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

  • Canova F
  • Pérez Forero F
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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. Time‐varying coefficient structural VAR models Metropolis algorithm identification restrictions monetary transmission mechanism C11 E51 E52

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Canova, F., & Pérez Forero, F. J. (2015). Estimating overidentified, nonrecursive, time-varying coefficients structural vector autoregressions. Quantitative Economics, 6(2), 359–384. https://doi.org/10.3982/qe305

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