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st: Re: Re: monte carlo on panel data

From   "Joseph Coveney" <>
To   <>
Subject   st: Re: Re: monte carlo on panel data
Date   Sun, 9 Feb 2014 10:35:31 +0900

Ghazal Zulfiqar wrote:

That helped in the sense that now I dont have to manually open the "results"
file, but it still gives me the problem of just 1000 observations rather than
500,000 i.e. one for each run.


Well, yes, that's what -postfile- does:   its saves a scalar and not a column of
data.  So, when you -post- your result in each pass through the loop, it will
save only the value in the first observation.

Frankly, I don't understand what your simulation is supposed to accomplish--your
algorithm doesn't look like what I do when performing Monte Carlo simulations
involving multilevel / hierarchical / panel models.  Regardless, if you're
interested in getting the half-million predictions, here's the mechanics:
First, use -save- an empty temporary dataset to receive the column of data from
each pass through the loop.  Then, in the loop, -append- and -save , replace-
the temporary dataset so that each five hundred observations cumulates in it.
It will be a bit slow because of all of the I/O.  Try something like that below
to get your 500 000 predictions.

Joseph Coveney

drop _all
save results, emptyok

set seed 3213799
quietly {
    generate float diversity = .	
    forvalues I = 1/1000 {
        replace diversity = median(conc_diversity)+ runiform()
       regress stddev diversity asia latin_am europe africa_mideast ///
        log_gdp_capita log_gdp_capita_1 log_gdp_capita_2 ///
        pop_g_rate barro_ipol investment_rate t t_sqrd
        predict xb

        keep xb
        append using results
        save results, replace
        drop xb

use results, clear
summarize xb


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