National Panel Survey 2014-2015
Wave 4 - Extended Panel
Tanzania, 2013 - 2016
Get MicrodataCreated on
Jan 16, 2021
Last modified
Feb 06, 2023
Page views
59033
Downloads
769
- Data files
- ag_filters
- 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_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
- hh_filters
- 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_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_filters
- 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_11a
- lf_sec_11b
- lf_sec_12
- lf_sec_13a
- lf_sec_13b
- lf_sec_a
- hh_sec_a
- consumptionnps4_extended_panel
District Name (ag_a02_2)
Data file: ag_sec_a
Overview
Valid:
627
Invalid:
0
Type:
Discrete
Start:
30
End:
48
Width:
19
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| ARUSHA MJINI | 1 |
0.2%
|
|
| BAGAMOYO | 1 |
0.2%
|
|
| BUKOBA MJINI | 16 |
2.6%
|
|
| BUKOBA VIJIJINI | 4 |
0.6%
|
|
| BUKOMBE | 1 |
0.2%
|
|
| BUTIAMA | 12 |
1.9%
|
|
| CHATO | 1 |
0.2%
|
|
| CHUNYA | 1 |
0.2%
|
|
| DODOMA MJINI | 1 |
0.2%
|
|
| GEITA | 27 |
4.3%
|
|
| HANDENI | 13 |
2.1%
|
|
| IGUNGA | 2 |
0.3%
|
|
| ILALA | 6 |
1%
|
|
| IRAMBA | 28 |
4.5%
|
|
| IRINGA MJINI | 12 |
1.9%
|
|
| IRINGA MJINI1 | 1 |
0.2%
|
|
| ITILIMA | 1 |
0.2%
|
|
| KAHAMA | 13 |
2.1%
|
|
| KAHAMA MJINI | 1 |
0.2%
|
|
| KAHAMA VIJIJINI | 9 |
1.4%
|
|
| KAHAMA VIJIJINI/USHETU | 1 |
0.2%
|
|
| KARAGWE | 14 |
2.2%
|
|
| KARAGWE VIJIJINI | 1 |
0.2%
|
|
| KARATU | 6 |
1%
|
|
| KASKAZINI A | 8 |
1.3%
|
|
| KASULU VIJIJINI | 17 |
2.7%
|
|
| KATI | 7 |
1.1%
|
|
| KILOMBERO | 14 |
2.2%
|
|
| KILOSA | 4 |
0.6%
|
|
| KILWA | 8 |
1.3%
|
|
| KINONDONI | 6 |
1%
|
|
| KONDOA | 8 |
1.3%
|
|
| KOROGWE | 3 |
0.5%
|
|
| KWIMBA | 2 |
0.3%
|
|
| LINDI MANISPAA | 3 |
0.5%
|
|
| LINDI MJINI | 4 |
0.6%
|
|
| LINDI VIJIJINI | 4 |
0.6%
|
|
| LUDEWA | 1 |
0.2%
|
|
| LUSHOTO | 12 |
1.9%
|
|
| MAFINGA | 2 |
0.3%
|
|
| MAGHARIBI | 3 |
0.5%
|
|
| MAGU | 8 |
1.3%
|
|
| MAKETE | 1 |
0.2%
|
|
| MASASI | 4 |
0.6%
|
|
| MASASI MJINI | 2 |
0.3%
|
|
| MASASI TC | 3 |
0.5%
|
|
| MASASI VIJIJINI | 12 |
1.9%
|
|
| MASWA | 21 |
3.3%
|
|
| MBEYA VIJIJINI | 22 |
3.5%
|
|
| MBINGA | 1 |
0.2%
|
|
| MBINGA (NYASA) | 4 |
0.6%
|
|
| MBINGA NYASA | 1 |
0.2%
|
|
| MBINGA(NYASA) | 3 |
0.5%
|
|
| MBOGWE | 3 |
0.5%
|
|
| MERU | 6 |
1%
|
|
| MICHEWENI | 5 |
0.8%
|
|
| MISSENYI | 2 |
0.3%
|
|
| MISUNGWI | 4 |
0.6%
|
|
| MJINI | 1 |
0.2%
|
|
| MKASI | 1 |
0.2%
|
|
| MKOANI | 8 |
1.3%
|
|
| MKURANGA | 3 |
0.5%
|
|
| MOMBA | 1 |
0.2%
|
|
| MOROGORO MJINI | 7 |
1.1%
|
|
| MOROGORO VIJIJINI | 4 |
0.6%
|
|
| MPWAPWA | 11 |
1.8%
|
|
| MTWARA MIKINDANI | 1 |
0.2%
|
|
| MTWARA VIJIJINI | 5 |
0.8%
|
|
| MUFINDI | 8 |
1.3%
|
|
| MUHEZA | 15 |
2.4%
|
|
| MULEBA | 14 |
2.2%
|
|
| MUSOMA VIJIJINI | 1 |
0.2%
|
|
| MVOMERO | 10 |
1.6%
|
|
| MWANGA | 8 |
1.3%
|
|
| NACHINGWEA | 9 |
1.4%
|
|
| NANYUMBU | 3 |
0.5%
|
|
| NEWALA | 17 |
2.7%
|
|
| NKASI | 23 |
3.7%
|
|
| NYAMAGANA | 1 |
0.2%
|
|
| NYANG'HWALE | 1 |
0.2%
|
|
| NYASA | 8 |
1.3%
|
|
| NZEGA | 1 |
0.2%
|
|
| ROMBO | 11 |
1.8%
|
|
| RUANGWA | 1 |
0.2%
|
|
| RUFIJI | 2 |
0.3%
|
|
| SENGEREMA | 4 |
0.6%
|
|
| SIKONGE | 2 |
0.3%
|
|
| SIMANJIRO | 6 |
1%
|
|
| SONGEA (V) | 2 |
0.3%
|
|
| SONGEA MJINI | 2 |
0.3%
|
|
| SONGEA VIJIJINI | 18 |
2.9%
|
|
| SUMBAWANGA MJINI | 2 |
0.3%
|
|
| TABORA MJINI | 6 |
1%
|
|
| TANDAHIMBA | 5 |
0.8%
|
|
| TANGA MJINI | 2 |
0.3%
|
|
| TEMEKE | 3 |
0.5%
|
|
| UKEREWE | 1 |
0.2%
|
|
| USHETU KAHAMA | 1 |
0.2%
|
|
| UYUI | 13 |
2.1%
|
|
| WETE | 4 |
0.6%
|
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.