Detecting and Analyzing the Effects of Time‐Varying Parameters in DSGE Models

21 Pages Posted: 22 May 2020

See all articles by Fabio Canova

Fabio Canova

BI Norwegian Business School

Filippo Ferroni

Federal Reserve Bank of Chicago

Christian Matthes

Federal Reserve Bank of Richmond

Date Written: February 2020

Abstract

We study how structural parameter variations affect the decision rules and economic inference. We provide diagnostics to detect parameter variations and to ascertain whether they are exogenous or endogenous. A constant parameter model poorly approximates a time‐varying data generating process (DGP), except in a handful of relevant cases. Linear approximations do not produce time‐varying decision rules; higher‐order approximations can do this only if parameter disturbances are treated as decision rule coefficients. Structural responses are time invariant regardless of order of approximation. Adding endogenous variations to the parameter controlling leverage in Gertler and Karadi's model substantially improves the fit of the model.

Suggested Citation

Canova, Fabio and Ferroni, Filippo and Matthes, Christian, Detecting and Analyzing the Effects of Time‐Varying Parameters in DSGE Models (February 2020). International Economic Review, Vol. 61, Issue 1, pp. 105-125, 2020, Available at SSRN: https://ssrn.com/abstract=3602116 or http://dx.doi.org/10.1111/iere.12418

Fabio Canova (Contact Author)

BI Norwegian Business School ( email )

Nydalsveien 37
Oslo, 0442
Norway

Filippo Ferroni

Federal Reserve Bank of Chicago ( email )

230 South LaSalle Street
Chicago, IL 60604
United States

Christian Matthes

Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

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