Empirical questions such as whether the Phillips curve or the Okun’s law is stable can
often be framed as a model comparison—e.g., comparing a vector autoregression (VAR)
in which the coefficients in one equation are constant versus one that has time-varying
parameters. We develop Bayesian model comparison methods to compare a class of
time-varying parameter VARs we call hybrid TVP-VARs—VARs with time-varying
parameters in some equations but constant coefficients in others. Using US data, we find
evidence that the VAR coefficients in some, but not all, equations are time varying. Our
finding highlights the empirical relevance of these hybrid TVP-VARs.