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Instrumental Variable Quantile Regression For Clustered Data

Author

Listed:
  • Galina Besstremyannaya

    (National Research University Higher School of Economics)

  • Sergei Golovan

    (National Research University Higher School of Economics)

Abstract

The purpose of the paper is to enable inference in case of quantile regression with endogenous covariates and clustered data. We prove that the instrumental variable quantile regression estimator is consistent where there is correlation of errors within clusters. We derive an asymptotic distribution for the estimator, which may be used for inference for a given tau. As regards inference based on the entire instrumental variable quantile regression process, we prove that cluster-based bootstrapping of a statistic of a certain class offers a computationally tractable approach for implementing asymptotic tests. Our theoretical results concerning the asymptotic properties of the instrumental variable quantile regression estimator for clustered data are supported by simulation analysis. The empirical part of the paper applies the technique to estimation of the earning equations of US men and women where female labor supply is endogenous and subject to the shock of World War II

Suggested Citation

  • Galina Besstremyannaya & Sergei Golovan, 2022. "Instrumental Variable Quantile Regression For Clustered Data," HSE Working papers WP BRP 255/EC/2022, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:255/ec/2022
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    References listed on IDEAS

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    More about this item

    Keywords

    quantile regression; endogeneity; clustered data; instrumental variables;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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