Francis Bloch

We study a model of non-cooperative interaction between two infrastructure managers (IMs) for international rail transport. We compare equilibrium access charges when the IMs are unregulated and regulated. We show that cooperation among IMs eliminates double-marginalization to the benefit of passengers and IMs. We also show that the delegation of access charge collection with adequate transfers allows the two IMs to reach efficiency, both in the unregulated and regulated régimes. We study the effect of differences in regulatory policies, and analyze the effect of monopoly power of train operators and competition among high speed and low speed train routes on access charges.

Lengthy cover-ups are a repeated feature of the organizational landscape. This paper studies executives’ optimal cover-up strategies given the penalties and the evolving beliefs of strategic outside parties who investigate malfeasance. The analysis shows that organizational self-policing and external investigation are strategic substitutes in any given period. Over time, successful cover-ups increase the incentive to cover up, and changes in the current environment, such as an increased awareness of the harmful effects of the employee’s actions, can result in a reduction in cover-ups in the short term but an increase in the long term. We analyze how fines for executives and rewards for investigators affect the welfare of different stakeholders. We extend the model to study two alternative prosecutorial regimes: a prosecutor who can commit to an investigation policy and a long-lived prosecutor who internalizes the impact of their early decisions on a subsequent prosecutor’s incentives.

This paper studies optimal targeting when the planner knows the architecture of the network but not the identities of agents occupying different positions in the network. We show that the planner’s ability to discriminate among agents depends on the balance between in- and out-neighborhoods in the social network. When influence is reciprocal, the knowledge of the network architecture is sufficient for the planner to implement the first-best actions. When in- and out-neighborhoods are imbalanced, pairs of players have an incentive to jointly misreport their identities. This situation arises when one agent influences all other agents, or when one agent is being influenced by all other agents. It also arises in hierarchical structures with nested neighborhoods where agents at lower tiers of the network are influenced by the same agents as agents at upper tiers who influence them.

We consider a problem of mechanism design without money, where a planner selects a winner among a set of agents with binary types and receives outside signals (like the report of external referees). We show that there is a gap between the optimal Dominant Strategy Incentive Compatible (DSIC) mechanism and the optimal Bayesian Incentive Compatible (BIC) mechanism. In the optimal BIC mechanism, the planner can leverage the outside signal to elicit information about agents’ types. BIC mechanisms are lexicographic mechanisms, where the planner first shortlists agents who receive high reports from the referees and then uses agents’ reports to break ties among agents in the shortlist. We compare the “self-evaluation” mechanism with a “peer evaluation” mechanism where agents evaluate other agents, and show that for the same signal precision, the self- evaluation mechanism outperforms the peer evaluation mechanism. We show that optimal Ex Post Incentive Compatible (EPIC) mechanisms give the planner an intermediate value between the optimal DSIC and BIC mechanisms

We show that prominent centrality measures in network analysis are all based on additively separable and linear treatments of statistics that capture a node’s position in the network. This enables us to provide a taxonomy of centrality measures that distills them to varying on two dimensions: (i) which information they make use of about nodes’ positions, and (ii) how that information is weighted as a function of distance from the node in question. The three sorts of information about nodes’ positions that are usually used—which we refer to as “nodal statistics”—are the paths from a given node to other nodes, the walks from a given node to other nodes, and the geodesics between other nodes that include a given node. Using such statistics on nodes’ positions, we also characterize the types of trees such that centrality measures all agree, and we also discuss the properties that identify some path-based centrality measures.

This paper studies a game of attack and interception in a network, where a single attacker chooses a target and a path, and each node chooses a level of protection. We show that the Nash equilibrium of the game exists and is unique. We characterize equilibrium attack paths and attack distributions as a function of the underlying network and target values. We show that adding a link or increasing the value of a target may harm the attacker – a comparative statics effect which is reminiscent of Braess’s paradox in transportation economics. Finally, we contrast the Nash equilibrium with the equilibrium of a variant of the model: one where all nodes cooperate in interception.

We model entry decisions of rival firms into a new market with uncertain common entry costs, potential product market competition, and experimentation. We show that a separating equilibrium, where firms enter only when they learn that the cost is low and are immediately followed by their rival, always exists. We also show the existence of pooling equilibria. In these equilibria, uninformed firms coordinate to enter at specific entry dates with positive probability and firms that learn that the cost is low before those dates strategically delay their entry to hide under the cover of the uninformed firms. We show that these pooling equilibria, which do not trigger immediate entry, are more likely to exist with an early than a late entry date, that they are unique given a fixed entry date, and that equilibrium payoffs are nonmonotonic in the entry date. We also study recurrent-entry pooling equilibria with multiple entry dates for uninformed firms.

We analyze the design of a mechanism to extract a ranking of individuals according to a unidimensional characteristic, such as ability or need. Individuals, connected on a social network, only have local information about the ranking. We show that a planner can construct an ex post incentive compatible and efficient mechanism if and only if every pair of friends has a friend in common. We characterize the windmill network as the sparsest social network for which the planner can always construct a complete ranking.

Lengthy cover-ups are a repeated feature of the organizational landscape. This paper studies executives’ optimal cover-up strategies given the penalties and the evolving beliefs of strategic outside parties who investigate malfeasance. The analysis shows that organizational self-policing and external investigation are strategic substitutes in any given period. Over time, successful cover-ups increase the incentive to cover up, and changes in the current environment, such as an increased awareness of the harmful effects of the employee’s actions, can result in a reduction in cover-ups in the short term but an increase in the long term. We analyze how fines for executives and rewards for investigators affect the welfare of different stakeholders. We extend the model to study two alternative prosecutorial regimes: a prosecutor who can commit to an investigation policy and a long-lived prosecutor who internalizes the impact of their early decisions on a subsequent prosecutor’s incentives.