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
379538
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- 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
In which ID_DISTRICT were you born? - NAME (hh_b29_1)
Data file: HH_SEC_B
Overview
Valid:
8703
Invalid:
0
Type:
Discrete
Start:
119
End:
134
Width:
16
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| AFRICA KUSINI | 1 |
0%
|
|
| ARUMERU | 55 |
0.6%
|
|
| ARUSHA | 63 |
0.7%
|
|
| BABATI | 52 |
0.6%
|
|
| BAGAMOYO | 80 |
0.9%
|
|
| BAHI | 19 |
0.2%
|
|
| BARIADI | 124 |
1.4%
|
|
| BIHARAMULO | 33 |
0.4%
|
|
| BUKOBA RURAL | 89 |
1%
|
|
| BUKOBA URBAN | 19 |
0.2%
|
|
| BUKOMBE | 43 |
0.5%
|
|
| BUNDA | 35 |
0.4%
|
|
| BURUNDI | 30 |
0.3%
|
|
| BURUNDI KITEGA | 1 |
0%
|
|
| CHAKECHAKE | 123 |
1.4%
|
|
| CHATO | 13 |
0.1%
|
|
| CHITIPA | 1 |
0%
|
|
| CHUNYA | 29 |
0.3%
|
|
| DODOMA RURAL | 28 |
0.3%
|
|
| DODOMA URBAN | 43 |
0.5%
|
|
| GEITA | 191 |
2.2%
|
|
| HAI | 64 |
0.7%
|
|
| HANANG | 10 |
0.1%
|
|
| HANDENI | 43 |
0.5%
|
|
| IGUNGA | 143 |
1.6%
|
|
| ILALA | 199 |
2.3%
|
|
| ILEJE | 29 |
0.3%
|
|
| ILEMELA | 31 |
0.4%
|
|
| INDIA | 1 |
0%
|
|
| IRAMBA | 91 |
1%
|
|
| IRINGA RURAL | 64 |
0.7%
|
|
| IRINGA URBAN | 36 |
0.4%
|
|
| KAHAMA | 146 |
1.7%
|
|
| KARAGWE | 53 |
0.6%
|
|
| KARATU | 28 |
0.3%
|
|
| KASKAZINI A | 97 |
1.1%
|
|
| KASKAZINI B | 51 |
0.6%
|
|
| KASULU | 124 |
1.4%
|
|
| KATI | 55 |
0.6%
|
|
| KENYA | 13 |
0.1%
|
|
| KIBAHA | 45 |
0.5%
|
|
| KIBONDO | 103 |
1.2%
|
|
| KIGALI | 1 |
0%
|
|
| KIGOMA RURAL | 53 |
0.6%
|
|
| KIGOMA URBAN | 39 |
0.4%
|
|
| KILIMANJARO | 1 |
0%
|
|
| KILINDI | 23 |
0.3%
|
|
| KILOLO | 29 |
0.3%
|
|
| KILOMBERO | 43 |
0.5%
|
|
| KILOSA | 74 |
0.9%
|
|
| KILWA | 106 |
1.2%
|
|
| KINONDONI | 287 |
3.3%
|
|
| KISARAWE | 48 |
0.6%
|
|
| KISHAPU | 110 |
1.3%
|
|
| KITETO | 5 |
0.1%
|
|
| KONDOA | 34 |
0.4%
|
|
| KONGO | 1 |
0%
|
|
| KONGWA | 23 |
0.3%
|
|
| KOROGWE | 60 |
0.7%
|
|
| KUSINI | 34 |
0.4%
|
|
| KWIMBA | 146 |
1.7%
|
|
| KYELA | 33 |
0.4%
|
|
| LINDI | 2 |
0%
|
|
| LINDI RURAL | 83 |
1%
|
|
| LINDI URBAN | 35 |
0.4%
|
|
| LIWALE | 52 |
0.6%
|
|
| LUDEWA | 16 |
0.2%
|
|
| LUSHOTO | 89 |
1%
|
|
| MAFIA | 15 |
0.2%
|
|
| MAGHARIBI | 81 |
0.9%
|
|
| MAGU | 167 |
1.9%
|
|
| MAKETE | 31 |
0.4%
|
|
| MALAWI | 5 |
0.1%
|
|
| MANYONI | 43 |
0.5%
|
|
| MASASI | 165 |
1.9%
|
|
| MASWA | 145 |
1.7%
|
|
| MBALALI | 14 |
0.2%
|
|
| MBEYA RURAL | 30 |
0.3%
|
|
| MBEYA URBAN | 18 |
0.2%
|
|
| MBINGA | 43 |
0.5%
|
|
| MBOZI | 59 |
0.7%
|
|
| MBULU | 43 |
0.5%
|
|
| MEATU | 74 |
0.9%
|
|
| MICHWEWENI | 66 |
0.8%
|
|
| MISENYE | 33 |
0.4%
|
|
| MISUNGWI | 54 |
0.6%
|
|
| MJINI | 174 |
2%
|
|
| MKINGA | 23 |
0.3%
|
|
| MKOANI | 96 |
1.1%
|
|
| MKURANGA | 58 |
0.7%
|
|
| MONDULI | 29 |
0.3%
|
|
| MOROGORO RURAL | 105 |
1.2%
|
|
| MOROGORO URBAN | 42 |
0.5%
|
|
| MOSHI | 1 |
0%
|
|
| MOSHI RURAL | 128 |
1.5%
|
|
| MOSHI URBAN | 34 |
0.4%
|
|
| MOZAMBIQUE | 13 |
0.1%
|
|
| MPANDA | 34 |
0.4%
|
|
| MPWAPWA | 27 |
0.3%
|
|
| MTWARA MIKINDANI | 69 |
0.8%
|
|
| MTWARA RURAL | 108 |
1.2%
|
|
| MUFINDI | 70 |
0.8%
|
|
| MUHEZA | 49 |
0.6%
|
|
| MULEBA | 112 |
1.3%
|
|
| MUSOMA RURAL | 75 |
0.9%
|
|
| MUSOMA URBAN | 26 |
0.3%
|
|
| MVOMERO | 29 |
0.3%
|
|
| MWANGA | 50 |
0.6%
|
|
| NACHINGWEA | 45 |
0.5%
|
|
| NAIROBI | 1 |
0%
|
|
| NAMTUMBO | 21 |
0.2%
|
|
| NEWALA | 110 |
1.3%
|
|
| NGARA | 55 |
0.6%
|
|
| NGORONGORO | 17 |
0.2%
|
|
| NJOMBE | 61 |
0.7%
|
|
| NKASI | 26 |
0.3%
|
|
| NYAMAGANA | 47 |
0.5%
|
|
| NZEGA | 101 |
1.2%
|
|
| PANGANI | 26 |
0.3%
|
|
| ROMBO | 57 |
0.7%
|
|
| RUANGWA | 40 |
0.5%
|
|
| RUFIJI | 83 |
1%
|
|
| RUKWA | 1 |
0%
|
|
| RUNGWE | 69 |
0.8%
|
|
| SAME | 84 |
1%
|
|
| SENGEREMA | 108 |
1.2%
|
|
| SHINYANGA RURAL | 158 |
1.8%
|
|
| SHINYANGA URBAN | 44 |
0.5%
|
|
| SIKONGE | 71 |
0.8%
|
|
| SIMANJIRO | 21 |
0.2%
|
|
| SINGEA VIJIJINI | 1 |
0%
|
|
| SINGIDA RURAL | 71 |
0.8%
|
|
| SINGIDA URBAN | 38 |
0.4%
|
|
| SINGIDA VIJIJINI | 1 |
0%
|
|
| SONGEA RURAL | 57 |
0.7%
|
|
| SONGEA URBAN | 21 |
0.2%
|
|
| SUMBAWANGA | 37 |
0.4%
|
|
| SUMBAWANGA URBAN | 12 |
0.1%
|
|
| TABORA URBAN | 36 |
0.4%
|
|
| TANDAHIMBA | 62 |
0.7%
|
|
| TANGA (LTW | 1 |
0%
|
|
| TANGA URBAN | 58 |
0.7%
|
|
| TARIME | 65 |
0.7%
|
|
| TEMEKE | 231 |
2.7%
|
|
| TUNDURU | 41 |
0.5%
|
|
| UGANDA | 1 |
0%
|
|
| UKEREWE | 75 |
0.9%
|
|
| ULANGA | 46 |
0.5%
|
|
| URAMBA | 48 |
0.6%
|
|
| UYUI | 56 |
0.6%
|
|
| WETE | 125 |
1.4%
|
|
| ZAMBIA | 9 |
0.1%
|
|
| ZIMBABWE | 2 |
0%
|
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.