首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Robustness and information processing
Institution:1. University of Minnesota, Federal Reserve Bank of Minneapolis, NBER, United States;2. Graduate School of Business, Stanford University, United States;1. University Hassan First, Laboratory LAMSAD, EST Bereechid, Morocco;2. Superior School of Technology, Berrechid, Morocco;3. Faculty of Sciences, University Mohammed First, Oujda, Morocco;1. Faculty of Mathematics and Computer Science, Institute of Computer Science, Jagiellonian University, ul. prof. S. ?ojasiewicza 6, 30-348 Kraków, Poland;2. University of Warsaw, Mathematics Department, ul.Banacha 2, 02-957 Warsaw, Poland
Abstract:This paper considers a standard Kalman filtering problem subject to model uncertainty and information-processing constraints. It draws a connection between robust filtering Hansen and Sargent, 2004. Robust control and economic model uncertainty. Monograph. In press] and Rational Inattention Sims, 2003. Implications of rational inattention, Journal of Monetary Economics 50 (3), 665–690]. Considered separately, robustness and Rational Inattention are shown to be observationally equivalent, in the sense that a higher filter gain can either be interpreted as an increased preference for robustness, or an increased ability to process information. However, it is more interesting to consider them jointly. In this case, it is argued that an increased preference for robustness can be interpreted as an increased demand for information processing, while Sims' model of Rational Inattention can be interpreted as placing a constraint on the available supply. This suggests that the way agents actually implement robust decision rules is by allocating some of their scarce information processing capacity to problems that are characterized by high degrees of model uncertainty and risk-sensitivity.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号