The Co-Integrated Vector Autoregression with Errors–in–Variables |
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Authors: | Heino Bohn Nielsen |
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Institution: | Department of Economics , University of Copenhagen , Copenhagen , Denmark |
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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. |
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Keywords: | Co-Integrated vector autoregression Expectation-Maximization (EM) algorithm Kalman filter Measurement errors State-space model Yield curve dynamics |
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