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* [01] Update code for Pref 1108
  * July 2021 Update
  * Anchor Year 2017
  * Pref 1108

* [011] updating data in folder 011

* [04] updating do-files and markdown files in 04 folder

* [02] updating .do files in 022 programs

* [03] updating do-files in folder 032

* [05]  updated files in 052
  * Updated files in 052  
  * Revised Excel Template

* [DOC] Update Metadata Pref 1108

Co-authored-by: Maryam Akmal <[email protected]>
Co-authored-by: yining-w <[email protected]>
Co-authored-by: Alison Gilberto <[email protected]>
Co-authored-by: Ahmed Raza <[email protected]>
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@jpazvd @maryam-akmal
@yining-w @aglbts @ARAZA13
5 people authored Apr 23, 2022
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32 changes: 16 additions & 16 deletions 00_documentation/002_repo_structure/0022_dataset_tables/enrollment.md
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Expand Up @@ -25,21 +25,21 @@ traitvars: enrollment_source enrollment_definition year_enrollment
. codebook, compact
Variable Obs Unique Mean Min Max Label
---------------------------------------------------------------------------------------------------------------------------------------
countrycode 6293 217 . . . WB country code (3 letters)
year 6293 29 2004 1990 2018 Year
en~dated_all 5771 2908 87.21567 19.10539 100 Validated % of children enrolled in school (using closest year, both genders)
enr~dated_fe 5348 2742 86.29536 15.50506 100 Validated % of children enrolled in school (using closest year, female only)
enr~dated_ma 5348 2743 87.94001 22.14 100.4548 Validated % of children enrolled in school (using closest year, male only)
e~dated_flag 6293 2 .194184 0 1 Flag for enrollment by gender filled up from aggregate (>=98.5%)
en~lated_all 5771 3755 87.24924 19.10539 100 Validated % of children enrolled in school (using interpolation, both genders)
enr~lated_fe 4739 2857 87.20877 15.50506 100 Validated % of children enrolled in school (using interpolation, female only)
enr~lated_ma 4739 2858 88.61073 22.14 100.4548 Validated % of children enrolled in school (using interpolation, male only)
e~lated_flag 6293 2 .1978389 0 1 Flag for enrollment by gender filled up from aggregate (>=98.5%)
enrollmen~ce 6293 4 . . . The source used for this enrollment value
enrollment~n 6293 6 . . . The definition used for this enrollment value
year_enrol~t 5771 29 2005.041 1990 2018 The year that the enrollment value is from
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Variable Obs Unique Mean Min Max Label
-----------------------------------------------------------------------------------------------------------------------
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,...
enr~dated_fe 5220 2565 86.06985 15.47124 100 Validated % of children enrolled in school (using closest year,...
enr~dated_ma 5224 2567 87.75847 22.7423 100 Validated % of children enrolled in school (using closest year,...
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...
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...
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
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~~~~
43 changes: 23 additions & 20 deletions 00_documentation/002_repo_structure/0022_dataset_tables/population.md
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Expand Up @@ -13,35 +13,38 @@ sources: World Bank staff estimates using the World Bank's total population
~~~~


About the **15 variables** in this dataset:
About the **18 variables** in this dataset:

~~~~
The variables belong to the following variable classifications:
idvars valuevars traitvars
idvars: countrycode year_population
valuevars: population_fe_10 population_fe_primary population_fe_9plus population_ma_10 population_ma_primary population_ma_9plus population_all_10 population_all_primary population_all_9plus population_fe_1014 population_ma_1014 population_all_1014 population_source
valuevars: population_fe_10 population_fe_0516 population_fe_primary population_fe_9plus population_ma_10 population_ma_0516 population_ma_primary population_ma_9plus population_all_10 population_all_0516 population_all_primary population_all_9plus population_fe_1014 population_ma_1014 population_all_1014 population_source
traitvars: population_source
. codebook, compact
Variable Obs Unique Mean Min Max Label
---------------------------------------------------------------------------------------------------------------------------------------
countrycode 13237 217 . . . WB country code (3 letters)
year_popul~n 13237 61 2020 1990 2050 Year of population
populat~e_10 11795 6667 320676.7 479 1.33e+07 Female population aged 10 (WB API)
po~e_primary 10514 7901 2282059 3477 7.53e+07 Female population primary age, country specific (WB API)
popu~e_9plus 11722 8056 1192931 967 5.14e+07 Female population aged 9 to end of primary, country specific (WB API)
populat~a_10 11795 6671 339959 492 1.42e+07 Male population aged 10 (WB API)
po~a_primary 10514 7939 2419477 3858 8.08e+07 Male population primary age, country specific (WB API)
popu~a_9plus 11722 8043 1259789 1007 5.52e+07 Male population aged 9 to end of primary, country specific (WB API)
populat~l_10 11795 7305 660635.7 971 2.75e+07 Total population aged 10 (WB API)
po~l_primary 10514 8655 4701535 7335 1.56e+08 Total population primary age, country specific (WB API)
popu~l_9plus 11722 8815 2452720 1974 1.07e+08 Total population aged 9 to end of primary, country specific (WB API)
popul~e_1014 11792 8026 1582075 2300 6.21e+07 Female population between ages 10 to 14 (WB API)
popul~a_1014 11792 8055 1676621 2300 6.72e+07 Male population between ages 10 to 14 (WB API)
popul~l_1014 11792 8758 3258696 4600 1.29e+08 Total population between ages 10 to 14 (WB API)
population~e 13237 1 . . . The source used for population variables
---------------------------------------------------------------------------------------------------------------------------------------
Variable Obs Unique Mean Min Max Label
-----------------------------------------------------------------------------------------------------------------------
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)
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)
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 (W...
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 (...
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
-----------------------------------------------------------------------------------------------------------------------
~~~~
46 changes: 23 additions & 23 deletions 00_documentation/002_repo_structure/0022_dataset_tables/proficiency.md
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Expand Up @@ -26,28 +26,28 @@ traitvars: min_proficiency_threshold source_assessment surveyid
. codebook, compact
Variable Obs Unique Mean Min Max Label
---------------------------------------------------------------------------------------------------------------------------------------
countrycode 697 146 . . . WB country code (3 letters)
year 697 20 2009.898 1996 2017 Year of assessment
idgrade 697 4 4.308465 3 6 Grade ID
test 697 7 . . . Assessment
nla_code 697 22 . . . Reference code for NLA in markdown documentation
subject 697 3 . . . Subject
nonprof_all 697 697 30.44595 .2252221 99.89659 % pupils below minimum proficiency (all)
se_nonprof~l 559 559 1.05663 .1218972 3.419903 SE of pupils below minimum proficiency (all)
nonprof_ma 561 561 25.08579 .1586974 97.96137 % pupils below minimum proficiency (ma)
se_nonprof~a 559 559 1.297817 .1287481 3.848194 SE of pupils below minimum proficiency (ma)
nonprof_fe 561 561 22.18714 .1284599 97.83222 % pupils below minimum proficiency (fe)
se_nonprof~e 559 559 1.245255 .1141958 4.098772 SE of pupils below minimum proficiency (fe)
fgt1_all 559 559 .1708391 .0308948 .7537994 Avg gap to minimum proficiency (all, FGT1)
fgt1_fe 559 559 .1641004 .0257019 .7643428 Avg gap to minimum proficiency (fe, FGT1)
fgt1_ma 559 559 .1757896 .0298228 .7457443 Avg gap to minimum proficiency (ma, FGT1)
fgt2_all 559 559 .0610742 .001687 .6159182 Avg gap squared to minimum proficiency (all, FGT2)
fgt2_fe 559 559 .0572421 .0011683 .6308874 Avg gap squared to minimum proficiency (fe, FGT2)
fgt2_ma 559 559 .0639653 .0017091 .6044815 Avg gap squared to minimum proficiency (ma, FGT2)
min_profic~d 694 18 . . . Minimum Proficiency Threshold (assessment-specific)
source_ass~t 697 3 . . . Source of assessment data
surveyid 697 503 . . . SurveyID (countrycode_year_assessment)
---------------------------------------------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------------------------
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
test 831 8 . . . Assessment
nla_code 831 22 . . . Reference code for NLA in markdown documentation
subject 831 3 . . . Subject
nonprof_all 831 831 29.61033 .2252197 99.89659 % pupils below minimum proficiency (all)
se_nonprof~l 693 693 1.100099 .1218972 4.659985 SE of pupils below minimum proficiency (all)
nonprof_ma 696 696 25.37036 .1586986 97.97008 % pupils below minimum proficiency (ma)
se_nonprof~a 693 693 1.344615 .1287481 5.034541 SE of pupils below minimum proficiency (ma)
nonprof_fe 696 696 22.64117 .1284603 97.83222 % pupils below minimum proficiency (fe)
se_nonprof~e 693 693 1.303262 .1141958 6.059458 SE of pupils below minimum proficiency (fe)
fgt1_all 693 693 .135403 .0308948 .5614824 Avg gap to minimum proficiency (all, FGT1)
fgt1_fe 693 693 .1293705 .0257019 .5376112 Avg gap to minimum proficiency (fe, FGT1)
fgt1_ma 693 693 .1398457 .0298228 .5797679 Avg gap to minimum proficiency (ma, FGT1)
fgt2_all 693 693 .0364274 .001687 .390271 Avg gap squared to minimum proficiency (all, FGT2)
fgt2_fe 693 693 .0333626 .0011683 .3641997 Avg gap squared to minimum proficiency (fe, FGT2)
fgt2_ma 693 693 .0387286 .0017091 .4102417 Avg gap squared to minimum proficiency (ma, FGT2)
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)
-----------------------------------------------------------------------------------------------------------------------
~~~~
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