Household Risk and Vulnerability Survey, Full Panel 2016-2018

Nepal, 2016 - 2018

Get Microdata

Reference ID

NPL_2016-2018_HRVS_v02_M

DOI

https://doi.org/10.48529/mqys-cp36

Producer(s)

The World Bank

Metadata

Documentation in PDF DDI/XML JSON

Created on

May 28, 2020

Last modified

Sep 17, 2021

Page views

165584

Downloads

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District where plot is located (s09q04a)

Data file: Section_9a1 (hh wave1)

Overview

Valid: 8844

Invalid: 12

Type: Discrete

Decimal: 2

Width: 15

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	104	1.2%
2	Panchthar	0	0%
3	Ilam	248	2.8%
4	Jhapa	176	2%
5	Morang	115	1.3%
6	Sunsari	96	1.1%
7	Dhankuta	127	1.4%
8	Tehrathum	0	0%
9	Sankhuwasabha	2	0%
10	Bhojpur	179	2%
11	Solukhumbu	82	0.9%
12	Okhaldhunga	112	1.3%
13	Khotang	194	2.2%
14	Udayapur	196	2.2%
15	Saptari	171	1.9%
16	Siraha	0	0%
17	Dhanusha	178	2%
18	Mahottari	171	1.9%
19	Sarlahi	185	2.1%
20	Sindhuli	180	2%
21	Ramechhap	0	0%
22	Dolakha	144	1.6%
23	Sindhupalchok	437	4.9%
24	Kabhrepalanchok	325	3.7%
25	Lalitpur	0	0%
26	Bhaktapur	3	0%
27	Kathmandu	3	0%
28	Nuwakot	213	2.4%
29	Rasuwa	0	0%
30	Dhading	294	3.3%
31	Makwanpur	223	2.5%
32	Rautahat	0	0%
33	Bara	153	1.7%
34	Parsa	170	1.9%
35	Chitwan	2	0%
36	Gorkha	115	1.3%
37	Lamjung	98	1.1%
38	Tanahun	143	1.6%
39	Syangja	109	1.2%
40	Kaski	0	0%
41	Manang	0	0%
42	Mustang	0	0%
43	Myagdi	85	1%
44	Parbat	0	0%
45	Baglung	153	1.7%
46	Gulmi	201	2.3%
47	Palpa	122	1.4%
48	Nawalparasi	283	3.2%
49	Rupandehi	235	2.7%
50	Kapilbastu	0	0%
51	Arghakhanchi	0	0%
52	Pyuthan	0	0%
53	Rolpa	258	2.9%
54	Rukum	331	3.7%
55	Salyan	0	0%
56	Dang	200	2.3%
57	Banke	140	1.6%
58	Bardiya	5	0.1%
59	Surkhet	223	2.5%
60	Dailekh	210	2.4%
61	Jajarkot	280	3.2%
62	Dolpa	1	0%
63	Jumla	87	1%
64	Kalikot	134	1.5%
65	Mugu	1	0%
66	Humla	0	0%
67	Bajura	115	1.3%
68	Bajhang	100	1.1%
69	Achham	161	1.8%
70	Doti	104	1.2%
71	Kailali	258	2.9%
72	Kanchanpur	1	0%
73	Dadeldhura	2	0%
74	Baitadi	106	1.2%
75	Darchula	95	1.1%
76	Other	5	0.1%
Sysmiss		12

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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