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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_R7p2_s1e2

Overview

Valid: 3159
Invalid: 0
Type: Discrete
Decimal: 0
Width: 22
Range: 1 - 270
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Mokor Chebote 3
0.1%
2 Meklo Sefer 16
0.5%
3 Gonde 3
0.1%
4 Burka 2
0.1%
5 Maekel 17
0.5%
6 Haresew 41
1.3%
7 Limeat 39
1.2%
8 Gichi 18
0.6%
9 Sirba 57
1.8%
10 Awaeho 11
0.3%
11 Yetmen 4
0.1%
12 Gelegel Yetmen 13
0.4%
13 Densit 12
0.4%
14 Arogea Ambo 2
0.1%
15 Minchit 1
0%
16 Yetmen Lay 6
0.2%
17 Lay Ambo 9
0.3%
18 Yetmen Abbo 2
0.1%
19 Felege Selam 2
0.1%
20 Karafio 24
0.8%
21 Dibe 13
0.4%
22 Ballo 4
0.1%
23 Woyenue Eshete 5
0.2%
24 Tekeleye Meshesha 1
0%
25 Mender Mesereto 6
0.2%
26 Aleka Merawi 3
0.1%
27 Golbo 2
0.1%
28 Dahadeba 1
0%
29 Fino 12
0.4%
30 Golele 4
0.1%
31 Ealka 1
0%
32 Beressa 5
0.2%
33 Mehal Faji 6
0.2%
34 Milki 5
0.2%
35 Tach Faji 8
0.3%
36 Asefa Meshesha 1
0%
37 Boka Fiya 3
0.1%
38 Boka Bodo 3
0.1%
39 Atabahiye 23
0.7%
40 Borkema 29
0.9%
41 Koyo 28
0.9%
42 Yerer 27
0.9%
43 Yesemie 21
0.7%
44 Yada 16
0.5%
45 Addis Ketema 42
1.3%
46 Gedereha 9
0.3%
47 Yerezeb 8
0.3%
48 Yetabhe 5
0.2%
49 Godety 7
0.2%
50 Turife 174
5.5%
51 Wotera 39
1.2%
52 Ketchema 5
0.2%
53 Tena Kelo 4
0.1%
54 Oda Mecro 4
0.1%
55 Morom Sefer 12
0.4%
56 Begejo 36
1.1%
57 Gonda Begajo 1
0%
58 Konisa 1
0%
59 Kobe G/Zaw 15
0.5%
60 Alini 1
0%
61 Worgbn 10
0.3%
62 Fino & Golele 3
0.1%
63 Makro 10
0.3%
64 Arekesa Kelo 6
0.2%
65 Gende Bele 7
0.2%
66 Adadie 2
0.1%
67 Yaboo 1
0%
68 Laftole Mesreta 1
0%
69 Boto 31
1%
70 Ebicho 97
3.1%
71 Alemgena 27
0.9%
72 Chelo 72
2.3%
73 Gera 35
1.1%
74 Woyde Tokisa 52
1.6%
75 Hago 174
5.5%
76 Wattro 16
0.5%
77 4
0.1%
78 Godo 12
0.4%
79 Weyde 3
0.1%
80 Koysha Totisa 5
0.2%
81 Cheba Tokisa 12
0.4%
82 Bako 5
0.2%
83 Muleta 4
0.1%
84 Laye Wite 35
1.1%
85 Tache Wite 19
0.6%
86 Azemish Kida 8
0.3%
87 Dokea 17
0.5%
88 Shafa 20
0.6%
89 2nd Bulla 5
0.2%
90 Mehkelawi 35
1.1%
91 Laye Deboo 19
0.6%
92 Merob Godana 6
0.2%
93 Laye Wonko 7
0.2%
94 Tach Wonko 18
0.6%
95 Wite 4
0.1%
96 Bulla 7
0.2%
97 Fuchere 45
1.4%
98 Meriager 0
0%
99 Alela Ager 8
0.3%
100 Telem Amba 1
0%
101 Gema 0
0%
102 Merere 1
0%
103 Tilko 2
0.1%
104 Dinki 44
1.4%
105 Genda Gerbi 11
0.3%
106 Kuslto 19
0.6%
107 G/Haro 3
0.1%
108 Gole Gendo Koclto 20
0.6%
109 Gole 8
0.3%
110 Tabia 3
0.1%
111 Galon 22
0.7%
112 Gole Genda Barentu 5
0.2%
113 H/Goro 1
0%
114 Doma 56
1.8%
115 Kokob 28
0.9%
116 Negot 3
0.1%
117 Kae Sefer 9
0.3%
118 Wacho 5
0.2%
119 Keysha 11
0.3%
120 Megazen Sefer 12
0.4%
121 Yemenged Sefer 0
0%
122 Omala 14
0.4%
123 Church Sefer 0
0%
124 Enquiry Beret 2
0.1%
125 Shume Sha 9
0.3%
126 Deorwo 25
0.8%
127 Aba Aregay 0
0%
128 Tewala 5
0.2%
129 Shikt 0
0%
130 Addis Amba 0
0%
131 Dendawhl 4
0.1%
132 Takora 18
0.6%
133 Denekel/ Bonito 12
0.4%
134 Semidoro 23
0.7%
135 Kosien 36
1.1%
136 Weielawer 25
0.8%
137 Errata 16
0.5%
138 Buko 0
0%
139 Degaga 8
0.3%
140 Emo 0
0%
141 Shalota 0
0%
142 Amola 0
0%
143 Arda 0
0%
144 Arda chikota 0
0%
145 Alelu 0
0%
146 kura 111
3.5%
147 Mona Barumso 37
1.2%
148 Tineshu Kamo 19
0.6%
149 Kokola 37
1.2%
150 Gerdi 36
1.1%
151 Habt 19
0.6%
152 Abeyi 12
0.4%
153 Abejede 50
1.6%
154 Yebbo 15
0.5%
155 Abukako 11
0.3%
156 Famo 16
0.5%
157 Yero 18
0.6%
158 Buraya 11
0.3%
159 Wayyu 6
0.2%
160 Somdo 12
0.4%
161 Lalo Mabe 6
0.2%
162 Kajaro 17
0.5%
163 Kulto 11
0.3%
164 Gole Ganda Sole 9
0.3%
165 Genda Muuda 6
0.2%
166 Kura 2
0.1%
167 Elemo 3
0.1%
168 Boba Sodere 0
0%
169 Dodota 0
0%
170 Dolo 39
1.2%
171 Bursa 32
1%
172 Adado 166
5.3%
173 Hago 52
1.6%
174 Waissa 28
0.9%
175 Kisha 106
3.4%
176 Bukicho 60
1.9%
177 Invester Chample /Roba 10
0.3%
178 Hassene/ Waissa 13
0.4%
179 Dude 8
0.3%
270 6
0.2%
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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