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The Bias of Elasticity Estimtors in Linear Regression: Some Analytic Results

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Abstract

Using small-disturbance expansions, we derive analytic expressions for the bias of the OLS estimator an elasticity in a linear model, both at an individual sample point and at the sample mean. The magnitudes of these biases are illustrated with Australian expenditure data.

Suggested Citation

  • Chen Qian & David E. Giles, 2005. "The Bias of Elasticity Estimtors in Linear Regression: Some Analytic Results," Econometrics Working Papers 0517, Department of Economics, University of Victoria.
    • Handle: RePEc:vic:vicewp:0517
    Note: ISSN 1485-6441
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    1. Kenneth W. Clements & Xueyan Zhao, 2005. "Economic Aspects of Marijuana," Economics Discussion / Working Papers 05-28, The University of Western Australia, Department of Economics.
    2. Ullah, Aman, 2004. "Finite Sample Econometrics," OUP Catalogue, Oxford University Press, number 9780198774488.
    3. Kadane, Joseph B, 1971. "Comparison of k-Class Estimators when the Disturbances are Small," Econometrica, Econometric Society, vol. 39(5), pages 723-737, September.
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    Cited by:

    1. Tokgoz, Simla & Traoré, Fousseini, 2023. "Understanding E10 markets in the U.S.: Evidence from spatial data," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1267-1281.

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    More about this item

    Keywords

    Elasticity; bias; small-distrurbance asymptotics;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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