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Estimation of Linear Regression Models from Bid-Ask Data by a Spread-Tolerant Estimator

Author

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  • Oliver Linton

    (Department of Economics, London School of Economics)

Abstract

We investigate a class of estimators for linear regression models where the dependent variable is subject to bid-ask censoring. Our estimation method is based on a definition of error that is zero when the predictor lies between the actual bid price and ask price, and linear outside this range. Our estimator minimizes a sum of such squared errors; it is nonlinear, and indeed the criterion function itself is non-smooth. We establish its asymptotic properties using the approach of Pakes and Pollard (1989). We compare the estimator with midpoint OLS.

Suggested Citation

  • Oliver Linton, 2001. "Estimation of Linear Regression Models from Bid-Ask Data by a Spread-Tolerant Estimator," Annals of Economics and Finance, Society for AEF, vol. 2(1), pages 237-248, May.
    • Handle: RePEc:cuf:journl:y:2001:v:2:i:1:p:237-284
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    More about this item

    Keywords

    Bid-ask spread; Censored data; Linear regression;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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