Dynamic Oligopoly with Incomplete Information
研究了企业生产成本私有且仅能观察受需求冲击影响的市场价格时，动态古诺寡头中的学习与信号传递问题，刻画了对称线性马尔可夫均衡，并发现长期博弈会收敛到完全信息结果。
We consider learning and signalling in a dynamic Cournot oligopoly where firms have private information about their production costs and only observe the market price, which is subject to unobservable demand shocks. An equilibrium is Markov if play depends on the history only through the firms’ beliefs about costs and calendar time. We characterize symmetric linear Markov equilibria as solutions to a boundary value problem. In every such equilibrium, given a long enough horizon, play converges to the static complete information outcome for the realized costs, but each firm only learns its competitors’ average cost. The weights assigned to costs and beliefs under the equilibrium strategies are non-monotone over time. We explain this by decomposing incentives into signalling and learning, and discuss implications for prices, quantities, and welfare.