Hi dear statalist users,
I have been in vacation but I work anyway.
Do you remember my problem?
I have a households survey and population proyections.
All the weights are wrong.
Some of my varriables are:
anio correlativ dpto secc ccz segm mes
estrato pesoan pesosem pesotri nper e1 e2 e3
e4 e5 e5_1 e5_2 e5_3 e5_4 e5_5
e5_6_1 e5_6_2 e6 e6_1_1 e6_1_2 e6_1_3 e7 e8_1 e8_2 e8_3 e8_4_1 e8_1_1 e8_1_2 e8_1_3 e9 e10 e11_1 e11_2 e11_3 e11_4 e11_4_1 e11_5 e11_6 e12_2 e13 e14 pobpcoac f1_1 f1_2 f2 f3 f4 f5_2 f6_2 f7 f8 f9_1 f10_1 f10_2 f11_2 f12_2 f13 f14 f15_1 f16_1 f16_2 f17_1 f17_2 f18 f19 f20 f21 f22 f23 f24 f25 f26 f27 f28 f29 f30 f31 f32 f33 f34 f35 f36 f37_2 f38_2 f39 f40_1 f40_2 f40_3 f40_4 f40_5 g1_1_1 g1_1_2 g1_1_3 g1_1_4 g1_1_5 g1_1_6 g1_1_7 g1_1_8 g1_1_9 g1_2_1 g1_2_2 g1_2_3 g1_2_4 g1_2_5 g1_2_6 g1_2_7 g1_2_8 g1_2_9 g2_1 g2_2 g2_3 g3_1 g3_2 g3_3 g3_4 g3_5 g3_6 g3_7 g3_8 g3_9_1 g3_9_2 g4_1_1 g4_1_2 g4_2_1 g4_2_2 g4_2_3 g4_2_4 g4_2_5 g4_2_6 g5_1 g5_2 g5_3 g5_4 g5_5 g5_6 g5_7 g5_8 g5_9 g5_10 g5_11 pt1 pt2 pt4 noregp norego subempl monto1 monto2 locech nomlocech barrio nombre ht11 ht13 ht19 _merge pond nuev_pond smn m65 ad_may adulto_may may60 may65 may70 ing_pc ipc ing_pc_def quintil quintil2 equiv n ing_equiv ing_equiv_pc quintil_eq quintil_eq2 par1 par2 par3 par4 par5 par6 par7 par8 par9 p!
ar10 par11 espos hijo hijot padsue nieto otfam yerno nopar tiphog cba02 indi02 lpine2 pobine02 lp96 cba96 pobine indi e_jefe eda_jefe ed_18_24 ed_25_29 ed_30_39 ed_40_49 ed_50_59 ed_más60 edad_jefe c_lab cond_lab asign asig_fam mayor60 mayor65 mayor70 s_desemp seg_desemp transf transf_9 transf_1 transf_2 transf_3 transf_4 transf_5 transf_6 transf_7 transf_8 monto_transf jubilado pension jubiladoh pensionh asigna asignasu affam benef benefsu benefh men15 men15h men15sum men18 menor18 menor18h men6 men6h men6sum men7 men7h men7sum asiprim asipsum asites asisec asisecsu trabjov actjov trabjh actjh formal formalh ocupfor ocupformh dessp dessph despp despph jubi95 jubi95h jubi jubih prodru prodruh ylab ylabh ylabf3 ylabf3h fran10 fran3 fran6 at16697 at16697h at16697s ben behipoh behipos elegible elegible2 eleg1 eleg2 eleg1se eleg2se ben2 behipoh2 eleg22 ypc_sv agegp n_h_0 n_h_1 n_h_5 n_h_10 n_h_15 n_h_20 n_h_25 n_h_30 n_h_35 n_h_40 n_h_45 n_h_50 n_h_55 n_h_60 n_h_65 n_h_70 n_h_7!
5 n_h_80 n_h_85 n_h_90 n_h_95 h_dpto h_1_p corrector vaa
2005 1 1 1 1 1 4 3 39 79 158 1 2 58 1 3 0 2 2 2 2 1 2 0 0 3 0 0 1 0 0 0 0 4 0 0 0 1 0 6 6 0 0 0 2 638 2 1 2 1 0 0 0 2 3460 9199 1 4 1 1 1 1310 5239 6 1 1 2 2 40 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 1 4000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 7975 4974.93 7975 0 1 0 974.93 0 0101 MONTEVIDEO 01 CIUDAD
VIE 12175 2300 2 3 1.067 41.613 1363 0 0 0 0 0 0 6087.5 .992 6038.8 4 4 1 1.7 7161.765 7104.47 4 4 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 1126.07 0 3333.167 0 4176.69 1332.3 0 0 58 58 0 0 0 0 1 0 5 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 8750 8750 8750 8750 1 0 0 1 1 2 0 0 0 0 0 0 0 0 0 0 1 0 4937.5 55 165 647 950 1100 1107 1090 963 880 797 841 835 772 691 644 561 502 441 271 83 25 7 13372 643547 25290
Weights in microsurvey are wrong, It must be corrected by new one
using population proyections.
I do the next but I have problems using a loop.
*Make a categorical variable for group of age:
egen agegp=cut(e2), at
(0,1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100)
*Put labels
label define agegp 0 "0" 1 "1-4" 5 "5-9" 10 "10-14" 15 "15-19" 20
"20-25" 25 "25-29" 30 "30-34" 35 "35-39" 40 "40-44" 45 "45-49" 50
"50-54" 55 "55-59" 60 "60-64" 65 "65-69" 70 "70-74" 75 "75-79" 80
"80-84" 85 "85-89" 90 "90-94" 95 "95+"
*Compute number of men by group of age and departamento (means state in English)
egen n_h_0=total(agegp==0 & e1==1), by (dpto)
egen n_h_1=total(agegp==1 & e1==1), by (dpto)
egen n_h_5=total(agegp==5 & e1==1), by (dpto)
egen n_h_10=total(agegp==10 & e1==1), by (dpto)
egen n_h_15=total(agegp==15 & e1==1), by (dpto)
egen n_h_20=total(agegp==20 & e1==1), by (dpto)
egen n_h_25=total(agegp==25 & e1==1), by (dpto)
egen n_h_30=total(agegp==30 & e1==1), by (dpto)
egen n_h_35=total(agegp==35 & e1==1), by (dpto)
egen n_h_40=total(agegp==40 & e1==1), by (dpto)
egen n_h_45=total(agegp==45 & e1==1), by (dpto)
egen n_h_50=total(agegp==50 & e1==1), by (dpto)
egen n_h_55=total(agegp==55 & e1==1), by (dpto)
egen n_h_60=total(agegp==60 & e1==1), by (dpto)
egen n_h_65=total(agegp==65 & e1==1), by (dpto)
egen n_h_70=total(agegp==70 & e1==1), by (dpto)
egen n_h_75=total(agegp==75 & e1==1), by (dpto)
egen n_h_80=total(agegp==80 & e1==1), by (dpto)
egen n_h_85=total(agegp==85 & e1==1), by (dpto)
egen n_h_90=total(agegp==90 & e1==1), by (dpto)
egen n_h_95=total(agegp==95 & e1==1), by (dpto)
*Computo total men by departemanto
egen h_dpto=rowtotal(n_h_*)
*Repit for women
egen n_m_0= total(agegp==0 & e1=!1), by (dpto)
…………………………………………………..
egen n_m_95=total(agegp==95 & e1=!1), by (dpto)
egen m_dpto=rowtotal(n_m_*)
*Make a constan equals men's proyection by departamento
gen h_1_p=643547
gen h_2_p=
…………………..
gen h_19_p=
*Repet for women
gen m_1_p=
gen m_2_p=
…………………..
gen m_19_p=
*Compute annual men expansor by departemanto
gen corrector=h_dpto/(h_1_p*n_h_0) if e1==1 & agegp==0
replace corrector=h_dpto/(h_1_p*n_h_1) if e1==1 & agegp==1
replace corrector=h_dpto/(h_1_p*n_h_5) if e1==1 & agegp==5
replace corrector=h_dpto/(h_1_p*n_h_10) if e1==1 & agegp==10
replace corrector=h_dpto/(h_1_p*n_h_15) if e1==1 & agegp==15
replace corrector=h_dpto/(h_1_p*n_h_20) if e1==1& agegp==20
replace corrector=h_dpto/(h_1_p*n_h_25) if e1==1 & agegp==25
replace corrector=h_dpto/(h_1_p*n_h_30) if e1==1& agegp==30
replace corrector=h_dpto/(h_1_p*n_h_35) if e1==1 & agegp==35
replace corrector=h_dpto/(h_1_p*n_h_40) if e1==1& agegp==40
replace corrector=h_dpto/(h_1_p*n_h_45) if e1==1 & agegp==45
replace corrector=h_dpto/(h_1_p*n_h_50) if e1==1& agegp==50
replace corrector=h_dpto/(h_1_p*n_h_55) if e1==1 & agegp==55
replace corrector=h_dpto/(h_1_p*n_h_60) if e1==1& agegp==60
replace corrector=h_dpto/(h_1_p*n_h_65) if e1==1 & agegp==65
replace corrector=h_dpto/(h_1_p*n_h_70) if e1==1& agegp==70
replace corrector=h_dpto/(h_1_p*n_h_75) if e1==1 & agegp==75
replace corrector=h_dpto/(h_1_p*n_h_80) if e1==1& agegp==80
replace corrector=h_dpto/(h_1_p*n_h_85) if e1==1 & agegp==85
replace corrector=h_dpto/(h_1_p*n_h_90) if e1==1& agegp==90
replace corrector=h_dpto/(h_1_p*n_h_95) if e1==1 & agegp==95
*Repet for women
replace corrector=h_dpto/(h_1_p*n_h_0) if e1==1
Bye,
Sebastian.
*
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* http://www.stata.com/support/faqs/res/findit.html
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