Wage analysis using “Swiss Labor Market Survey 1998” data

Author

Fernando Rios-Avila

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 wages).

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.do

Model Specification

For Imputation we assume prices are a function of the following variables: education, experience, tenure, gender, age, age squared, and marital status.

For modeling, we only consider education, expererience, tenure, gender and age.

Ploting Conditional and Unconditional Quantile Regressions

Conditional Quantile Regression

Unconditional Quantile Regression

Conditional Quantile Regression

Unconditional Quantile Regression

Conditional Quantile Regression

Unconditional Quantile Regression