arXiv 16 Dec 2021 · Econometrics · publishedStatistics & Probability Letters (2023) · 3 citations (OpenAlex)
arXiv:2112.08546 · PDF · DOI · OpenAlex · Extracted main text
This paper examines the local linear regression (LLR) estimate of the conditional distribution function $F(y|x)$. We derive three uniform convergence results: the uniform bias expansion, the uniform convergence rate, and the uniform asymptotic linear representation. The uniformity in the above results is with respect to both $x$ and $y$ and therefore has not previously been addressed in the literature on local polynomial regression. Such uniform convergence results are especially useful when the conditional distribution estimator is the first stage of a semiparametric estimator. We demonstrate the usefulness of these uniform results with two examples: the stochastic equicontinuity condition in $y$, and the estimation of the integrated conditional distribution function.
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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 | Fan, Y. and Guerre, E (2016) Multivariate Local Polynomial Estimators: Uniform Boundary Properties and Asymptotic Linear Representation, volume 36, pages 489… | 0.843 | 5 | 4 | 60% |
| 2 | Hansen, B. E (2004) Nonparametric estimation of smooth conditional distributions | 0.843 | 3 | 3 | 100% |
| 3 | Giné, E. and Guillou, A (2001) On consistency of kernel density estimators for randomly censored data: rates holding uniformly over adaptive intervals | 0.737 | 3 | 3 | 67% |
| 4 | Kong, E., Linton, O., and Xia, Y (2010) Uniform bahadur representation for local polynomial estimates of m-regression and its application to the additive model | 0.737 | 3 | 2 | 100% |
| 5 | Masry, E (1996) Multivariate local polynomial regression for time series: uniform strong consistency and rates | 0.737 | 3 | 2 | 100% |
| 6 | Nolan, D. and Pollard, D (1987) U-processes: Rates of convergence | 0.644 | 3 | 2 | 67% |
| 7 | Giné, E. and Guillou, A (2002) Rates of strong uniform consistency for multivariate kernel density estimators | 0.644 | 2 | 2 | 100% |
| 8 | Yu, K (1997) Smooth regression quantile estimation | 0.644 | 2 | 2 | 100% |
| 9 | Yu, K. and Jones, M. C (1998) Local linear quantile regression | 0.644 | 2 | 2 | 100% |
| 10 | Giné, E. and Guillou, A (1999) Laws of the Iterated Logarithm for Censored Data | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 20 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Sharp Bounds and Inference in Sample Selection Models with Treatment Endogeneity | 0.405 | 1 | 1 |