Released on 10/06/2010:
• | The tools for DSGE-VARs have been extended to include unconditional forecasts, observed variable decompositions, spectral decompositions, and forecast error variance decompositions. |
• | As an aid to identification issues, the information matrix output has been extended. First of all, Whittle's frequency domain based estimator is now available. For the time and frequency domain estimates of the matrix, YADA now also tries to sort parameters based on the degree to which they can be identified. This follows Michal Andrle's ideas and therefore makes use of a rank revealing algorithm (Q-R factorization with column pivoting). Moreover, all the eigenvalues and eigenvectors of the information matrix are provided. |
• | Coherence statistics can be computed when studying observed variable and state variable correlations. |
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