Estimation of Parameters in the Presence of Model misspecification and Measurement Error
Misspecifications of econometric models can lead to biased coefficients and error terms, which in turn can lead to incorrect inference and incorrect models. There are specific techniques such as instrumental variables which attempt to deal with some individual forms of model misspecification. However these can typically only address one problem at a time. This paper proposes a general method for estimating underlying parameters in the presence of a range of unknown model misspecifications. It is argued that this method can consistently estimate the direct effect of an independent variable on a dependent variable with all of its other determinants held constant even in the presence of a misspecified functional form, measurement error and omitted variables.
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- Cuthbertson, Keith & Taylor, Mark P., 1990. ""The case of the missing money" and the Lucas critique," Journal of Macroeconomics, Elsevier, vol. 12(3), pages 437-454.
- Swamy, P.A.V.B. & Mehta, Jatinder S. & Chang, I-Lok & Zimmerman, T.S., 2009. "An efficient method of estimating the true value of a population characteristic from its discrepant estimates," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2378-2389, April.
- Swamy, P.A.V.B. & Yaghi, Wisam & Mehta, Jatinder S. & Chang, I-Lok, 2007. "Empirical best linear unbiased prediction in misspecified and improved panel data models with an application to gasoline demand," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3381-3392, April.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
Oxford University Press,
edition 2, number 9780199641178, April.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543, April.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Swamy, P. A. V. B. & Tinsley, P. A., 1980. "Linear prediction and estimation methods for regression models with stationary stochastic coefficients," Journal of Econometrics, Elsevier, vol. 12(2), pages 103-142, February.
- P. A. V. B. Swamy & Peter A. Tinsley, 1976. "Linear prediction and estimation methods for regression models with stationary stochastic coefficients," Special Studies Papers 78, Board of Governors of the Federal Reserve System (U.S.).
- Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
- Pratt, John W. & Schlaifer, Robert, 1988. "On the interpretation and observation of laws," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 23-52. Full references (including those not matched with items on IDEAS)