March 24, 2009 at 9:31 am 2 comments

| Gabriel |

My MDC technique is basically a multilevel version of a much older technique (as in so old it could have been used for marketing analysis at Sterling Cooper on “Mad Men”) created by Edwin Mansfield. This older technique first does a series of Bass analyses (Mansfield published the equation before Bass but the older version is under-theorized which is why we call it the “Bass” model today). It then treats the coefficients from the first stage as a dataset to itself be regressed. Although more recent work supersedes it in several ways, it’s still worth using for diagnostic purposes. However it’s a pain in the ass to use as it requires you to run a separate regression for each of your innovations and then aggregate them. As such, I wrote this code to automate it.

Even if for some bizarre reason you’re not particularly interested in diffusion models dating from the Kennedy administration, this code may be interesting for a few reasons:

  • It uses the “estout” package not for the (indispensable) usual purpose of making results meet publication style, but for the off-label purpose of creating a meta-analysis dataset.
  • It makes extensive (and extremely clumsy) use of shell-based regular expression commands to clean this output. (I am under no illusions that the “awk” code is remotely elegant).
  • It saves the cluster id variable in a local, then attaches it back using a loop.
capture program drop mansfield
program define mansfield
 *NOTE: dependency, "vallist" and "estout"

 set more off

 local caseid `1'
 local genre  `1'

 sort `caseid'
 by `caseid': drop if [_N]<5

 vallist `caseid', quoted 

 shell touch emptyresults
 shell mv emptyresults `genre'results.txt
 foreach case in `r(list)' {
  disp "`case'"
  quietly reg w_adds Nt Nt2 if `caseid'==`case'
  esttab using `genre'results.txt, plain append

 shell awk '{ gsub(" +b/t", ""); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub(" +", "\t"); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub("\n\t.*", ""); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '/.+/{print $0}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub("^\t.+", ""); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub("^$", ""); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '/.+/{print $0}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub("Nt2\t", ""); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub("_cons\t", ""); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub("N\t", ""); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell awk '{ gsub("Nt\t", "NR\t"); print $0;}' `genre'results.txt > tmp ;  mv tmp `genre'results.txt
 shell #!/bin/sh
 shell awk -f mansfield.awk `genre'results.txt > tmp ;  mv tmp `genre'results.txt

 insheet using `genre'results.txt, clear
 drop v1 v6
 ren v4 A
 ren v2 B
 ren v3 C
 ren v5 n
 gen b    = -C
 gen nmax = (-B - ((B^2)-4*A*C)^0.5) / (2*C)
 gen a    = A / nmax

 gen `caseid'=.
 global n=1
 foreach case in `r(list)' {
  replace `caseid'=`case' in $n/$n
  global n=$n+1
 save `genre'_mansfield.dta, replace

*note, text of mansfield.awk follows
*it should be in the same directory as the data and made executable the command
*"chmod mansfield.awk -x"
*    FS="\n"
*    RS="Nt\t"
*    ORS=""
*        x=1
*        while ( x<NF ) {
*                print $x "\t"
*                x++
*        }
*        print $NF "\n"

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Commercial visualization Estout


  • 1. MDC code « Code and Culture  |  June 16, 2009 at 5:11 am

    […] already posted code to do the precursor approach by Edwin Mansfield, though I recently learned some matrix syntax that […]

  • […] syntax. Even until now, I’d never understood how to use matrices (which is why this script is so hideously clunky, really, please don’t click the link) but Long has a very clear […]

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