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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F214]
agricultural-surveys

Household Risk and Vulnerability Survey 2016-2018

Nepal, 2016 - 2018
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Reference ID
NPL_2016-2018_HRVS_v01_EN_M_v01_A_OCS
Producer(s)
The World Bank
Collections
Agricultural Surveys
Metadata
Documentation in PDF DDI/XML JSON
Created on
Oct 06, 2020
Last modified
Nov 08, 2022
Page views
210275
Downloads
558
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • 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 where plot is located (s09q04a)

Data file: Section_9a1

Overview

Valid: 9725
Invalid: 19
Type: Discrete
Decimal: 2
Start: 63
End: 67
Width: 5
Range: 1 - 76
Format: Numeric

Questions and instructions

Literal question
9.4a. Where is this plot located - District? (write a code)
Categories
Value Category Cases
1 Taplejung 112
1.2%
2 Panchthar 0
0%
3 Ilam 259
2.7%
4 Jhapa 195
2%
5 Morang 124
1.3%
6 Sunsari 97
1%
7 Dhankuta 135
1.4%
8 Tehrathum 0
0%
9 Sankhuwasabha 2
0%
10 Bhojpur 188
1.9%
11 Solukhumbu 98
1%
12 Okhaldhunga 115
1.2%
13 Khotang 204
2.1%
14 Udayapur 215
2.2%
15 Saptari 178
1.8%
16 Siraha 0
0%
17 Dhanusha 192
2%
18 Mahottari 174
1.8%
19 Sarlahi 193
2%
20 Sindhuli 188
1.9%
21 Ramechhap 0
0%
22 Dolakha 148
1.5%
23 Sindhupalchok 479
4.9%
24 Kabhrepalanchok 363
3.7%
25 Lalitpur 1
0%
26 Bhaktapur 3
0%
27 Kathmandu 4
0%
28 Nuwakot 231
2.4%
29 Rasuwa 0
0%
30 Dhading 319
3.3%
31 Makwanpur 238
2.4%
32 Rautahat 0
0%
33 Bara 156
1.6%
34 Parsa 172
1.8%
35 Chitwan 5
0.1%
36 Gorkha 148
1.5%
37 Lamjung 140
1.4%
38 Tanahun 197
2%
39 Syangja 132
1.4%
40 Kaski 1
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 104
1.1%
44 Parbat 0
0%
45 Baglung 183
1.9%
46 Gulmi 248
2.6%
47 Palpa 129
1.3%
48 Nawalparasi 298
3.1%
49 Rupandehi 248
2.6%
50 Kapilbastu 1
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 300
3.1%
54 Rukum 373
3.8%
55 Salyan 0
0%
56 Dang 236
2.4%
57 Banke 156
1.6%
58 Bardiya 6
0.1%
59 Surkhet 251
2.6%
60 Dailekh 221
2.3%
61 Jajarkot 291
3%
62 Dolpa 1
0%
63 Jumla 88
0.9%
64 Kalikot 145
1.5%
65 Mugu 1
0%
66 Humla 0
0%
67 Bajura 127
1.3%
68 Bajhang 106
1.1%
69 Achham 182
1.9%
70 Doti 115
1.2%
71 Kailali 274
2.8%
72 Kanchanpur 4
0%
73 Dadeldhura 2
0%
74 Baitadi 118
1.2%
75 Darchula 105
1.1%
76 Other 6
0.1%
Sysmiss 19
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.
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