We propose an easy technique to test for time-variation in coefficients and volatilities. Specifically, by using a noncentered parameterization for state space models, we develop a method to directly calculate the relevant Bayes factor using the Savage-Dickey density ratio — thus avoiding the computation of the marginal likelihood altogether. The proposed methodology is illustrated via two empirical applications. In the first application we test for time-variation in the volatility of inflation in the G7 countries. The second application investigates if there is substantial time-variation in the NAIRU in the US
An efficient method for Bayesian inference in stochastic volatility models uses a linear state space...
There are both theoretical and empirical reasons for believing that the parameters of macroeconomic ...
Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomic...
© 2016 Taylor & Francis Group, LLC. We propose an easy technique to test for time-variation in coeff...
We propose an easy technique to test for time-variation in coefficients and volatili-ties. Specifica...
We develop importance sampling methods for computing two popular Bayesian model comparison criteria,...
We develop importance sampling methods for computing two popular Bayesian model comparison criteria,...
We develop a Bayesian semiparametric method to estimate a time-varying parameter regression model wi...
We propose a semiparametric extension of the time-varying parameter regression model with asymmetric...
This article develops a new econometric methodology for performing stochastic model specification se...
A vast empirical literature has documented the widespread nature of structural instability in m...
Macroeconomic practitioners frequently work with multivariate time series models such as VARs, facto...
This article develops a new econometric methodology for performing stochastic model specification se...
© 2017 American Statistical Association. This article generalizes the popular stochastic volatility ...
We provide a flexible means of estimating time-varying parameter models in a Bayesian framework. By...
An efficient method for Bayesian inference in stochastic volatility models uses a linear state space...
There are both theoretical and empirical reasons for believing that the parameters of macroeconomic ...
Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomic...
© 2016 Taylor & Francis Group, LLC. We propose an easy technique to test for time-variation in coeff...
We propose an easy technique to test for time-variation in coefficients and volatili-ties. Specifica...
We develop importance sampling methods for computing two popular Bayesian model comparison criteria,...
We develop importance sampling methods for computing two popular Bayesian model comparison criteria,...
We develop a Bayesian semiparametric method to estimate a time-varying parameter regression model wi...
We propose a semiparametric extension of the time-varying parameter regression model with asymmetric...
This article develops a new econometric methodology for performing stochastic model specification se...
A vast empirical literature has documented the widespread nature of structural instability in m...
Macroeconomic practitioners frequently work with multivariate time series models such as VARs, facto...
This article develops a new econometric methodology for performing stochastic model specification se...
© 2017 American Statistical Association. This article generalizes the popular stochastic volatility ...
We provide a flexible means of estimating time-varying parameter models in a Bayesian framework. By...
An efficient method for Bayesian inference in stochastic volatility models uses a linear state space...
There are both theoretical and empirical reasons for believing that the parameters of macroeconomic ...
Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomic...