Price analysis using “Hedonic House Price” data.
Setup
For the following analysis, all the data process is done in the file example.do.
This do-file loads the data and creates auxiliary variables that mimic the interval censoring of the data (in this case price).
Using the brackets data, it estimates the heteroskedastic interval regression model, and then uses the intreg_mi command to obtain the imputations for the data. We assume 3 cases, where data is categorized in 5, 7, and 10 groups.
The imputed data is then used to estimate conditional and unconditional quantile regressions, using the fully observed data, and the imputed data.
The results are then saved in a matrix, and then used to create the figures.
ssc install frause
run example.doModel Specification
For Imputation we assume prices are a function of the following variables: Distance from City center, Log of Landsize, Number of Rooms, Number of Bathrooms, Number of Cars spaces, Type of Property, and region. Type of Property is interacted with distance and Log of Landsize.
For modeling, we use the same list of variables but without the interaction terms. Only selected items are included in the plot.
Ploting Conditional and Unconditional Quantile Regressions
