Ubudehe CategorizationSEPTEMBER, 20TH 2015

ProgressBEFORE APPEAL AFTER APPEAL (Data Integration)

Activity Status Activity Status

Data Collection Completed Data Collection Completed

Data Entry Completed Data Entry Completed

Data Processing Data Processing

Data Cleaning Completed Data Cleaning Completed

Data Analysis Completed Data Preliminary Analysis In Progress

Data Publication Completed Categorization Reporting In Progress

UBUDEHE CATEGORIZATION KEY DATA BY PROVINCE

Community Based Classification by Province PopulationMean 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 4.4

Rwanda 311,272

977,922

548,619

13,895

675

2,347,955

10,309,441 5.6

% 13% 42% 23% 1% 0% 100%   

HOUSEHOLDS SHARE BY CATEGORY (CB)

Kig al i S o u t h N o r t h W est East

12%

23%

12%

17%

11%

44%

54% 55

%

55%

45%

41%

23%

33%

27%

44%

3%

0% 0% 0% 1%0% 0% 0% 0% 0%

CAT 1 CAT 2 CAT 3 CAT 4 UN CAT

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.

C A T 1

C A T 2

C A T 3

429,095

1,093,812

800,923

(364,571)

(1,203,084)

(762,535)

compar is on be twe e n Cate gor ie s by t ype of c las s ifi cation

Response Based Classification Community Based Classification

KEY FINDINGS – DISTRICT LEVELSN District HHs Appealed HHs Before Appeal % of HHs BA1 Bugesera 25,680 83,353 30.81%2 Gakenke 32,117 80,129 40.08%3 Karongi 34,646 72,798 47.59%4 Ruts i ro 11,183 71,586 15.62%5 Rul indo 28,140 70,191 40.09%6 Nyagatare 37,702 91,109 41.38%7 Rubavu 37,668 85,861 43.87%8 Gats ibo 39,939 95,835 41.67%9 Burera 29,938 75,674 39.56%

10 Ngororero 47,993 80,469 59.64%11 Nyaruguru 28,807 62,834 45.85%12 Ruhango 41,657 77,457 53.78%

13 Muhanga 32,488 74,427 43.65%

14 Kirehe 18,363 78,509 23.39%15 Kicukiro 15,625 53,064 29.45%16 Nyamagabe 33,955 76,054 44.65%17 Gisagara 46,081 79,891 57.68%18 Kayonza 22,024 75,046 29.35%19 Huye 43,686 78,510 55.64%

20 Gicumbi 26,178 95,650 27.37%21 Kamonyi 41,008 77,856 52.67%22 Nyarugenge 14,241 55,821 25.51%

23 Nyamas heke 30,710 84,429 36.37%24 Rus izi 31,564 83,540 37.78%25 Rwamagana 28,200 71,720 39.32%26 Ngoma 20,836 78,330 26.60%

27 Nyanza 35,590 72,757 48.92%28 Musanze 35,141 85,130 41.28%29 Gas abo 56,144 116,229 48.30%30 Nyabihu 24,136 63,696 37.89%

Total 951,440 2,347,955 40.52%

INFORMATION ON APPEALS PROCESS

RB vs CB CATEGORIZATION (AA)

RB vs CB CATEGORIZATION (BA)

CONSISTENCY WITH EICV4

 

 

CAT1 Extrem Pov EICV

4

Diff. Ext pov CAT1 & CAT2

Pov line EICV 4  

 

CAT1 Extrem Pov EICV 4

Diff. Ext pov

CAT1 & CAT2

Pov line EICV 4

No District

Cat 1 (CB)

No District

Cat 1 (CB)

1 Bugesera RB 9.7% 13.4%   57.15% 34.30% 16 Nyamagabe RB 30.7% 13%   74.52% 41.50%CB 11.6%   1.8% 62.89%   CB 26.9%   -13.91% 79.06%  

2 Gakenke RB 12.3% 16.2%   59.23% 42.00% 17 Gisagara RB 28.7% 20.60%   75.94% 53.30%CB 10.6%   5.6% 63.70%   CB 23.2%   -2.64% 75.49%  

3 Karongi RB 31.2% 21.3%   76.19% 45.30% 18 Kayonza RB 10.0% 9.50%   42.70% 26.40%CB 29.8%   -8.5% 81.34%   CB 7.9%   1.60% 45.18%  

4 Rutsiro RB 14.1% 23.6%   49.27% 51.40% 19 Huye RB 20.8% 5.70%   76.00% 32.50%CB 16.3%   7.3% 52.41%   CB 22.1%   -16.38% 77.28%  

5 Rulindo RB 9.5% 20.2%   69.23% 48.10% 20 Gicumbi RB 8.8% 24.70%   53.01% 55.30%CB 22.7%   -2.5% 74.11%   CB 6.4%   18.31% 53.39%  

6 Nyagatare RB 16.4% 19.5%   63.56% 44.10% 21 Kamonyi RB 25.7% 6.00%   61.37% 25.90%CB 19.3%   0.2% 64.54%   CB 18.5%   -12.53% 66.19%  

7 Rubavu RB 18.0% 14.2%   71.63% 35.50% 22 Nyarugenge RB 6.2% 8.40%   42.52% 19.90%CB 17.3%   -3.1% 70.69%   CB 10.8%   -2.41% 47.55%  

8 Gatsibo RB 15.1% 18.5%   61.20% 43.80% 23 Nyamasheke RB 21.0% 39.20%   83.84% 62.00%CB 8.6%   9.9% 61.94%   CB 14.4%   24.78% 84.56%  

9 Burera RB 20.4% 23.0%   70.86% 50.40% 24 Rusizi RB 12.0% 15.80%   66.18% 35.10%CB 10.8%   12.2% 74.26%   CB 8.6%   7.24% 68.36%  

10 Ngororero RB 34.9% 23.5%   82.89% 49.60% 25 Rwamagana RB 12.0% 8.00%   54.76% 25.40%CB 24.6%   -1.1% 84.40%   CB 11.2%   -3.16% 60.01%  

11 Nyaruguru RB 22.8% 20.0%   65.00% 47.90% 26 Ngoma RB 4.7% 19.50%   47.67% 46.80%CB 20.5%   -0.5% 73.56%   CB 9.1%   10.39% 50.07%  

12 Ruhango RB 16.9% 12.8%   83.50% 37.80% 27 Nyanza RB 34.0% 17.60%   80.43% 38.00%CB 27.5%   -14.7% 87.61%   CB 23.9%   -6.30% 81.14%  

13 Muhanga RB 23.4% 7.8%   68.81% 30.50% 28 Musanze RB 16.0% 16.80%   71.92% 34.90%CB 19.6%   -11.8% 73.44%   CB 10.9%   5.85% 73.39%  

14 Kirehe RB 8.0% 17.8%   39.08% 41.80%29 Gasabo

RB 21.4% 11.30%   64.58% 23.40%CB 4.8%   13.0% 39.40%   CB 15.4%   -4.13% 66.71%  

15 Kicukiro RB 4.2% 6.5%   39.50% 16.30%30 Nyabihu

RB 8.7% 12.60%   53.14% 39.60%CB 4.1%   2.4% 39.43%   CB 8.8%   3.83% 59.55%  

CONSISTENCY WITH EICV 4 (Cont.)

Ubudehe CAT1 EICV4 RB CB (Below Extrm Pov Line)

Total HHs 18.18% 15.55% 16.30%

CONSISTENCY WITH EICV 4 (Cont.)

Ubudehe CAT 1 & 2 ICV4 RB CB (Below Pov Line)

Total HHs 64.45% 66.39% 39.10%

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% -0.08%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% -0.10%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%

Same IDs and Locationwith different HH Code

Diff. Location/Name with same NID

Total HHs Duplicated

Cases 52447 20220 72667

% of Total Ubudehe Categorization

Households2.2% 0.8% 3%

Challenge 2 - Address the issue of duplicated data

Recommendations and Suggested Way ForwardProposed actions RemarksKeep 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