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Nonparametric Gini-Frisch bounds

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  • Chalak, Karim

Abstract

The Gini-Frisch bounds partially identify the constant slope coefficient in a linear equation when the explanatory variable suffers from classical measurement error. This paper generalizes these quintessential bounds to accommodate nonparametric heterogeneous effects. It provides suitable conditions under which the main insights that underlie the Gini-Frisch bounds apply to partially identify the average marginal effect of an error-laden variable in a nonparametric nonseparable equation. To this end, the paper puts forward a nonparametric analogue to the standard “forward” and “reverse” linear regression bounds. The nonparametric forward regression bound generalizes the linear regression “attenuation bias” due to classical measurement error.

Suggested Citation

  • Chalak, Karim, 2024. "Nonparametric Gini-Frisch bounds," Journal of Econometrics, Elsevier, vol. 238(1).
    • Handle: RePEc:eee:econom:v:238:y:2024:i:1:s0304407623002762
    DOI: 10.1016/j.jeconom.2023.105560
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    More about this item

    Keywords

    Attenuation bias; Gini-Frisch bounds; Measurement error; Nonparametric nonseparable equation; Partial identification;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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