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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F208]
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
177766
Downloads
494
  • 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
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  • 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

Non food id (nonfoodid)

Data file: Section_6a

Overview

Valid: 49818
Invalid: 0
Type: Discrete
Decimal: 0
Start: 34
End: 36
Width: 3
Range: 211 - 998
Format: Numeric

Questions and instructions

Literal question
Non food id
Categories
Value Category Cases
211 Wood (bundle wood, logwood, sawdust) 2957
5.9%
212 Kerosene oil 508
1%
213 Coal, charcoal 3
0%
214 Cylinder gas (LPG) 1500
3%
215 Matches, candles, lighters., lanterns, etc 5853
11.7%
221 Ready-made clothing and apparel 5808
11.7%
222 Shoes, slippers, sandals, etc. 5887
11.8%
223 Personal care items like shampoo, cosmetics, soap 5912
11.9%
224 Dry cleaning and washing expenses 70
0.1%
225 Personal services (haircuts, shaving, shoeshine) 4736
9.5%
231 Public transportation (buses, taxis, rickshaws, train tickets 5486
11%
232 Petrol, diesel, motor oil (for personal vehicle only) 688
1.4%
233 Entertainment (cinema, CD/cassette rentals, etc.) 100
0.2%
234 Newspapers, books, stationery supplies(except educational expenses) 172
0.3%
235 Pocket money to children 1232
2.5%
236 Wages paid to watchman, servant, gardener, driver, etc 24
0%
237 Light bulbs, shades, batteries, etc 3052
6.1%
238 Household cleaning articles (soap, bleach, washing powder) 5812
11.7%
239 Other frequent expenses not mentioned 18
0%
998 None of them 0
0%
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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