Suchergebnisse

AbstractForward induction, as defined by Govindan and Wilson (2009. "On Forward Induction." Econometrica 77:1–28), places a local dominance condition on off-equilibrium beliefs that restricts relevant strategy profiles for an equilibrium outcome to be infinitely more likely than profiles that include irrelevant strategies. Meanwhile, it places no global dominance restrictions and thus leaves open the possibility that a dominated strategy is deemed more likely than strategies dominating it. This paper defines strong forward induction, which improves upon forward induction. We also develop a solution concept called strong forward induction equilibrium that is obtained from iterative application of the strong forward induction criterion.

ABSTRACTWe analyse R&D cooperation between product‐market competitors within a repeated‐game framework with imperfect monitoring. When firms are patient enough, R&D cooperation is attainable without product‐market collusion. However, if firms are less patient, we show that collusion in the product market is necessary to sustain R&D cooperation. Moreover, consumers can be better off when collusion is allowed in this case.

AbstractWe study multiple research joint ventures (RJVs) using a repeated game with imperfect monitoring. Compared with the single joint venture case, we show that cooperation in multiple joint ventures creates two advantages for participating firms. First, by linking decisions together across all joint ventures firms can mitigate the likelihood of cooperation breakdowns following bad R&D outcomes. Second, as the incentive cost to sustain cooperation is independent of the number of joint ventures, the economy of scale effect reduces the efficiency loss due to imperfect monitoring.

We study a T‐period contracting problem where performance evaluations are subjective and private. We find that the principal should punish the agent for performing poorly in the future even when the evaluations were good in the past; at the same time, the agent should be given opportunities to make up for poor evaluations in the past with better performance in the future. Optimal incentives are thus asymmetric. Conditional on the same number of good evaluations, an agent whose performance improves over time should be better rewarded than one whose performance deteriorates.

Abstract The paper develops a simple model of repeated automobile insurance contracts, providing a framework for analyzing changes in aggregate insurance data in periods of changes that affect driver incentives. Experience rating of premiums gives drivers an incentive to exert effort to avoid accidents (ex ante moral hazard), and an incentive to hide accidents (ex post moral hazard). The empirical analysis, using data from the competitive insurance markets in Ontario and Alberta over a period of major legislative changes in Ontario, suggests that much of the recent decline in accidents in Ontario was due to an increased incentive to hide accidents.