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Estimation of Parameters in the Presence of Model misspecification and Measurement Error

Author

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  • P.A.V.B. Swamy
  • George S. Tavlas
  • Stephen G. Hall

    ()

  • George Hondroyiannis

Abstract

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.

Suggested Citation

  • P.A.V.B. Swamy & George S. Tavlas & Stephen G. Hall & George Hondroyiannis, 2008. "Estimation of Parameters in the Presence of Model misspecification and Measurement Error," Discussion Papers in Economics 08/27, Department of Economics, University of Leicester.
    • Handle: RePEc:lec:leecon:08/27
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    File URL: http://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp08-27.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, June.
    5. 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.
    6. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    7. Pratt, John W. & Schlaifer, Robert, 1988. "On the interpretation and observation of laws," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 23-52.
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    Citations

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    Cited by:

    1. Stephen G. Hall & P. A. V. B. Swamy & George S. Tavlas, 2012. "Milton Friedman, the demand for money, and the ECB’s monetary policy strategy," Review, Federal Reserve Bank of St. Louis, issue May, pages 153-186.
    2. P.A.V.B. Swamy & Stephen G. Hall & George S. Tavlas & I-Lok Chang & Heather D. Gibson & William H. Greene & Jatinder S. Mehta, 2016. "A Method for Measuring Treatment Effects on the Treated without Randomization," Econometrics, MDPI, Open Access Journal, vol. 4(2), pages 1-23, March.
    3. Stephen Hall & P. Swamy & George Tavlas, 2012. "Generalized cointegration: a new concept with an application to health expenditure and health outcomes," Empirical Economics, Springer, vol. 42(2), pages 603-618, April.
    4. Peter Smith, 2010. "Discussion of the Fisher Effect Puzzle: A Case of Non-Linear Relationship," Open Economies Review, Springer, vol. 21(1), pages 105-108, February.
    5. Ettredge, Michael & Fuerherm, Elizabeth Emeigh & Li, Chan, 2014. "Fee pressure and audit quality," Accounting, Organizations and Society, Elsevier, vol. 39(4), pages 247-263.
    6. Stephen Hall & George Hondroyiannis & P. Swamy & George Tavlas, 2010. "The Fisher Effect Puzzle: A Case of Non-Linear Relationship?," Open Economies Review, Springer, vol. 21(1), pages 91-103, February.
    7. repec:cup:macdyn:v:21:y:2017:i:05:p:1158-1174_00 is not listed on IDEAS
    8. Hall, Stephen G. & Kenjegaliev, Amangeldi & Swamy, P.A.V.B. & Tavlas, George S., 2013. "Measuring currency pressures: The cases of the Japanese yen, the Chinese yuan, and the UK pound," Journal of the Japanese and International Economies, Elsevier, vol. 29(C), pages 1-20.
    9. Hall, Stephen G. & Hondroyiannis, George & Kenjegaliev, Amangeldi & Swamy, P.A.V.B. & Tavlas, George S., 2013. "Is the relationship between prices and exchange rates homogeneous?," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 411-438.
    10. Hall, Stephen G. & Swamy, P. A. V. B. & Tavlas, George S., 2017. "Time-Varying Coefficient Models: A Proposal For Selecting The Coefficient Driver Sets," Macroeconomic Dynamics, Cambridge University Press, vol. 21(05), pages 1158-1174, July.
    11. P. Swamy & Stephen Hall, 2012. "Measurement of causal effects," Economic Change and Restructuring, Springer, vol. 45(1), pages 3-23, February.
    12. Swamy, P.A.V.B. & Mehta, J.S. & Tavlas, G.S. & Hall, S.G., 2015. "Two applications of the random coefficient procedure: Correcting for misspecifications in a small area level model and resolving Simpson's paradox," Economic Modelling, Elsevier, vol. 45(C), pages 93-98.
    13. David, S.A. & Machado, J.A.T. & Quintino, D.D. & Balthazar, J.M., 2016. "Partial chaos suppression in a fractional order macroeconomic model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 122(C), pages 55-68.

    More about this item

    Keywords

    Misspecified model; Correct interpretation of coefficients; Appropriate assumption; Time-varying coefficient model; Coefficient driver;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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