Integrated Household Survey 2003-2004
Sierra Leone, 2003 - 2004
Get MicrodataCreated on
Apr 12, 2012
Last modified
Mar 29, 2019
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- 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
Purchase price (1) (s12bq3a)
Data file: Section12B_HouseholdAssets
Overview
Valid:
10496
Invalid:
75384
Minimum:
0
Maximum:
5000000000
Type:
Discrete
Decimal:
0
Start:
18
End:
27
Width:
10
Range:
-
Format:
Questions and instructions
Literal question
What was its purchase price - 1?
Categories
| Value | Category |
|---|---|
| 0 | |
| 1 | |
| 5 | |
| 10 | |
| 14 | |
| 15 | |
| 19 | |
| 20 | |
| 23 | |
| 30 | |
| 40 | |
| 50 | |
| 54 | |
| 100 | |
| 120 | |
| 150 | |
| 160 | |
| 180 | |
| 200 | |
| 240 | |
| 270 | |
| 280 | |
| 450 | |
| 500 | |
| 600 | |
| 1000 | |
| 1300 | |
| 1500 | |
| 1600 | |
| 2000 | |
| 2100 | |
| 2500 | |
| 2600 | |
| 3000 | |
| 3500 | |
| 3800 | |
| 4000 | |
| 4500 | |
| 5000 | |
| 5400 | |
| 5500 | |
| 5800 | |
| 6000 | |
| 6500 | |
| 7000 | |
| 7500 | |
| 8000 | |
| 8500 | |
| 9000 | |
| 9500 | |
| 10000 | |
| 11000 | |
| 12000 | |
| 12500 | |
| 13000 | |
| 13500 | |
| 14000 | |
| 14700 | |
| 15000 | |
| 16000 | |
| 17000 | |
| 17500 | |
| 18000 | |
| 18500 | |
| 19000 | |
| 20000 | |
| 20600 | |
| 21000 | |
| 22000 | |
| 22500 | |
| 23000 | |
| 24000 | |
| 25000 | |
| 26000 | |
| 27000 | |
| 28000 | |
| 28500 | |
| 29000 | |
| 29600 | |
| 30000 | |
| 31000 | |
| 32000 | |
| 32700 | |
| 33000 | |
| 34000 | |
| 35000 | |
| 36000 | |
| 37000 | |
| 37500 | |
| 38000 | |
| 39000 | |
| 39500 | |
| 40000 | |
| 41000 | |
| 42000 | |
| 43000 | |
| 44000 | |
| 45000 | |
| 46000 | |
| 47000 | |
| 48000 | |
| 49000 | |
| 50000 | |
| 51000 | |
| 52000 | |
| 53000 | |
| 54000 | |
| 55000 | |
| 56000 | |
| 57000 | |
| 58000 | |
| 59000 | |
| 60000 | |
| 62000 | |
| 63000 | |
| 63500 | |
| 64500 | |
| 65000 | |
| 66000 | |
| 67000 | |
| 67500 | |
| 68000 | |
| 70000 | |
| 72000 | |
| 73000 | |
| 74000 | |
| 75000 | |
| 76000 | |
| 77000 | |
| 78000 | |
| 79000 | |
| 80000 | |
| 81000 | |
| 84000 | |
| 85000 | |
| 86000 | |
| 87000 | |
| 90000 | |
| 91000 | |
| 92000 | |
| 94000 | |
| 95000 | |
| 96000 | |
| 97000 | |
| 98000 | |
| 100000 | |
| 102000 | |
| 103000 | |
| 104000 | |
| 105000 | |
| 106000 | |
| 108000 | |
| 110000 | |
| 114000 | |
| 115000 | |
| 116000 | |
| 118000 | |
| 120000 | |
| 122000 | |
| 125000 | |
| 126000 | |
| 128000 | |
| 130000 | |
| 132000 | |
| 135000 | |
| 136000 | |
| 137000 | |
| 140000 | |
| 142000 | |
| 145000 | |
| 146000 | |
| 148000 | |
| 150000 | |
| 155000 | |
| 157000 | |
| 160000 | |
| 165000 | |
| 168000 | |
| 170000 | |
| 175000 | |
| 180000 | |
| 185000 | |
| 190000 | |
| 195000 | |
| 200000 | |
| 205000 | |
| 208000 | |
| 210000 | |
| 211000 | |
| 212000 | |
| 214000 | |
| 217000 | |
| 220000 | |
| 225000 | |
| 230000 | |
| 231000 | |
| 233000 | |
| 235000 | |
| 240000 | |
| 250000 | |
| 260000 | |
| 265000 | |
| 270000 | |
| 275000 | |
| 280000 | |
| 288000 | |
| 290000 | |
| 300000 | |
| 300745 | |
| 320000 | |
| 325000 | |
| 330000 | |
| 340000 | |
| 345000 | |
| 350000 | |
| 355000 | |
| 360000 | |
| 365000 | |
| 375000 | |
| 380000 | |
| 400000 | |
| 410000 | |
| 414000 | |
| 420000 | |
| 430000 | |
| 435000 | |
| 441000 | |
| 450000 | |
| 456000 | |
| 460000 | |
| 475000 | |
| 480000 | |
| 500000 | |
| 520000 | |
| 550000 | |
| 560000 | |
| 566000 | |
| 570000 | |
| 575000 | |
| 580000 | |
| 588000 | |
| 600000 | |
| 645000 | |
| 650000 | |
| 670000 | |
| 680000 | |
| 700000 | |
| 715000 | |
| 740000 | |
| 750000 | |
| 755000 | |
| 780000 | |
| 790000 | |
| 800000 | |
| 820000 | |
| 830000 | |
| 850000 | |
| 880000 | |
| 900000 | |
| 920000 | |
| 935000 | |
| 950000 | |
| 990000 | |
| 1000000 | |
| 1040000 | |
| 1050000 | |
| 1100000 | |
| 1105000 | |
| 1150000 | |
| 1200000 | |
| 1205000 | |
| 1215000 | |
| 1250000 | |
| 1300000 | |
| 1325000 | |
| 1400000 | |
| 1500000 | |
| 1600000 | |
| 1615000 | |
| 1700000 | |
| 1800000 | |
| 1900000 | |
| 2000000 | |
| 2300000 | |
| 2390000 | |
| 2400000 | |
| 2500000 | |
| 2700000 | |
| 2800000 | |
| 3000000 | |
| 3500000 | |
| 3750000 | |
| 4000000 | |
| 4500000 | |
| 5000000 | |
| 5200000 | |
| 6000000 | |
| 6150000 | |
| 7000000 | |
| 8000000 | |
| 9000000 | |
| 9500000 | |
| 10000000 | |
| 12000000 | |
| 14000000 | |
| 15000000 | |
| 17000000 | |
| 19000000 | |
| 20000000 | |
| 25000000 | |
| 30000000 | |
| 40000000 | |
| 50000000 | |
| 2000000000 | |
| 2500000000 | |
| 4000000000 | |
| 5000000000 | |
| 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.