Juan Carlos Escanciano, Chuan Goh
arXiv 18 Jul 2018 · Econometrics
arXiv:1807.06977 · PDF · DOI · OpenAlex · Extracted main text
Regression quantiles have asymptotic variances that depend on the conditional densities of the response variable given regressors. This paper develops a new estimate of the asymptotic variance of regression quantiles that leads any resulting Wald-type test or confidence region to behave as well in large samples as its infeasible counterpart in which the true conditional response densities are embedded. We give explicit guidance on implementing the new variance estimator to control adaptively the size of any resulting Wald-type test. Monte Carlo evidence indicates the potential of our approach to deliver powerful tests of heterogeneity of quantile treatment effects in covariates with good size performance over different quantile levels, data-generating processes and sample sizes. We also include an empirical example. Supplementary material is available online.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Hendricks, W. and R. Koenker (1992) Hierarchical spline models for conditional quantiles and the demand for electricity | 1.000 | 5 | 3 | 100% |
| 2 | Powell, J. L (1991) Estimation of monotonic regression models under quantile restrictions | 1.000 | 5 | 3 | 100% |
| 3 | Portnoy, S (2012) Nearly root-$n$ approximation for regression quantile processes | 0.874 | 6 | 2 | 100% |
| 4 | Koenker, R (2018) quantreg: Quantile Regression | 0.737 | 3 | 2 | 100% |
| 5 | Koenker, R. and Z. Xiao (2002) Inference on the quantile regression process | 0.693 | 6 | 1 | 100% |
| 6 | Koenker, R (2005) Quantile Regression | 0.644 | 2 | 2 | 100% |
| 7 | Koenker, R. and G. Bassett (1978) Regression quantiles | 0.644 | 2 | 2 | 100% |
| 8 | Newey, W. K. and J. L. Powell (1990) Efficient estimation of linear and type I censored regression models under conditional quantile restrictions | 0.644 | 2 | 2 | 100% |
| 9 | R Core Team (2016) R: A Language and Environment for Statistical Computing | 0.644 | 2 | 2 | 100% |
| 10 | Hall, P. and S. J. Sheather (1988) On the distribution of a Studentized quantile | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 35 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates | 0.405 | 1 | 1 |