We develop a similarity-based structural vector autoregressive (SVAR) model using the similar clusters of data relevant for the prevailing initial macroeconomic conditions of interest. Our computationally attractive simple approach enables us to uncover time-varying effects of structural...

We propose simulation-based forecasting methods for the noncausal vector autoregressive model proposed by Lanne and Saikkonen (2012). Simulation or numerical methods are required because the prediction problem is generally nonlinear and, therefore, its analytical solution is not available. It...

We introduce a structural vector autoregressive model containing strictly positive components. Our nonlinear model results in explicit formulae for impulse response and forecast error variance decomposition analyses, which ease practical computations and structural interpretations. We illustrate...