Since I moved to belgium specifically Leuven my hair became a mess. After a while I realized it must be the water. Is there anyone who solved this? I need recommendations before I invest in shower head filers... I'm really desperate 😭
For information I have an unbalanced panel data. I created boxplots for each of my variables (the data is already organized in panel data format). But received a warning ⚠️ "Removed 16619 rows containing non-finite outside the scale range ('stat_boxplot()')". I think I made a mistake in my code. I used the following code.
Library(ggplot2)
Library(tidyr)
df_variables %>%
select(size, age, growth, liquidity, equity, revenues) %>%
pivot_longet(cols = everything()) %>%
ggplot(aes(x = name, y = value)) +
geom_boxplot(fill = "steelblue", outlier.color = "red") +
facet_wrap(~name, scales ="free") +
theme_minimal() +
labs(title ="outliers before winsorizing")
I have a unbalanced data. T=6 and N around 8000. I'm using R and will do regression analysis. There is no Muticollinearity in my independent data (I did pearson correlation and Iv and 1/IV test). I did Breuschpagan lagrange multiplier test and result is RE. Then did hausman test and the result indicates fixed effect model. Then to check my model and refine it. I did the tests for heteroskedasticity (breusch pagan), autocorrelation (wooldridge test) and I also tested if my variables are endogenous. The results indicate that there's heteroskedasticity and autocorrelation. Also 5 out of my 6 variables are endogenous. I did my research and I know that I may solve the heteroskedasticity and autocorrelation by using cluster/robust standard error. However for the endogenous variables, I'm a bit lost. I have one exogenous variable and the rest are endogenous. If I use two-stage fixed effects (FE-2SLS) or Wooldridge’s endogenous methods (Control Functions) may cause problems as one variable is exogenous and the result will be an unorganized structure. GMM is for dynamic panel. Did someone face issues? Fyi: I use R and also FYI I ran stationary tests but got errors because of small T but read an academic article that it's fine to skip it when T is very small (I did augmented DF tests for each variable but the tests are for linear not panel). Sorry if I made mistakes I'm writing my thesis and these tests are all new to me.