Integrated Household Living Conditions Survey 2005
Rwanda, 2005
Reference ID
RWA_2005_EICV-II_v01_M
Producer(s)
Direction de la Statistique (DS)
Metadata
Created on
May 02, 2012
Last modified
Mar 29, 2019
Page views
271744
Downloads
6108
- Data files
- eng_eicv2_s0_id
- eng_eicv2_s0_IDmerged
- eng_eicv2_s1_demo
- eng_eicv2_s2_education
- eng_eicv2_s3_health
- eng_eicv2_s4_migration
- eng_eicv2_s5_housing
- eng_eicv2_s5e_services
- eng_eicv2_s6abc_employment
- eng_eicv2_s6d_employment_roster
- eng_eicv2_s6e_employ_wages
- eng_eicv2_s6f_nonremuner
- eng_eicv2_s7_enterprise
- eng_eicv2_s8a1_livestock
- eng_eicv2_s8a2_livestock_products
- eng_eicv2_s8a3_livestock_expenditure
- eng_eicv2_s8b_ag_assets
- eng_eicv2_s8c_ag_plots
- eng_eicv2_s8d_ag_production1
- eng_eicv2_s8e_ag_production2
- eng_eicv2_s8f_ag_other
- eng_eicv2_s8g_ag_expense
- eng_eicv2_s8h_ag_process
- eng_eicv2_s9a1_nfood_annual
- eng_eicv2_s9a2_nfood_month
- eng_eicv2_s9a3_nfood_freq
- eng_eicv2_s9b_food
- eng_eicv2_s9c_availability
- eng_eicv2_s9d_ex_owncons
- eng_eicv2_s10a_transfer_out
- eng_eicv2_s10b_transfer_in
- eng_eicv2_s10c_misc
- eng_eicv2_s11a_credit
- eng_eicv2_s11b_durables
- eng_eicv2_s11c_savings
- employment
- employment_onejobonly
- eng_eicv2_b_filters
-
poverty
file_161206 -
poverty
file_161206_EICV2only - eng_eicv2_com0_intro
- eng_eicv2_com1_migration
- eng_eicv2_com2_econactivity
- eng_eicv2_com3_education
- eng_eicv2_com4_health
- eng_eicv2_com5_agri
- eng_eicv2_com6_livestock
- eng_eicv2_com7_ag_extention
- eng_eicv2_com8_comm_service
- deflators
expenses of the enterprise (s7aq6)
Data file: eng_eicv2_s7_enterprise
Overview
Valid:
2513
Invalid:
3
Type:
Discrete
Decimal:
0
Start:
35
End:
43
Width:
9
Range:
-
Format:
Questions and instructions
Categories
| Value | Category |
|---|---|
| 0 | zero |
| 20 | |
| 40 | |
| 50 | |
| 70 | |
| 100 | |
| 105 | |
| 120 | |
| 150 | |
| 180 | |
| 200 | |
| 220 | |
| 250 | |
| 270 | |
| 300 | |
| 320 | |
| 350 | |
| 400 | |
| 440 | |
| 450 | |
| 500 | |
| 520 | |
| 550 | |
| 600 | |
| 640 | |
| 650 | |
| 700 | |
| 750 | |
| 780 | |
| 800 | |
| 850 | |
| 900 | |
| 980 | |
| 1000 | |
| 1100 | |
| 1200 | |
| 1240 | |
| 1250 | |
| 1280 | |
| 1300 | |
| 1350 | |
| 1400 | |
| 1440 | |
| 1450 | |
| 1500 | |
| 1600 | |
| 1650 | |
| 1660 | |
| 1700 | |
| 1720 | |
| 1750 | |
| 1800 | |
| 1920 | |
| 1960 | |
| 2000 | |
| 2100 | |
| 2200 | |
| 2250 | |
| 2280 | |
| 2300 | |
| 2340 | |
| 2400 | |
| 2410 | |
| 2460 | |
| 2500 | |
| 2600 | |
| 2700 | |
| 2800 | |
| 2880 | |
| 3000 | |
| 3200 | |
| 3300 | |
| 3400 | |
| 3500 | |
| 3600 | |
| 3700 | |
| 3750 | |
| 3760 | |
| 3800 | |
| 3900 | |
| 4000 | |
| 4150 | |
| 4200 | |
| 4300 | |
| 4450 | |
| 4500 | |
| 4560 | |
| 4600 | |
| 4700 | |
| 4750 | |
| 4800 | |
| 4900 | |
| 4950 | |
| 5000 | |
| 5040 | |
| 5100 | |
| 5200 | |
| 5250 | |
| 5300 | |
| 5400 | |
| 5450 | |
| 5500 | |
| 5550 | |
| 5600 | |
| 5640 | |
| 5700 | |
| 5800 | |
| 5900 | |
| 5950 | |
| 6000 | |
| 6200 | |
| 6300 | |
| 6400 | |
| 6500 | |
| 6600 | |
| 6630 | |
| 7000 | |
| 7100 | |
| 7200 | |
| 7400 | |
| 7440 | |
| 7500 | |
| 7600 | |
| 7700 | |
| 7830 | |
| 7950 | |
| 8000 | |
| 8100 | |
| 8200 | |
| 8400 | |
| 8500 | |
| 8675 | |
| 8850 | |
| 8940 | |
| 9000 | |
| 9200 | |
| 9400 | |
| 9500 | |
| 9600 | |
| 9800 | |
| 10000 | |
| 10100 | |
| 10150 | |
| 10200 | |
| 10400 | |
| 10500 | |
| 10800 | |
| 10900 | |
| 11000 | |
| 11040 | |
| 11500 | |
| 11600 | |
| 11700 | |
| 11800 | |
| 12000 | |
| 12100 | |
| 12500 | |
| 12550 | |
| 12600 | |
| 13000 | |
| 13500 | |
| 14000 | |
| 14300 | |
| 14500 | |
| 14650 | |
| 14750 | |
| 15000 | |
| 15500 | |
| 15600 | |
| 16000 | |
| 16500 | |
| 16700 | |
| 16800 | |
| 17000 | |
| 17210 | |
| 17500 | |
| 17600 | |
| 17700 | |
| 18000 | |
| 19000 | |
| 20000 | |
| 21000 | |
| 22000 | |
| 22300 | |
| 22500 | |
| 22700 | |
| 23000 | |
| 24000 | |
| 25000 | |
| 25200 | |
| 25300 | |
| 26000 | |
| 26500 | |
| 26800 | |
| 27000 | |
| 27500 | |
| 28000 | |
| 28800 | |
| 29000 | |
| 30000 | |
| 31000 | |
| 32000 | |
| 33000 | |
| 34000 | |
| 35000 | |
| 36000 | |
| 37000 | |
| 37200 | |
| 37500 | |
| 38000 | |
| 38300 | |
| 39750 | |
| 40000 | |
| 41000 | |
| 41500 | |
| 42000 | |
| 42800 | |
| 43000 | |
| 44200 | |
| 44600 | |
| 45000 | |
| 46000 | |
| 46300 | |
| 48000 | |
| 48500 | |
| 50000 | |
| 51000 | |
| 51100 | |
| 52500 | |
| 53850 | |
| 54600 | |
| 55000 | |
| 56000 | |
| 57000 | |
| 58000 | |
| 58200 | |
| 60000 | |
| 62000 | |
| 63000 | |
| 65000 | |
| 67500 | |
| 69000 | |
| 70000 | |
| 70700 | |
| 72000 | |
| 75000 | |
| 76000 | |
| 78000 | |
| 80000 | |
| 84000 | |
| 87000 | |
| 90000 | |
| 91200 | |
| 95000 | |
| 96000 | |
| 100000 | |
| 101500 | |
| 104000 | |
| 105000 | |
| 108000 | |
| 112000 | |
| 114000 | |
| 117000 | |
| 120000 | |
| 122550 | |
| 128000 | |
| 130000 | |
| 132000 | |
| 139250 | |
| 140000 | |
| 141300 | |
| 146000 | |
| 150000 | |
| 154000 | |
| 155000 | |
| 158000 | |
| 160000 | |
| 160500 | |
| 166500 | |
| 170000 | |
| 178000 | |
| 180000 | |
| 182000 | |
| 190000 | |
| 192000 | |
| 194000 | |
| 200000 | |
| 205000 | |
| 220000 | |
| 230000 | |
| 250000 | |
| 252225 | |
| 260000 | |
| 286000 | |
| 288000 | |
| 292000 | |
| 300000 | |
| 340000 | |
| 350000 | |
| 360000 | |
| 370000 | |
| 372000 | |
| 388000 | |
| 390000 | |
| 400000 | |
| 420000 | |
| 450000 | |
| 465700 | |
| 470000 | |
| 480000 | |
| 500000 | |
| 550000 | |
| 600000 | |
| 650000 | |
| 695000 | |
| 700000 | |
| 720000 | |
| 800000 | |
| 850000 | |
| 910000 | |
| 1000000 | |
| 1140000 | |
| 1200000 | |
| 1248000 | |
| 1500000 | |
| 1700000 | |
| 1768000 | |
| 2000000 | |
| 2200000 | |
| 2500000 | |
| 2900000 | |
| 3000000 | |
| 3500000 | |
| 4000000 | |
| 4800000 | |
| 5760000 | |
| 6800000 | |
| 7650000 | |
| 10000000 | |
| 12000000 | |
| 14000000 | |
| 25000000 | |
| 212000000 | |
| Sysmiss |
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.