Parameter Learning in General Equilibrium: The Asset Pricing Implications
研究了当代表性代理人偏好早期解决不确定性时，参数学习如何放大宏观经济冲击对边际效用的影响，通过理性信念更新产生主观长期消费风险，有助于解释标准资产定价谜题。
Parameter learning strongly amplifies the impact of macroeconomic shocks on marginal utility when the representative agent has a preference for early resolution of uncertainty. This occurs as rational belief updating generates subjective long-run consumption risks. We consider general equilibrium models with unknown parameters governing either long-run economic growth, rare events, or model selection. Overall, parameter learning generates long-lasting, quantitatively significant additional macroeconomic risks that help explain standard asset pricing puzzles.