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Re: st: __000000 not found


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: __000000 not found
Date   Mon, 17 Dec 2012 13:37:41 +0000

No help file, no provenance.

People will (and definitely should) make their own decisions, but mine
is that I decline even to read code like this. I recommend seeking
support from the unnamed authors.

I should add that in principle __000000 could be any temporary name.

Nick

On Mon, Dec 17, 2012 at 1:17 PM, Rubil Ivica <irubil@eizg.hr> wrote:
> Yes, it's a user-written command and here's the code:
>
> // elpp, varname() weights1() weights2() file1() file2() pline()
> program elpp, rclass
> version 10.1
>         syntax, varname(string) weights1(string) weights2(string)
> file1(string) ///
>                         file2(string) PLINE(real) [graph]
>
>                 local data `varname'
>                 local wagi1 "`weights1'"
>                 local wagi2 "`weights2'"
>
>                 qui {
>
>                 tempname bal
>                 tempfile `bal'
>
>                 local year1 = substr("`file1'",5,4)
>                 local year2 = substr("`file2'",5,4)
>
>                 use "`file1'", clear
>
>                 total `wagi1'
>                 mat r1=e(b)
>                 scalar totw=r1[1,1]
>
>                 count
>                 scalar nobs_1=r(N)
>                 tempvar poor
>                 gen `poor'=0
>                 replace `poor'=1 if `data' < `pline'
>                 mean `poor' [aw=`wagi1']
>                 mat r1=e(b)
>                 scalar headcount=r1[1,1]
>                 count if `data' < `pline'
>                 scalar poor_no=r(N)
>                 keep `data' `wagi1'
>
>                 rename `data' `data'1
>                 save "`bal'", replace
>
>                 use "`file2'", clear
>                 keep `data' `wagi2'
>                 rename `data' `data'2
>                 merge using "`bal'"
>
>                 sum `data'1 [aw=`wagi1'], meanonly
>                 scalar m1=r(mean)
>                 sum `data'2 [aw=`wagi2'], meanonly
>                 scalar m2=r(mean)
>
>                 return scalar m1=m1
>                 return scalar m2=m2
>
>                 sort `data'1
>                 //tempname invF2
>
>                 cumul `data'1 [aw=`wagi1'], generate(cum_`data'1) equal
>                  invcdf cum_`data'1 [aw=`wagi2'], ref(`data'2) g(invF2)
>
>                 cumul `data'2 [aw=`wagi2'], generate(cum_`data'2) equal
>                 sort cum_`data'2
>                 gen invF2_2 = `data'2
>                 sort `data'1
>
>                 tempvar q f_watts k_watts f_fgt1_pi f_fgt1_k
> f_fgt1_k_deno f_fgt2_pi f_fgt2_k_nom f_fgt2_k_denom
>                 gen double `q' = m1/(m2-m1)*(invF2/`data'1 -1)
>
>
>                 // estimate for Watts
>
>                 gen double `f_watts'=0
>                 replace `f_watts'=`q'-1 if `data'1 < `pline'
>                 mean `f_watts' [aw=`wagi1']
>                 mat w=e(b)
>                 tempname w1 w2 w3 w4 w5 w6 w7 w8 w9
>                 scalar `w1'=w[1,1]
>                 return scalar pi_watts=`w1'
>
>                 gen double `k_watts'=0
>                 replace `k_watts'=`q' if `data'1 < `pline'
>                 mean `k_watts' [aw=`wagi1']
>                 mat w=e(b)
>                 scalar `w2'=w[1,1]
>                 return scalar kappa_watts=`w2'/(headcount)
>
>
>                 // estimate for headcount index
>
>                 kdens `data'1 [aw=`wagi1'], at(`data'1) generate(den)
> nograph
>                 local pline_ind=poor_no+1
>                 scalar den_at_pline=den[`pline_ind']
>                 return scalar pi_headcount =
> `pline'*(`q'[`pline_ind']-1)*den_at_pline
>                 return scalar kappa_headcount = `q'[`pline_ind']
>
>                 // estimate for FGT1 - normalized poverty deficit
>
>                 gen double `f_fgt1_pi' =0
>                 replace `f_fgt1_pi' = `data'1/`pline'*(`q'-1) if `data'1
> < `pline'
>                 mean `f_fgt1_pi' [aw=`wagi1']
>                 mat w=e(b)
>                 scalar `w3'=w[1,1]
>                 return scalar pi_fgt1=`w3'
>
>                 gen double `f_fgt1_k' = 0
>                 replace `f_fgt1_k' = `data'1 * `q' if `data'1 < `pline'
>                 mean `f_fgt1_k' [aw=`wagi1']
>                 mat w=e(b)
>                 scalar `w4'=w[1,1]
>
>                 gen double `f_fgt1_k_deno'=0
>                 replace `f_fgt1_k_deno' = `data'1 if `data'1 < `pline'
>                 mean `f_fgt1_k_deno' [aw=`wagi1']
>                 mat w=e(b)
>                 scalar `w5'=w[1,1]
>                 return scalar kappa_fgt1=`w4'/`w5'
>
>                 // estimate for FGT2 - squared poverty gap
>                 gen double `f_fgt2_pi' =0
>                 replace `f_fgt2_pi' =
> 2*`data'1/`pline'*(1-`data'1/`pline')*(`q'-1) if `data'1 < `pline'
>                 mean `f_fgt2_pi' [aw=`wagi1']
>                 mat w=e(b)
>                 scalar `w6'=w[1,1]
>                 return scalar pi_fgt2=`w6'
>
>                 gen double `f_fgt2_k_nom'=0
>                 replace `f_fgt2_k_nom' =
> 2*`data'1*(1-`data'1/`pline')*`q' if `data'1 < `pline'
>                 mean `f_fgt2_k_nom'
>                 mat w=e(b)
>                 scalar `w7'=w[1,1]
>
>                 gen double `f_fgt2_k_denom' = 0
>                 replace `f_fgt2_k_denom' = 2*`data'1*(1-`data'1/`pline')
> if `data'1 < `pline'
>                 mean `f_fgt2_k_denom'
>                 mat w=e(b)
>                 scalar `w8'=w[1,1]
>
>                 ratio `f_fgt2_k_nom'/`f_fgt2_k_denom' [pw=`wagi1']
>                 mat w=e(b)
>                 scalar `w9'=w[1,1]
>
>                 return scalar kappa_fgt2=`w9'
>
>                 // graph
>                 if "`graph'"=="graph" & "`savegraph'"=="" {
>                         gen qq=`q'
>                         gen bench =1
>                         gen cumpop = sum(`wagi1')/totw*100 if `data'1!=.
>                         sum `q', meanonly
>                         twoway mspline qq cumpop, legend(off)
> title("Pattern of growth") ///
>                         ytitle("Growth rates") xtitle("Cumulative
> percentage of population") ///
>                         xlabel(#11) yscale(titlegap(5))
> xscale(titlegap(5))  || line bench cumpop
>                 }
>
>
>                 if (m2/m1) <1 {
>                 noi dis
>                 noi dis as error " Warning! There was negative income
> growth during the period"
>                 noi dis as error " growth pattern curve and all
> coefficients have non-standard meaning"
>                 noi dis as error " and have been transformed, see
> Essamah and Lambert (2009), p. 8, 17)"
>
>                 return scalar pi_watts= -return(pi_watts)
>                 return scalar pi_headcount = -return(pi_headcount)
>                 return scalar pi_fgt1= -return(pi_fgt1)
>                 return scalar pi_fgt2= -return(pi_fgt2)
>                 return scalar kappa_watts=1/return(kappa_watts)
>                 return scalar kappa_headcount=1/return(kappa_headcount)
>                 return scalar kappa_fgt1=1/return(kappa_fgt1)
>                 return scalar kappa_fgt2=1/return(kappa_fgt2)
>                 }
>
>                 } //end qui
>
>
> dis _n as res "Essama-Nssah and Lambert pro-poorness indices"
> di _n as text "Mean income in period 1 = " as res return(m1)
> di as text "Mean income in period 2 = " as res return(m2)
> di _n as text "Additive index for the headcount ratio: " as res
> return(pi_headcount)
> di    as text "Additive index for the FGT(1) index     " as res
> return(pi_fgt1)
> di    as text "Additive index for the FGT(2) index     " as res
> return(pi_fgt2)
> di    as text "Additive index for the Watts index      " as res
> return(pi_watts)
>
> di _n as text "Ratio index for the headcount ratio     " as res
> return(kappa_headcount)
> di    as text "Ratio index for the FGT(1) index        " as res
> return(kappa_fgt1)
> di    as text "Ratio index for the FGT(2) index        " as res
> return(kappa_fgt2)
> di    as text "Ratio index for the Watts index         " as res
> return(kappa_watts)
>
> end // EssamaLambert
>
>
>
>
>
> --
> Ivica Rubil
> Ekonomski institut || The Institute of Economics, Zagreb
> Trg J. F. Kennedyja 7, 10 000 Zagreb, Croatia
> tel. +385-1-2362-269 || fax. +385-1-2335-165
> irubil@eizg.hr || www.eizg.hr
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
> Sent: 17. prosinac 2012 14:10
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: __000000 not found
>
> -elpp- is presumably some user-written command. You should explain
> where you got it.
>
> __000000 is the name of a temporary variable. I've not tried looking
> inside -elpp- or even finding the file -- as above, that's your job to
> explain -- but on this evidence -elpp- is not (easily) bootstrappable.
> Its use of -file*()- options seems to hint at that too.
>
> Nick
>
> On Mon, Dec 17, 2012 at 12:53 PM, Rubil Ivica <irubil@eizg.hr> wrote:
>
>> Is there anybody who used the -elpp- for estimating the Essama-Nssah &
>> Lambert pro-poor indices? The command runs well but when I try to
> obtain
>> bootstrap standard errors I get a strange error message. Here are the
>> code and what Stata returns:
>>
>>
>>
>> bootstrap pi_hc=r(pi_headcount): elpp, varname(y) pline(849) ///
>>                                  weights1(w0) weights2(w1) ///
>>                                  file1(test_alb_y0) file2(test_alb_y1)
>> (running elpp on estimation sample)
>>
>> Bootstrap replications (50)
>> ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
>> ..................................................    50
>> variable __000000 not found
>> r(111);
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