New Wine in Old Bottles: A Sequential Estimation Technique for the LPM
AbstractThe conditions under which ordinary least squares (OLS) is an unbiased and consistent estimator of the linear probability model (LPM) are unlikely to hold in many instances. Yet the LPM still may be the correct model or, perhaps, justified for practical reasons. A sequential least squares (SLS) esti-mation procedure is introduced that may outperform OLS in terms of finite sample bias and yields a consistent estimator. Monte Carlo simulations reveal that SLS outperforms OLS, probit and logit in terms of mean squared error of the predicted probabilities. An empirical example is provided.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0206002.
Length: 43 pages
Date of creation: 19 Jun 2002
Date of revision: 11 May 2003
Note: Type of Document - Acrobat PDF; prepared on IBM PC; to print on HP; pages: 43; figures: included. A new estimation technique for the LPM model
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Linear Probability Model; Sequential Least Squares; Consistency; Monte Carlo;
Other versions of this item:
- Horrace, William C. & Oaxaca, Ronald L., 2003. "New Wine in Old Bottles: A Sequential Estimation Technique for the LPM," IZA Discussion Papers 703, Institute for the Study of Labor (IZA).
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- Another Gripe About the Linear Probability Model
by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-06-01 16:11:00
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