How to use an index in a multiple regression

I'm performing a multiple regression to see whether the free trade agreement (FTA) between South Korea and the EU had an effect upon the bilateral trade. I am regressing my dependent variable (bilateral trade) upon 4 independent variables:

• x1= GDP (nominal data)
• x2= CPI
• x3= NEER (the nominal effective exchange rate), which is an index number
• x4= dummy variable for the FTA.

I am using quarterly panel data computed for 10 years for all 22 countries included in the FTA. I am a bit confused how to use the fourth variable, the index number in this multiple regression. The base year of the data set I found (from the IMF) is 2010. How do I put this index (NEER) in my regression? Do I use the changes of the index in my regression, with log? And how can I interpret this variable? An increase of 1 (1%) in the index is a increase of … in the dependent variable?

• By terminological convention, we say that you 'regress your dependent variable on 4 independent variables'. Can you say more about the "FTA"? What does that stand for? Are you asking how to enter the year into your model? Are you asking how to interpret dummy variables when you are working with logs / % changes? Are you asking how to difference a dummy variable? – gung - Reinstate Monica Sep 14 '15 at 19:38
• Oh sorry, I corrected it already. The FTA means Free Trade Agreement. I am using panel data in quarters over 10 years. I have one index variable, which gives values of the effective exchange rate compared to the year 2010. I am wondering how to include this variable in the regression, do I have to transform it? Because I can't simply plug in indexed data. – BobbyJO Sep 14 '15 at 19:42

You go right ahead and include that index (in levels) in the model you wish to estimate. The interpretation is the same always, when the x increase by 1 y increase by $\beta$.