Social Assistance Grants for Empowerment Programme 2013, Evaluation Follow-Up Survey
Uganda, 2013
Get Microdata
Reference ID
UGA_2013_SAGE-ML_v01_M
Producer(s)
Oxford Policy Management Ltd.
Metadata
Created on
Jul 21, 2016
Last modified
Jul 21, 2016
Page views
122243
Downloads
14414
- Data files
- SAGE_HHWEIGHTSV2
- districts_SCG
- districts_VFSG
- districts2010_SCG
- districts2010_VFSG
- int_community
- int_facilities1
- int_facilities2
- int_markets1
- int_markets2
- int_markets3
- int_tracking
- int_treatment_status
- sage_comids
- sage_fcsexpanded
- sage_foodsecintermed
- sage_labourintermed
- int_operational
- int_welfare_hhassets_productive
- int_welfare_hhlivestock
- int_welfare_memdata
- int_welfare_hh
- int_cohesion_dec1
- int_cohesion_dec2
- int_cohesion_dec3
- int_cohesion_empow
- int_consexp
- int_demographics_hh
- int_demographics_mem
- int_migration
- int_migration_HH
- int_asset_index
- int_cohesion
- int_access_health
- int_access_health_hh
- int_access_school
- int_access_educ18plus
- int_access_fin
- sage_anthrointermed
- int_ben_characteristics
(NAME_1)
Data file: districts2010_SCG
Overview
Valid:
112
Invalid:
0
Type:
Discrete
Start:
328
End:
340
Width:
13
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| Abim | 1 |
0.9%
|
|
| Adjumani | 1 |
0.9%
|
|
| Agago | 1 |
0.9%
|
|
| Alebtong | 1 |
0.9%
|
|
| Amolatar | 1 |
0.9%
|
|
| Amudat | 1 |
0.9%
|
|
| Amuria | 1 |
0.9%
|
|
| Amuru | 1 |
0.9%
|
|
| Apac | 1 |
0.9%
|
|
| Arua | 1 |
0.9%
|
|
| Budaka | 1 |
0.9%
|
|
| Bududa | 1 |
0.9%
|
|
| Bugiri | 1 |
0.9%
|
|
| Buikwe | 1 |
0.9%
|
|
| Bukedea | 1 |
0.9%
|
|
| Bukomansimbi | 1 |
0.9%
|
|
| Bukwo | 1 |
0.9%
|
|
| Bulambuli | 1 |
0.9%
|
|
| Buliisa | 1 |
0.9%
|
|
| Bundibugyo | 1 |
0.9%
|
|
| Bushenyi | 1 |
0.9%
|
|
| Busia | 1 |
0.9%
|
|
| Butaleja | 1 |
0.9%
|
|
| Butambala | 1 |
0.9%
|
|
| Buvuma | 1 |
0.9%
|
|
| Buyende | 1 |
0.9%
|
|
| Dokolo | 1 |
0.9%
|
|
| Gomba | 1 |
0.9%
|
|
| Gulu | 1 |
0.9%
|
|
| Hoima | 1 |
0.9%
|
|
| Ibanda | 1 |
0.9%
|
|
| Iganga | 1 |
0.9%
|
|
| Isingiro | 1 |
0.9%
|
|
| Jinja | 1 |
0.9%
|
|
| Kaabong | 1 |
0.9%
|
|
| Kabale | 1 |
0.9%
|
|
| Kabarole | 1 |
0.9%
|
|
| Kaberamaido | 1 |
0.9%
|
|
| Kalangala | 1 |
0.9%
|
|
| Kaliro | 1 |
0.9%
|
|
| Kalungu | 1 |
0.9%
|
|
| Kampala | 1 |
0.9%
|
|
| Kamuli | 1 |
0.9%
|
|
| Kamwenge | 1 |
0.9%
|
|
| Kanungu | 1 |
0.9%
|
|
| Kapchorwa | 1 |
0.9%
|
|
| Kasese | 1 |
0.9%
|
|
| Katakwi | 1 |
0.9%
|
|
| Katerere | 1 |
0.9%
|
|
| Kayunga | 1 |
0.9%
|
|
| Kibaale | 1 |
0.9%
|
|
| Kibingo | 1 |
0.9%
|
|
| Kiboga | 1 |
0.9%
|
|
| Kibuku | 1 |
0.9%
|
|
| Kiruhura | 1 |
0.9%
|
|
| Kiryandongo | 1 |
0.9%
|
|
| Kisoro | 1 |
0.9%
|
|
| Kitgum | 1 |
0.9%
|
|
| Koboko | 1 |
0.9%
|
|
| Kole | 1 |
0.9%
|
|
| Kotido | 1 |
0.9%
|
|
| Kumi | 1 |
0.9%
|
|
| Kween | 1 |
0.9%
|
|
| Kyankwanzi | 1 |
0.9%
|
|
| Kyegegwa | 1 |
0.9%
|
|
| Kyenjojo | 1 |
0.9%
|
|
| Lamwo | 1 |
0.9%
|
|
| Lira | 1 |
0.9%
|
|
| Luuka | 1 |
0.9%
|
|
| Luwero | 1 |
0.9%
|
|
| Lwengo | 1 |
0.9%
|
|
| Lyantonde | 1 |
0.9%
|
|
| Manafwa | 1 |
0.9%
|
|
| Maracha | 1 |
0.9%
|
|
| Masaka | 1 |
0.9%
|
|
| Masindi | 1 |
0.9%
|
|
| Mayuge | 1 |
0.9%
|
|
| Mbale | 1 |
0.9%
|
|
| Mbarara | 1 |
0.9%
|
|
| Mitooma | 1 |
0.9%
|
|
| Mityana | 1 |
0.9%
|
|
| Moroto | 1 |
0.9%
|
|
| Moyo | 1 |
0.9%
|
|
| Mpigi | 1 |
0.9%
|
|
| Mubende | 1 |
0.9%
|
|
| Mukono | 1 |
0.9%
|
|
| Nakapiripirit | 1 |
0.9%
|
|
| Nakaseke | 1 |
0.9%
|
|
| Nakasongola | 1 |
0.9%
|
|
| Namiyango | 1 |
0.9%
|
|
| Namutumba | 1 |
0.9%
|
|
| Napak | 1 |
0.9%
|
|
| Nebbi | 1 |
0.9%
|
|
| Ngora | 1 |
0.9%
|
|
| Nsiika | 1 |
0.9%
|
|
| Ntoroko | 1 |
0.9%
|
|
| Ntungamo | 1 |
0.9%
|
|
| Nwoya | 1 |
0.9%
|
|
| Otuke | 1 |
0.9%
|
|
| Oyam | 1 |
0.9%
|
|
| Pader | 1 |
0.9%
|
|
| Pallisa | 1 |
0.9%
|
|
| Rakai | 1 |
0.9%
|
|
| Rukungiri | 1 |
0.9%
|
|
| Serere | 1 |
0.9%
|
|
| Sironko | 1 |
0.9%
|
|
| Soroti | 1 |
0.9%
|
|
| Ssembabule | 1 |
0.9%
|
|
| Tororo | 1 |
0.9%
|
|
| Wakiso | 1 |
0.9%
|
|
| Yumbe | 1 |
0.9%
|
|
| Zombo | 1 |
0.9%
|
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.