Integrated Household Survey 2003-2004
Sierra Leone, 2003 - 2004
Get MicrodataCreated on
Apr 12, 2012
Last modified
Mar 29, 2019
Page views
339799
Downloads
8557
- Data files
- Section7_Housing
- Section8E_FarmProcessed
- Section8A1_Agriculture
- Expenditure
- Section1_HouseholdRoster
- Section2_Education
- Section3_Health
- Section4_Occupation
- Section5_Migration
- Section7b_Anthropometric
- Section8H_OwnConsumption
- Section9A1_NonFood_Infrequent
- Section9A2_NonFood_Frequent
- Section9B_FoodPurchases
- Section8A3_AgEquipment
- Section8B1_PlotDetails
- Section8D_Season
- Section8F_Inputs
- Section8G_Process
- Section8A2_Livestock
- Section10B_Enterprise1_Expenditure
- Section10B_Enterprise2_Expenditure
- Section10C_Enterprise1_Assets
- Section10C_Enterprise2_Assets
- Section10D_Enterprise_Income
-
Section10E_Enterprise_Income
use - Section11BA_TransfersOUT
- Section11BB_TransfersIN
- Section11C_Miscellaneous
- Section12A_HouseholdCredits
- Section12B_HouseholdAssets
- Section12C_HouseholdSavings
- Section10A_Enterprise
- comm_agriculture
- comm_demographics
- comm_economics
- comm_education
- comm_health
- corr ea codes
- CPI deflator
- cyclebudget
- cycles
- date_interview
- food prices
-
no of hhs per
ea - price deflators
- weights
How much could you sell? (1) (s12bq4a)
Data file: Section12B_HouseholdAssets
Overview
Valid:
10531
Invalid:
75349
Minimum:
0
Maximum:
8020040000
Type:
Discrete
Decimal:
0
Start:
36
End:
45
Width:
10
Range:
-
Format:
Questions and instructions
Literal question
For how much could you sell it now - item, (1)?
Categories
| Value | Category |
|---|---|
| 0 | |
| 100 | |
| 300 | |
| 400 | |
| 500 | |
| 600 | |
| 800 | |
| 1000 | |
| 1400 | |
| 1500 | |
| 2000 | |
| 2500 | |
| 3000 | |
| 3800 | |
| 4000 | |
| 4500 | |
| 5000 | |
| 5200 | |
| 5600 | |
| 6000 | |
| 7000 | |
| 7500 | |
| 8000 | |
| 9000 | |
| 10000 | |
| 10500 | |
| 11000 | |
| 11500 | |
| 12000 | |
| 13000 | |
| 14000 | |
| 14500 | |
| 15000 | |
| 16000 | |
| 17000 | |
| 18000 | |
| 18500 | |
| 19000 | |
| 20000 | |
| 21000 | |
| 22000 | |
| 23000 | |
| 24000 | |
| 25000 | |
| 26000 | |
| 27000 | |
| 28000 | |
| 29000 | |
| 30000 | |
| 30800 | |
| 31000 | |
| 32000 | |
| 33000 | |
| 34000 | |
| 35000 | |
| 36000 | |
| 38000 | |
| 40000 | |
| 41000 | |
| 43000 | |
| 44000 | |
| 45000 | |
| 46000 | |
| 47000 | |
| 48000 | |
| 50000 | |
| 52000 | |
| 53000 | |
| 55000 | |
| 56000 | |
| 58000 | |
| 60000 | |
| 61000 | |
| 64000 | |
| 65000 | |
| 67000 | |
| 68000 | |
| 69000 | |
| 70000 | |
| 72000 | |
| 74000 | |
| 75000 | |
| 76000 | |
| 77000 | |
| 78000 | |
| 80000 | |
| 84000 | |
| 85000 | |
| 87000 | |
| 90000 | |
| 95000 | |
| 96000 | |
| 100000 | |
| 101500 | |
| 102000 | |
| 107000 | |
| 110000 | |
| 112000 | |
| 115000 | |
| 116000 | |
| 117000 | |
| 120000 | |
| 125000 | |
| 128000 | |
| 130000 | |
| 135000 | |
| 140000 | |
| 145000 | |
| 150000 | |
| 154000 | |
| 158000 | |
| 160000 | |
| 170000 | |
| 175000 | |
| 178000 | |
| 180000 | |
| 185000 | |
| 190000 | |
| 200000 | |
| 210000 | |
| 220000 | |
| 225000 | |
| 230000 | |
| 231000 | |
| 240000 | |
| 245000 | |
| 250000 | |
| 260000 | |
| 270000 | |
| 275000 | |
| 280000 | |
| 290000 | |
| 300000 | |
| 305000 | |
| 310000 | |
| 320000 | |
| 340000 | |
| 345000 | |
| 350000 | |
| 360000 | |
| 370000 | |
| 380000 | |
| 400000 | |
| 410000 | |
| 420000 | |
| 440000 | |
| 450000 | |
| 451000 | |
| 460000 | |
| 475000 | |
| 480000 | |
| 500000 | |
| 520000 | |
| 550000 | |
| 560000 | |
| 566000 | |
| 580000 | |
| 600000 | |
| 608000 | |
| 620000 | |
| 650000 | |
| 660000 | |
| 680000 | |
| 700000 | |
| 710000 | |
| 720000 | |
| 750000 | |
| 800000 | |
| 810000 | |
| 850000 | |
| 852000 | |
| 900000 | |
| 950000 | |
| 960000 | |
| 980000 | |
| 1000000 | |
| 1000600 | |
| 1080000 | |
| 1100000 | |
| 1200000 | |
| 1215000 | |
| 1240000 | |
| 1250000 | |
| 1260000 | |
| 1280000 | |
| 1300000 | |
| 1350000 | |
| 1400000 | |
| 1500000 | |
| 1600000 | |
| 1650000 | |
| 1700000 | |
| 1750000 | |
| 1800000 | |
| 1900000 | |
| 2000000 | |
| 2100000 | |
| 2200000 | |
| 2300000 | |
| 2350000 | |
| 2390000 | |
| 2400000 | |
| 2450000 | |
| 2500000 | |
| 2600000 | |
| 2700000 | |
| 2800000 | |
| 2900000 | |
| 3000000 | |
| 3200000 | |
| 3250000 | |
| 3500000 | |
| 3560000 | |
| 3600000 | |
| 3700000 | |
| 3800000 | |
| 4000000 | |
| 4200000 | |
| 4300000 | |
| 4400000 | |
| 4500000 | |
| 4800000 | |
| 4900000 | |
| 5000000 | |
| 5200000 | |
| 5400000 | |
| 5500000 | |
| 6000000 | |
| 6150000 | |
| 6500000 | |
| 6600000 | |
| 6800000 | |
| 7000000 | |
| 7060000 | |
| 7100000 | |
| 7200000 | |
| 7250000 | |
| 7600000 | |
| 7900000 | |
| 8000000 | |
| 8500000 | |
| 9000000 | |
| 10000000 | |
| 10700000 | |
| 11000000 | |
| 12000000 | |
| 13000000 | |
| 14000000 | |
| 15000000 | |
| 15500000 | |
| 16000000 | |
| 16400000 | |
| 17000000 | |
| 17500000 | |
| 18000000 | |
| 20000000 | |
| 22000000 | |
| 22250000 | |
| 24000000 | |
| 25000000 | |
| 27000000 | |
| 30000000 | |
| 31000000 | |
| 32200000 | |
| 34000000 | |
| 35000000 | |
| 36000000 | |
| 40000000 | |
| 40500000 | |
| 45000000 | |
| 46000000 | |
| 48000000 | |
| 50000000 | |
| 56000000 | |
| 60000000 | |
| 68000000 | |
| 70000000 | |
| 75000000 | |
| 80000000 | |
| 81500000 | |
| 90000000 | |
| 92000000 | |
| 95000000 | |
| 100000000 | |
| 140000000 | |
| 160000000 | |
| 200000000 | |
| 250000000 | |
| 400000000 | |
| 600000000 | |
| 1000000000 | |
| 1050000000 | |
| 1500000000 | |
| 1700000000 | |
| 2000000000 | |
| 2200000000 | |
| 2500000000 | |
| 5600000000 | |
| 8020040000 | |
| 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.