st: STATA won't read command

["Mason, Patrick" <pmason@fsu.edu>]

I use STATA/SE 13.1 for Windows (64 bit x86-64) 

The code appended below works fine on a small hypothetical sample. I manually enter the data, then copy the code from a Microsoft Word .doc file and past the commands directly into STATA's command window. The commands execute without a problem.

I place these same commands inside a .do file. I call the do file in STATA and the commands do not work!

I get the following message.

quietly forvalues i = 1/`r(max)’ {
invalid syntax
r(198);

Is there a way to save the .do so that the forvalues command will execute?

thanks, plmason

generate meanwage = .

by region, sort: gen pid = _n 

summarize pid

quietly forvalues i = 1/`r(max)’ {
         generate include = 1 if pid != `i’ 
         egen work = mean(wage*include), by(region)
         replace meanwage = work if pid == `i’
         drop include work
} 


________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Z. Liu [zl290@cam.ac.uk]
Sent: Thursday, March 06, 2014 8:45 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: Fwd: -cmp- not concave

Dear all,

I've been trying to fit a bivariate tobit model using the user-written
command -cmp-. The model looks like this:

cmp (equation1: y1 = X1) (equation2: y2 = y1 + X2), indicators(2 2)
robust

This model doesn't work out. Stata keeps showing 'log pseudolikelihood =
0 (not concave)'. I tried to start with minimum regressors (1-2
explanatory variables) in each equation, but the problem remains. I also
tried alternative ml options such as - tech(dfp)- and -difficult- but
still can't fix it. However, the two tobit equations can be estimated
separately, although the Pseudo R2 is quite small (around 5%). As well,
the system model
can be estimated if I change the two tobit equations into linear
equations. Some descriptive statistics of the two dependent variables
are as follows:

y1: Percentiles: 1% (0), 25% (0), 50% (23.57), 99% (6127.14); mean
(365.00); SD (1186.90); Skewness (7.14); Kurtosis (71.23)

y2: Percentiles: 1% (0), 50% (0), 75% (0), 90% (78.10), 99% (1128.53);
mean (61.29); SD (401.82); Skewness (13.27); Kurtosis (217.49)

Anybody out there knows what might be the problem? Any advice or
suggestions
would be appreciated. Thanks a lot in advance.


Best Regards,


Leo


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