Estimating Overidentified, Nonrecursive Time-Varying Coefficients Structural VARs

Estimating overidentied, non-recursive, time varying coe¢ cients structural VARs

This paper provides a general procedure to estimate structural VARs. The algorithm can be used in constant or time varying coe¢ cient models, and in the latter case, the law of motion of the coe¢ cients can be linear or non-linear. It can deal in a uni…ed way with just-identi…ed (recursive or non-recursive) or overidenti…ed systems where identi…cation restrictions are of linear or of nonlinear ...

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Bayesian Analysis and Modeling Summer Workshop 2015

9:55 – 10:40 Rodney Strachan (University of Queensland) Reducing Dimensions in Large Time-varying Parameter VAR Models This paper proposes a new approach to estimating high dimensional time varying parameter vector autoregressive models (TVP-VARs). Such models are rarely used with more than 4-5 variables. However recent work has shown the advantages of modelling VARs with large numbers of varia...

Cross-Sectional Relative Price Variability and Inflation in Turkey: Time Varying Estimation

Abstract This study investigates the empirical validity of the variability hypothesis in Turkey for the period of February 2005-November 2015, by using cross-sectional relative price data and by focusing on the assumptions of linearity and stability. The linearity assumption between the two variables is ensured by estimating quadratic regression equation. The assumption of stability is secur...

Data-based priors for vector autoregressions with drifting coefficients

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require minimal input by the user, and they result in shrinkage posterior representations, thus, making them approp...