Serially Correlated Measurement Errors in Time Series Regression: The Potential of Instrumental Variable Estimators
The measurement error problem in linear time series regression, with focus on the impact of error memory, modeled as finite-order MA processes, is considered. Three prototype models, two bivariate and one univariate ARMA, and ways of handling the problem by using instrumental variables (IVs) are discussed as examples. One has a bivariate regression equation that is static, although with dynamics, entering via the memory of its latent variables. The examples illustrate how 'structural dynamics' interacting with measurement error memory create bias in Ordinary Least Squares (OLS) and illustrate the potential of IV estimation procedures. Supplementary Monte Carlo simulations are provided for two of the example models.
|Date of creation:||30 Dec 2014|
|Contact details of provider:|| Postal: Department of Economics, University of Oslo, P.O Box 1095 Blindern, N-0317 Oslo, Norway|
Phone: 22 85 51 27
Fax: 22 85 50 35
Web page: http://www.oekonomi.uio.no/indexe.html
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Nowak, Eugen, 1993. "The identification of multivariate linear dynamic errors-in-variables models," Journal of Econometrics, Elsevier, vol. 59(3), pages 213-227, October.
- Staudenmayer, John & Buonaccorsi, John P., 2005. "Measurement Error in Linear Autoregressive Models," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 841-852, September.
- Grether, D M & Maddala, G S, 1973.
"Errors in Variables and Serially Correlated Disturbances in Distributed Lag Models,"
Econometric Society, vol. 41(2), pages 255-262, March.
- Grether, David M. & Maddala, G. S., "undated". "Errors in Variables and Serially Correlated Disturbances in Distributed Lag Models," Working Papers 6, California Institute of Technology, Division of the Humanities and Social Sciences.
When requesting a correction, please mention this item's handle: RePEc:hhs:osloec:2014_028. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Magnus Gabriel Aase)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.