Integrated Household Survey 2015
Gambia, The, 2015 - 2016
Get MicrodataCreated on
Sep 19, 2018
Last modified
Sep 19, 2018
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- Data files
-
Household
adjusted_weight -
Part A Section
0-Cover -
Part A Section
0-HH
particulars -
Part A Section
1-6
Individual-level -
Part A Section
4C-Labor
overview-7 days -
Part A Section
7A-Credit
received -
Part A Section
7B-Credit
denied -
Part A Section
7C-Savings -
Part A Section
8-Housing -
Part A Section
9-Ownership of
durable assets -
Part A Section
10-Environment -
Part A Section
11-Governance -
Part A Section
12A-Transfers
received -
Part A Section
12B-Trasnfers
made out -
Part A Section
13-Subjective
poverty -
Part A Section
14-Access to
amenities -
Part A Section
15A-Crime HH
Members -
Part A Section
15B-Crime
Community -
Part B Section
1A-Food_consumption
expenditure -
Part B Section
1A-Food_consumption
expenditure1 -
Part B Section
1A-Food_consumption
expenditure-2 -
Part B Section
1B-Food_outside -
Part B Section
2A-Nonfood last
7 days -
Part B Section
2B-Nonfood last
1 month -
Part B Section
2C-Nonfood last
3 months -
Part B Section
2D-Nonfood last
12 months -
Part B Section
3A-Agriculture
holding -
Part B Section
3B-Crop
production -
Part B Section
3C-Processing
agricultural
produce -
Part B Section
3D-Agricultural
costs-crops -
Part B Section
3E-Livestock -
Part B Section
3F-Agricultural
costs-livestock -
Part B Section
4A-Household
income -
Part B Section
4B-Miscellaneous
income -
Part B Section
4C-Miscellaneous
income -
Part B Section
5-HH enterprise -
Part C Market
questionnaire
Average expenditure on raw materials during typical month of operations (s5q20)
Data file: Part B Section 5-HH enterprise
Overview
Valid:
2931
Invalid:
10896
Type:
Discrete
Decimal:
0
Start:
107
End:
113
Width:
7
Range:
-
Format:
Questions and instructions
Literal question
What is/was the average expenditure on raw materials during a typical month of operation of [ENTERPRISE] last 12 months?
Categories
| Value | Category |
|---|---|
| -99 | Don't know |
| 0 | |
| 2 | |
| 25 | |
| 35 | |
| 50 | |
| 60 | |
| 75 | |
| 80 | |
| 89 | |
| 90 | |
| 100 | |
| 120 | |
| 125 | |
| 130 | |
| 140 | |
| 150 | |
| 180 | |
| 200 | |
| 250 | |
| 275 | |
| 300 | |
| 350 | |
| 370 | |
| 375 | |
| 400 | |
| 441 | |
| 450 | |
| 475 | |
| 500 | |
| 510 | |
| 550 | |
| 600 | |
| 640 | |
| 650 | |
| 700 | |
| 740 | |
| 750 | |
| 756 | |
| 795 | |
| 800 | |
| 810 | |
| 850 | |
| 858 | |
| 864 | |
| 900 | |
| 924 | |
| 945 | |
| 950 | |
| 1000 | |
| 1080 | |
| 1100 | |
| 1200 | |
| 1220 | |
| 1250 | |
| 1300 | |
| 1350 | |
| 1400 | |
| 1485 | |
| 1500 | |
| 1550 | |
| 1600 | |
| 1650 | |
| 1700 | |
| 1750 | |
| 1800 | |
| 1875 | |
| 1900 | |
| 1950 | |
| 2000 | |
| 2050 | |
| 2080 | |
| 2100 | |
| 2125 | |
| 2160 | |
| 2195 | |
| 2200 | |
| 2250 | |
| 2301 | |
| 2400 | |
| 2500 | |
| 2525 | |
| 2600 | |
| 2700 | |
| 2800 | |
| 2875 | |
| 2880 | |
| 2900 | |
| 2975 | |
| 3000 | |
| 3200 | |
| 3300 | |
| 3400 | |
| 3460 | |
| 3500 | |
| 3600 | |
| 3700 | |
| 3750 | |
| 3800 | |
| 4000 | |
| 4200 | |
| 4500 | |
| 4700 | |
| 4800 | |
| 5000 | |
| 5400 | |
| 5460 | |
| 5500 | |
| 5600 | |
| 5800 | |
| 5960 | |
| 6000 | |
| 6100 | |
| 6400 | |
| 6500 | |
| 6600 | |
| 7000 | |
| 7200 | |
| 7250 | |
| 7350 | |
| 7500 | |
| 8000 | |
| 8400 | |
| 8500 | |
| 8600 | |
| 8780 | |
| 9000 | |
| 9500 | |
| 9600 | |
| 9800 | |
| 10000 | |
| 10050 | |
| 10350 | |
| 10800 | |
| 10850 | |
| 10900 | |
| 11000 | |
| 11250 | |
| 11300 | |
| 11500 | |
| 12000 | |
| 12600 | |
| 12800 | |
| 12850 | |
| 13000 | |
| 13200 | |
| 13400 | |
| 13750 | |
| 13800 | |
| 14000 | |
| 14500 | |
| 14550 | |
| 14600 | |
| 14750 | |
| 15000 | |
| 16000 | |
| 16500 | |
| 17000 | |
| 17500 | |
| 18000 | |
| 19000 | |
| 19200 | |
| 20000 | |
| 21000 | |
| 21150 | |
| 22000 | |
| 22500 | |
| 23000 | |
| 23600 | |
| 23750 | |
| 24000 | |
| 24600 | |
| 25000 | |
| 26000 | |
| 27500 | |
| 28000 | |
| 28350 | |
| 29000 | |
| 30000 | |
| 31500 | |
| 33000 | |
| 33488 | |
| 35000 | |
| 36000 | |
| 39000 | |
| 40000 | |
| 42000 | |
| 43000 | |
| 43200 | |
| 45000 | |
| 48000 | |
| 50000 | |
| 53000 | |
| 59000 | |
| 60000 | |
| 63000 | |
| 64000 | |
| 67000 | |
| 69000 | |
| 69450 | |
| 70000 | |
| 72000 | |
| 73000 | |
| 75000 | |
| 80000 | |
| 89000 | |
| 90000 | |
| 93000 | |
| 100000 | |
| 108000 | |
| 120000 | |
| 125000 | |
| 130000 | |
| 140000 | |
| 148200 | |
| 150000 | |
| 160000 | |
| 185000 | |
| 190000 | |
| 200000 | |
| 240000 | |
| 250000 | |
| 280000 | |
| 350000 | |
| 360000 | |
| 380000 | |
| 400000 | |
| 450000 | |
| 468000 | |
| 500000 | |
| 590000 | |
| 900000 | |
| 1075320 | |
| 1500000 | |
| 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.