How to create a composite variable to use as a response variable? I am a student doing my master's thesis and I have a question regarding my study. 
I am working with country data for 25 countries and I am looking into cultural values, attitudes and sociodemographics as predictors of environmental behavior.
For the dependent variable environmental behavior I would like to combine several aspects (Generation of waste, waste treatment, GHG emissions, energy consumption, public transportation expenditure, car usage, environmental protection expenditures)
Could you please give me some advice on how to combine these into one composite variable? If I transform each variable into quartiles (1 being environment protection and 4 environment degradation) can I then add the "rankings" and form a composite? or is this not a valid way to create a composite?
Also, is it a good idea to combine the variables into one composite dependent variable, or should I focus on making regressions for each aspect of environmental behavior separately?
I use the software Eviews and SPSS. Please if I am not clear enough let me know to give further details.
 A: I would not discretize / categorize your date into quartiles and sum them.  This is too coarse-grained as it does not take into account how far a data point is from the boundary between the quartiles, for instance.  (For more information on this topic, you might want to read my answer here: How to choose between ANOVA and ANCOVA in a designed experiment, especially the update.)  A common approach to a situation like this would be to turn your data into z-scores (i.e., subtract the mean from every value and divide the difference by the standard deviation), and then average the z-scores for the variables you want to combine.  This is often done when working with responses to questionnaires, in which case you want to be careful to 'reverse-score' responses to questions that were asked from the opposite perspective (e.g., how much do you dislike..., rather than how much do you like), but I can't tell if there will be an analogue of this in your data.  
Before jumping in to combining your response variables, however, I would explore them to see if they really do hang together the way you expect them to.  You should look into factor analysis to do this.  All of the top returns listed by the Google search for factor analysis are worth exploring, as are the CV threads tagged under factor-analysis.  
You may also want to pursue a more comprehensive approach than using a composite variable as your response in a multiple regression model.  It may be better to use structural equation modeling instead.  Wikipedia's article may be a good place to start, as well as the CV threads under sem.  I don't know much about eviews, but SPSS will not do SEM, you would need to buy their companion product AMOS instead.  
