Harold D. Chiang, Bing Yang Tan
arXiv 17 Oct 2020 · Econometrics · publishedJournal of Business and Economic Statistics (2022) · 3 citations (OpenAlex)
arXiv:2010.08838 · PDF · DOI · OpenAlex · Extracted main text
This paper studies the asymptotic properties of and alternative inference methods for kernel density estimation (KDE) for dyadic data. We first establish uniform convergence rates for dyadic KDE. Secondly, we propose a modified jackknife empirical likelihood procedure for inference. The proposed test statistic is asymptotically pivotal regardless of presence of dyadic clustering. The results are further extended to cover the practically relevant case of incomplete dyadic data. Simulations show that this modified jackknife empirical likelihood-based inference procedure delivers precise coverage probabilities even with modest sample sizes and with incomplete dyadic data. Finally, we illustrate the method by studying airport congestion in the United States.
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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 | Cattaneo, M., Y. Feng, and W. Underwood (2022) Uniform inference for kernel density estimators with dyadic data | 0.874 | 6 | 4 | 67% |
| 2 | Matsushita, Y. and T. Otsu (2021) Jackknife empirical likelihood: small bandwidth, sparse network and high-dimension asymptotic | 0.811 | 5 | 2 | 80% |
| 3 | Graham, B. S., F. Niu, and J. L. Powell (2019) Kernel density estimation for undirected dyadic data | 0.794 | 18 | 6 | 50% |
| 4 | Efron, B. and C. Stein (1981) The jackknife estimate of variance | 0.737 | 3 | 3 | 67% |
| 5 | Graham, B. S., F. Niu, and J. L. Powell (2021) Minimax risk and uniform convergence rates for nonparametric dyadic regression, Tech | 0.644 | 2 | 2 | 100% |
| 6 | Owen, A (1990) Empirical likelihood ratio confidence regions | 0.511 | 2 | 2 | 50% |
| 7 | Fafchamps, M. and F. Gubert (2007) The formation of risk sharing networks | 0.511 | 2 | 1 | 100% |
| 8 | Menzel, K (2021) Bootstrap with cluster-dependence in two or more dimensions | 0.511 | 2 | 1 | 100% |
| 9 | Akritas, M. G. and I. Van Keilegom (2001) Non-parametric estimation of the residual distribution | 0.405 | 1 | 1 | 100% |
| 10 | Aronow, P. M., C. Samii, and V. A. Assenova (2015) Cluster–robust variance estimation for dyadic data | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 59 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Inference in Linear Dyadic Data Models with Network Spillovers | 0.405 | 1 | 1 |
| 2 | Extremal Quantiles under Two-Way Clustering | 0.405 | 1 | 1 |