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经济与工商管理学院“复杂性与宏观经济学研究”跨学科沙龙讲座之五Bounded Optimization and Learning
发布时间：2011-12-19
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时间：12月21日（星期三）3:00pm—4:30pm
地点：经济与工商管理学院1610会议室（后主楼）
Abstract：This paper constructs and analyzes a decentralized DSGE model in which the forward-looking representative agent is endowed with both incomplete knowledge and limited computing skills. For some “long-run” consistent beliefs, his lifetime planning problem can be reduced to an infinite sequence of finite horizon problems which are within his computing range and depend on “short-run” price forecasts. The resulting framework which also encompasses the optimal infinite horizon case, the rolling infinite horizon case, can be used to analyze how an economy learns to grow optimally, and to respond to exogenous shocks or to changes in future growth forecasts.
Keywords: Economic growth, Dynamic optimization, Bounded rationality.
Laurent Cellarier博士毕业于美国南加州大学经济系，现任加拿大圭尔夫大学(University of Guelph) 经济系副教授，主要研究领域为宏观经济动力学以及学习与适应性行为，是国际非线性经济动力学前沿领域十分活跃的主要研究者，在Journal of Macroeconomics, Journal of Population Economics和Journal of Economic Behavior & Organization等宏观经济学顶级期刊发表论文多篇。