Quantile regression with multiple proxy variables

Data integration has become increasingly popular owing to the availability of multiple data sources. This study considered quantile regression estimation when a key covariate had proxies across several datasets. In unified procedure, proposed method incorporates that have both linear and nonlinear relationships with unobserved covariates. The approach allows inference function covariates does not require function's linearity. Simulation studies demonstrated this methodology successfully integrates reveals for wide range data. is applied administrative obtained from Survey Household Finances Living Conditions provided by Statistics Korea, specify relationship between assets salary income in presence records.