National Panel Survey 2012-2013, Wave 3
Tanzania, 2012 - 2013
Get Microdata
Reference ID
TZA_2012_NPS-R3_v01_M
Producer(s)
National Bureau of Statistics
Collection(s)
Metadata
Created on
Apr 28, 2015
Last modified
Jan 30, 2020
Page views
379902
Downloads
49911
- Data files
- AG_NETWORK
- AG_SEC_01
- AG_SEC_2A
- AG_SEC_2B
- AG_SEC_3A
- AG_SEC_3B
- AG_SEC_4A
- AG_SEC_4B
- AG_SEC_5A
- AG_SEC_5B
- AG_SEC_6A
- AG_SEC_6B
- AG_SEC_7A
- AG_SEC_7B
- AG_SEC_08
- AG_SEC_9A
- AG_SEC_9B
- AG_SEC_9C
- AG_SEC_10
- AG_SEC_11
- AG_SEC_12A
- AG_SEC_12B
- AG_SEC_A
- COM_SEC_A1A2
- COM_SEC_CB
- COM_SEC_CC
- COM_SEC_CD
- COM_SEC_CE
- COM_SEC_CF
- COM_SEC_CF_ID
- COM_SEC_CG
- ConsumptionNPS3
- FILTERS
- HH_SEC_A
- HH_SEC_B
- HH_SEC_C
- HH_SEC_D
- HH_SEC_E
- HH_SEC_F
- HH_SEC_G
- HH_SEC_H
- HH_SEC_I
- HH_SEC_J1
- HH_SEC_J2
- HH_SEC_J3
- HH_SEC_J4
- HH_SEC_K
- HH_SEC_L
- HH_SEC_M
- HH_SEC_N
- HH_SEC_O1
- HH_SEC_O2
- HH_SEC_P
- HH_SEC_Q1
- HH_SEC_Q2
- HH_SEC_R
- HH_SEC_S
- HH_SEC_U2
- HH_SEC_V
- LF_NETWORK
- LF_SEC_01
- LF_SEC_02
- LF_SEC_03
- LF_SEC_04
- LF_SEC_05
- LF_SEC_06
- LF_SEC_07
- LF_SEC_08
- LF_SEC_09
- LF_SEC_10
- LF_SEC_11A
- LF_SEC_11B
- LF_SEC_12
- LF_SEC_13A
- LF_SEC_13B
- LF_SEC_A
- HouseholdGeovars_Y3
- NPSY3.PANEL.KEY
- PlotGeovars_Y3
- Y3_weights
District Name (ag_a02_2)
Data file: AG_SEC_A
Overview
Valid:
3336
Invalid:
0
Type:
Discrete
Start:
36
End:
59
Width:
24
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| ARUMERU | 20 |
0.6%
|
|
| ARUSHA | 8 |
0.2%
|
|
| ARUSHA MJINI | 3 |
0.1%
|
|
| BABATI | 18 |
0.5%
|
|
| BAGAMOYO | 14 |
0.4%
|
|
| BAHI | 1 |
0%
|
|
| BAHI/DODOMA VIJIJINI | 1 |
0%
|
|
| BARIADI | 20 |
0.6%
|
|
| BIHARAMULO | 19 |
0.6%
|
|
| BUKOBA RURAL | 32 |
1%
|
|
| BUKOBA URBAN | 18 |
0.5%
|
|
| BUKOMBE | 22 |
0.7%
|
|
| BUNDA | 14 |
0.4%
|
|
| CHAKECHAKE | 46 |
1.4%
|
|
| CHATO | 8 |
0.2%
|
|
| CHUNYA | 33 |
1%
|
|
| DODOMA | 1 |
0%
|
|
| DODOMA RURAL | 41 |
1.2%
|
|
| DODOMA URBAN | 25 |
0.7%
|
|
| DODOMA VIJIJINI(BAHI) | 1 |
0%
|
|
| GEITA | 47 |
1.4%
|
|
| HAI | 28 |
0.8%
|
|
| HANANG | 13 |
0.4%
|
|
| HANDENI | 27 |
0.8%
|
|
| IGUNGA | 55 |
1.6%
|
|
| IKUNGI(SINGIDA VIJIJINI) | 1 |
0%
|
|
| ILALA | 27 |
0.8%
|
|
| ILEJE | 17 |
0.5%
|
|
| ILEMELA | 16 |
0.5%
|
|
| IRAMBA | 24 |
0.7%
|
|
| IRINGA RURAL | 18 |
0.5%
|
|
| IRINGA URBAN | 21 |
0.6%
|
|
| KAHAMA | 48 |
1.4%
|
|
| KARAGWE | 36 |
1.1%
|
|
| KARATU | 13 |
0.4%
|
|
| KASKAZINI A | 28 |
0.8%
|
|
| KASKAZINI B | 40 |
1.2%
|
|
| KASULU | 77 |
2.3%
|
|
| KATI | 15 |
0.4%
|
|
| KIBAHA | 11 |
0.3%
|
|
| KIBONDO | 40 |
1.2%
|
|
| KIGOMA RURAL | 30 |
0.9%
|
|
| KIGOMA URBAN | 2 |
0.1%
|
|
| KILINDI | 15 |
0.4%
|
|
| KILOLO | 10 |
0.3%
|
|
| KILOMBERO | 22 |
0.7%
|
|
| KILOSA | 28 |
0.8%
|
|
| KILWA | 49 |
1.5%
|
|
| KILWA MASOKO | 2 |
0.1%
|
|
| KINONDONI | 53 |
1.6%
|
|
| KISARAWE | 7 |
0.2%
|
|
| KISHAPU | 33 |
1%
|
|
| KITETO | 8 |
0.2%
|
|
| KONDOA | 9 |
0.3%
|
|
| KONGWA | 24 |
0.7%
|
|
| KOROGWE | 29 |
0.9%
|
|
| KUSINI | 12 |
0.4%
|
|
| KWIMBA | 34 |
1%
|
|
| KYELA | 22 |
0.7%
|
|
| LINDI RURAL | 40 |
1.2%
|
|
| LINDI URBAN | 19 |
0.6%
|
|
| LIWALE | 38 |
1.1%
|
|
| LUDEKIA | 1 |
0%
|
|
| LUDEWA | 25 |
0.7%
|
|
| LUSHOTO | 21 |
0.6%
|
|
| MAFIA | 7 |
0.2%
|
|
| MAFINGA | 1 |
0%
|
|
| MAGHARIBI | 29 |
0.9%
|
|
| MAGU | 41 |
1.2%
|
|
| MAHENGE/ULANGA | 1 |
0%
|
|
| MAKETE | 9 |
0.3%
|
|
| MANYONI | 25 |
0.7%
|
|
| MASASI | 70 |
2.1%
|
|
| MASASI-NAYUMBU | 1 |
0%
|
|
| MASWA | 26 |
0.8%
|
|
| MBARALI | 10 |
0.3%
|
|
| MBEYA RURAL | 23 |
0.7%
|
|
| MBEYA URBAN | 12 |
0.4%
|
|
| MBINGA | 51 |
1.5%
|
|
| MBINGA NYASA | 3 |
0.1%
|
|
| MBOZI | 40 |
1.2%
|
|
| MBOZI (MOMBA) | 1 |
0%
|
|
| MBULU | 10 |
0.3%
|
|
| MEATU | 28 |
0.8%
|
|
| MICHEWENI | 32 |
1%
|
|
| MIKINDANI | 3 |
0.1%
|
|
| MISENYE | 4 |
0.1%
|
|
| MISUNGWI | 29 |
0.9%
|
|
| MKINGA | 1 |
0%
|
|
| MKOANI | 29 |
0.9%
|
|
| MKURANGA | 10 |
0.3%
|
|
| MONDULI | 19 |
0.6%
|
|
| MOROGORO RURAL | 13 |
0.4%
|
|
| MOROGORO URBAN | 22 |
0.7%
|
|
| MOSHI RURAL | 29 |
0.9%
|
|
| MPANDA | 29 |
0.9%
|
|
| MPWAPWA | 20 |
0.6%
|
|
| MTWARA | 1 |
0%
|
|
| MTWARA MIKINDANI | 12 |
0.4%
|
|
| MTWARA RURAL | 74 |
2.2%
|
|
| MTWARA URBAN | 12 |
0.4%
|
|
| MUFINDI | 36 |
1.1%
|
|
| MUHEZA | 20 |
0.6%
|
|
| MULEBA | 34 |
1%
|
|
| MUSOMA | 1 |
0%
|
|
| MUSOMA RURAL | 25 |
0.7%
|
|
| MUSOMA URBAN | 2 |
0.1%
|
|
| MVOMERO | 37 |
1.1%
|
|
| MWANGA | 17 |
0.5%
|
|
| NACHINGWEA | 15 |
0.4%
|
|
| NAMTUMBO | 23 |
0.7%
|
|
| NANYUMBU | 1 |
0%
|
|
| NEWALA | 59 |
1.8%
|
|
| NEWARA | 2 |
0.1%
|
|
| NGARA | 38 |
1.1%
|
|
| NGORONGORO | 8 |
0.2%
|
|
| NGWALA | 1 |
0%
|
|
| NICHRWENI | 1 |
0%
|
|
| NJOMBE | 16 |
0.5%
|
|
| NJOMBE RURAL | 1 |
0%
|
|
| NJOMBE URBAN | 1 |
0%
|
|
| NKASI | 26 |
0.8%
|
|
| NYAMAGANA | 5 |
0.1%
|
|
| NYASA | 4 |
0.1%
|
|
| NZEGA | 25 |
0.7%
|
|
| PANGANI | 11 |
0.3%
|
|
| ROMBO | 27 |
0.8%
|
|
| RUANGWA | 30 |
0.9%
|
|
| RUFIJI | 22 |
0.7%
|
|
| RUNGWE | 22 |
0.7%
|
|
| RUVUMA MJINI | 1 |
0%
|
|
| SAME | 18 |
0.5%
|
|
| SENGEREMA | 30 |
0.9%
|
|
| SERENGETI | 8 |
0.2%
|
|
| SHINYANGA RURAL | 30 |
0.9%
|
|
| SHINYANGA URBAN | 25 |
0.7%
|
|
| SIKONGE | 44 |
1.3%
|
|
| SIMANJIRO | 27 |
0.8%
|
|
| SINGIDA RURAL | 11 |
0.3%
|
|
| SINGIDA URBAN | 11 |
0.3%
|
|
| SONGEA | 1 |
0%
|
|
| SONGEA RURAL | 47 |
1.4%
|
|
| SONGEA URBAN | 5 |
0.1%
|
|
| SUMBAWANGA | 8 |
0.2%
|
|
| SUMBAWANGA RURAL | 24 |
0.7%
|
|
| SUMBAWANGA URBAN | 9 |
0.3%
|
|
| TABORA URBAN | 17 |
0.5%
|
|
| TANDAHIMBA | 39 |
1.2%
|
|
| TANGA | 1 |
0%
|
|
| TANGA URBAN | 10 |
0.3%
|
|
| TARIME | 15 |
0.4%
|
|
| TARIME(RORYA) | 1 |
0%
|
|
| TEMEKE | 64 |
1.9%
|
|
| TUNDURU | 42 |
1.3%
|
|
| UKEREWE | 16 |
0.5%
|
|
| ULANGA | 20 |
0.6%
|
|
| ULANGA/MAHENGE | 1 |
0%
|
|
| URAMBO | 20 |
0.6%
|
|
| URAMBO (KALIUA) | 5 |
0.1%
|
|
| URBAN | 6 |
0.2%
|
|
| UYUI | 27 |
0.8%
|
|
| WETE | 36 |
1.1%
|
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.