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Investigating omitted variable bias in regression parameter estimation: A genetic algorithm approach

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  • Sessions, David N.
  • Stevans, Lonnie K.

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  • Sessions, David N. & Stevans, Lonnie K., 2006. "Investigating omitted variable bias in regression parameter estimation: A genetic algorithm approach," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2835-2854, June.
  • Handle: RePEc:eee:csdana:v:50:y:2006:i:10:p:2835-2854
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    References listed on IDEAS

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    1. Wickens, Michael R, 1972. "A Note on the Use of Proxy Variables," Econometrica, Econometric Society, vol. 40(4), pages 759-761, July.
    2. McCallum, B T, 1972. "Relative Asymptotic Bias from Errors of Omission and Measurement," Econometrica, Econometric Society, vol. 40(4), pages 757-758, July.
    3. Aigner, D. J., 1974. "MSE dominance of least squares with errors-of-observation," Journal of Econometrics, Elsevier, vol. 2(4), pages 365-372, December.
    4. Hamada M. & Martz H. F. & Reese C. S. & Wilson A. G., 2001. "Finding Near-Optimal Bayesian Experimental Designs via Genetic Algorithms," The American Statistician, American Statistical Association, vol. 55, pages 175-181, August.
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    Cited by:

    1. Jonathan E. Leightner, 2013. "The Changing Effectiveness of Monetary Policy," Economies, MDPI, Open Access Journal, vol. 1(3), pages 1-16, November.
    2. Jonathan E Leightner & Tomoo Inoue, 2014. "Political Instability and the Effectiveness of Economic Policies: The Case of Thailand from 1993-2013," Economy, Asian Online Journal Publishing Group, vol. 1(1), pages 20-31.
    3. Coppi, Renato & Gil, Maria A. & Kiers, Henk A.L., 2006. "The fuzzy approach to statistical analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 1-14, November.

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