Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models

Fair, Ray C.; Taylor, John B.

doi:10.2307/1912057

Cited by 420 publications

(337 citation statements)

References 3 publications

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“…We do so by using the extended path method, introduced by Fair and Taylor (1983). 27 Our main example is the transitional dynamics after a large discount rate shock equal to .…”

Section: Transitional Dynamics: Slope and Curvature Of The Phillips Cmentioning

confidence: 99%

Downward Nominal Wage Rigidities Bend the Phillips Curve

Daly

Hobijn

2014

ERWP

108

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We introduce a model of monetary policy with downward nominal wage rigidities and show that both the slope and curvature of the Phillips curve depend on the level of inflation and the extent of downward nominal wage rigidities. This is true for the both the long-run and the short-run Phillips curve. Comparing simulation results from the model with data on U.S. wage patterns, we show that downward nominal wage rigidities likely have played a role in shaping the dynamics of unemployment and wage growth during the last three recessions and subsequent recoveries.

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“…We do so by using the extended path method, introduced by Fair and Taylor (1983). 27 Our main example is the transitional dynamics after a large discount rate shock equal to .…”

Section: Transitional Dynamics: Slope and Curvature Of The Phillips Cmentioning

confidence: 99%

Downward Nominal Wage Rigidities Bend the Phillips Curve

Daly

Hobijn

2014

ERWP

108

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“…The following is a brief review of the solution method for this model. More details are presented in Fair and Taylor (1983). In what follows i is always meant to run from 1 through n.…”

Section: The Solution Methodsmentioning

confidence: 99%

“…In an earlier paper (Fair and Taylor, 1983) we presented methods for the solution and full information estimation of models with rational expectations. The basic solution method, called the 'extended path' method, has come to be widely used for deterministic simulations of rational expectations models' but, probably because of the expense, the full information estimation method has not to our knowledge been tried by others.…”

Section: Introductionmentioning

confidence: 99%

Full information estimation and stochastic simulation of models with rational expectations

Fair

Taylor

1990

J of Applied Econometrics

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“…Subsequently a number of generic methods to solve models with forward looking variables were developed. For instance, Fair and Taylor (1983) used an iterative method for solving RE models and, in the tradition of Theil (1964), Fisher, Holly and Hughes Hallett (1986) used a method based on stacking the model variables. Blanchard and Kahn (1980) and Anderson and Moore (1985) both presented methods based on the saddle point property.…”

Section: Learning With Forward Looking Variablesmentioning

confidence: 99%

Learning About Learning in Dynamic Economic Models

Kendrick

Amman

Tucci

2014

Handbook of Computational Economics Vol. 3

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This chapter of the Handbook of Computational Economics is mostly about research on active learning and is confined to discussion of learning in dynamic models in which the systems equations are linear, the criterion function is quadratic and the additive noise terms are Gaussian. Though there is much work on learning in more general systems, it is useful here to focus on models with these specifications since more general systems can be approximated in this way and since much of the early work on learning has been done with these quadratic-linear-gaussian systems.We begin with what has been learned about learning in dynamic economic models in the last few decades. Then we progress to a discussion of what we hope to learn in the future from a new project that is just getting underway. However before doing either of these it is useful to provide a short description of the mathematical framework that will be used in the chapter.Key words: Active learning, dual control, optimal experimentation, stochastic optimization, time-varying parameters, forward looking variables, numerical experiments.JEL Classification: C63, E61.Email addresses: kendrick@austin.utexas.edu (David A. Kendrick), h.m.amman@uu.nl (Hans M. Amman), tucci@unisi.it (Marco P. Tucci). 1 Corresponding author David A. Kendrick. We are indebted to a referee for many helpful comments and suggestions.

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Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models

Cited by 420 publications

References 3 publications

Downward Nominal Wage Rigidities Bend the Phillips Curve

Downward Nominal Wage Rigidities Bend the Phillips Curve

Full information estimation and stochastic simulation of models with rational expectations

Learning About Learning in Dynamic Economic Models

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