Abstract
The co-integrated vector autoregression is extended to allow variables to be observed with classical measurement errors (ME). For estimation, the model is parametrized as a time invariant state-space form, and an accelerated expectation-maximization algorithm is derived. A simulation study shows that (i) the finite-sample properties of the maximum likelihood (ML) estimates and reduced rank test statistics are excellent (ii) neglected measurement errors will generally distort unit root inference due to a moving average component in the residuals, and (iii) the moving average component may–in principle–be approximated by a long autoregression, but a pure autoregression cannot identify the autoregressive structure of the latent process, and the adjustment coefficients are estimated with a substantial asymptotic bias. An application to the zero-coupon yield-curve is given.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Econometric Reviews |
| Vol/bind | 35 |
| Udgave nummer | 2 |
| Sider (fra-til) | 169-200 |
| ISSN | 0747-4938 |
| DOI | |
| Status | Udgivet - 7 feb. 2016 |