Firstly, I am applying a 2sls model in my paper:
Corruption= o+1bq+2da+3lawandorder+4unemprate+5politicalregime+6gdpgrowthrate+7govermentstability Log (FDI) =o+1corr+2buerucraticquality+3lawandorder+4da+5investmentprofile +6gdpgrowthrate+7populationgrowth+8inflation+9openess+10politicalterrorscale.
As a part of time series data I know that I have to check these variables for stationary and s serial correlation.
Once I check my variables for stationary, and then do the first difference then my variables do become stationary but when I regress that, then the results comes weird.
Apart from that, I have checked for serial correlation through acf and pacf graphs in order to determine the lags.
I am somewhat confused either to run regression on lagged values or difference data.
It would be great if you could guide me on this