This paper establishes vector autoregressive moving average (VARMA) models for Malaysian monetary policy analysis by efficiently identifying and simultaneously estimating the model parameters using full information maximum likelihood. The monetary literature is largely dominated by vector autoregressive (VAR) and structural vector autoregressive (SVAR) models, and to the best of our knowledge, ...

This paper develops a new methodology for identifying the structure of VARMA time series models. The analysis proceeds by examining the echelon canonical form and presents a fully automatic data driven approach to model specification using a new technique to determine the Kronecker invariants. A novel feature of the inferential procedures developed here is that they work in terms of a canonical...

This appendix is divided into seven sections labelled A through G. Almost all details of the prior are specified in the paper itself, but the few remaining details about the prior are given in Appendix A. An outline of the MCMC algorithm was provided in the paper, but complete details and formulae are provided in Appendix B. Appendix C describes how we calculate the DIC which is one of the meth...

An important question in empirical macroeconomics is whether structural vector autoregressions (SVARs) can reliably discriminate between competing DSGE models. Several recent papers have suggested that one reason SVARs may fail to do so is because they are finite-order approximations to infinite-order processes. In this context, we investigate the performance of models that do not suffer from t...