Semiparametric M-quantile regression with measurement error in spatial covariates: an application to housing price modelling
针对空间数据中协变量存在测量误差的问题，提出一种半参数M分位数回归方法，用于分析米兰公寓市场的异质性，并给出参数估计和标准误的解析表达式。
Abstract Spatial data are becoming increasingly accessible to urban scientists, but these data are often prone to measurement error. Motivated by the analysis of the Milan (Italy) apartment market heterogeneity, we propose a semiparametric approach to adjust for the presence of measurement error in the covariates when estimating M-quantile regression. The M-quantile approach helps explain the heterogeneity across individual units, preserving robustness and efficiency in the estimates. The model’s parameters are estimated within a penalised likelihood framework and an analytical expression is proposed to estimate standard errors. Asymptotic properties of estimates are also provided.