Interaction effects in Fixed Effect Models

Dear all,

I am currently writing my Master thesis and in addition to finding a relationship, I examine whether the relationship between X and Y became stronger over time. I use a firm fixed effect model, and this is my base regression:


I have 6 x variables and 6 control variables, the x variables are regressed separately. To examine whether the relationship became stronger, I created a new variable: year*x1 ,, year*x2 etc. (the interaction coefficient)

My question is, can I use year plain and simple use 2006,2007,2008 etc. as a variable., or do I need to create a categorical variable? Also, neither as a control or x-variable, year is included in my base regression. Since every interaction variable should also be in the regression individually, can I just add a variable year to my base regression?

With regards to the interpretation of the coefficient in a regression output, if it is significant, it indicates that the relationship is significantly different over time. A positive significant interaction coefficient would indicate that the effect became stronger over time and a significant negative effect would indicate that the relation became less strong?

Thank you in advance,

I figured it out and used a categorical variable for year: 2007 = 1, 2008 =2 etc. Base model (1), turns to this:


- Shocks stands for the 6 x-variables that are seperately regressed in the Fixed Effect Model.

The year variable is significant and negative: indicating that the relation between X and Y defers in the years. Does the sign of the year variable tell me extra information?
The interaction effect is significant and negative: indicating that the relation between X and Y is stronger in the beginnning of the sample period (i.e. higher categorical year variable decreases the effect of X on Y)

My real question here is: some of the X-variables in my base regression suddenly became significant in the regression with the year and interaction variables added. How is this possible and what does this tell me?

Kind regards,