约束(计算机辅助设计)
计量经济学
理性预期
下载
经济
差异(会计)
多样性(控制论)
变量(数学)
极限(数学)
数理经济学
心理学
计算机科学
数学
统计
会计
数学分析
几何学
操作系统
作者
Rava Azeredo da Silveira,Yeji Sung,Michael Woodford
出处
期刊:Social Science Research Network
[Social Science Electronic Publishing]
日期:2020-01-01
被引量:17
摘要
We propose a model of optimal decision making subject to a memory constraint. The constraint is a limit on the complexity of memory measured using Shannon's mutual information, as in models of rational inattention; but our theory differs from that of Sims (2003) in not assuming costless memory of past cognitive states. We show that the model implies that both forecasts and actions will exhibit idiosyncratic random variation; that average beliefs will also differ from rational-expectations beliefs, with a bias that fluctuates forever with a variance that does not fall to zero even in the long run; and that more recent news will be given disproportionate weight in forecasts. We solve the model under a variety of assumptions about the degree of persistence of the variable to be forecasted and the horizon over which it must be forecasted, and examine how the nature of forecast biases depends on these parameters. The model provides a simple explanation for a number of features of reported expectations in laboratory and field settings, notably the evidence of over-reaction in elicited forecasts documented by Afrouzi et al. (2020) and Bordalo et al. (2020a).Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
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