In the context of a dynamic model with incomplete information, we isolate a novel mechanism of shock propagation. We term the mechanism confounding dynamics because it arises from agents' optimal signal extraction efforts on variables whose dynamics—as opposed to super-imposed noise—prevents full revelation of information. Employing methods in the space of analytic functions, we are able to obtain analytical characterizations of the equilibria that generalize the celebrated Hansen-Sargent optimal prediction formula. Our main theorem establishes conditions under which confounding dynamics emerge in equilibrium in general settings. We apply our results to a canonical one-sector real business cycle model with dispersed information. In that setting, confounding dynamics is shown to amplify the propagation of a productivity shock, producing hump-shaped impulse response functions.

在信息不完整的动态模型的背景下，我们隔离了一种新的冲击传播机制。我们称之为混淆动力学的机制因为它产生于代理对变量的最佳信号提取工作，这些变量的动态（与叠加噪声相反）阻止了信息的完全揭示。使用解析函数空间中的方法，我们能够获得均衡的解析特征，从而推广著名的 Hansen-Sargent 最优预测公式。我们的主要定理建立了在一般情况下在均衡中出现混杂动态的条件。我们将我们的结果应用于具有分散信息的规范的单一部门真实商业周期模型。在这种情况下，混杂的动态被证明会放大生产力冲击的传播，产生驼峰状的脉冲响应函数。