Hunger Safety Net Programme Impact Evaluation 2012, Second Follow-up Round
Kenya, 2012
Oxford Policy Management Limited
Created on
January 15, 2014
Last modified
January 15, 2014
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- Data files
- 3moves
- 3table
- 5table
- 6education
- 6health
- 6personnel
- 6table
- 7food
- 7food1
- 7other
- 7other1
- comq_linking_FU2
- comq_weights
- coversheet
- section3
- section4
- section5
- section8
- section9
- section10
- section11
- section99
- ClusterMaster
- disaggregation_data
- HHAsset
- HHAssetLivelihood
- HHBeneficiaries
- HHCHild
- HHconsData
- HHCopingStrategy
- HHData
- HHEmploymentProgramme
- HHEnterprise
- HHEnterpriseMember
- HHFoodAid
- HHFoodconsData
- HHImpact
- HHItemPurchaseDistance
- HHLivestock
- HHMember
- HHMover
- HHOpMon
- HHOtherCashTrans
- HHPreambleTracking
- HHProvidedFor
- HHSampleRecord
- HHTransfer
- HHVisit
- hh_weights_original
3.07:Migrated to where (q307name)
Data file: section3
Overview
Valid:
334
Invalid:
0
Type:
Discrete
Width:
30
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| ABEKUT | 2 |
0.6%
|
|
| ADADO | 1 |
0.3%
|
|
| ADEMATL | 1 |
0.3%
|
|
| AFMADOW | 1 |
0.3%
|
|
| AKIDINGOT | 2 |
0.6%
|
|
| ANCHORS | 1 |
0.3%
|
|
| ARDHAWA | 1 |
0.3%
|
|
| ASAWA | 1 |
0.3%
|
|
| ASHABIKO | 1 |
0.3%
|
|
| ASHABILO | 1 |
0.3%
|
|
| ASHABITO | 2 |
0.6%
|
|
| BABALOI | 2 |
0.6%
|
|
| BANGOI | 1 |
0.3%
|
|
| BANISA | 4 |
1.2%
|
|
| BARASOI | 10 |
3%
|
|
| BATALU | 1 |
0.3%
|
|
| BULUK/THOROTTE | 1 |
0.3%
|
|
| BUNA | 3 |
0.9%
|
|
| BURGABO | 1 |
0.3%
|
|
| BURMAYO | 1 |
0.3%
|
|
| BUTE | 1 |
0.3%
|
|
| DAAHANTALE | 1 |
0.3%
|
|
| DAMBAS | 1 |
0.3%
|
|
| DEF | 1 |
0.3%
|
|
| DHIDANANI | 1 |
0.3%
|
|
| DIBEDA | 1 |
0.3%
|
|
| DIIF | 3 |
0.9%
|
|
| DUNTO | 1 |
0.3%
|
|
| EIPA | 1 |
0.3%
|
|
| ELDANABA | 1 |
0.3%
|
|
| ELDAS | 2 |
0.6%
|
|
| ELDERO | 1 |
0.3%
|
|
| ELMOLE | 1 |
0.3%
|
|
| ELNURI | 1 |
0.3%
|
|
| EMOLE | 1 |
0.3%
|
|
| EMULE | 1 |
0.3%
|
|
| ETHIOPIA | 13 |
3.9%
|
|
| EWASO | 1 |
0.3%
|
|
| FILATU | 1 |
0.3%
|
|
| FILTU | 1 |
0.3%
|
|
| FLITU | 1 |
0.3%
|
|
| GALANA | 14 |
4.2%
|
|
| GODOMA | 1 |
0.3%
|
|
| GUBA | 4 |
1.2%
|
|
| GUBOUR | 1 |
0.3%
|
|
| GUNAN | 1 |
0.3%
|
|
| GUNANE | 1 |
0.3%
|
|
| GUNANEI | 1 |
0.3%
|
|
| GURAR | 1 |
0.3%
|
|
| GURAV | 1 |
0.3%
|
|
| GUWADONLE | 1 |
0.3%
|
|
| H. HILLS | 1 |
0.3%
|
|
| HADADO | 6 |
1.8%
|
|
| HAGARA DULAW | 1 |
0.3%
|
|
| HAGARSU | 1 |
0.3%
|
|
| HALOKOMA | 1 |
0.3%
|
|
| HAYSUFTU | 1 |
0.3%
|
|
| HOTE | 1 |
0.3%
|
|
| HUNGAI | 1 |
0.3%
|
|
| JULUK | 1 |
0.3%
|
|
| KAAKULIT | 1 |
0.3%
|
|
| KABRISAGER | 1 |
0.3%
|
|
| KAEKORONGOLE | 1 |
0.3%
|
|
| KAIKUNYUIK | 1 |
0.3%
|
|
| KAILONGOKOL | 1 |
0.3%
|
|
| KAKONGU | 1 |
0.3%
|
|
| KALEMORINGOU | 1 |
0.3%
|
|
| KALEMUNGOROK | 1 |
0.3%
|
|
| KALOKOL | 4 |
1.2%
|
|
| KANAODON | 1 |
0.3%
|
|
| KANGALITA | 1 |
0.3%
|
|
| KAPUTUKEI | 1 |
0.3%
|
|
| KARANDILE | 1 |
0.3%
|
|
| KARARI | 1 |
0.3%
|
|
| KARUKO | 1 |
0.3%
|
|
| KATOTE | 2 |
0.6%
|
|
| KATUMANI | 2 |
0.6%
|
|
| KENO | 1 |
0.3%
|
|
| KHOROFALTAIR | 1 |
0.3%
|
|
| KHOROFHARER | 1 |
0.3%
|
|
| KILIWEHERI | 1 |
0.3%
|
|
| KINYAU/SIRA | 1 |
0.3%
|
|
| KOBANYET | 1 |
0.3%
|
|
| KOBAYOCUB | 1 |
0.3%
|
|
| KOCHODIN | 1 |
0.3%
|
|
| KODE KODE | 1 |
0.3%
|
|
| KODEKODE | 1 |
0.3%
|
|
| KOKISELEI | 1 |
0.3%
|
|
| KOM | 6 |
1.8%
|
|
| KOME | 1 |
0.3%
|
|
| KORONDILE | 1 |
0.3%
|
|
| KOSEYE | 1 |
0.3%
|
|
| KOTARUK | 2 |
0.6%
|
|
| KOTOMARUKON | 2 |
0.6%
|
|
| KOTORUK | 1 |
0.3%
|
|
| KOYOU | 1 |
0.3%
|
|
| KULAL | 1 |
0.3%
|
|
| KWATARUK | 1 |
0.3%
|
|
| L. TURKANA | 2 |
0.6%
|
|
| L. TURKANA / BULUK | 1 |
0.3%
|
|
| LAGBOGOL | 1 |
0.3%
|
|
| LAKE TURKANA | 2 |
0.6%
|
|
| LAPUR | 8 |
2.4%
|
|
| LBARATA | 2 |
0.6%
|
|
| LBARTA | 11 |
3.3%
|
|
| LEBARTA | 2 |
0.6%
|
|
| LEHEY | 2 |
0.6%
|
|
| LOCHAKULA | 1 |
0.3%
|
|
| LOCHARAIKENY | 1 |
0.3%
|
|
| LOCHEKEI | 1 |
0.3%
|
|
| LODOSOI | 1 |
0.3%
|
|
| LOIMA | 9 |
2.7%
|
|
| LOKICHAR | 1 |
0.3%
|
|
| LOKITALA | 1 |
0.3%
|
|
| LOKITALAIKITUKO | 1 |
0.3%
|
|
| LOKITELA | 1 |
0.3%
|
|
| LOKITELAETUKO | 2 |
0.6%
|
|
| LOKORIA | 1 |
0.3%
|
|
| LOKWAMUSING | 1 |
0.3%
|
|
| LOKWANAMOR | 3 |
0.9%
|
|
| LOPETAREGAE | 3 |
0.9%
|
|
| LOPII | 1 |
0.3%
|
|
| LOPUKE | 1 |
0.3%
|
|
| LORIONOTOM | 1 |
0.3%
|
|
| LORIU | 1 |
0.3%
|
|
| LOROGUM | 1 |
0.3%
|
|
| LOROKON | 1 |
0.3%
|
|
| LOTERE | 2 |
0.6%
|
|
| LOTONGOT | 2 |
0.6%
|
|
| LUMUNYEN KOWA | 1 |
0.3%
|
|
| MACHIONE TOSI | 1 |
0.3%
|
|
| MANSA | 2 |
0.6%
|
|
| MARALAL | 1 |
0.3%
|
|
| MARLAL | 1 |
0.3%
|
|
| MATAARBA | 1 |
0.3%
|
|
| MOITE | 1 |
0.3%
|
|
| MORUAPOLON | 3 |
0.9%
|
|
| MORULEM | 1 |
0.3%
|
|
| MOYALE | 2 |
0.6%
|
|
| MUSUG | 7 |
2.1%
|
|
| MYALE | 1 |
0.3%
|
|
| NAKWAKAL | 1 |
0.3%
|
|
| NAKWAMUROO | 1 |
0.3%
|
|
| NAKWANAMORU | 1 |
0.3%
|
|
| NAKWANAMSO | 1 |
0.3%
|
|
| NAKWANAMU | 1 |
0.3%
|
|
| NAPOROTO | 2 |
0.6%
|
|
| NAPUSMORU | 1 |
0.3%
|
|
| NARO | 1 |
0.3%
|
|
| NAROO | 4 |
1.2%
|
|
| NATIRA | 1 |
0.3%
|
|
| NATOWAK | 1 |
0.3%
|
|
| NUUR GUSE | 1 |
0.3%
|
|
| ODHA | 1 |
0.3%
|
|
| OGARALE | 1 |
0.3%
|
|
| OLLA | 1 |
0.3%
|
|
| PELEKECH | 1 |
0.3%
|
|
| QAYAI | 1 |
0.3%
|
|
| RAMATA / BAS BALESA | 1 |
0.3%
|
|
| RAMATROPI | 1 |
0.3%
|
|
| RHAMU | 2 |
0.6%
|
|
| SABAR WAIKUL | 1 |
0.3%
|
|
| SABARMAWA | 1 |
0.3%
|
|
| SABARWAWA | 5 |
1.5%
|
|
| SADAY | 1 |
0.3%
|
|
| SALOLO | 1 |
0.3%
|
|
| SANKURAR | 1 |
0.3%
|
|
| SARIMO | 1 |
0.3%
|
|
| SARMANI | 1 |
0.3%
|
|
| SELLAGO | 1 |
0.3%
|
|
| SEREBARWA | 1 |
0.3%
|
|
| SERELEPI | 1 |
0.3%
|
|
| SEREPARWA | 2 |
0.6%
|
|
| SEREPLUYI | 1 |
0.3%
|
|
| SHINBIR FATWA | 1 |
0.3%
|
|
| SIGARSO/GALANO | 2 |
0.6%
|
|
| SIRA/KINYA | 1 |
0.3%
|
|
| SOM. GOGNIL | 1 |
0.3%
|
|
| SOMALI | 1 |
0.3%
|
|
| SOMALIA | 1 |
0.3%
|
|
| SORIADI | 1 |
0.3%
|
|
| SOYA | 1 |
0.3%
|
|
| SOYAMA | 1 |
0.3%
|
|
| TAKABA | 3 |
0.9%
|
|
| TALBAJ | 1 |
0.3%
|
|
| TAMU | 1 |
0.3%
|
|
| TORICH | 1 |
0.3%
|
|
| TORICH / L. TURKANA | 1 |
0.3%
|
|
| WAJIR | 1 |
0.3%
|
|
| WAJIR BOR | 1 |
0.3%
|
|
| WARGADUD | 3 |
0.9%
|
|
| WASO | 11 |
3.3%
|
|
| WELL ALI | 1 |
0.3%
|
|
| WILA | 1 |
0.3%
|
|
| YAMICHA | 1 |
0.3%
|
|
| YAMIT | 1 |
0.3%
|
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.