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Ethiopian Rural Household Survey 1989-2009

Ethiopia, 1989 - 2009
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Reference ID
eth-csae-erhs-1989-2009-v1
Producer(s)
International Food Policy Research Institute (IFPRI), Centre for the study of African Economies (CSAE), Department of Economics, Addis Ababa University (AAU)
Metadata
DDI/XML JSON
Created on
Oct 15, 2012
Last modified
Oct 26, 2015
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Name of village/neighbourhood/got/kushet within the pa (village)

Data file: ERHS 2009_R7roster_r7

Overview

Valid: 15006
Invalid: 5
Type: Discrete
Decimal: 0
Width: 22
Range: 1 - 270
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Mokor Chebote 49
0.3%
2 Meklo Sefer 122
0.8%
3 Gonde 33
0.2%
4 Burka 13
0.1%
5 Maekel 158
1.1%
6 Haresew 257
1.7%
7 Limeat 278
1.9%
8 Gichi 68
0.5%
9 Sirba 367
2.4%
10 Awaeho 72
0.5%
11 Yetmen 36
0.2%
12 Gelegel Yetmen 90
0.6%
13 Densit 100
0.7%
14 Arogea Ambo 43
0.3%
15 Minchit 11
0.1%
16 Yetmen Lay 66
0.4%
17 Lay Ambo 91
0.6%
18 Yetmen Abbo 24
0.2%
19 Felege Selam 13
0.1%
20 Karafio 222
1.5%
21 Dibe 114
0.8%
22 Ballo 33
0.2%
23 Woyenue Eshete 37
0.2%
24 Tekeleye Meshesha 12
0.1%
25 Mender Mesereto 46
0.3%
26 Aleka Merawi 34
0.2%
27 Golbo 24
0.2%
28 Dahadeba 5
0%
29 Fino 123
0.8%
30 Golele 49
0.3%
31 Ealka 4
0%
32 Beressa 54
0.4%
33 Mehal Faji 65
0.4%
34 Milki 47
0.3%
35 Tach Faji 104
0.7%
36 Asefa Meshesha 11
0.1%
37 Boka Fiya 26
0.2%
38 Boka Bodo 30
0.2%
39 Atabahiye 55
0.4%
40 Borkema 105
0.7%
41 Koyo 69
0.5%
42 Yerer 78
0.5%
43 Yesemie 72
0.5%
44 Yada 61
0.4%
45 Addis Ketema 123
0.8%
46 Gedereha 25
0.2%
47 Yerezeb 23
0.2%
48 Yetabhe 10
0.1%
49 Godety 63
0.4%
50 Turife 941
6.3%
51 Wotera 221
1.5%
52 Ketchema 30
0.2%
53 Tena Kelo 12
0.1%
54 Oda Mecro 16
0.1%
55 Morom Sefer 42
0.3%
56 Begejo 259
1.7%
57 Gonda Begajo 14
0.1%
58 Konisa 11
0.1%
59 Kobe G/Zaw 146
1%
60 Alini 10
0.1%
61 Worgbn 93
0.6%
62 Fino & Golele 61
0.4%
63 Makro 45
0.3%
64 Arekesa Kelo 69
0.5%
65 Gende Bele 86
0.6%
66 Adadie 32
0.2%
67 Yaboo 15
0.1%
68 Laftole Mesreta 5
0%
69 Boto 197
1.3%
70 Ebicho 298
2%
71 Alemgena 153
1%
72 Chelo 182
1.2%
73 Gera 103
0.7%
74 Woyde Tokisa 140
0.9%
75 Hago 508
3.4%
76 Wattro 62
0.4%
77 15
0.1%
78 Godo 27
0.2%
79 Weyde 13
0.1%
80 Koysha Totisa 23
0.2%
81 Cheba Tokisa 46
0.3%
82 Bako 11
0.1%
83 Muleta 10
0.1%
84 Laye Wite 102
0.7%
85 Tache Wite 53
0.4%
86 Azemish Kida 30
0.2%
87 Dokea 43
0.3%
88 Shafa 63
0.4%
89 2nd Bulla 31
0.2%
90 Mehkelawi 90
0.6%
91 Laye Deboo 60
0.4%
92 Merob Godana 20
0.1%
93 Laye Wonko 16
0.1%
94 Tach Wonko 52
0.3%
95 Wite 14
0.1%
96 Bulla 15
0.1%
97 Fuchere 119
0.8%
98 Meriager 46
0.3%
99 Alela Ager 104
0.7%
100 Telem Amba 46
0.3%
101 Gema 41
0.3%
102 Merere 70
0.5%
103 Tilko 13
0.1%
104 Dinki 317
2.1%
105 Genda Gerbi 69
0.5%
106 Kuslto 154
1%
107 G/Haro 30
0.2%
108 Gole Gendo Koclto 133
0.9%
109 Gole 75
0.5%
110 Tabia 18
0.1%
111 Galon 135
0.9%
112 Gole Genda Barentu 38
0.3%
113 H/Goro 6
0%
114 Doma 310
2.1%
115 Kokob 117
0.8%
116 Negot 19
0.1%
117 Kae Sefer 22
0.1%
118 Wacho 11
0.1%
119 Keysha 33
0.2%
120 Megazen Sefer 33
0.2%
121 Yemenged Sefer 9
0.1%
122 Omala 41
0.3%
123 Church Sefer 15
0.1%
124 Enquiry Beret 125
0.8%
125 Shume Sha 364
2.4%
126 Deorwo 171
1.1%
127 Aba Aregay 72
0.5%
128 Tewala 144
1%
129 Shikt 5
0%
130 Addis Amba 15
0.1%
131 Dendawhl 9
0.1%
132 Takora 65
0.4%
133 44
0.3%
134 122
0.8%
135 167
1.1%
136 107
0.7%
137 125
0.8%
138 140
0.9%
139 310
2.1%
140 66
0.4%
141 160
1.1%
142 118
0.8%
143 221
1.5%
144 34
0.2%
145 43
0.3%
146 137
0.9%
147 Mona Barumso 49
0.3%
148 Tineshu Kamo 28
0.2%
149 Kokola 53
0.4%
150 Gerdi 69
0.5%
151 Habt 27
0.2%
152 Abeyi 15
0.1%
153 Abejede 52
0.3%
154 Yebbo 36
0.2%
155 Abukako 25
0.2%
156 Famo 11
0.1%
157 Yero 25
0.2%
158 Buraya 10
0.1%
159 Wayyu 3
0%
160 Somdo 10
0.1%
161 Lalo Mabe 9
0.1%
162 88
0.6%
163 56
0.4%
164 61
0.4%
165 34
0.2%
166 13
0.1%
167 18
0.1%
168 10
0.1%
169 24
0.2%
170 116
0.8%
171 81
0.5%
172 368
2.5%
173 128
0.9%
174 80
0.5%
175 323
2.2%
176 158
1.1%
177 Invester Chample /Roba 37
0.2%
178 Hassene/ Waissa 28
0.2%
179 Dude 15
0.1%
185 36
0.2%
232 14
0.1%
270 8
0.1%
Sysmiss 5
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.
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