Household Risk and Vulnerability Survey 2016-2018
Nepal, 2016 - 2018
Get Microdata
Reference ID
NPL_2016-2018_HRVS_v01_EN_M_v01_A_OCS
Producer(s)
The World Bank
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Metadata
Created on
Oct 06, 2020
Last modified
Nov 08, 2022
Page views
108983
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- Data files
- Section_0
- Section_1
- Section_2
- Section_3a
- Section_3b
- Section_4a
- Section_4b
- Section_5
- Section_0
- Section_1
- Section_2
- Section_3
- Section_4
- Section_5a
- Section_5b
- Section_6a
- Section_6b
- Section_6c
- Section_6d
- Section_7
- Section_8
- Section_9a1
- Section_9a2
- Section_9a3
- Section_9a4
- Section_9b1
- Section_9b2
- Section_9c
- Section_9d
- Section_9e
- Section_9f
- Section_10
- Section_11
- Section_12a
- Section_12b
- Section_12c
- Section_12d
- Section_13a
- Section_13b
- Section_13c
- Section_13d
- Section_14a
- Section_14b
- Section_14c
- Section_15a
- Section_15b
- Section_17
- Section_0
- Section_1
- Section_2
- Section_3a
- Section_3b
- Section_5
- Section_0
- Section_2
- Section_3
- Section_4
- Section_5a
- Section_5b
- Section_6a
- Section_6b
- Section_6c
- Section_6d
- Section_7
- Section_8
- Section_9a1
- Section_9a2
- Section_9a3
- Section_9a4
- Section_9b1
- Section_9b2
- Section_9c
- Section_9d
- Section_9e
- Section_9f
- Section_10
- Section_11
- Section_12a
- Section_12b
- Section_12c
- Section_12d
- Section_13a
- Section_13b
- Section_13c
- Section_13d
- Section_14a
- Section_14b
- Section_14c
- Section_15a
- Section_15b
- Section_16
- Section_17
- Section_0
- Section_1
- Section_2
- Section_3a
- Section_3b
- Section_4a
- Section_4b
- Section_5
- Section_0
- Section_1
- Section_2
- Section_3
- Section_4
- Section_5a
- Section_5b
- Section_6a
- Section_6b
- Section_6c
- Section_6d
- Section_7
- Section_8
- Section_9a1
- Section_9a2
- Section_9a3
- Section_9a4
- Section_9b1
- Section_9b2
- Section_9c
- Section_9d
- Section_9e
- Section_9f
- Section_10
- Section_11
- Section_12a
- Section_12b
- Section_12c
- Section_12d
- Section_13a
- Section_13b
- Section_13c
- Section_13d
- Section_14a
- Section_14c
- Section_15b
- Section_16
- Section_17
- Section_16
- Section_4a
- Section_4b
- Section_1
- Section_11a
- Section_14b
- Section_15a
District of donor (s13q15d)
Data file: Section_13b
Overview
Valid:
23
Invalid:
124
Type:
Discrete
Decimal:
2
Start:
60
End:
64
Width:
5
Range:
1 - 75
Format:
Numeric
Questions and instructions
Literal question
13.15d. Which district does he/she live in?
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 1 | Achham | 0 |
0%
|
| 2 | Arghakhanchi | 0 |
0%
|
| 3 | Baglung | 0 |
0%
|
| 4 | Baitadi | 0 |
0%
|
| 5 | Bajhang | 0 |
0%
|
| 6 | Bajura | 0 |
0%
|
| 7 | Banke | 1 |
4.3%
|
| 8 | Bara | 0 |
0%
|
| 9 | Bardiya | 0 |
0%
|
| 10 | Bhaktapur | 0 |
0%
|
| 11 | Bhojpur | 1 |
4.3%
|
| 12 | Chitwan | 0 |
0%
|
| 13 | Dadeldhura | 0 |
0%
|
| 14 | Dailekh | 0 |
0%
|
| 15 | Dang | 0 |
0%
|
| 16 | Darchula | 0 |
0%
|
| 17 | Dhading | 0 |
0%
|
| 18 | Dhankuta | 1 |
4.3%
|
| 19 | Dhanusa | 0 |
0%
|
| 20 | Dolakha | 0 |
0%
|
| 21 | Dolpa | 0 |
0%
|
| 22 | Doti | 0 |
0%
|
| 23 | Gorkha | 0 |
0%
|
| 24 | Gulmi | 0 |
0%
|
| 25 | Humla | 0 |
0%
|
| 26 | Illam | 0 |
0%
|
| 27 | Jajarkot | 2 |
8.7%
|
| 28 | Jhapa | 1 |
4.3%
|
| 29 | Jumla | 0 |
0%
|
| 30 | Kailali | 0 |
0%
|
| 31 | Kalikot | 0 |
0%
|
| 32 | Kanchanpur | 2 |
8.7%
|
| 33 | Kapilbastu | 0 |
0%
|
| 34 | Kaski | 0 |
0%
|
| 35 | Kathmandu | 7 |
30.4%
|
| 36 | Kavrepalanchowk | 0 |
0%
|
| 37 | Khotang | 0 |
0%
|
| 38 | Lalitpur | 0 |
0%
|
| 39 | Lamjung | 0 |
0%
|
| 40 | Mahottari | 1 |
4.3%
|
| 41 | Makwanpur | 1 |
4.3%
|
| 42 | Manang | 0 |
0%
|
| 43 | Morang | 1 |
4.3%
|
| 44 | Mugu | 0 |
0%
|
| 45 | Mustang | 0 |
0%
|
| 46 | Myagdi | 0 |
0%
|
| 47 | Nawalparasi | 0 |
0%
|
| 48 | Nuwakot | 0 |
0%
|
| 49 | Okhaldhunga | 0 |
0%
|
| 50 | Palpa | 0 |
0%
|
| 51 | Panchthar | 0 |
0%
|
| 52 | Parbat | 0 |
0%
|
| 53 | Parsa | 0 |
0%
|
| 54 | Pyuthan | 0 |
0%
|
| 55 | Ramechhap | 0 |
0%
|
| 56 | Rasuwa | 0 |
0%
|
| 57 | Rautahat | 0 |
0%
|
| 58 | Rolpa | 0 |
0%
|
| 59 | Rukum | 0 |
0%
|
| 60 | Rupandehi | 0 |
0%
|
| 61 | Salyan | 0 |
0%
|
| 62 | Sankhuwasabha | 0 |
0%
|
| 63 | Saptari | 1 |
4.3%
|
| 64 | Sarlahi | 0 |
0%
|
| 65 | Sindhuli | 0 |
0%
|
| 66 | Sindhupalchowk | 0 |
0%
|
| 67 | Siraha | 2 |
8.7%
|
| 68 | Solukhumbhu | 0 |
0%
|
| 69 | Sunsari | 1 |
4.3%
|
| 70 | Surkhet | 0 |
0%
|
| 71 | Syangja | 1 |
4.3%
|
| 72 | Tanahu | 0 |
0%
|
| 73 | Taplejung | 0 |
0%
|
| 74 | Terhathum | 0 |
0%
|
| 75 | Udayapur | 0 |
0%
|
| Sysmiss | 124 |
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.