test post for code entry

[Diana Hechavarria]

 *====================================================================*
*WIERSEMA & BOWEN SMJ Limited Dependent Variable (2007) procedures      *
*====================================================================*

* Estimate Logit model
logit    patent ceo_dst
* Predict probability of patent, store values in variable pprob
predict pprob
* Define expression for X’s marginal effect to use in predictnl command
* Save marginal effect values in meX; standard error values in meX se
local vb b[ cons] + b[X]*X + b[Z]*Z
local phat (exp(‘vb’)/(1+exp(‘vb’)))
predictnl meX = ‘phat’*(1-‘phat’)* b[X], se(meX se)
* Compute z-statistic values and store in variable z stat
gen z stat = meX/meX se
* print summary statistics for marginal effect and z-statistic values
tabstat meX z stat, stats(mean min max)
* Graph marginal effect and z-statistic values (Figure 1)
graph twoway (scatter meX pprob) || ///
(scatter z stat pprob, yaxis(2)yline
(−1.96 1.96, axis(2)))
* Compute and save sample means of variables X and Z
egen meanX = mean(X)
egen meanZ = mean(Z)
* Determine value and significance of marginal effect at data means
local vb b[ cons] + b[X]*meanX + b[Z] *meanZ
local phat (exp(‘vb’)/(1+exp(‘vb’)))
nlcom meX means: ‘phat’*(1-‘phat’)* b[X]
nlcom meZ means: ‘phat’*(1-‘phat’)* b[Z]

[Diana Hechavarria]

I am working int Stata/SE 15.1 to replicate a user-contributed command published in Strategic Management Journal (SMJ) by Wiersema and Bowen (2007)- citation and link provided below. On page 690 the authors provide suggested code to compute, at each observation, the value of the marginal effect given by Equation 2 presented in their paper, its standard error, and implied z-statistic value. Summary statistics for the marginal effect and z-statistic values are computed, the marginal effect and z-statistic values are plotted as in Figure 1 of thier paper, and the marginal effect at the variable means and its associated z-statistic are computed for each model variable. I am trying to replicate this procedure for my data.
Reference
Wiersema, M. F., & Bowen, H. P. (2009). The use of limited dependent variable techniques in strategy research: Issues and methods. Strategic management journal, 30(6), 679-692. https://doi.org/10.1002/smj.758

Here is an example of my data.

* Example generated by -dataex-. To install: ssc install dataex
clear
input byte patent long ceo_dst
0   2
0   0
0   0
0  15
0   .
0   0
0   5
0 400
0   3
0   .
0   .
0   1
0   .
0   2
0   3
0   0
0   .
0   1
0   2
0   3
0   0
0   4
0   4
0   .
0   4
0   .
0   1
0   2
0   .
0   .
0   5
0   .
0   .
0   5
0   4
0   0
0 200
0   6
0   2
0   1
0   1
0   0
0   3
0   .
0   5
0   2
0   .
0   2
0   1
0   1
0   3
0 100
0   5
0   0
0   6
0   0
0   0
0   4
0   .
0   0
0   2
0   0
0   3
0   .
0   0
0  30
0   1
0   8
0   .
0   3
0   5
0   5
0   2
0   0
0   .
0   4
0   1
0   1
0   2
0   .
0   2
0   2
0   2
0   .
0   .
0   .
0   0
0   1
0   3
0 100
0   .
0   2
0   4
0   2
0   5
0   2
0   .
0   2
0   1
0   0
end

Here is the code from the Appendix of the SMJ paper.

*====================================================================*
*WIERSEMA & BOWEN SMJ Limited Dependent Variable (2007) procedures                     *
*====================================================================*

* Estimate Logit model
logit    patent ceo_dst
* Predict probability of patent, store values in variable pprob
predict pprob
* Define expression for X’s marginal effect to use in predictnl command
* Save marginal effect values in meX; standard error values in meX se
local vb b[ cons] + b[X]*X + b[Z]*Z
local phat (exp(‘vb’)/(1+exp(‘vb’)))
predictnl meX = ‘phat’*(1-‘phat’)* b[X], se(meX se)
* Compute z-statistic values and store in variable z stat
gen z stat = meX/meX se
* print summary statistics for marginal effect and z-statistic values
tabstat meX z stat, stats(mean min max)
* Graph marginal effect and z-statistic values (Figure 1)
graph twoway (scatter meX pprob) || ///
(scatter z stat pprob, yaxis(2)yline
(−1.96 1.96, axis(2)))
* Compute and save sample means of variables X and Z
egen meanX = mean(X)
egen meanZ = mean(Z)
* Determine value and significance of marginal effect at data means
local vb b[ cons] + b[X]*meanX + b[Z] *meanZ
local phat (exp(‘vb’)/(1+exp(‘vb’)))
nlcom meX means: ‘phat’*(1-‘phat’)* b[X]
nlcom meZ means: ‘phat’*(1-‘phat’)* b[Z]

However, I get the following message after I attempt to run the program.

. do "/var/folders/q3/qcf4ctpn0192x8czkl8x7fth0000gn/T//SD14010.000000"

. * Estimate Logit model
. logit   patent ceo_dst

Iteration 0:   log likelihood = -397.95179  
Iteration 1:   log likelihood = -397.92964  
Iteration 2:   log likelihood = -397.92947  
Iteration 3:   log likelihood = -397.92947  

Logistic regression                             Number of obs     =        913
                                                LR chi2(1)        =       0.04
                                                Prob > chi2       =     0.8327
Log likelihood = -397.92947                     Pseudo R2         =     0.0001

------------------------------------------------------------------------------
      patent |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     ceo_dst |   .0000492   .0002269     0.22   0.828    -.0003955    .0004939
       _cons |  -1.677191   .0912855   -18.37   0.000    -1.856107   -1.498275
------------------------------------------------------------------------------

. * Predict probability of patent, store values in variable pprob
. predict pprob
(option pr assumed; Pr(patent))
(1,131 missing values generated)

. * Define expression for X’s marginal effect to use in predictnl command
. * Save marginal effect values in meX; standard error values in meX se
. local vb b[ cons] + b[X]*X + b[Z]*Z

. local phat (exp(‘vb’)/(1+exp(‘vb’)))

. predictnl meX = ‘phat’*(1-‘phat’)* b[X], se(meX se)
may only specify one se variable
r(103);

end of do-file

r(103);

I am certain the error is in this line of code.

predictnl meX = ‘phat’*(1-‘phat’)* b[X], se(meX se)

Can anyone provide guidance how to debug?