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A Simple Approach to Simultaneous Quantile Regression under Partial Homogeneity Constraints

Javier Alejo

Journal of Econometric Methods2026https://doi.org/10.1515/jem-2025-0003article
AJG 1ABDC B
Weight
0.50

What the paper says

Quantile regression is one of the most important methods to estimate heterogeneous effects on a variable of interest. In many applications there is a subset of covariates of interest, while the rest operate as controls in the regression equation. This work presents a straightforward empirical strategy for situations in which the control variables have a homogeneous effect on the conditional distribution. We develop the asymptotic theory for the proposed estimator and the corresponding inference procedures. An application using environmental pollution data illustrates the method by estimating the Environmental Kuznets Curve.

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https://doi.org/https://doi.org/10.1515/jem-2025-0003

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@article{javier2026,
  title        = {{A Simple Approach to Simultaneous Quantile Regression under Partial Homogeneity Constraints}},
  author       = {Javier Alejo},
  journal      = {Journal of Econometric Methods},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1515/jem-2025-0003},
}

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A Simple Approach to Simultaneous Quantile Regression under Partial Homogeneity Constraints

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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