Household Risk and Vulnerability Survey, Full Panel 2016-2018

Nepal, 2016 - 2018

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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

298749

Downloads

9552

Place of residence (s08q04)

Data file: Section_8 (hh wave2)

Overview

Valid: 319

Invalid: 3226

Type: Discrete

Decimal: 2

Width: 20

Range: 1 - 97

Format: Numeric

Questions and instructions

Question pretext

For those working in agriculture or no-agriculture sectors on wage or salary basis.

Literal question

8.4. Where? (job localtion)

Categories

Value	Category	Cases
1	Taplejung	6	1.9%
2	Panchthar	1	0.3%
3	Ilam	0	0%
4	Jhapa	0	0%
5	Morang	8	2.5%
6	Sunsari	0	0%
7	Dhankuta	0	0%
8	Tehrathum	0	0%
9	Sankhuwasabha	0	0%
10	Bhojpur	2	0.6%
11	Solukhumbu	2	0.6%
12	Okhaldhunga	1	0.3%
13	Khotang	3	0.9%
14	Udayapur	4	1.3%
15	Saptari	1	0.3%
16	Siraha	1	0.3%
17	Dhanusha	0	0%
18	Mahottari	0	0%
19	Sarlahi	1	0.3%
20	Sindhuli	0	0%
21	Ramechhap	1	0.3%
22	Dolakha	1	0.3%
23	Sindhupalchok	1	0.3%
24	Kabhrepalanchok	2	0.6%
25	Lalitpur	0	0%
26	Bhaktapur	0	0%
27	Kathmandu	39	12.2%
28	Nuwakot	1	0.3%
29	Rasuwa	0	0%
30	Dhading	7	2.2%
31	Makwanpur	4	1.3%
32	Rautahat	0	0%
33	Bara	2	0.6%
34	Parsa	3	0.9%
35	Chitwan	5	1.6%
36	Gorkha	2	0.6%
37	Lamjung	0	0%
38	Tanahun	1	0.3%
39	Syangja	2	0.6%
40	Kaski	4	1.3%
41	Manang	0	0%
42	Mustang	0	0%
43	Myagdi	0	0%
44	Parbat	0	0%
45	Baglung	1	0.3%
46	Gulmi	1	0.3%
47	Palpa	1	0.3%
48	Nawalparasi	4	1.3%
49	Rupandehi	1	0.3%
50	Kapilbastu	5	1.6%
51	Arghakhanchi	0	0%
52	Pyuthan	0	0%
53	Rolpa	1	0.3%
54	Rukum	2	0.6%
55	Salyan	0	0%
56	Dang	4	1.3%
57	Banke	2	0.6%
58	Bardiya	0	0%
59	Surkhet	0	0%
60	Dailekh	1	0.3%
61	Jajarkot	2	0.6%
62	Dolpa	2	0.6%
63	Jumla	0	0%
64	Kalikot	0	0%
65	Mugu	1	0.3%
66	Humla	0	0%
67	Bajura	0	0%
68	Bajhang	0	0%
69	Achham	1	0.3%
70	Doti	1	0.3%
71	Kailali	1	0.3%
72	Kanchanpur	0	0%
73	Dadeldhura	0	0%
74	Baitadi	0	0%
75	Darchula	1	0.3%
76	Other	0	0%
81	India	145	45.5%
82	Bhutan	1	0.3%
83	China	0	0%
84	Bangladesh	0	0%
85	Hongkong	0	0%
86	Malayasia	10	3.1%
87	Japan	1	0.3%
88	Saudi Arabia	10	3.1%
89	Qatar	12	3.8%
90	United Arab Emirates	1	0.3%
91	United Kingdom	0	0%
92	United States	0	0%
93	South Korea	0	0%
94	Australia	0	0%
95	Israel	0	0%
96	Other	2	0.6%
97	Other	0	0%
Sysmiss		3226

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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