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Estimation of Linear Regression Models by a Spread-Tolerant Estimator

Author

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  • Oliver Linton
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 non-linear, and indeed the criterion function itself is non smooth. We establish its asymptotic properties using the approach of Pakes & Pollard (1989). We compare the estimator with mid-point OLS.

Suggested Citation

  • Oliver Linton, 2004. "Estimation of Linear Regression Models by a Spread-Tolerant Estimator," FMG Discussion Papers dp512, Financial Markets Group.
    • Handle: RePEc:fmg:fmgdps:dp512
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    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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