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Usage of an estimated coefficient as a dependent variable

Author

Listed:
  • Abigail S. Hornstein
  • William H. Greene

    (Stern School of Business, New York University)

Abstract

Two-step estimation with large panel data sets generally involves estimating vectors of individual-specific coefficients in a first-stage. In a second-stage estimation a vector of estimated coefficients is used as the dependent variable. Potential problems of heteroskedasticity in the second stage may be mitigated by weighting all independent observations by the inverse of the variance of the dependent variable, which is obtained from the first stage estimation. This approach needs to be modified if the dependent variable in the second stage is a non-linear function of the estimated coefficient.

Suggested Citation

  • Abigail S. Hornstein & William H. Greene, 2012. "Usage of an estimated coefficient as a dependent variable," Wesleyan Economics Working Papers 2012-011, Wesleyan University, Department of Economics.
  • Handle: RePEc:wes:weswpa:2012-011
    DOI: 10.1016/j.econlet.2012.03.027
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    References listed on IDEAS

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    1. Saxonhouse, Gary R, 1976. "Estimated Parameters as Dependent Variables," American Economic Review, American Economic Association, vol. 66(1), pages 178-183, March.
    2. Art Durnev & Randall Morck & Bernard Yeung, 2004. "Value-Enhancing Capital Budgeting and Firm-specific Stock Return Variation," Journal of Finance, American Finance Association, vol. 59(1), pages 65-105, February.
    3. Greene, William H. & Hornstein, Abigail S. & White, Lawrence J., 2009. "Multinationals do it better: Evidence on the efficiency of corporations' capital budgeting," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 703-720, December.
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    More about this item

    Keywords

    two-step estimation; heteroskedasticity; random parameters; GLS; OLS;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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