I am currently running two fixed effects regressions. One is to illustrate the impact of gambling on total annual hours worked. The other is to illustrate the impact of gambling on total annual wages.
I have decided to use Log Wages and also Log Hours which means that all individuals with zero wages and/or zero hours worked are excluded (so only employed individuals are in the sample).
Currently, pretty much all of the variables that are significant for the regression of total annual wages are also significant for the regression of total hours worked. Is this an issue? I don't think that I can realistically find any variables that wouldn't be in both equations... I've read some literature and people use variables like non-labour income for hours worked and experience for wages but I don't have these variables in my dataset. I tried using marital status (which some literature says only affects hours worked) but I find them significant for wages too and in my head, I can understand why they would be.
If it is important for me to have different variables in each equation, should I maybe ignore the regression results and put marital status and number of kids solely in the regression for hours worked?
Also, given my panel data is only 6 years apart (with individuals ranging from ages 21 to 40 years old), do you think I can say that age shouldn't make a difference in the total hours worked as those are prime working ages? My regression shows that age does make a difference to hours worked though...
I have decided to use Log Wages and also Log Hours which means that all individuals with zero wages and/or zero hours worked are excluded (so only employed individuals are in the sample).
Currently, pretty much all of the variables that are significant for the regression of total annual wages are also significant for the regression of total hours worked. Is this an issue? I don't think that I can realistically find any variables that wouldn't be in both equations... I've read some literature and people use variables like non-labour income for hours worked and experience for wages but I don't have these variables in my dataset. I tried using marital status (which some literature says only affects hours worked) but I find them significant for wages too and in my head, I can understand why they would be.
If it is important for me to have different variables in each equation, should I maybe ignore the regression results and put marital status and number of kids solely in the regression for hours worked?
Also, given my panel data is only 6 years apart (with individuals ranging from ages 21 to 40 years old), do you think I can say that age shouldn't make a difference in the total hours worked as those are prime working ages? My regression shows that age does make a difference to hours worked though...