We introduce a new method for drawing state variables in Gaussian state space models from their conditional distribution given parameters and observations. Unlike standard methods, our method does not involve Kalman filtering. We show that for some important cases, our method is computationally...

We propose methods for testing hypotheses of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses...

We propose methods for testing hypotheses of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses...

We introduce a new method for drawing state variables in Gaussian state space models from their conditional distribution given parameters and observations. Unlike standard methods, our method does not involve Kalman filtering. We show that for some important cases, our method is computationally...

Models use for natural resources prices usually preclude the possibility of large changes (jumps) resulting from discrete, unexpected events. To test for the presence of jumps and ARCH effects, we propose to use bounds and bootstrap test techniques, thus solving the unidentified nuisance...

Models used for natural resources prices usually preclude the possibility of large changes (jumps) resulting from discrete, unexpected events. To test for the presence of jumps and ARCH effects, we propose to use bounds and bootstrap test techniques, thus solving the unidentified nuisance...