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    Home / Central Data Catalog / RWA_2016_EICV-V_V01_M / variable [F18]
central

Integrated Household Living Conditions Survey 2016-2017

Rwanda, 2016 - 2017
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Reference ID
RWA_2016_EICV-V_v01_M
Producer(s)
National Institute of Statistics Rwanda (NISR)
Metadata
DDI/XML JSON
Created on
Jan 16, 2021
Last modified
Jan 16, 2021
Page views
21045
Downloads
382
  • Study Description
  • Data Dictionary
  • Downloads
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  • Data files
  • cs_S0_S5_Household.dta
  • cs_S1_S2_S3_S4_S6A_S6E_Person.dta
  • cs_S5F_Access_to_services.dta
  • cs_S6B_Employement_6C_Salaried_S6D_Business.dta
  • cs_S7A1_livestock.dta
  • cs_S7A2_livestock.dta
  • cs_S7A3_livestock.dta
  • cs_S7A4_livestock.dta
  • cs_S7B1_land_Agriculture.dta
  • cs_S7B2_land_Agriculture.dta
  • cs_S7C_parcels.dta
  • cs_S7D_large_crop.dta
  • cs_S7E_small_crop.dta
  • cs_S7F_income_agriculture.dta
  • cs_S7G_expenditure_agriculture.dta
  • cs_S7H_transformation_agriculture.dta
  • cs_S8A1_expenditure.dta
  • cs_S8A2_expenditure.dta
  • cs_S8A3_expenditure.dta
  • cs_S8B_expenditure.dta
  • cs_S8C_farming.dta
  • cs_S9A_transfers_out.dta
  • cs_S9B_transfers_in.dta
  • cs_S9C_Vup_ubudehe_and_Rssp_schemes.dta
  • cs_S9C3_Vup_ubudehe_and_Rssp_schemes.dta
  • cs_S9C4_Vup_ubudehe_and_Rssp_schemes.dta
  • cs_S9D_other_income.dta
  • cs_S9E_Other_expenditure.dta
  • cs_S10A1_Credits.dta
  • cs_S10A2_Listing_of_credits.dta
  • cs_S10B1_Durable_household_goods.dta
  • cs_S10B2_Durable_household_goods.dta
  • cs_S10C1_Savings.dta
  • cs_S10C2_Tontine.dta
  • EICV5_Poverty_file.dta

Article (s8a2q0)

Data file: cs_S8A2_expenditure.dta

Overview

Valid: 801900
Invalid: -
Minimum: 1
Maximum: 55
Type: Discrete
Decimal: 0
Start: 37
End: 38
Width: 2
Range: 1 - 55
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Laundry services _washing clothes & others_ 14580
1.8%
2 Rubbish collection services 14580
1.8%
3 Bleach 14580
1.8%
4 Disinfectant and cleaners 14580
1.8%
5 Broom/Brush 14580
1.8%
6 Shoe brush 14580
1.8%
7 Shoe polish 14580
1.8%
8 Other non-durable household goods e.g, sponges, window cleaning products etc 14580
1.8%
9 Wages for household _domestic_ help 14580
1.8%
10 Spare parts of Vehicle 14580
1.8%
11 Spare parts of motorcycle or bicycle _parts_ 14580
1.8%
12 Vehicle repair _labour_ 14580
1.8%
13 Repair of motorcycle or bicycle _labour_ 14580
1.8%
14 CD and DVD disks 14580
1.8%
15 Audio video cassettes & internet downloads 14580
1.8%
16 Film and developing 14580
1.8%
17 Toys 14580
1.8%
18 Natural & artificial flowers,foliages& plants 14580
1.8%
19 Other interior decorations 14580
1.8%
20 Other recreational or cultural items, _Pets:- cats, dogs, Birds_ 14580
1.8%
21 Books 14580
1.8%
22 Magazines 14580
1.8%
23 Stationary supplies _stapler, perforator, Folder, etc.._ 14580
1.8%
24 Passport photos 14580
1.8%
25 Men's haircut _barber_ 14580
1.8%
26 Women's haircut _stylist & treatment_ 14580
1.8%
27 Beauty Treatment/Massage_Non-medical_/ Manicure & steam bath 14580
1.8%
28 Shaving accessories 14580
1.8%
29 Combs 14580
1.8%
30 Other personal hygiene products, e.g; razor blades, nail cutters 14580
1.8%
31 Toothpaste _and accessories_ 14580
1.8%
32 Hair products 14580
1.8%
33 Beauty/cosmetics products 14580
1.8%
34 Deodorants 14580
1.8%
35 Sanitary napkins, pampers 14580
1.8%
36 Postage stamps 14580
1.8%
37 Rwandatel/MTN fixed line charges 14580
1.8%
38 Fax and courier services 14580
1.8%
39 Internet connection subscription _Rwandatel /MTN/TIGO/?_ 14580
1.8%
40 Security services 14580
1.8%
41 Photocopies/printing/scanner/other secretarial services 14580
1.8%
42 Diabetes drugs 14580
1.8%
43 Heart disease medicines 14580
1.8%
44 High/low blood pressure drugs 14580
1.8%
45 Asthma drugs 14580
1.8%
46 ARV drugs 14580
1.8%
47 Pain relievers _Aspirin/Paracetamol/Hedex,?_ 14580
1.8%
48 Antimalarial drugs 14580
1.8%
49 Astringents _iodine, alcohol_ 14580
1.8%
50 Worm medicine 14580
1.8%
51 Contraceptive drugs 14580
1.8%
52 Other basic/preventive medicines 14580
1.8%
53 Condoms 14580
1.8%
54 Medical consultations 14580
1.8%
55 Medical exams 14580
1.8%
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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