Optimal policy with partial information in a forward-looking model
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Optimal policy with partial information in a forward-looking model certainty-equivalence redux by Lars E. O. Svensson

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Published by National Bureau of Economic Research in Cambridge, Mass .
Written in English

Subjects:

  • Economic policy -- Mathematical models,
  • Monetary policy -- Mathematical models

Book details:

Edition Notes

StatementLars E. O. Svensson, Michael Woodford.
SeriesNBER working paper series -- no. 9430., Working paper series (National Bureau of Economic Research) -- working paper no. 9430.
ContributionsWoodford, Michael, Professor., National Bureau of Economic Research.
The Physical Object
Pagination21 p. ;
Number of Pages21
ID Numbers
Open LibraryOL17612625M
OCLC/WorldCa51675389

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This paper proves a certainty equivalence result for optimal policy under commitment with symmetric partial information about the state of the economy in a model with forward-looking :// CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): This paper proves a certainty equivalence result for optimal policy under commitment with symmetric partial information about the state of the economy in a model with forwardlooking variables. This result is used in our previous paper [9], which synthesizes what is known about the case of symmetric partial information ?doi= Get this from a library! Optimal policy with partial information in a forward-looking model: certainty-equivalence redux. [Lars E O Svensson; Michael Woodford; National Bureau of Economic Research.] -- This paper proves a certainty equivalence result for optimal policy under commitment with symmetric partial information about the state of the economy in a model with forward-looking :// Get this from a library! Optimal policy with partial information in a forward-looking model: certainty-equivalence redux. [Lars E O Svensson; Michael Woodford; National Bureau of Economic Research.]

Optimal Policy with Partial Information in a Forward-Looking Model: Certainty-Equivalence Redux. policy response coefficients and efficient estimates of the state of the economy in the context of a fairly general forward-looking rational-expectations model. In particular, our proof takes into account that, under commitment, the policymaker Optimal Policy with Partial Information in a Forward   •Policy makers are limited in the information and policy alternatives they can process •Policy makers lack complete information and knowledge of all policy options •Consequences of options are unknown and ‘educated guesses’ at best •Individuals have Jans Policy Forward Selection chooses a subset of the predictor variables for the final model. We can do forward stepwise in context of linear regression whether n is less than p or n is greater than p. Forward selection is a very attractive approach, because it's both tractable and it gives a good sequence of ://

  We begin with a brief overview of how economists think about optimal tax policy, based largely on the foundational work of Ramsey () and Mirrlees (). We then put forward eight general lessons suggested by optimal tax theory as it has developed in recent decades: 1)   We develop a graphical 3-equation New Keynesian model for macroeconomic analysis to replace the traditional IS-LM-AS model. The new graphical IS-PC-MR model is a simple version of the one commonly used in central banks and captures the forward-looking thinking engaged in by the policy ~uctpa36/ Information theory has a special place among theoretical approaches to neurobiology. While it is the framework that can provide general model independent bounds on information processing in biological systems, it is also one of the most elusive, misunderstood and abused conceptual ://   Stepwise regression is a semi-automated process of building a model by successively adding or removing variables based solely on the t-statistics of their estimated ly used, the stepwise regression option in Statgraphics (or other stat packages) puts more power and information at your fingertips than does the ordinary multiple regression option, and it is especially useful ~rnau/