Also available in Stata and Python versions
Load libraries
library(wooldridge)
library(stargazer)
library(quantreg)
library(sandwich)
Quantile Regression for Financial Wealth
OLS<-lm(nettfa ~ inc + age + agesq + e401k, data=k401ksubs, subset=fsize==1)
OLSr <- sqrt(diag(vcovHC(OLS, type="HC")))
Q10<-rq(nettfa ~ inc + age + agesq + e401k, data=k401ksubs, subset=fsize==1, tau = .10)
Q25<-rq(nettfa ~ inc + age + agesq + e401k, data=k401ksubs, subset=fsize==1, tau = .25)
LAD<-rq(nettfa ~ inc + age + agesq + e401k, data=k401ksubs, subset=fsize==1, tau = .50)
Q75<-rq(nettfa ~ inc + age + agesq + e401k, data=k401ksubs, subset=fsize==1, tau = .75)
Q90<-rq(nettfa ~ inc + age + agesq + e401k, data=k401ksubs, subset=fsize==1, tau = .90)
stargazer(OLS, Q10,Q25,LAD,Q75,Q90, column.labels = c("OLS", "Q10","Q25","LAD","Q75","Q90"), se=list(OLSr), no.space=TRUE, type="text")
##
## ==========================================================================================
## Dependent variable:
## ----------------------------------------------------------------------
## nettfa
## OLS quantile
## regression
## OLS Q10 Q25 LAD Q75 Q90
## (1) (2) (3) (4) (5) (6)
## ------------------------------------------------------------------------------------------
## inc 0.783*** -0.018 0.071*** 0.324*** 0.798*** 1.291***
## (0.104) (0.037) (0.013) (0.033) (0.057) (0.111)
## age -1.568 -0.066 0.034 -0.244 -1.386*** -3.579***
## (1.075) (0.222) (0.097) (0.149) (0.486) (1.219)
## agesq 0.028** 0.002 0.0004 0.005** 0.024*** 0.061***
## (0.014) (0.003) (0.001) (0.002) (0.007) (0.017)
## e401k 6.837*** 0.949 1.281*** 2.598*** 4.460*** 6.001***
## (2.171) (0.633) (0.345) (0.394) (0.935) (2.325)
## Constant 2.534 -5.228 -4.373** -3.573 7.539 37.268*
## (19.237) (4.550) (2.089) (2.637) (8.351) (21.980)
## ------------------------------------------------------------------------------------------
## Observations 2,017 2,017 2,017 2,017 2,017 2,017
## R2 0.127
## Adjusted R2 0.126
## Residual Std. Error 44.502 (df = 2012)
## F Statistic 73.387*** (df = 4; 2012)
## ==========================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01