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Randomized Response and the Binary Probit Model

Author

Listed:
  • Gerd Ronning
  • Niels Schulz

Abstract

The paper analyzes eects of randomized response with respect to some binary dependent variable on the estimation of the probit model. This approach is used in interviews when asking sensitive questions. Alternatively randomization can be considered as a means of statistical disclosure control which has been termed post randomization method (PRAM). The paper shows that all properties concerning parameter estimation are maintained although there is a loss in (asymptotic) eciency.

Suggested Citation

  • Gerd Ronning & Niels Schulz, 2003. "Randomized Response and the Binary Probit Model," IAW Discussion Papers 10, Institut für Angewandte Wirtschaftsforschung (IAW).
    • Handle: RePEc:iaw:iawdip:10
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    File URL: http://www.iaw.edu/RePEc/iaw/pdf/iaw_dp_10.pdf
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    More about this item

    Keywords

    Asymptotic Eciency; Maximum Likelihood; Post Randomisation; Statistical Disclosure;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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