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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_R7p1_s4b1

Overview

Valid: 1521
Invalid: 0
Type: Discrete
Decimal: 0
Width: 22
Range: 1 - 232
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Mokor Chebote 7
0.5%
2 Meklo Sefer 13
0.9%
3 Gonde 2
0.1%
4 Burka 1
0.1%
5 Maekel 14
0.9%
6 Haresew 20
1.3%
7 Limeat 21
1.4%
8 Gichi 19
1.2%
9 Sirba 97
6.4%
10 Awaeho 14
0.9%
11 Yetmen 2
0.1%
12 Gelegel Yetmen 7
0.5%
13 Densit 6
0.4%
14 Arogea Ambo 2
0.1%
15 Minchit 1
0.1%
16 Yetmen Lay 3
0.2%
17 Lay Ambo 7
0.5%
18 Yetmen Abbo 1
0.1%
19 Felege Selam 0
0%
20 Karafio 9
0.6%
21 Dibe 3
0.2%
22 Ballo 0
0%
23 Woyenue Eshete 0
0%
24 Tekeleye Meshesha 0
0%
25 Mender Mesereto 2
0.1%
26 Aleka Merawi 3
0.2%
27 Golbo 1
0.1%
28 Dahadeba 0
0%
29 Fino 9
0.6%
30 Golele 3
0.2%
31 Ealka 0
0%
32 Beressa 1
0.1%
33 Mehal Faji 2
0.1%
34 Milki 1
0.1%
35 Tach Faji 4
0.3%
36 Asefa Meshesha 1
0.1%
37 Boka Fiya 1
0.1%
38 Boka Bodo 1
0.1%
39 Atabahiye 10
0.7%
40 Borkema 19
1.2%
41 Koyo 16
1.1%
42 Yerer 19
1.2%
43 Yesemie 11
0.7%
44 Yada 12
0.8%
45 Addis Ketema 24
1.6%
46 Gedereha 3
0.2%
47 Yerezeb 4
0.3%
48 Yetabhe 1
0.1%
49 Godety 11
0.7%
50 Turife 66
4.3%
51 Wotera 20
1.3%
52 Ketchema 1
0.1%
53 Tena Kelo 0
0%
54 Oda Mecro 2
0.1%
55 Morom Sefer 5
0.3%
56 Begejo 44
2.9%
57 Gonda Begajo 1
0.1%
58 Konisa 1
0.1%
59 Kobe G/Zaw 8
0.5%
60 Alini 1
0.1%
61 Worgbn 3
0.2%
62 Fino & Golele 5
0.3%
63 Makro 3
0.2%
64 Arekesa Kelo 4
0.3%
65 Gende Bele 5
0.3%
66 Adadie 1
0.1%
67 Yaboo 0
0%
68 Laftole Mesreta 2
0.1%
69 Boto 25
1.6%
70 Ebicho 34
2.2%
71 Alemgena 16
1.1%
72 Chelo 22
1.4%
73 Gera 9
0.6%
74 Woyde Tokisa 17
1.1%
75 Hago 62
4.1%
76 Wattro 6
0.4%
77 1
0.1%
78 Godo 3
0.2%
79 Weyde 1
0.1%
80 Koysha Totisa 2
0.1%
81 Cheba Tokisa 4
0.3%
82 Bako 1
0.1%
83 Muleta 3
0.2%
84 Laye Wite 14
0.9%
85 Tache Wite 6
0.4%
86 Azemish Kida 13
0.9%
87 Dokea 10
0.7%
88 Shafa 11
0.7%
89 2nd Bulla 5
0.3%
90 Mehkelawi 19
1.2%
91 Laye Deboo 9
0.6%
92 Merob Godana 5
0.3%
93 Laye Wonko 0
0%
94 Tach Wonko 12
0.8%
95 Wite 0
0%
96 Bulla 1
0.1%
97 Fuchere 20
1.3%
98 Meriager 4
0.3%
99 Alela Ager 12
0.8%
100 Telem Amba 1
0.1%
101 Gema 5
0.3%
102 Merere 4
0.3%
103 Tilko 2
0.1%
104 Dinki 23
1.5%
105 Genda Gerbi 7
0.5%
106 Kuslto 6
0.4%
107 G/Haro 1
0.1%
108 Gole Gendo Koclto 6
0.4%
109 Gole 7
0.5%
110 Tabia 4
0.3%
111 Galon 12
0.8%
112 Gole Genda Barentu 4
0.3%
113 H/Goro 0
0%
114 Doma 54
3.6%
115 Kokob 12
0.8%
116 Negot 2
0.1%
117 Kae Sefer 4
0.3%
118 Wacho 2
0.1%
119 Keysha 6
0.4%
120 Megazen Sefer 5
0.3%
121 Yemenged Sefer 1
0.1%
122 Omala 6
0.4%
123 Church Sefer 1
0.1%
124 Enquiry Beret 13
0.9%
125 Shume Sha 39
2.6%
126 Deorwo 8
0.5%
127 Aba Aregay 4
0.3%
128 Tewala 7
0.5%
129 Shikt 1
0.1%
130 Addis Amba 2
0.1%
131 Dendawhl 1
0.1%
132 Takora 10
0.7%
133 Denekel/ Bonito 8
0.5%
134 Semidoro 6
0.4%
135 Kosien 19
1.2%
136 Weielawer 9
0.6%
137 Errata 10
0.7%
138 Buko 23
1.5%
139 Degaga 33
2.2%
140 Emo 9
0.6%
141 Shalota 12
0.8%
142 Amola 8
0.5%
143 Arda 20
1.3%
144 Arda chikota 8
0.5%
145 Alelu 7
0.5%
146 kura 14
0.9%
147 Mona Barumso 6
0.4%
148 Tineshu Kamo 0
0%
149 Kokola 4
0.3%
150 Gerdi 5
0.3%
151 Habt 3
0.2%
152 Abeyi 2
0.1%
153 Abejede 6
0.4%
154 Yebbo 3
0.2%
155 Abukako 3
0.2%
156 Famo 2
0.1%
157 Yero 7
0.5%
158 Buraya 2
0.1%
159 Wayyu 0
0%
160 Somdo 1
0.1%
161 Lalo Mabe 0
0%
162 Kajaro 11
0.7%
163 Kulto 2
0.1%
164 Gole Ganda Sole 6
0.4%
165 Genda Muuda 4
0.3%
166 Kura 3
0.2%
167 Elemo 4
0.3%
168 Boba Sodere 0
0%
169 Dodota 1
0.1%
170 Dolo 6
0.4%
171 Bursa 3
0.2%
172 Adado 27
1.8%
173 Hago 7
0.5%
174 Waissa 3
0.2%
175 Kisha 9
0.6%
176 Bukicho 9
0.6%
177 Invester Chample /Roba 5
0.3%
178 Hassene/ Waissa 1
0.1%
179 Dude 0
0%
185 1
0.1%
232 2
0.1%
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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