SMOOTH VARYING-COEFFICIENT ESTIMATION AND INFERENCE FOR QUALITATIVE AND QUANTITATIVE DATA

By Qi Li, Jeffrey S. Racine. Econometric Theory, 2010

97 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9c921aa6f6239f9f51aedc1a25cc17251e1cf9f9

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In Statistics and Probability

1. Xiaohui Zhang
2. Bin Peng
3. Samuel A. Cushman
4. R. Khosravi
5. Guohua Feng
6. Mahmoud Hemami
7. Jiti Gao

Citations in the corpus

• A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks (2017, background): “Case 4: Varying-coefficient Panel Data Models with Mixed Covariates Optimal bandwidth selection has been fully investigated in the i.i.d. cross-sectional setting in the literature (see Li and Racine (2010) and Li et al. (2013) for details), but little work has been done for panel data models.”
• How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice (2016, unknown): “The second estimation strategy is a kernel smoothing estimator of the marginal effect, which is an application of semiparametric smooth varying-coefficient models (Li and Racine 2010).”
• Multispecies assessment of core areas and connectivity of desert carnivores in central Iran (2018, methodology): “The initial expected density for our target species was set to 1 in each cell containing an occurrence record, and the kernel density buffering for each short path was calculated using Gaussian function (as in Li & Racine, 2010).”