Finite Sample Inference for Quantile Regression Models
By Victor Chernozhukov, Christian Hansen, Michael Jansson. 2006
90 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/8e400e66320abf135fac8803be22ce0abf9f5364
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Christian Hansen
- Isaiah Andrews
- Yixiao Sun
- David M. Kaplan
- Victor Chernozhukov
- Liangjun Su
- Zhenlin Yang
- D. Chetverikov
In Statistics and Probability
- Liangjun Su
- Victor Chernozhukov
- Christian Hansen
- Yixiao Sun
- David M. Kaplan
- Isaiah Andrews
- Zhenlin Yang
- Alexandre Belloni
Citations in the corpus
- Nonparametric estimation and inference on conditional quantile processes (2015, background): “0 Q2(sjx)ds for all 2 (0; 1): (2) This concept traces back to Lehmann (1975) and Doksum (1974); recent works include Heckman, Smith and Clements (1997), Abadie, Angrist and Imbens (2002), Chernozhukov and Hansen (2005) and Firpo (2007), among others.”
- Robust Spectral Analysis (2011, unknown): “More recently, Chernozhukov, Hansen, and Jansson (2009) use it to construct finite sample confidence intervals for quantile regression estimators.”
- SMOOTHED ESTIMATING EQUATIONS FOR INSTRUMENTAL VARIABLES QUANTILE REGRESSION (2016, methodology): “Within this framework, Chernozhukov and Hansen (2006) and Chernozhukov et al. (2009) develop estimation and inference procedures under strong identification.”
- Conditional Linear Combination Tests for Weakly Identified Models (2016, methodology): “parameter space performs well, but one could also consider more refined MCMC-based approaches as in Chernozhukov et al. (2009). Since we compute the PI test using the discretized problem (26), note that a point —0 can be included in the PI confidence set only if it is included in the confidence set ”
- Instrumental Variable Quantile Estimation of Spatial Autoregressive Models (2007, background): “However, previous literature focuses on the estimation of the structural quantile regression 2Chernozhukov and Hansen (2008) and Chernozhukov et al. (2007, 2009) proposed various alternative inference methods.”
- Instrumental Variable Quantile Regression (2004, methodology): “To alleviate this problem, Chernozhukov et al. (2009) develop suitable MCMC algorithms.”