Integrated Household Living Conditions Survey 2010-2011

Rwanda, 2010 - 2011

Reference ID

RWA_2010_EICV-III_v01_M

Producer(s)

National Institute of Statistics of Rwanda (NISR)

Metadata

DDI/XML JSON

Created on

Jul 10, 2013

Last modified

Mar 29, 2019

Page views

140024

Downloads

5662

Visit 6 (S9A3Q9)

Data file: S09A3_consnonfood

Overview

Valid: 151964

Valid: 23990289.12

Invalid: 391740

Invalid: 61617787.349

Type: Discrete

Decimal: 0

Start: 67

End: 72

Width: 6

Range: -

Format:

Questions and instructions

Literal question

How much did you spend on "…." since my last visit?

Categories

Value	Category
0	None
10
15
20
25
30
40
45
50
60
65
70
75
80
90
100
110
115
120
125
130
140
150
160
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200
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220
225
230
240
245
250
260
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275
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285
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325
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345
350
360
370
375
380
390
400
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430
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450
460
470
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510
520
540
550
560
570
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600
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725
730
750
760
770
800
820
840
850
860
870
880
900
950
960
980
990
1000
1020
1030
1040
1045
1050
1080
1090
1100
1120
1140
1150
1180
1200
1240
1250
1270
1280
1300
1320
1350
1370
1400
1440
1460
1480
1500
1540
1550
1600
1620
1650
1670
1700
1730
1740
1750
1800
1850
1900
1920
1950
2000
2100
2160
2170
2180
2200
2220
2250
2280
2300
2340
2400
2460
2480
2500
2520
2600
2670
2700
2750
2800
2850
2880
2900
2940
2950
3000
3080
3100
3150
3180
3200
3300
3350
3400
3500
3530
3550
3600
3700
3750
3800
3900
4000
4040
4060
4080
4100
4110
4200
4300
4400
4450
4500
4560
4600
4660
4670
4700
4740
4750
4780
4800
4900
5000
5100
5200
5210
5300
5400
5500
5600
5650
5700
5800
5900
6000
6100
6200
6300
6380
6400
6500
6600
6700
6900
7000
7200
7400
7500
7600
7800
8000
8150
8200
8250
8500
8600
8700
8780
9000
9100
9300
9600
9700
9710
10000
10040
10300
10400
10500
10580
10800
11000
11500
11800
12000
12600
13000
14000
15000
15510
16000
18000
18400
18880
19800
20000
21000
23000
23300
24000
25000
28000
30000
31800
32900
35000
39000
39100
40000
45000
47000
47800
50000
65000
77000
80000
100000
150000
197000
230500
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.

Imputation and derivation

Imputation

If missing during visit:
- Impute by habitual consumption over the last year and habitual consumption reported on previous visits,
- Impute by empty (not applicable) any consumption that is reported and not habitual.

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