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Re: st: RE: creating loops using combinations of variables


From   Zeynep Ozkok <zeynepozkok@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: creating loops using combinations of variables
Date   Thu, 16 Feb 2012 13:10:58 +0100

Hi,

Thank you very much for your comment Nick.

Let me try to clarify the issue a bit by taking three variables as you
suggested. The three variables are: var1, var2, and var3.

What I would like to do is the following:

Step 1: Generate two variables called lex1, and lex2 such that, lex1 =
var1 and lex2= var2+var3
Generate two indices index1 and index2, such that: index1 = ln(1+
lex1) and index2 = ln(1+lex2)

Run a regression of the following form: Y_i,s,t= alpha_i +alpha_s
+alpha_t +beta*(index1)_i,t +lamda* (index2)_i,t + error_i,s,t

Save the coefficients for index1 and index2, and the Rsquare.

Clear lex1, lex2, index1, index2.

Step 2: Generate two variables called lex1, and lex2 such that, lex1 =
var2 and lex2= var1+var3
Generate two indices index1 and index2, such that: index1 = ln(1+
lex1) and index2 = ln(1+lex2)

Run a regression of the following form: Y_i,s,t= alpha_i +alpha_s
+alpha_t +beta*(index1)_i,t +lamda* (index2)_i,t + error_i,s,t

Save the coefficients for index1 and index2, and the Rsquare.

Clear lex1, lex2, index1, index2.

Step 3: Generate two variables called lex1, and lex2 such that, lex1 =
var3 and lex2= var1+var2
Generate two indices index1 and index2, such that: index1 = ln(1+
lex1) and index2 = ln(1+lex2)

Run a regression of the following form: Y_i,s,t= alpha_i +alpha_s
+alpha_t +beta*(index1)_i,t +lamda* (index2)_i,t + error_i,s,t

Save the coefficients for index1 and index2, and the Rsquare.

Clear lex1, lex2, index1, index2.

Unfortunately the order of the variables included in the index
measures are important. I should be able to tell which significant
indices include which variables. To me that seems almost impossible
when considering 27 variables. Is there a way to construct a loop to
run this entire process?

Thank you so much for all your help.

Zeynep


> On Thu, Feb 16, 2012 at 11:41 AM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
>> "All possible combinations" would usually mean, for 27 variables, 27 ways of selecting just one, comb(27, 2) = 351 ways of selecting two, ..., up to comb(27, 27) = 1 way of selecting them all. In total that means 2^27 - 1 ~ 10^8 combinations. That is, precisely, 134,217,727 combinations.
>>
>> My suggestion is to set aside the fact that you have 27 variables. Show us exactly what you would do with just 3 variables, say.
>>
>> Nick
>> n.j.cox@durham.ac.uk
>>
>> Zeynep Ozkok
>>
>> I have a question on how to create loops for combinations of different
>> variables. I have 27 variables that I would like to put in two different
>> indices.
>>
>> The indices can be constructed in two steps:
>>
>> Lex1=sum(of different variables out of 27)   this variable should be able
>> to take on 1 to 27 variables, so it should allow for all possible
>> combinations. It could be equal to only 1 variable, or it could be equal to
>> the sum of different variables
>>
>> Index1 = ln (1+lex1)  this index is then dependent on what values lex1
>> takes on
>>
>> Similarly
>>
>> Lex2 = sum (of all the variables that are not accounted in lex1) again this
>> could take on one variable, or more than one depending on the structure of
>> lex1.
>>
>> Index2 = ln(1+lex2) this index is once again dependent on what values lex2
>> takes on, which is dependent on the values that lex1 takes on.
>>
>> Then these two indices will simultaneously be used in fixed effects
>> regressions as follows:
>>
>> Y_i,s,t= alpha_i +alpha_s +alpha_t +beta*(index1)_i,t +lamda* (index2)_i,t
>> + error_i,s,t
>>
>> The loop must go on until all possibilities/ combinations are completed. I
>> need to check the results of the beta and lamda coefficients and their
>> corresponding rsquares for each regression. Since there are numerous
>> possibilities in constructing each index I need to create a loop. However I
>> don't even know how to start out a loop that depends on combinations of
>> variables. Could you possibly help me out in writing and solving this
>> problem?
>>
>>
>> *
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