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Econometrics.m: A Package for Doing Econometrics in Mathematica

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Abstract

Econometrics is an area of applied statistics that has developed with a very strong individual flavor although its techniques are also widely used in such disciplines as biometrics, psychometrics, and sociometrics, and, to be somewhat polemical, are applicable to a far wider statistical audience than seems aware of their need.

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References

  • Belsley, D. A. (1991), Conditioning Diagnostics, John Wiley & Sons: New York.

    MATH  Google Scholar 

  • Belsley, D. A. (1992), “Paring 3SLS Calculations Down to Manageable Proportions,” Computational Science in Economics and Management, 5, 157–169.

    Article  MathSciNet  MATH  Google Scholar 

  • Belsley, D. A., E. Kuh, and R. E. Welsch (1980), Regression Diagnostics, John Wiley & Sons: New York.

    Book  MATH  Google Scholar 

  • Durbin, J. (1970), “Testing for Serial Correlation in Least-Squares Regression when Some of the Regressors are Lagged Dependent Variables,” Econometrica, 38, 410–421.

    Article  MathSciNet  Google Scholar 

  • Johnston, J. (1984), Econometric Methods, 3rd Edition, McGraw Hill: New York.

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  • MacKinnon, J. G. “Model Specification Tests and Artificial Regressions,” Journal of Economic Literature, 30, 102–146.

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  • Theil, H. (1971), Principles of Econometrics, John Wiley & Sons: New York.

    MATH  Google Scholar 

  • White, H. (1980), “A Heteroskedasticity Consistent Covariance Matrix Estimator and a Direct Test of Heteroskedasticity,” Econometrica, 48, 817–838.

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© 1993 Springer Science+Business Media New York

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Belsley, D.A. (1993). Econometrics.m: A Package for Doing Econometrics in Mathematica. In: Varian, H.R. (eds) Economic and Financial Modeling with Mathematica®. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2281-9_14

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  • DOI: https://doi.org/10.1007/978-1-4757-2281-9_14

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4757-2283-3

  • Online ISBN: 978-1-4757-2281-9

  • eBook Packages: Springer Book Archive

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