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Estimating overidentified, nonrecursive, time‐varying coefficients structural vector autoregressions

Fabio Canova () and Fernando Pérez Forero ()

Quantitative Economics, 2015, vol. 6, issue 2, 359-384

Abstract: This paper provides a general procedure to estimate structural vector autoregressions. The algorithm can be used in constant or time‐varying coefficient models, and in the latter case, the law of motion of the coefficients can be linear or nonlinear. It can deal in a unified way with just‐identified (recursive or nonrecursive) or overidentified systems where identification restrictions are of linear or of nonlinear form. We study the transmission of monetary policy shocks in models with time‐varying and time‐invariant parameters.

Date: 2015
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