1. Ubudehe Categorization
SEPTEMBER, 20TH 2015

2. AFTER APPEAL (Data Integration)
Progress
BEFORE APPEAL
AFTER APPEAL (Data Integration)
Activity
Status
Data Collection
Completed
Data Entry
Data Processing
Data Cleaning
Data Analysis
Data Preliminary Analysis
In Progress
Data Publication
Categorization Reporting

3. UBUDEHE CATEGORIZATION KEY DATA BY PROVINCE
Community Based Classification by Province
Population
Mean HHs
CAT 1
CAT 2
CAT 3
CAT 4
UN CAT
Total HHs
(Ubudehe)
Size
Kigali City
26,136
98,864
92,938
7,101 75
225,114
916,549
4.1
Southern
136,991
323,410
137,324
2,004 57
599,786
2,614,156
4.4
Northern
48,033
224,762
132,303
1,614 62
406,774
1,751,987
4.3
Western
92,980
298,802
147,566
2,571
460
542,379
2,476,327
4.6
Eastern
60,431
257,246
252,404
3,189
632
573,902
2,550,422
Rwanda
311,272
977,922
548,619
13,895
675
2,347,955
10,309,441
5.6 %
13%
42%
23% 1% 0%
100%

4. HOUSEHOLDS SHARE BY CATEGORY (CB)

5. KEY FINDINGS: SIGNIFICANT GAPS BETWEEN CAT 1 and CAT 2
The difference between CAT 1 and CAT 2 remains significant before and after appeals. These 2 categories cumulate the Population below Poverty Line
The difference between CAT 2 and CAT 3 tends to increase after appeals, suggesting that Households in CAT 3 may have been moved in CAT 2.

6. KEY FINDINGS – DISTRICT LEVEL
INFORMATION ON APPEALS PROCESS

7. RB vs CB CATEGORIZATION (AA)

8. RB vs CB CATEGORIZATION (BA)

9. CONSISTENCY WITH EICV4 CAT1 Extrem Pov EICV 4 Diff. Ext pov
CAT1
Extrem Pov EICV 4
Diff. Ext pov
CAT1 & CAT2
Pov line EICV 4 No
District
Cat 1 (CB) 1
Bugesera RB
9.7%
13.4%
57.15%
34.30% 16
Nyamagabe
30.7%
13%
74.52%
41.50% CB
11.6%
1.8%
62.89%
26.9%
-13.91%
79.06% 2
Gakenke
12.3%
16.2%
59.23%
42.00% 17
Gisagara
28.7%
20.60%
75.94%
53.30%
10.6%
5.6%
63.70%
23.2%
-2.64%
75.49% 3
Karongi
31.2%
21.3%
76.19%
45.30% 18
Kayonza
10.0%
9.50%
42.70%
26.40%
29.8%
-8.5%
81.34%
7.9%
1.60%
45.18% 4
Rutsiro
14.1%
23.6%
49.27%
51.40% 19
Huye
20.8%
5.70%
76.00%
32.50%
16.3%
7.3%
52.41%
22.1%
-16.38%
77.28% 5
Rulindo
9.5%
20.2%
69.23%
48.10% 20
Gicumbi
8.8%
24.70%
53.01%
55.30%
22.7%
-2.5%
74.11%
6.4%
18.31%
53.39% 6
Nyagatare
16.4%
19.5%
63.56%
44.10% 21
Kamonyi
25.7%
6.00%
61.37%
25.90%
19.3%
0.2%
64.54%
18.5%
-12.53%
66.19% 7
Rubavu
18.0%
14.2%
71.63%
35.50% 22
Nyarugenge
6.2%
8.40%
42.52%
19.90%
17.3%
-3.1%
70.69%
10.8%
-2.41%
47.55% 8
Gatsibo
15.1%
61.20%
43.80% 23
Nyamasheke
21.0%
39.20%
83.84%
62.00%
8.6%
9.9%
61.94%
14.4%
24.78%
84.56% 9
Burera
20.4%
23.0%
70.86%
50.40% 24
Rusizi
12.0%
15.80%
66.18%
35.10%
12.2%
74.26%
7.24%
68.36% 10
Ngororero
34.9%
23.5%
82.89%
49.60% 25
Rwamagana
8.00%
54.76%
25.40%
24.6%
-1.1%
84.40%
11.2%
-3.16%
60.01% 11
Nyaruguru
22.8%
20.0%
65.00%
47.90% 26
Ngoma
4.7%
19.50%
47.67%
46.80%
20.5%
-0.5%
73.56%
9.1%
10.39%
50.07% 12
Ruhango
16.9%
12.8%
83.50%
37.80% 27
Nyanza
34.0%
17.60%
80.43%
38.00%
27.5%
-14.7%
87.61%
23.9%
-6.30%
81.14% 13
Muhanga
23.4%
7.8%
68.81%
30.50% 28
Musanze
16.0%
16.80%
71.92%
34.90%
19.6%
-11.8%
73.44%
10.9%
5.85%
73.39% 14
Kirehe
8.0%
17.8%
39.08%
41.80% 29
Gasabo
21.4%
11.30%
64.58%
23.40%
4.8%
13.0%
39.40%
15.4%
-4.13%
66.71% 15
Kicukiro
4.2%
6.5%
39.50%
16.30% 30
Nyabihu
8.7%
12.60%
53.14%
39.60%
4.1%
2.4%
39.43%
3.83%
59.55%

10. CONSISTENCY WITH EICV 4 (Cont.)
Ubudehe CAT1
EICV4 RB CB
(Below Extrm Pov Line)
Total HHs
18.18%
15.55%
16.30%

11. CONSISTENCY WITH EICV 4 (Cont.)
Ubudehe CAT 1 & 2
ICV4 RB CB
(Below Pov Line)
Total HHs
64.45%
66.39%
39.10%

12. Challenge 1 - Check differences (red) between RB & CB in 11 Districts
Difference RB&CB CAT1
Difference RB&CB CAT2
Difference RB&CB CAT3
Difference RB&CB CAT4 No
District 1
Rulindo
13.20%
-8.32%
-2.98%
-0.10% 2
Gatsibo
-6.47%
7.21%
-2.36%
-0.33% 3
Burera
-9.60%
12.99%
-1.24%
-0.08% 4
Ngororero
-10.25%
11.76%
-0.18% 5
Ruhango
10.63%
-6.53%
-2.68%
-0.13% 6
Muhanga
-3.76%
8.39%
-1.68%
-0.14% 7
Nyamagabe
-3.81%
8.35%
-1.49% 8
Kamonyi
-7.13%
11.95%
-2.64%
-0.34% 9
Nyamasheke
-6.58%
7.30%
-0.71%
-0.01% 10
Nyanza
-10.11%
10.82%
-0.61%
-0.09% 11
Gasabo
-5.96%
8.10%
-1.61%
-0.52%

13. Challenge 2 - Address the issue of duplicated data
Same IDs and Location
with different HH Code
Diff. Location/Name
with same NID
Total HHs Duplicated
Cases
52447
20220
72667
% of Total Ubudehe Categorization Households
2.2%
0.8% 3%

14. Recommendations and Suggested Way Forward
Proposed actions
Remarks
Keep Category 1 and Category 4 classification as they appear in preliminary analysis
- Preliminary data analysis confirms coherence between Category 1 criteria’s and extreme poverty situation.
Resolve Issues of Category 2 and Category 3
The high number of households in Category 2 suggests either some inconsistencies in the Algorithm or incorrect information's provided by households. Two options are considered to clear this issues:
Adjustments should be made in order to upgrade to Category 3 all eligible Households, while not affecting households already classified in Category 3.
Physical verification of a sample of 150 HHs from Category 2.
Correct NID duplicates
Meetings at village level are suggested to verify and check individual cases
Identify reasons of the differences between RB & CB in 11 Districts
Significant differences are detected between Response Based and Community Based classification in 11 Districts that need to be addressed