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Merge pull request #8 from worldbank/develop
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Develop
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@jpazvd
jpazvd authored Apr 25, 2022
2 parents 200896d + 9b1c7f0 commit 67e26f4
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17 changes: 17 additions & 0 deletions 00_documentation/002_repo_structure/0022_dataset_tables/enrollment.md
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Expand Up @@ -26,6 +26,18 @@ traitvars: enrollment_source enrollment_definition year_enrollment
. codebook, compact
Variable Obs Unique Mean Min Max Label
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
countrycode 6727 217 . . . WB country code (3 letters)
year 6727 31 2005 1990 2020 Year
en~dated_all 6231 2964 87.78292 19.18834 100 Validated % of children enrolled in school (using closest year, both genders)
enr~dated_fe 5220 2565 86.06985 15.47124 100 Validated % of children enrolled in school (using closest year, female only)
enr~dated_ma 5224 2567 87.75847 22.7423 100 Validated % of children enrolled in school (using closest year, male only)
e~dated_flag 6727 2 .2332392 0 1 Flag for enrollment by gender filled up from aggregate (>=98.5%)
en~lated_all 6231 3967 87.81469 19.18834 100 Validated % of children enrolled in school (using interpolation, both genders)
enr~lated_fe 4614 2766 87.00985 15.47124 100 Validated % of children enrolled in school (using interpolation, female only)
enr~lated_ma 4618 2769 88.48919 22.7423 100 Validated % of children enrolled in school (using interpolation, male only)
=======
-----------------------------------------------------------------------------------------------------------------------
countrycode 6727 217 . . . WB country code (3 letters)
year 6727 31 2005 1990 2020 Year
Expand All @@ -36,10 +48,15 @@ e~dated_flag 6727 2 .2332392 0 1 Flag for enrollment by gend
en~lated_all 6231 3967 87.81469 19.18834 100 Validated % of children enrolled in school (using interpolation...
enr~lated_fe 4614 2766 87.00985 15.47124 100 Validated % of children enrolled in school (using interpolation...
enr~lated_ma 4618 2769 88.48919 22.7423 100 Validated % of children enrolled in school (using interpolation...
>>>>>>> develop
e~lated_flag 6727 2 .2357663 0 1 Flag for enrollment by gender filled up from aggregate (>=98.5%)
enrollmen~ce 6727 4 . . . The source used for this enrollment value
enrollment~n 6727 6 . . . The definition used for this enrollment value
year_enrol~t 6231 30 2005.948 1990 2019 The year that the enrollment value is from
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
~~~~
20 changes: 20 additions & 0 deletions 00_documentation/002_repo_structure/0022_dataset_tables/population.md
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Expand Up @@ -26,12 +26,27 @@ traitvars: population_source
. codebook, compact
Variable Obs Unique Mean Min Max Label
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
countrycode 13237 217 . . . WB country code (3 letters)
year_popul~n 13237 61 2020 1990 2050 Year of population
populat~e_10 11795 6832 320676.8 479 1.33e+07 Female population aged 10 (WB API)
popul~e_0516 11795 9464 3837089 5500 1.43e+08 Female population aged 05-16 (WB API)
po~e_primary 10941 8257 2210692 3477 7.53e+07 Female population primary age, country specific (WB API)
<<<<<<< HEAD
popu~e_9plus 11413 8005 1198257 967 5.14e+07 Female population aged 9 to end of primary, country specific (WB API)
populat~a_10 11795 6836 339959 492 1.42e+07 Male population aged 10 (WB API)
popul~a_0516 11795 9528 4067005 5800 1.60e+08 Male population aged 05-16 (WB API)
po~a_primary 10941 8286 2343564 3858 8.08e+07 Male population primary age, country specific (WB API)
popu~a_9plus 11413 8004 1265978 1007 5.52e+07 Male population aged 9 to end of primary, country specific (WB API)
populat~l_10 11795 7468 660635.8 971 2.75e+07 Total population aged 10 (WB API)
popul~l_0516 11795 10279 7904094 11300 3.04e+08 Total population aged 05-16 (WB API)
po~l_primary 10941 9035 4554256 7335 1.56e+08 Total population primary age, country specific (WB API)
popu~l_9plus 11413 8713 2464235 1974 1.07e+08 Total population aged 9 to end of primary, country specific (WB API)
=======
popu~e_9plus 11413 8005 1198257 967 5.14e+07 Female population aged 9 to end of primary, country specific ...
populat~a_10 11795 6836 339959 492 1.42e+07 Male population aged 10 (WB API)
popul~a_0516 11795 9528 4067005 5800 1.60e+08 Male population aged 05-16 (WB API)
Expand All @@ -41,10 +56,15 @@ populat~l_10 11795 7468 660635.8 971 2.75e+07 Total population aged 10
popul~l_0516 11795 10279 7904094 11300 3.04e+08 Total population aged 05-16 (WB API)
po~l_primary 10941 9035 4554256 7335 1.56e+08 Total population primary age, country specific (WB API)
popu~l_9plus 11413 8713 2464235 1974 1.07e+08 Total population aged 9 to end of primary, country specific (...
>>>>>>> develop
popul~e_1014 11792 8157 1582125 2300 6.21e+07 Female population between ages 10 to 14 (WB API)
popul~a_1014 11792 8190 1676713 2300 6.72e+07 Male population between ages 10 to 14 (WB API)
popul~l_1014 11792 8890 3258838 4600 1.29e+08 Total population between ages 10 to 14 (WB API)
population~e 13237 1 . . . The source used for population variables
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
~~~~
8 changes: 8 additions & 0 deletions 00_documentation/002_repo_structure/0022_dataset_tables/proficiency.md
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Expand Up @@ -26,7 +26,11 @@ traitvars: min_proficiency_threshold source_assessment surveyid
. codebook, compact
Variable Obs Unique Mean Min Max Label
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
countrycode 831 153 . . . WB country code (3 letters)
year 831 21 2011.366 1996 2019 Year of assessment
idgrade 831 4 4.309266 3 6 Grade ID
Expand All @@ -48,6 +52,10 @@ fgt2_ma 693 693 .0387286 .0017091 .4102417 Avg gap squared to minim
min_profic~d 822 18 . . . Minimum Proficiency Threshold (assessment-specific)
source_ass~t 831 3 . . . Source of assessment data
surveyid 831 580 . . . SurveyID (countrycode_year_assessment)
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
~~~~
31 changes: 31 additions & 0 deletions 00_documentation/002_repo_structure/0022_dataset_tables/rawfull.md
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Expand Up @@ -26,7 +26,11 @@ traitvars: year_enrollment year_population source_assessment enrollment_source p
. codebook, compact
Variable Obs Unique Mean Min Max Label
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
countrycode 1042 217 . . . WB country code (3 letters)
year_asses~t 1042 21 2012.495 1996 2019 Year of assessment
idgrade 1042 5 -204.6315 -999 6 Grade ID
Expand All @@ -45,6 +49,28 @@ fgt1_ma 687 687 .1403113 .0298228 .5797679 Avg gap to minimum pro
fgt2_all 687 687 .0366347 .001687 .390271 Avg gap squared to minimum proficiency (all, FGT2)
fgt2_fe 687 687 .0335486 .0011683 .3641997 Avg gap squared to minimum proficiency (fe, FGT2)
fgt2_ma 687 687 .0389487 .0017091 .4102417 Avg gap squared to minimum proficiency (ma, FGT2)
<<<<<<< HEAD
en~dated_all 1022 584 92.44464 23.54786 100 Validated % of children enrolled in school (using closest year, both genders)
enr~dated_fe 862 486 91.9935 16.75778 100 Validated % of children enrolled in school (using closest year, female only)
enr~dated_ma 864 488 92.50133 30.29106 100 Validated % of children enrolled in school (using closest year, male only)
e~dated_flag 1042 2 .2303263 0 1 Flag for enrollment by gender filled up from aggregate (>=98.5%)
en~lated_all 1022 622 92.4566 23.54786 100 Validated % of children enrolled in school (using interpolation, both gend...
enr~lated_fe 792 463 92.7003 16.75778 100 Validated % of children enrolled in school (using interpolation, female only)
enr~lated_ma 794 464 93.03792 30.29106 100 Validated % of children enrolled in school (using interpolation, male only)
e~lated_flag 1042 2 .2447217 0 1 Flag for enrollment by gender filled up from aggregate (>=98.5%)
populat~e_10 1016 193 293790.7 672 1.21e+07 Female population aged 10 (WB API)
popul~e_0516 1016 193 3507837 8061 1.43e+08 Female population aged 05-16 (WB API)
po~e_primary 970 179 2013042 4379 7.18e+07 Female population primary age, country specific (WB API)
popu~e_9plus 990 186 1085839 1356 3.63e+07 Female population aged 9 to end of primary, country specific (WB API)
populat~a_10 1016 193 310473.2 687 1.34e+07 Male population aged 10 (WB API)
popul~a_0516 1016 193 3706547 8324 1.59e+08 Male population aged 05-16 (WB API)
po~a_primary 970 179 2125880 4534 7.94e+07 Male population primary age, country specific (WB API)
popu~a_9plus 990 186 1143901 1400 4.03e+07 Male population aged 9 to end of primary, country specific (WB API)
populat~l_10 1016 193 604263.9 1359 2.55e+07 Total population aged 10 (WB API)
popul~l_0516 1016 193 7214384 16385 3.02e+08 Total population aged 05-16 (WB API)
po~l_primary 970 179 4138922 8913 1.51e+08 Total population primary age, country specific (WB API)
popu~l_9plus 990 186 2229740 2756 7.65e+07 Total population aged 9 to end of primary, country specific (WB API)
=======
en~dated_all 1022 584 92.44464 23.54786 100 Validated % of children enrolled in school (using closest ...
enr~dated_fe 862 486 91.9935 16.75778 100 Validated % of children enrolled in school (using closest ...
enr~dated_ma 864 488 92.50133 30.29106 100 Validated % of children enrolled in school (using closest ...
Expand All @@ -65,6 +91,7 @@ populat~l_10 1016 193 604263.9 1359 2.55e+07 Total population aged
popul~l_0516 1016 193 7214384 16385 3.02e+08 Total population aged 05-16 (WB API)
po~l_primary 970 179 4138922 8913 1.51e+08 Total population primary age, country specific (WB API)
popu~l_9plus 990 186 2229740 2756 7.65e+07 Total population aged 9 to end of primary, country specifi...
>>>>>>> develop
popul~e_1014 1016 193 1432652 3328 6.01e+07 Female population between ages 10 to 14 (WB API)
popul~a_1014 1016 193 1514505 3467 6.72e+07 Male population between ages 10 to 14 (WB API)
popul~l_1014 1016 193 2947158 6795 1.27e+08 Total population between ages 10 to 14 (WB API)
Expand All @@ -86,6 +113,10 @@ incomeleve~e 1042 4 . . . Income Level Name
lendingtype 1042 4 . . . Lending Type Code
lendingty~me 1042 4 . . . Lending Type Name
cmu 774 48 . . . WB Country Management Unit
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
~~~~
26 changes: 26 additions & 0 deletions 00_documentation/002_repo_structure/0022_dataset_tables/rawlatest.md
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Expand Up @@ -13,20 +13,32 @@ sources: All population, enrollment and proficiency sources combined.
~~~~


<<<<<<< HEAD
About the **49 variables** in this dataset:
=======
About the **52 variables** in this dataset:
>>>>>>> develop
~~~~
The variables belong to the following variable classifications:
idvars valuevars traitvars
idvars: countrycode preference
<<<<<<< HEAD
valuevars: adj_nonprof_all adj_nonprof_fe adj_nonprof_ma nonprof_all se_nonprof_all nonprof_ma se_nonprof_ma nonprof_fe se_nonprof_fe fgt1_all fgt1_fe fgt1_ma fgt2_all fgt2_fe fgt2_ma enrollment_all enrollment_ma enrollment_fe population_2017_fe population_2017_ma population_2017_all population_source anchor_population anchor_population_w_assessment
=======
valuevars: adj_nonprof_all adj_nonprof_fe adj_nonprof_ma nonprof_all se_nonprof_all nonprof_ma se_nonprof_ma nonprof_fe se_nonprof_fe fgt1_all fgt1_fe fgt1_ma fgt2_all fgt2_fe fgt2_ma enrollment_all enrollment_ma enrollment_fe population_fe_0516 population_ma_0516 population_all_0516 population_2017_fe population_2017_ma population_2017_all population_source anchor_population anchor_population_w_assessment
>>>>>>> develop
traitvars: idgrade test nla_code subject year_assessment year_enrollment enrollment_flag enrollment_source enrollment_definition min_proficiency_threshold surveyid countryname region regionname adminregion adminregionname incomelevel incomelevelname lendingtype lendingtypename cmu preference_description lp_by_gender_is_available
. codebook, compact
Variable Obs Unique Mean Min Max Label
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
countrycode 217 217 . . . WB country code (3 letters)
preference 217 1 . . . Preference
adj_nonpro~l 121 121 40.24131 2.186121 97.71729 Learning Poverty (adjusted non-proficiency, all)
Expand All @@ -44,12 +56,18 @@ fgt1_ma 110 110 .1503822 .0448706 .5445552 Avg gap to minimum profi
fgt2_all 110 110 .0393368 .0034088 .3331398 Avg gap squared to minimum proficiency (all, FGT2)
fgt2_fe 110 110 .0356563 .0031767 .2936567 Avg gap squared to minimum proficiency (fe, FGT2)
fgt2_ma 110 110 .0419848 .0035797 .3594563 Avg gap squared to minimum proficiency (ma, FGT2)
<<<<<<< HEAD
enrollment~l 201 197 90.5746 23.54786 100 Validated % of children enrolled in school (using closest year, both genders)
enrollment~a 161 157 90.01606 30.29106 100 Validated % of children enrolled in school (using closest year, male only)
enrollmen~fe 160 156 89.272 16.75778 100 Validated % of children enrolled in school (using closest year, female only)
=======
enrollment~l 201 197 90.5746 23.54786 100 Validated % of children enrolled in school (using closest ye...
enrollment~a 161 157 90.01606 30.29106 100 Validated % of children enrolled in school (using closest ye...
enrollmen~fe 160 156 89.272 16.75778 100 Validated % of children enrolled in school (using closest ye...
popul~e_0516 193 193 3799861 8061 1.43e+08 Female population aged 05-16 (WB API)
popul~a_0516 193 193 4067900 8324 1.59e+08 Male population aged 05-16 (WB API)
popul~l_0516 193 193 7867761 16385 3.02e+08 Total population aged 05-16 (WB API)
>>>>>>> develop
populatio~fe 193 193 1553426 3328 6.01e+07 Female population between ages 10 to 14 (WB API)
population~a 193 193 1664672 3467 6.72e+07 Male population between ages 10 to 14 (WB API)
population~l 193 193 3218098 6795 1.27e+08 Total population between ages 10 to 14 (WB API)
Expand All @@ -62,7 +80,11 @@ nla_code 217 11 . . . Reference code for NLA i
subject 217 4 . . . Subject
year_asses~t 217 13 2015.857 2001 2019 Year of assessment
year_enrol~t 201 18 2013.99 1993 2018 The year that the enrollment value is from
<<<<<<< HEAD
enrollment~g 217 2 .235023 0 1 Flag for enrollment by gender filled up from aggregate (>=98.5%)
=======
enrollment~g 217 2 .235023 0 1 Flag for enrollment by gender filled up from aggregate (>=98...
>>>>>>> develop
enrollmen~ce 217 4 . . . The source used for this enrollment value
enrollment~n 217 6 . . . The definition used for this enrollment value
min_profic~d 116 10 . . . Minimum Proficiency Threshold (assessment-specific)
Expand All @@ -79,6 +101,10 @@ lendingty~me 217 4 . . . Lending Type Name
cmu 169 48 . . . WB Country Management Unit
preference~n 217 1 . . . Preference description
lp_by_gend~e 217 2 .4239631 0 1 Dummy for availibility of Learning Poverty gender disaggregated
<<<<<<< HEAD
---------------------------------------------------------------------------------------------------------------------------------------
=======
-----------------------------------------------------------------------------------------------------------------------
>>>>>>> develop
~~~~
7 changes: 6 additions & 1 deletion 05_working_paper/052_programs/0523_bmp_pisa_validation.do
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Expand Up @@ -3,6 +3,11 @@
*==============================================================================*
qui {

* Change here only if wanting to use a different preference
* than what is being passed in the global in 032_run
* But don't commit any change here (only commit in global 032_run)
local chosen_preference = $chosen_preference

*-----------------------------------------------------------------------------
local outputs "${clone}/05_working_paper/053_outputs"
local rawdata "${clone}/05_working_paper/051_rawdata"
Expand All @@ -14,7 +19,7 @@ qui {
*-----------------------------------------------------------------------------
* create and save Learning Poverty dataset

use "${clone}/01_data/013_outputs/preference1005.dta", clear
use "${clone}/01_data/013_outputs/preference`chosen_preference'.dta", clear
keep if !missing(adj_nonprof_all)
sort region countryname
local vars2keep "countrycode countryname enrollment_all nonprof_all adj_nonprof_all test year_assessment"
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