This post is following of the above post.
Hello. In this post, I will do Heteroskedasiticity test usung R.
In te previous post, I meade regression model using R.
Let's plot fitted value vs. residual value
Above plot is men_15_29 ~ log(usd) + capi.
Above plot is for women_15_29 ~ log(usd) + capi.
Let's test if those models have heteroskedasticity.
FIrstly, I use Breush-Pegan test manually.
p-value is 0.04711, which is smaller than 0.05. So, lm_men model has heteroskedasticity.
Next, let's use lmtest package and bptest() function.
p-value is 0.04729, it is close to manual calculation.
Then, let's check for lm_women. I use manual Special Case of White Test.
P-value is almost 0. So, lm_women model has heteroskedasticiy.
SInce the both model, lm_men and lm_women have heteroskedasticity, let's see heteroskedasticiry-robust standard error.
I use car package and lmtest package, then use coeftest() function.
On Heteroskedasticity-robust standard error, log(usd) and capi are statistically significant.
log(usd) and capi are statistically significant on lm_women model under heteroskedasticity robust inference.
Thant's it. Thank you!
Next post is,
To read from the 1st post,