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DTSTART;TZID=America/New_York:20190220T163000
DTEND;TZID=America/New_York:20190220T173000
DTSTAMP:20240514T182813Z
CREATED:20240212T114533Z
LAST-MODIFIED:20240514T182813Z
UID:10002102-1550680200-1550683800@cmsa.fas.harvard.edu
SUMMARY:Optimally Imprecise Memory and Biased Forecasts
DESCRIPTION:Speaker: Michael Woodford (Columbia) \nTitle: Optimally Imprecise Memory and Biased Forecasts \nAbstract: 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; the structure of the imprecise memory is optimized (for a given decision problem and noisy environment) subject to this constraint. We characterize the form of the optimally imprecise memory\, and show that the model implies that both forecasts and actions will exhibit idiosyncratic random variation; that beliefs will fluctuate forever around the rational-expectations (perfect-memory) beliefs with a variance that does not fall to zero; and that more recent news will be given disproportionate weight. The model provides a simple explanation for a number of features of observed forecast bias in laboratory and field settings. [Joint work with Rava Azeredo da Silveira and Yeji Sung
URL:https://cmsa.fas.harvard.edu/event/2-20-2019-colloquium/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-022019-791x1024-1.png
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