Include dummy variables (time series) for industries

#1
Hi all,

I have a question about including dummy variables in mijn analysis for master thesis.

In my analysis I investigate the relationship between a couple of macro-economic indicators (GDP, unemployement, inflation) and valuation multiples of companies/industries in the DJSTOXX600 (f.e. Price/Equity ratio). I am interested in the predictive power of the macro-economic indicators related to valuation multiples. 566 companies are included with data over the period 1998-2008.

I created the following variables in SPSS:

PE-ratio (all 566 companies lined uit in a colomn, sorted from 1998-2008, a total of 566*11 lines)
GDP
Unemployment
Inflation
Size (control variable)
Assets (control variable)
Liabilities (control variable)

Now I have to perform a multiple regression analysis including dummies for years, industries and countries. For example for industries; there are a total of 12 industries represented in the sample. I created 11 dummies, with '1' and '0'. The 11 dummies created 11 variables.

My research question is: is there a significant relationship between the development of economic indicators and the valuation multiples of different industries over time?

Now I have the following problem. I started to fill these variables in multiple regression analsyse with the 11 dummies in the category independent variables. Then I run the regression.

My questions are:
- Is this the right way to include dummy variables? Is the output in the attachment the proper output to analyse the relationship between the influence of GDP, Inflation, Unemployment to the PE ratio of a specific industry? How do I have to read the outcomes in the industry dummies (f.e. see attachment voor PE-ratio, the dummy variables are BASICR - UTILITIES).
- Can I perform the same analysis for the year/country dummies?
- What should be additional analysis to further robust the analysis?

I hope someone can help me. Thanks in advance.

Kleos