We derive a framework for asymptotically valid inference in stable vector autoregressive (VAR) models with conditional heteroskedasticity of unknown form. We prove a joint central limit theorem for the VAR slope parameter and innovation covariance parameter estimators and address bootstrap...

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...

It is argued that standard impulse response analysis based on vector autoregressive models has a number of shortcomings. Although the impulse responses are estimated quantities, measures for sampling variability such as confidence intervals are often not provided. If confidence intervals are...

Because the parameters of vector autoregressive processes are often difficult to interpret directly, econometricians use quantities derived from the parameters to disentangle the relationships between the variables. Bootstrap methods are often used for inference on the derived quantities....

The small sample properties of two types of Chow tests are investigated in the context of multiple time series models. It is found that the tests may have substantially distorted size if the sample size is not large relative to the number of parameters in the model under study. In particular the...