Correcting for Omitted-Variable and Measurement-Error Bias in Autoregressive Model Estimation with Panel Data
The parameter estimates based on an econometric equation are biased and can also be inconsistent when relevant regressors are omitted from the equation or when included regressors are measured with error. This problem gets complicated when the `true' functional form of the equation is unknown. Here, we demonstrate how auxiliary variables, called concomitants, can be used to remove omitted-variable and measurement-error biases from the coefficients of an equation with the unknown `true' functional form. The method is specifically designed for panel data. Numerical algorithms for enacting this procedure are presented and an illustration is given using a practical example of forecasting small-area employment from nonlinear autoregressive models. Copyright Kluwer Academic Publishers 2003
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 22 (2003)
Issue (Month): 2 (October)
|Contact details of provider:|| Web page: http://www.springer.com|
|Order Information:||Web: http://www.springer.com/economics/economic+theory/journal/10614/PS2|
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.:
- Basmann, R. L., 1988. "Causality tests and observationally equivalent representations of econometric models," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 69-104.
- P. A. V. B. Swamy & Garry J. Schinasi, 1986. "Should fixed coefficients be reestimated every period for extrapolation?," International Finance Discussion Papers 287, Board of Governors of the Federal Reserve System (U.S.).
- I-Lok Chang & P.A.V.B. Swamy & Charles Hallahan & George S. Tavlas, 2000. "A Computational Approach to Finding Causal Economic Laws," Computational Economics, Springer;Society for Computational Economics, vol. 16(1/2), pages 105-136, October.
- Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
- Friedman, Milton & Schwartz, Anna J, 1991. "Alternative Approaches to Analyzing Economic Data," American Economic Review, American Economic Association, vol. 81(1), pages 39-49, March.