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.
| Original language | English |
|---|---|
| Journal | Econometric Reviews |
| Volume | 35 |
| Issue number | 2 |
| Pages (from-to) | 169-200 |
| ISSN | 0747-4938 |
| DOIs | |
| Publication status | Published - 7 Feb 2016 |