Quantile regression methods for recursive structural equation models

By Lingjie Ma, Roger W. Koenker. 2004

218 citations recorded by the source corpus.

Subfields: Education, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0d61ed9deed687a3644efb504bf9e9804ce4b143

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Citations in the corpus

QUANTILE AND PROBABILITY CURVES WITHOUT CROSSING (2007, background): “We consider a target function u 7→ Q0(u|x) that, for each x ∈ X , maps (0, 1) to the real line and is increasing in u. Suppose that u 7→ Q̂(u|x) is a parametric or nonparametric estimator of Q0(u|x).”
Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions (2016, methodology): “There are currently two approaches to model the QQ method: (1) a triangular system of equations based on Ma and Koenker (2006) and (2) a single equation regression approach based on Sim and Zhou (2015), which is also based on Ma and Koenker (2006).”
Changes in Compulsory Schooling, Education and the Distribution of Wages in Europe (2009, unknown): “On the other hand, if we fix sa and allow su to vary, we can shed light on how the sa quantile of s affects the entire distribution of log wages (Ma and Koenker, 2006).”
Instrumental Variable Quantile Regression (2004, methodology): “These QTE may then be used to summarize the impact of variables of interest D on the quantiles of potential outcomes as suggested in Doksum (1974) and Lehmann (1975). It is important to note that the structural error Ud in (1) is responsible for heterogeneity of potential outcomes among individuals ”
Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality (2009, methodology): “These results confirm the findings in Willis and Rosen (1979), Carneiro, Heckman and Vytlacil (2007), and Deschenes (2007).”
An Approach to Multivariate Covariate-Dependent Quantile Contours With Application to Bivariate Conditional Growth Charts (2008, methodology): “This marginal-conditional structure also was used by Ma and Koenker (2006) to construct structural equation models.”
Nonparametric Instrumental Variables Estimation of a Quantile Regression Model (2006, methodology): “Chernozhukov and Hansen (2005a), and Ma and Koenker (2006) .”
A quantile correlated random coefficients panel data model (2016, background): “Since (39) conditions on a subpopulation with mass shrinking to zero, estimation of δ(τ) will not be possible at the regular rate of √ N .”
Identification and Estimation of Triangular Simultaneous Equations Models without Additivity (2002, unknown): “Ma and Koenker (2006) consider identification and estimation of parametric nonseparable quantile effects using a parametric, quantile based control variable.”