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On Ill-Posedness of Nonparametric Instrumental Variable Regression With Convexity Constraints

Author

Listed:
  • Olivier Scaillet

    (University of Geneva GSEM and GFRI; Swiss Finance Institute)

Abstract

This note shows that adding monotonicity or convexity constraints on the regression function does not restore well-posedness in nonparametric instrumental variable regression. The minimum distance problem without regularisation is still locally ill-posed.

Suggested Citation

  • Olivier Scaillet, 2016. "On Ill-Posedness of Nonparametric Instrumental Variable Regression With Convexity Constraints," Swiss Finance Institute Research Paper Series 16-06, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1606
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    Cited by:

    1. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 14/17, Institute for Fiscal Studies.
    2. Denis Chetverikov & Daniel Wilhelm, 2016. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 48/16, Institute for Fiscal Studies.
    3. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric Instrumental Variable Estimation Under Monotonicity," Econometrica, Econometric Society, vol. 85, pages 1303-1320, July.

    More about this item

    Keywords

    Nonparametric Estimation; Instrumental Variable; Ill-Posed Inverse Problems;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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