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Unconditional Quantile Partial Effects via Conditional Quantile Regression

Author

Listed:
  • Montes Rojas Gabriel
  • Alejo Javier
  • Galvao Antonio
  • Martínez-Iriarte Julián
Abstract
This paper develops a semi-parametric procedure for estimation of unconditional quantile partial effects using quantile regression coefficients. The estimator is based on an identification result showing that, for continuous covariates, unconditional quantile effects are a weighted average of conditional ones at particular quantile levels that depend on the covariates. We propose a two-step estimator for the unconditional effects where in the first step one estimates a structural quantile regression model, and in the second step a nonparametric regression is applied to the first step coefficients. We establish the asymptotic properties of the estimator, say consistency and asymptotic normality. Monte Carlo simulations show numerical evidence that the estimator has very good finite sample performance and is robust to the selection of bandwidth and kernel. To illustrate the proposed method, we study the canonical application of the Engel’s curve, i.e. food expenditures as a share of income.

Suggested Citation

  • Montes Rojas Gabriel & Alejo Javier & Galvao Antonio & Martínez-Iriarte Julián, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Asociación Argentina de Economía Política: Working Papers 4674, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4674
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    References listed on IDEAS

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    1. Martínez-Iriarte, Julián & Montes-Rojas, Gabriel & Sun, Yixiao, 2024. "Unconditional effects of general policy interventions," Journal of Econometrics, Elsevier, vol. 238(2).

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    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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