Household Risk and Vulnerability Survey 2016, Wave 1
Nepal, 2016
Get Microdata
Reference ID
NPL_2016_HRVS_v01_M
Producer(s)
Thomas Walker, Hanan Jacoby
Metadata
Created on
Sep 19, 2017
Last modified
Oct 05, 2017
Page views
130895
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- Data files
- weights
- 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_7a
- Section_7b
- 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_13a
- Section_13b
- Section_13c
- Section_13d
- Section_14a
- Section_14b
- Section_14c
- Section_15a
- Section_15b
- Section_16
Name of District (district)
Data file: Section_9b2
Overview
Valid:
9024
Invalid:
0
Type:
Discrete
Decimal:
0
Width:
8
Range:
1 - 75
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 1 | Taplejung | 58 |
0.6%
|
| 2 | Panchthar | 0 |
0%
|
| 3 | Ilam | 290 |
3.2%
|
| 4 | Jhapa | 262 |
2.9%
|
| 5 | Morang | 122 |
1.4%
|
| 6 | Sunsari | 103 |
1.1%
|
| 7 | Dhankuta | 91 |
1%
|
| 8 | Tehrathum | 0 |
0%
|
| 9 | Sankhuwasabha | 0 |
0%
|
| 10 | Bhojpur | 117 |
1.3%
|
| 11 | Solukhumbu | 81 |
0.9%
|
| 12 | Okhaldhunga | 88 |
1%
|
| 13 | Khotang | 111 |
1.2%
|
| 14 | Udayapur | 123 |
1.4%
|
| 15 | Saptari | 136 |
1.5%
|
| 16 | Siraha | 0 |
0%
|
| 17 | Dhanusha | 164 |
1.8%
|
| 18 | Mahottari | 147 |
1.6%
|
| 19 | Sarlahi | 170 |
1.9%
|
| 20 | Sindhuli | 164 |
1.8%
|
| 21 | Ramechhap | 0 |
0%
|
| 22 | Dolakha | 95 |
1.1%
|
| 23 | Sindhupalchok | 190 |
2.1%
|
| 24 | Kabhrepalanchok | 302 |
3.3%
|
| 25 | Lalitpur | 0 |
0%
|
| 26 | Bhaktapur | 0 |
0%
|
| 27 | Kathmandu | 0 |
0%
|
| 28 | Nuwakot | 104 |
1.2%
|
| 29 | Rasuwa | 0 |
0%
|
| 30 | Dhading | 41 |
0.5%
|
| 31 | Makwanpur | 256 |
2.8%
|
| 32 | Rautahat | 0 |
0%
|
| 33 | Bara | 174 |
1.9%
|
| 34 | Parsa | 144 |
1.6%
|
| 35 | Chitwan | 0 |
0%
|
| 36 | Gorkha | 42 |
0.5%
|
| 37 | Lamjung | 63 |
0.7%
|
| 38 | Tanahun | 94 |
1%
|
| 39 | Syangja | 30 |
0.3%
|
| 40 | Kaski | 0 |
0%
|
| 41 | Manang | 0 |
0%
|
| 42 | Mustang | 0 |
0%
|
| 43 | Myagdi | 105 |
1.2%
|
| 44 | Parbat | 0 |
0%
|
| 45 | Baglung | 361 |
4%
|
| 46 | Gulmi | 520 |
5.8%
|
| 47 | Palpa | 312 |
3.5%
|
| 48 | Nawalparasi | 343 |
3.8%
|
| 49 | Rupandehi | 332 |
3.7%
|
| 50 | Kapilbastu | 0 |
0%
|
| 51 | Arghakhanchi | 0 |
0%
|
| 52 | Pyuthan | 0 |
0%
|
| 53 | Rolpa | 265 |
2.9%
|
| 54 | Rukum | 349 |
3.9%
|
| 55 | Salyan | 0 |
0%
|
| 56 | Dang | 282 |
3.1%
|
| 57 | Banke | 167 |
1.9%
|
| 58 | Bardiya | 0 |
0%
|
| 59 | Surkhet | 420 |
4.7%
|
| 60 | Dailekh | 239 |
2.6%
|
| 61 | Jajarkot | 320 |
3.5%
|
| 62 | Dolpa | 0 |
0%
|
| 63 | Jumla | 35 |
0.4%
|
| 64 | Kalikot | 129 |
1.4%
|
| 65 | Mugu | 0 |
0%
|
| 66 | Humla | 0 |
0%
|
| 67 | Bajura | 97 |
1.1%
|
| 68 | Bajhang | 99 |
1.1%
|
| 69 | Achham | 106 |
1.2%
|
| 70 | Doti | 87 |
1%
|
| 71 | Kailali | 429 |
4.8%
|
| 72 | Kanchanpur | 0 |
0%
|
| 73 | Dadeldhura | 0 |
0%
|
| 74 | Baitadi | 145 |
1.6%
|
| 75 | Darchula | 120 |
1.3%
|
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.