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Does adding data always improve linear regression estimates?

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  • den Boer, A.V.

Abstract

Intuitively one might expect that the quality of statistical estimates cannot worsen if they are based on more data. We show in a least-squares linear regression setting that this intuition is wrong. Adding data may worsen the quality of parameter estimates, and in fact may even cause a design sequence to lose strong consistency.

Suggested Citation

  • den Boer, A.V., 2013. "Does adding data always improve linear regression estimates?," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 829-835.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:3:p:829-835
    DOI: 10.1016/j.spl.2012.12.001
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    References listed on IDEAS

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    1. Lai, T. L. & Robbins, Herbert & Wei, C. Z., 1979. "Strong consistency of least squares estimates in multiple regression II," Journal of Multivariate Analysis, Elsevier, vol. 9(3), pages 343-361, September.
    2. Josef Broder & Paat Rusmevichientong, 2012. "Dynamic Pricing Under a General Parametric Choice Model," Operations Research, INFORMS, vol. 60(4), pages 965-980, August.
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    Cited by:

    1. Arnoud V. den Boer & Bert Zwart, 2015. "Dynamic Pricing and Learning with Finite Inventories," Operations Research, INFORMS, vol. 63(4), pages 965-978, August.

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