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Estimation and Solution of Models with Expectations and Structural Changes
Author(s) -
Kulish Mariano,
Pagan Adrian
Publication year - 2017
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2527
Subject(s) - disinflation , markov chain , inflation (cosmology) , econometrics , variety (cybernetics) , new keynesian economics , process (computing) , computer science , economics , estimation , function (biology) , markov process , monetary policy , keynesian economics , mathematics , statistics , artificial intelligence , machine learning , physics , management , evolutionary biology , theoretical physics , biology , operating system
Summary In this paper, we develop solutions for linearized models with forward‐looking expectations and structural changes under a variety of assumptions regarding agents' beliefs about those structural changes. For each solution, we show how its associated likelihood function can be constructed by using a ‘backward–forward’ algorithm. We illustrate the techniques with two examples. The first considers an inflationary program in which beliefs about the inflation target evolve differently from the inflation target itself, and the second applies the techniques to estimate a new Keynesian model through the Volcker disinflation. We compare our methodology with the alternative in which structural change is captured by switching between regimes via a Markov switching process. We show that our method can produce accurate results much faster than the Markov switching method as well as being easily adapted to handle beliefs departing from reality. Copyright © 2016 John Wiley & Sons, Ltd.