Author: Andrew P. BlakePublisher:
ISBN:
Category : Computer software
Languages : en
Pages :
Book Description
A General Approach to the Solution of Nonlinear Rational Expectations Models
Author: Andrew P. BlakePublisher:
ISBN:
Category : Computer software
Languages : en
Pages :
Book Description
Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models
Author: Ray C. FairPublisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 41
Book Description
A solution method and an estimation method for nonlinear rational expectations models are presented in this paper. The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates. When applied to linear models, the solution method yields the same results as those obtained from currently available methods that are designed specifically for linear models. It is, however, more flexible and general than these methods. For large nonlinear models the results in this paper indicate that the method works quite well. The estimation method is based on the maximum likelihood principal. It is, as far as we know, the only method available for obtaining maximum likelihood estimates for nonlinear rational expectations models. The method has the advantage of being applicable to a wide range of models, including, as a special case, linear , models. The method can also handle different assumptions about the expectations of the exogenous variables, something which is not true of currently available approaches to linear models.
Computationally Efficient Solution and Maximum Likelihood Estimation of Nonlinear Rational Expectation Models
Author: Jeffrey C. FuhrerPublisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 54
Book Description
Linear Rational Expectations Models
Author: Charles H. WhitemanPublisher: U of Minnesota Press
ISBN: 1452907935
Category : Business & Economics
Languages : en
Pages : 151
Book Description
Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rationalexpectations Models
Author: Ray C. FairPublisher:
ISBN:
Category :
Languages : en
Pages : 43
Book Description
A solution method and an estimation method for nonlinear rational expectations models are presented in this paper. The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates. When applied to linear models, the solution method yields the same results as those obtained from currently available methods that are designed specifically for linear models. It is, however, more flexible and general than these methods. For large nonlinear models the results in this paper indicate that the method works quite well. The estimation method is based on the maximum likelihood principal. It is, as far as we know, the only method available for obtaining maximum likelihood estimates for nonlinear rational expectations models. The method has the advantage of being applicable to a wide range of models, including, as a special case, linear ,models. The method can also handle different assumptions about the expectations of the exogenous variables, something which is not true of currently available approaches to linear models.
Solving Nonlinear Rational Expectations Models by Parameterized Expectations
Author: Albert MarcetPublisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 118
Book Description
The Solution of Nonlinear Forward Looking Rational Expectations Models
Author: Peter JurriënsMethods of Solution and Simulation for Dynamic Rational Expectations Models
Author: Olivier J. BlanchardPublisher:
ISBN:
Category : Rational expectations (Economic theory)
Languages : en
Pages : 38
Book Description
Many methods have been proposed for the solution and simulation of medium or large size models under the assumption of rational expectations. The purpose of this paper is to present these methods, and to show how and where each can be applied. The methods fall into two groups. Methods in the first can be used to solve for perfect foresight paths in non-linear models. Methods in the second can be used in linear models, to solve either for paths or processes followed by endogenous variables. All the methods described here have been used in empirical applications and computer algorithms are available for most.
The Forward Method as a Solution Refinement in Rational Expectations Models
Author: Seonghoon ChoPublisher:
ISBN:
Category :
Languages : en
Pages : 43
Book Description
This paper generalizes the standard forward method of recursive substitution to a general class of linear Rational Expectations models with potentially multiple fundamental solutions. We propose a key property embedded in the forward solution -- the no-bubble condition -- as an economically sensible solution refinement in the class of fundamental solutions. In the literature, the no-bubble condition has been assumed to rule out non-fundamental bubble solutions. However, since the condition involves expectations of the future endogenous variables, it must be verified for every Rational Expectations equilibrium. We show that the forward solution is the only fundamental solution satisfying the no-bubble condition and that it is hard to justify economically fundamental solutions violating this condition. We provide several economic examples where the fundamental solutions obtained by other solution methods and refined by other solution selection criteria violate the no-bubble condition.
Rational Expectations in Macroeconomic Models
Author: P. FisherPublisher: Springer Science & Business Media
ISBN: 9401580022
Category : Business & Economics
Languages : en
Pages : 215
Book Description
It is commonly believed that macroeconomic models are not useful for policy analysis because they do not take proper account of agents' expectations. Over the last decade, mainstream macroeconomic models in the UK and elsewhere have taken on board the `Rational Expectations Revolution' by explicitly incorporating expectations of the future. In principle, one can perform the same technical exercises on a forward expectations model as on a conventional model -- and more! Rational Expectations in Macroeconomic Models deals with the numerical methods necessary to carry out policy analysis and forecasting with these models. These methods are often passed on by word of mouth or confined to obscure journals. Rational Expectations in Macroeconomic Models brings them together with applications which are interesting in their own right. There is no comparable textbook in the literature. The specific subjects include: (i) solving for model consistent expectations; (ii) the choice of terminal condition and time horizon; (iii) experimental design: i.e., the effect of temporary vs permanent, anticipated vs. unanticipated shocks; deterministic vs. stochastic, dynamic vs. static simulation; (iv) the role of exchange rate; (v) optimal control and inflation-output tradeoffs. The models used are those of the Liverpool Research Group in Macroeconomics, the London Business School and the National Institute of Economic and Social Research.