In the thread about using Mata to create a matrix of the number of
agreements between firms, and in response to my last posting,
Joe. J. said the first part was "exactly what I was looking for"
and wondered politely why I had felt obligated to add the
second part. To remind you, in the final iteration of the first
part, the resulting data looks like this,
      +-------------------------------------------------+
      | company  f_11A  f_11K  f_12Z  f_14T  f_21S |
      |-------------------------------------------------|
     1. |   11A    0    0    2    1    0 |
     2. |   11K    0    0    1    0    1 |
     3. |   12Z    2    1    0    1    1 |
     4. |   14T    1    0    1    0    0 |
     5. |   21S    0    1    1    0    0 |
      +-------------------------------------------------+
and in the part I felt obligated to add, I recorded the data like this:
      +-----------------------------------+
      | c1  c2  company1  company2  n |
      |-----------------------------------|
     1. |  1   2     11A     11K  0 |
     2. |  1   3     11A     12Z  2 |
     3. |  1   4     11A     14T  1 |
     4. |  1   5     11A     21S  0 |
     5. |  2   3     11K     12Z  1 |
      |-----------------------------------|
     6. |  2   4     11K     14T  0 |
     7. |  2   5     11K     21S  1 |
     8. |  3   4     12Z     14T  1 |
     9. |  3   5     12Z     21S  1 |
    10. |  4   5     14T     21S  0 |
      +-----------------------------------+
There were two reasons for my unasked-for suggestion.
First, Joe mentioned something about merging in the characteristics of the
firms and, looking at the first organization, that looked hard to do.
Obviously, it would be easy to merge in the characteristics of one of the
parties -- the one recorded in the variable company -- but what about the
characteristics of the other parties? In the first observation, for
instance, also needed would be the characteristics of 12Z and 14T.
That lead me to the second organization, where each observation records a pair
of the parties and so that parties are on equal footing. One could merge in
characteristics of company1 and of company2 into the data easily.
Second, I thought to myself, how would I analyze these data? I should hasten
to add that I am not an expert or at least have to reason to think that I am,
since I don't even know the details of the problem. Were those details
revealed, I could prove I'm not an expert. Anyway, I wasn't sure what I would
do with these data in the first organization, but how to analyze them in
the second organization seemed obvious to me. I could use logistic or
Poisson regression, or even a hurdle model. To be explained would be whether
(or how many) agreements there were between pairs of companies based on their
characteristics and, presumably, interactions of their characteristics.
-- Bill
[email protected]
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