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Accounting for Skewed or One-Sided Measurement Error in the Dependent Variable

Author

Listed:
  • Millimet, Daniel L.

    (Southern Methodist University)

  • Parmeter, Christopher F.

    (University of Miami)

Abstract

While classical measurement error in the dependent variable in a linear regression framework results only in a loss of precision, non-classical measurement error can lead to estimates which are biased and inference which lacks power. Here, we consider a particular type of non-classical measurement error: skewed errors. Unfortunately, skewed measurement error is likely to be a relatively common feature of many outcomes of interest in political science research. This study highlights the bias that can result even from relatively "small" amounts of skewed measurement error, particularly if the measurement error is heteroskedastic. We also assess potential solutions to this problem, focusing on the stochastic frontier model and nonlinear least squares. Simulations and three replications highlight the importance of thinking carefully about skewed measurement error, as well as appropriate solutions.

Suggested Citation

  • Millimet, Daniel L. & Parmeter, Christopher F., 2019. "Accounting for Skewed or One-Sided Measurement Error in the Dependent Variable," IZA Discussion Papers 12576, IZA Network @ LISER.
    • Handle: RePEc:iza:izadps:dp12576
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    Cited by:

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    5. Castañeda Dower, Paul & Gerber, Theodore P. & Weber, Shlomo, 2022. "Firms, kinship networks, and economic growth in the Kyrgyz Republic," Journal of Comparative Economics, Elsevier, vol. 50(4), pages 997-1018.
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    8. Alvarez, Sean P. & Geloso, Vincent & Scheck, Macy, 2024. "Revisiting the relationship between economic freedom and development to account for statistical deception by autocratic regimes," European Journal of Political Economy, Elsevier, vol. 85(C).
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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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