scholarly journals Diffusing Coordination Risk

2020 ◽  
Vol 110 (1) ◽  
pp. 271-297 ◽  
Author(s):  
Deepal Basak ◽  
Zhen Zhou
Keyword(s):  
Information Disclosure ◽  
Regime Change ◽  
Dynamic Information ◽  
Viability Test ◽  
Disclosure Policy ◽  
Private Signals

In a regime change game, privately informed agents sequentially decide whether to attack without observing others’ previous actions. To dissuade them from attacking, a principal adopts a dynamic information disclosure policy, frequent viability tests. A viability test publicly discloses whether the regime has survived the previous attacks. When such tests are sufficiently frequent, in the unique cutoff equilibrium, agents never attack if the regime passes the latest test, regardless of their private signals. We apply this theory to demonstrate that a borrower can eliminate panic-based runs by sufficiently diffusing the rollover choices across different maturity dates. (JEL C72, D82, G21)

The impacts of adaptive attacking and defending strategies on mitigation of intentional threats

Kybernetes ◽  
2010 ◽  
Vol 39 (5) ◽  
pp. 825-837 ◽  
Author(s):  
Jing Zhang ◽  
Shifei Shen ◽  
Rui Yang
Keyword(s):  
Information Disclosure ◽  
Stochastic Game ◽  
Adaptive Strategies ◽  
Decision Makers ◽  
Strategic Decision ◽  
Theoretic Approach ◽  
Content Type ◽  
Disclosure Policy ◽  
Game Theoretic ◽  
Game Theoretic Approach

PurposeThe purpose of this paper is to focus on resource allocation and information disclosure policy for defending multiple targets against intentional attacks. The intentional attacks, like terrorism events, probably cause great losses and fatalities. Attackers and defenders usually make decisions based on incomplete information. Adaptive attacking and defending strategies are considered, to study how both sides make more effective decisions according to previous fights.Design/methodology/approachA stochastic game‐theoretic approach is proposed for modeling attacker‐defender conflicts. Attackers and defenders are supposed both to be strategic decision makers and partially aware of adversary's information. Adaptive strategies are compared with different inflexible strategies in a fortification‐patrol problem, where the fortification affects the security vulnerability of targets and the patrol indicates the defensive signal.FindingsThe result shows that the intentional risk would be elevated by adaptive attack strategies. An inflexible defending strategy probably fails when facing uncertainties of adversary. It is shown that the optimal response of defenders is to adjust defending strategies by learning from previous games and assessing behaviors of adversaries to minimize the expected loss.Originality/valueThis paper explores how adaptive strategies affect attacker‐defender conflicts. The key issue is defense allocation and information disclosure policy for mitigation of intentional threats. Attackers and defenders can adjust their strategies by learning from previous fights, and the strategic adjustment of both sides may be asynchronous.

EXPRESS: Information Disclosure Policy and Its Implications: Ratcheting in Supply Chains

2021 ◽  
pp. 002224372110351
Author(s):  
Brian Mittendorf ◽  
Jiwoong Shin ◽  
Dae-Hee Yoon
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Information Disclosure ◽  
Wholesale Price ◽  
Ratchet Effect ◽  
Disclosure Policy ◽  
Long Run ◽  
Short Run ◽  
Near Term ◽  
Express Information

Fear of escalating input prices in response to retail success is a commonly-discussed phenomenon affecting supply chains. Such a ratchet effect arises when a retailer feels compelled to modify his investments to better serve the end customers in order to hide positive prospects and restrain future wholesale price hikes. In a two-period model of supply chain interactions, the authors demonstrate that such an endogenous ratchet effect can have multi-faceted reverberations. A retailer fearing price hikes may be tempted to curtail near-term profits to ensure favorable long-term pricing. In response, the supplier can use deep discounts in its initial wholesale prices to convince the retailer to focus on its short-run profits rather than long-run pricing concerns. These deep discounts not only encourage mutually beneficial investments but also alleviate double-marginalization inefficiencies along the supply chain. In light of these results, the authors demonstrate that the mandatory information disclosure policy to reduce the ratchet effect decreases total channel efficiency compared to the case without information disclosure, precisely because mandatory disclosure interrupts the healthy tension among supply chain partners. Thus, the model presents a scenario where ratcheting concerns can create a degree of self-enforcing cooperation that results in socially beneficial responses in supply chains.

scholarly journals Dynamic Information Design: A Simple Problem on Optimal Sequential Information Disclosure

2021 ◽  
Author(s):  
Farzaneh Farhadi ◽  
Demosthenis Teneketzis
Keyword(s):  
Markov Chain ◽  
Information Disclosure ◽  
Mixed Strategy ◽  
Transition Probabilities ◽  
Infinite Horizon ◽  
Information Design ◽  
Simple Problem ◽  
Time Varying ◽  
Dynamic Information ◽  
Time Threshold

AbstractWe study a dynamic information design problem in a finite-horizon setting consisting of two strategic and long-term optimizing agents, namely a principal (he) and a detector (she). The principal observes the evolution of a Markov chain that has two states, one “good” and one “bad” absorbing state, and has to decide how to sequentially disclose information to the detector. The detector’s only information consists of the messages she receives from the principal. The detector’s objective is to detect as accurately as possible the time of the jump from the good to the bad state. The principal’s objective is to delay the detector as much as possible from detecting the jump to the bad state. For this setting, we determine the optimal strategies of the principal and the detector. The detector’s optimal strategy is described by time-varying thresholds on her posterior belief of the good state. We prove that it is optimal for the principal to give no information to the detector before a time threshold, run a mixed strategy to confuse the detector at the threshold time, and reveal the true state afterward. We present an algorithm that determines both the optimal time threshold and the optimal mixed strategy that could be employed by the principal. We show, through numerical experiments, that this optimal sequential mechanism outperforms any other information disclosure strategy presented in the literature. We also show that our results can be extended to the infinite-horizon problem, to the problem where the matrix of transition probabilities of the Markov chain is time-varying, and to the case where the Markov chain has more than two states and one of the states is absorbing.

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