1973
DOI: 10.2307/2525972
|View full text |Cite
|
Sign up to set email alerts
|

Implications of Learning for Economic Models of Uncertainty

Abstract: JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

1975
1975
1997
1997

Publication Types

Select...
4
3

Relationship

0
7

Authors

Journals

citations
Cited by 13 publications
(2 citation statements)
references
References 3 publications
0
2
0
Order By: Relevance
“…As has been known for a long time, such stochastic difference equations generate series that "look like" economic time series. Further, if viewed as structural (i.e., invariant with respect to policy For example, see Crawford [5 ] and Grossman [ 11 ].…”
Section: Inflation and Unemploymentmentioning
confidence: 99%
“…As has been known for a long time, such stochastic difference equations generate series that "look like" economic time series. Further, if viewed as structural (i.e., invariant with respect to policy For example, see Crawford [5 ] and Grossman [ 11 ].…”
Section: Inflation and Unemploymentmentioning
confidence: 99%
“…Both of these assumptions can be abandoned, albeit at a cost in terms of the simplicity of the model. (For example, see Crawford 1971 andGrossman 1975. ) In fact, within the framework of quadratic objective functions, in which the "separation principle" applies, one can apply the Kalman filtering formula to derive optimum linear decision rules with time dependent coefficients.…”
Section: Stationary Models and The Neglect Of Learningmentioning
confidence: 99%