three conditions are satisfied. First, external deviations should be horizon-K deterred. Second, from any network outside of $$G_{K}$$ there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in $$G_{K}$$ . Third, there is no proper subset of $$G_{K}$$ satisfying the first two conditions. We show that a horizon-K farsighted set always exists and that the horizon-1 farsighted set $$G_{1}$$ is always unique. For generic allocation rules, the set $$G_{1}$$ always contains a horizon-K farsighted set for any K. We provide easy to verify conditions for a set of networks to be a horizon-K farsighted set, and we consider the efficiency of networks in horizon-K farsighted sets. We discuss the effects of players with different horizons in an example of criminal networks.
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Network Formation Games
The Oxford Handbook of the Economics of Networks, 2016Co-Authors: Ana Mauleon, Vincent VannetelboschAbstract:In many economic networks, the network is not exogenous but instead agents decide what links they want to build. A central question is predicting the networks that agents will form. This chapter presents myopic and farsighted concepts for modeling network formation when the formation of a link requires the consent of both agents. The chapter illustrates the bites that these solution concepts have on economic applications and investigates whether the networks formed by farsighted agents are efficient and different from those formed by myopic agents. Three models of network formation are analyzed: networks of R&D collaborations, networks of free trade agreements, and criminal networks. It is shown that, depending on the application, myopia and Farsightedness may lead to divergent predictions, and Farsightedness can help to support the emergence of efficient networks.
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stability of networks under level k Farsightedness
Social Science Research Network, 2014Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We provide a tractable concept that can be used to study the influence of the degree of Farsightedness on network stability. A set of networks GK is a level-K farsightedly stable set if three conditions are satisfied. First, external deviations should be deterred. Second, from any network outside of GK there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in GK. Third, there is no proper subset of GK satisfying the first two conditions.We show that a level-K farsightedly stable set always exists and we provide a sufficient condition for the uniqueness of a level-K farsightedly stable set. There is a unique level-1 farsightedly stable set G1 consisting of all networks that belong to closed cycles. Level-K farsighted stability leads to a refinement of G1 for generic allocation rules. We then provide easy to verify conditions for a set to be level-K farsightedly stable and we consider the relationship between level-K farsighted stability and efficiency of networks. We show the tractability of the concept by applying it to a model of criminal networks.
Ana Mauleon - One of the best experts on this subject based on the ideXlab platform.
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horizon k Farsightedness in criminal networks
Games, 2021Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We study the criminal networks that will emerge in the long run when criminals are neither myopic nor completely farsighted but have some limited degree of Farsightedness. We adopt the horizon-K farsighted set to answer this question. We find that in criminal networks with n criminals, the set consisting of the complete network is a horizon-K farsighted set whenever the degree of Farsightedness of the criminals is larger than or equal to (n−1). Moreover, the complete network is the unique horizon-(n−1) farsighted set. Hence, the predictions obtained in case of completely farsighted criminals still hold when criminals are much less farsighted.
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horizon k Farsightedness in criminal networks
Research Papers in Economics, 2021Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We study the criminal networks that will emerge in the long run when criminals are neither myopic nor completely farsighted but have some limited degree of Farsightedness. We adopt the horizon-K farsighted set of Herings, Mauleon and Vannetelbosch (2019) to answer this question. We Ond that in criminal networks with n criminals, the set consisting of the complete network is a horizon-K farsighted set whenever the degree of Farsightedness of the criminals is larger than or equal to (n 1). Moreover, the complete network is the unique horizon-(n 1) farsighted set. Hence, the predictions obtained in case of completely farsighted criminals still hold when criminals are much less farsighted.
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stability of networks under horizon k Farsightedness
Economic Theory, 2019Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We introduce the concept of a horizon-K farsighted set to study the influence of the degree of Farsightedness on network stability. The concept generalizes existing concepts where all players are either fully myopic or fully farsighted. A set of networks $$G_{K}$$ is a horizon-K farsighted set if three conditions are satisfied. First, external deviations should be horizon-K deterred. Second, from any network outside of $$G_{K}$$ there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in $$G_{K}$$ . Third, there is no proper subset of $$G_{K}$$ satisfying the first two conditions. We show that a horizon-K farsighted set always exists and that the horizon-1 farsighted set $$G_{1}$$ is always unique. For generic allocation rules, the set $$G_{1}$$ always contains a horizon-K farsighted set for any K. We provide easy to verify conditions for a set of networks to be a horizon-K farsighted set, and we consider the efficiency of networks in horizon-K farsighted sets. We discuss the effects of players with different horizons in an example of criminal networks.
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Network Formation Games
The Oxford Handbook of the Economics of Networks, 2016Co-Authors: Ana Mauleon, Vincent VannetelboschAbstract:In many economic networks, the network is not exogenous but instead agents decide what links they want to build. A central question is predicting the networks that agents will form. This chapter presents myopic and farsighted concepts for modeling network formation when the formation of a link requires the consent of both agents. The chapter illustrates the bites that these solution concepts have on economic applications and investigates whether the networks formed by farsighted agents are efficient and different from those formed by myopic agents. Three models of network formation are analyzed: networks of R&D collaborations, networks of free trade agreements, and criminal networks. It is shown that, depending on the application, myopia and Farsightedness may lead to divergent predictions, and Farsightedness can help to support the emergence of efficient networks.
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stability of networks under level k Farsightedness
Social Science Research Network, 2014Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We provide a tractable concept that can be used to study the influence of the degree of Farsightedness on network stability. A set of networks GK is a level-K farsightedly stable set if three conditions are satisfied. First, external deviations should be deterred. Second, from any network outside of GK there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in GK. Third, there is no proper subset of GK satisfying the first two conditions.We show that a level-K farsightedly stable set always exists and we provide a sufficient condition for the uniqueness of a level-K farsightedly stable set. There is a unique level-1 farsightedly stable set G1 consisting of all networks that belong to closed cycles. Level-K farsighted stability leads to a refinement of G1 for generic allocation rules. We then provide easy to verify conditions for a set to be level-K farsightedly stable and we consider the relationship between level-K farsighted stability and efficiency of networks. We show the tractability of the concept by applying it to a model of criminal networks.
Jeanjacques P Herings - One of the best experts on this subject based on the ideXlab platform.
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horizon k Farsightedness in criminal networks
Games, 2021Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We study the criminal networks that will emerge in the long run when criminals are neither myopic nor completely farsighted but have some limited degree of Farsightedness. We adopt the horizon-K farsighted set to answer this question. We find that in criminal networks with n criminals, the set consisting of the complete network is a horizon-K farsighted set whenever the degree of Farsightedness of the criminals is larger than or equal to (n−1). Moreover, the complete network is the unique horizon-(n−1) farsighted set. Hence, the predictions obtained in case of completely farsighted criminals still hold when criminals are much less farsighted.
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horizon k Farsightedness in criminal networks
Research Papers in Economics, 2021Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We study the criminal networks that will emerge in the long run when criminals are neither myopic nor completely farsighted but have some limited degree of Farsightedness. We adopt the horizon-K farsighted set of Herings, Mauleon and Vannetelbosch (2019) to answer this question. We Ond that in criminal networks with n criminals, the set consisting of the complete network is a horizon-K farsighted set whenever the degree of Farsightedness of the criminals is larger than or equal to (n 1). Moreover, the complete network is the unique horizon-(n 1) farsighted set. Hence, the predictions obtained in case of completely farsighted criminals still hold when criminals are much less farsighted.
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stability of networks under horizon k Farsightedness
Economic Theory, 2019Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We introduce the concept of a horizon-K farsighted set to study the influence of the degree of Farsightedness on network stability. The concept generalizes existing concepts where all players are either fully myopic or fully farsighted. A set of networks $$G_{K}$$ is a horizon-K farsighted set if three conditions are satisfied. First, external deviations should be horizon-K deterred. Second, from any network outside of $$G_{K}$$ there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in $$G_{K}$$ . Third, there is no proper subset of $$G_{K}$$ satisfying the first two conditions. We show that a horizon-K farsighted set always exists and that the horizon-1 farsighted set $$G_{1}$$ is always unique. For generic allocation rules, the set $$G_{1}$$ always contains a horizon-K farsighted set for any K. We provide easy to verify conditions for a set of networks to be a horizon-K farsighted set, and we consider the efficiency of networks in horizon-K farsighted sets. We discuss the effects of players with different horizons in an example of criminal networks.
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Stability of Networks under Horizon-K Farsightedness
'Springer Science and Business Media LLC', 2018Co-Authors: Jeanjacques P Herings, Mauleon Ana, Vannetelbosch VincentAbstract:We introduce the concept of a horizon-K farsighted set to study the influence of the degree of Farsightedness on network stability. The concept generalizes existing concepts where all players are either fully myopic or fully farsighted. We show that a horizon-K farsighted set always exists and that the horizon-1 farsighted set G₁ is always unique. For generic allocation rules, the set G₁ always contains a horizon-K farsighted set for any K. We provide easy to verify conditions for a set of networks to be a horizon-K farsighted set and we consider the efficiency of networks in horizon-K farsighted sets. We discuss the effects of players with different horizons in an example of criminal networks
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stability of networks under level k Farsightedness
Social Science Research Network, 2014Co-Authors: Jeanjacques P Herings, Ana Mauleon, Vincent VannetelboschAbstract:We provide a tractable concept that can be used to study the influence of the degree of Farsightedness on network stability. A set of networks GK is a level-K farsightedly stable set if three conditions are satisfied. First, external deviations should be deterred. Second, from any network outside of GK there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in GK. Third, there is no proper subset of GK satisfying the first two conditions.We show that a level-K farsightedly stable set always exists and we provide a sufficient condition for the uniqueness of a level-K farsightedly stable set. There is a unique level-1 farsightedly stable set G1 consisting of all networks that belong to closed cycles. Level-K farsighted stability leads to a refinement of G1 for generic allocation rules. We then provide easy to verify conditions for a set to be level-K farsightedly stable and we consider the relationship between level-K farsighted stability and efficiency of networks. We show the tractability of the concept by applying it to a model of criminal networks.
Marina Sandomirskaia - One of the best experts on this subject based on the ideXlab platform.
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Nash-2 Equilibrium: Selective Farsightedness Under Uncertain Response
Group Decision and Negotiation, 2019Co-Authors: Marina SandomirskaiaAbstract:This paper provides an extended analysis of an equilibrium concept for non-cooperative games with boundedly rational players: Nash-2 equilibrium. Players think one step ahead and account for all profitable responses of player-specific subsets of opponents because of both the cognitive limitations on predicting everyone’s reaction and the inability to make deeper and certain predictions. They cautiously reject improvements that might lead to worse profits after some reasonable response. For n-person games we introduce the notion of a reflection network consisting of direct competitors to express the idea of selective Farsightedness. For almost every 2-person game with a complete reflection network, we prove the existence of a Nash-2 equilibrium. Nash-2 equilibrium sets are obtained in models of price and quantity competition, and in Tullock’s rent-seeking model with two players. It is shown that such farsighted behavior may provide strategic support for tacit collusion. The analyses of n-person Prisoner’s dilemma and oligopoly models with a star reflection structure demonstrate some possibilities of strategic collusion and a large variety of potentially stable outcomes.
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nash 2 equilibrium selective Farsightedness under uncertain response
MPRA Paper, 2017Co-Authors: Marina SandomirskaiaAbstract:This paper provides an extended analysis of an equilibrium concept for non-cooperative games with boundedly rational players: a Nash-2 equilibrium. Players think one step ahead and account all profitable responses of player-specific subsets of opponents because of both the cognitive limitations to predict everyone's reaction and the inability to make more deep and certain prediction even about a narrow sample of agents. They cautiously reject improvements that might lead to poorest profit after some possible reasonable response. For $n$-person games we introduce a notion of reflection network consisting of direct competitors to express the idea of selective Farsightedness. For almost every 2-person game with a complete reflection network, we prove the existence of Nash-2 equilibrium. Nash-2 equilibrium sets in the models of price and quantity competition, and in Tullock's rent-seeking model with 2 players are obtained. It is shown that such a farsighted behavior may provide a strategic support for tacit collusion.
Tomas Sjostrom - One of the best experts on this subject based on the ideXlab platform.
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sovereign debt election concerns and the democratic disadvantage
Oxford Economic Papers, 2019Co-Authors: Amrita Dhillon, Andrew Pickering, Tomas SjostromAbstract:We examine default decisions under different political systems. If democratically elected politicians are unable to make credible commitments to repay externally held debt, default rates are inefficiently high because politicians internalize voter utility loss from repayment. Politicians who are motivated by electoral concerns are more likely to default in order to avoid voter utility losses, and, since lenders recognize this, interest rates and risk premiarise. Therefore, democracy potentially confers a credit market disadvantage. However, farsighted institutions that take into account how interest rates respond to default risk can ameliorate the disadvantage. Using a numerical measure of institutional Farsightedness obtained from the Government Insight Business Risk and Conditions database, we …find that the observed relationship between credit-ratings and democratic status is indeed strongly conditional on Farsightedness. With myopic institutions, democracy is estimated to cost on average about 2.5 investment grades. With farsighte institutions there is, if anything, a democratic advantage.
